{"embedding_dim": 1024, "data": [{"__id__": "chunk-19bbd48c2201bbfcdd17bbc233a5af55", "__created_at__": 1754880286, "content": "预 备 课： 高中入学第一课 （学法指导）\n教学目的：了解高中阶段数学学习目标和基本能力要求，了解新课程标准的基本思路，了解高考意向，掌握高中数学学习基本方法，激发学生学习数学兴趣，强调布置有关数学学习要求和安排。\n教学过程：\n一、欢迎词：1、祝贺同学们通过自己的努力，从初中升入到高中进行更深层次的学习。希望同学们能够继续努力，坚持不懈，圆满度过高中三年的学习和生活，并祝愿同学们在这三年中次次取得优异成绩，并最终实现自己的宏伟目标。\n> 2、我是你们的数学老师，我姓陈。从今天开始我将会和同学们一起努力，帮助每\n>\n> 一位同学实现自己的目标\n>\n> 3、本节课我将和大家谈几个问题：为什么要学数学？如何学数学？高中数学知识\n>\n> 结构？本期数学教学活动安排？作业要求？\n二、几个问题：\n1. 什么是数学：数学是一门研究空间图形和数量关系的科学\n2.\n为什么要学数学：数学是各科的研究工具，它渗透到我们生活中的各个领域；计算机等高科技应用的需要；生活实践应用的需要。对个人而言，它可以训练我们的思维，培养我们的运算能力、逻辑思维能力、空间想像能力、分析和解决实际问题的能力；在学习数学的过程中得到的训练和修养会很好的帮助我们学习其他理论，数学素质的提高对于个人能力的发展也是至关重要的。\n3. 如何学数学：\n请几个同学发表自己的看法\n，共同完善归纳得出：抓好自学和预习；带着问题认真听课；独立完成作业；及时复习。注重自学能力的培养，在学习中有的放矢，形成学习能力。善于提问，善于对比，善于总结\n高中数学由于高考要求，学习时与初中有所不同，精通书本知识外，还要适当加大难度，即能够思考完成一些课后练习册，教材上每章复习参考题一定要题题会做。适当阅读一些课外资料，如订阅一份数学报刊，购买一本同步辅导资料.\n5. 本期学习任务：\n本学期我们要学习的是高中数学必修课程5个模块中的必修1，内容包括\"集合与函数的概念\"\"基本初等函数（1）\"\"函数的应用\"三个章节，共36课时，约一个半月时间。另外，我们还将学习剩下四个模块当中的一个，这将会按照教育局的统一安排进行学习。课时和时间与必修1基本相当。\n6. 本期数学教学、活动安排：\n上课方式：每周正课6节，自习课一节；\n学习方式：预习后做节后练习；补充知识写在书的边缘；\n主要活动：学校、全国每年的数学竞赛；数学课外活动（每期两次）。\n7. 作业要求：\n①\n课堂作业本设置三本（一本做课堂演算，一本课堂笔记与纠错，一本课后作业）；\n② 批阅用\"？\"号代表错误，一般画在错误开始处；每位同学必须自觉更正\n③练习册同步完成，按进度交阅，自觉订正；\n④当天布置，第二天早读之前交\n三、了解情况：初中数学开课情况；暑假自学情况；作图工具准备情况。\n四、布置作业：1、复习初中的因式分解，方程和函数\n2、预习必修1P1/~P5，完成P5的练习题1，2\n课题：§1.1.1 集合的含义与表示\n教材分析：\n教科书首先从8个实例入手，引入集合的相关概念，随后介绍了一些特殊集合的记号，最后介绍了集合的两种表示方法------例举法和描述法\n集合是一个原始的，不定义的概念。教科书上给出的只是集合的描述性说明。因此在刚刚接触集合时，主要还是通过实例，让学生了解其含义。教科书第二页的思考，目的也是让学生通过分析8个背景例子的共同特征，进一步概括出元素和集合的含义，以及它们之间的关系。\n教科书中给出的常用数集的记法是国家标准。其中，新的国家标准规定自然数集N包含元素0，即自然数集与非负整数集是相同的，这与国际标准化组织（ISO）制定的国际标准相衔接。\n例题1不仅要使学生明白用例举法表示集合的方法，同时还要让学生知道例举法表示集合时，集合中的元素具有无序性。第四页的思考，目的在于使学生认识到仅用例举法表示集合是不够的，由此说明学习描述法的必要性。学习描述法时，可以让学生针对具体的集合，先用自然语言描述集合中元素具有的共同属性，再介绍用描述法表示集合的方法。\n教科书给出了两种集合的表示方法，不仅让学生学习两种表示法，同时还", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-f097b0e93578a4cd37cc6131e8e6b59e", "__created_at__": 1754880286, "content": "表示集合时，集合中的元素具有无序性。第四页的思考，目的在于使学生认识到仅用例举法表示集合是不够的，由此说明学习描述法的必要性。学习描述法时，可以让学生针对具体的集合，先用自然语言描述集合中元素具有的共同属性，再介绍用描述法表示集合的方法。\n教科书给出了两种集合的表示方法，不仅让学生学习两种表示法，同时还要让学生体会如何恰当的选择表示法表示集合。在教学时，可以让学生选择适当的表示法表示本节开始时的8个例子，并完成教科书第五页练习第二题。\n课 时：一课时\n课 型：新授课\n教学目标：（1）通过实例，了解集合的含义，体会元素与集合的\n\"属于\"关系；\n> （2）能选择自然语言、集合语言（列举法或描述法）描述不同的具体问题，感受集合语言的意义和作用；\n教学重点：集合的基本概念与表示方法；\n教学难点：运用集合的两种表示法（列举法与描述法）正确表示一些简单的集合；\n教学关键：本小节的新概念，新符号较多，教学时先引导学生阅读教科书，然后进行交流，让学生在阅读与交流中理解概念并熟悉新符号的使用，从而培养学生主动学习的习惯，提高阅读与理解，合作与交流的能力。\n教学流程：创设情境给出集合含义 自主学习元素与集合的关系及记号\n> 课堂练习，小结与课后作业 集合的两种表示 自学常见数集及其记号\n教学过程：\n1.  引入课题\n在小学，初中，我们已经接触过一些集合，例如，自然数的集合，有理数的集合，不等式x-7/<3的解的集合，到一个定点的距离等于定长的点的集合（即圆），到线段两端点距离相等的点的集合（即线段的垂直平分线）。。。。。。\n那么，集合的含义是什么呢？下面我们再考察几组对象：\n① 1～10以内所有的质数；\n② 到定点的距离等于定长的所有点；\n③ 所有的锐角三角形；\n④ x, 3x+2, 5y-x, x+y；\n⑤ 地球上的四大洋\n⑥ 方程的所有实数根；\n⑦第一汽车制造总厂2008年8月生产的所有汽车；\n⑧ 2005年1月,克拉玛依市所有出生婴儿。\n提问：各组对象分别是一些什么？有多少个对象？（数、点、形、式、解、物、人）\n2.  新课教学\n（一）集合的有关概念\n1.  定义：一般地，我们把研究对象统称为元素（element）,把一些元素组成的总体叫作集合（set）（简称集）。\n阅读课本P~2~-P~3~内容，思考1：课本P2，P~3~的思考题\n2.  关于集合的元素的特征\n> （1）确定性：设A是一个给定的集合，x是某一个具体对象，则或者是A的元素，或者不是A的元素，两种情况必有一种且只有一种成立。\n>\n> （2）互异性：一个给定集合中的元素，指属于这个集合的互不相同的个体（对象），因此，同一集合中不应重复出现同一元素。\n>\n> （3）集合相等：构成两个集合的元素完全一样\n3.  元素与集合的关系；\n> （1）如果a是集合A的元素，就说a属于（belong to）A，记作a∈A\n>\n> （2）如果a不是集合A的元素，就说a不属于（not belong to）A，记作aA\n>\n> 常用数集及其记法：\n全体非负整数组成的集合称为非负整数集（或自然数集），记作N\n全体正整数组成的集合称为正整数集，记作N^/*^或N~+~；\n全体整数组成的集合称为整数集，记作Z\n全体有理数组成的集合称为有理数集，记作Q\n全体实数组成的集合称为实数集，记作R\n（二）集合的表示方法\n我们可以用自然语言来描述一个集合，但这将给我们带来很多不便，除此之外还常用列举法和描述法来表示集合。\n1.  列举法：把集合中的元素一一列举出来，写在大括号内。\n> 如：{1，2，3，4，5}，{x^2^，3x+2，5y^3^-x，x^2^+y^2^}，...；\n1.  用例举法表示下列集合：\n> （1）小于10的所有自然数组成的集合\n>\n> （2）方程x^2^=x的所有实数根组成的集合\n>\n> （3）由1/~20以内的所有质数组成的集合\n说明：集合中的元素具有无序性，所以用列", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-135defb81f961538f9b5cd1d1ef1d88f", "__created_at__": 1754880286, "content": "，5y^3^-x，x^2^+y^2^}，...；\n1.  用例举法表示下列集合：\n> （1）小于10的所有自然数组成的集合\n>\n> （2）方程x^2^=x的所有实数根组成的集合\n>\n> （3）由1/~20以内的所有质数组成的集合\n说明：集合中的元素具有无序性，所以用列举法表示集合时不必考虑元素的顺序。\n思考2，P4思考题（引入描述法）\n2.  描述法：把集合中的元素的公共属性描述出来，写在[大括号{}]{.ul}内。\n> 具体方法：在大括号内先写上表示这个集合元素的一般符号及取值（或变化）范围，再画一条竖线，在竖线后写出这个集合中元素所具有的共同特征。\n>\n> 如：A={x∈R/|x/>2}，B={(x,y)/|y=x^2^+1,x∈R，y∈R}，...；\n2.  是分别用例举法和描述法表示下列集合：\n```{=html}\n<!-- -->\n```\n1.  方程x^2^-2=0的所有实数根组成的集合；\n2.  由大于10小于20的所有整数组成的集合。\n说明：如果从上下文的关系来看，x∈R,x∈Z是明确的，那么x∈R,x∈Z可以省略，只写其元素x。例如：集合A={x∈R/|x/>2}可以表示为A={x/|x/>2}，集合B={(x,y)/|y=x^2^+1,x∈R，y∈R}可以表示为B={(x,y)/|y=x^2^+1\n}，\n思考3：（课本P~6~思考）简述三种集合表示的优缺点\n强调：描述法表示集合时应注意集合的[代表元素]{.ul}，这是非常关键的，例如集合\n> {(x,y)/|y= x^2^+3x+2}与 {y/|y=\n> x^2^+3x+2}不同，只要不引起误解，集合的代表元素也可省略，例如：{整数}，即代表整数集Z。\n辨析：这里的{\n}已包含\"所有\"的意思，所以不必写{全体整数}。下列写法{实数集}，{R}也是错误的。\n说明：列举法与描述法各有优点，应该根据具体问题确定采用哪种表示法，要注意，一般集合中元素较多或有无限个元素时，不宜采用列举法。\n（三）课堂练习（课本P~5~练习）\n3.  归纳小结\n本节课从实例入手，非常自然贴切地引出集合与集合的概念，并且结合实例对集合的概念作了说明，然后介绍了集合的常用表示方法，包括列举法、描述法。\n4.  作业布置\n> 书面作业：习题1.1，第1- 4题\n板书设计：\n课后反馈：\n/\n课题:§1.1.2集合间的基本关系\n教材分析：本小节包含两个集合间的包含与相等，子集、真子集与空集等概念，表示这些关系与概念的符号，以及集合的Venn图表示\n教科书在第六页用思考启发学生类比熟悉的两个实数之间的关系，联想两个集合之间的关系。这种由类比某事物已有的性质，以类比，联想的方式猜想另一类相似事物的性质，是数学逻辑思考的重要思维方法。这种思考在教科书中还有很多，教学时应抓住机会让学生充分思考和积极探索，并鼓励他们说出自己的想法。在学生类比并对两个集合之间的关系产生了某些想法后，教科书通过分析三个具体例子的共同特点给出了集合间的包含关系。教学时让学生自己观察、发现相应的共同点，然后再给出包含关系的定义。\n> Venn图可以形象直观的表示集合之间的关系，教学时只要让学生知道表示集合的Venn图的边界是封闭的曲线，它可以是圆形，可以是矩形，也可以是其他的封闭曲线即可。\n>\n> 本小节的例题3不仅可以让学生加深对子集、真子集及包含关系的理解，同时，还可以让学生学习分类思想方法。这里是按子集的元素个数为标准进行分类的，共分为三类，即不含元素的集合为一类：；只含一个元素的集合为一类：{a}，{b}；含有两个元素的集合为一类：{a，b}\n>\n> 练习中的第一题与例题3是配套的，第2题除了让学生熟悉正确使用符号以外，还要学生进一步熟悉集合的例举法与描述法；第3题不仅要学生学会判断两个集合之间是否具有包含关系，同时，还要让学生进一步学会集合的两种表示方法之间", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-177eb1b020ec2a17f0791c67459c919a", "__created_at__": 1754880286, "content": "：{a}，{b}；含有两个元素的集合为一类：{a，b}\n>\n> 练习中的第一题与例题3是配套的，第2题除了让学生熟悉正确使用符号以外，还要学生进一步熟悉集合的例举法与描述法；第3题不仅要学生学会判断两个集合之间是否具有包含关系，同时，还要让学生进一步学会集合的两种表示方法之间的相互转化。\n课 时：一课时\n课 型：新授课\n教学目的：（1）了解集合之间的包含、相等关系的含义；\n> （2）理解子集、真子集的概念；\n>\n> （3）能利用Venn图表达集合间的关系；\n>\n> （4）了解与空集的含义。\n教学重点：子集与空集的概念；用Venn图表达集合间的关系。\n教学难点：弄清元素与子集 、属于与包含之间的区别；\n教学关键：（1）空集是较难理解的一个抽象概念，教学时宜多举些方程无解，不等式无解的例子。\n> （2）在包含关系及相关概念的教学中，应使学生从三个方面理解它们：自然语言，符号语言，图形语言\n>\n> （3）包含关系发生在两个集合之间，而属于关系发生在元素与集合之间。教学时应多举例子并引导学生区分这类容易混淆的关系和符号。\n>\n> 例如与的区别，a与{a}的区别，0与{0}的区别等等\n教学流程：\n教具准备：无\n教学过程：\n1.  引入课题\n```{=html}\n<!-- -->\n```\n1.  复习元素与集合的关系------属于与不属于的关系，填以下空白：\n（1）0 N；（2） Q；（3）-1.5 R\n2.  类比实数的大小关系，如5/<7，2≤2，试想集合间是否有类似的\"大小\"关系呢？\n```{=html}\n<!-- -->\n```\n2.  新课教学\n```{=html}\n<!-- -->\n```\n1.  集合与集合之间的\"包含\"关系；\n观察下面的两个例子，你能发现两个集合之间的关系吗？\n（1）A={1，2，3}，B={1，2，3，4}\n（2）C={x/|x是一个角为直角的三角形}，\nD={x/|x是有两内角和为90^o^的三角形}\n集合A是集合B的部分元素构成的集合，我们说集合B包含集合A；\n如果集合A的任何一个元素都是集合B的元素，我们说这两个集合有包含关系，称集合A是集合B的子集（subset）。\n> 记作：\n>\n> 读作：A包含于（is contained in）B，或B包含（contains）A\n当集合A不包含于集合B时，记作A B\n在数学中，我们常用平面内封闭曲线的内部代表集合，这种图称为Venn图，故上述两个集合间的\"包含\"关系可用右图表示\n2.  集合与集合之间的 \"相等\"关系；\n在上节课，我们已经知道，如果两个集合中的元素完全一样，那么这两个集合相等，现在我们再在子集概念的基础上，再对两个集合相等做进一步的数学描述\n如果集合A是集合B的子集（），且集合B也是集合A的子集（），那么集合A与集合B中的元素是一样的，因此，集合A与集合B相等，记作：\n> 即\n练习1、P7练习题第一题\n结论：任何一个集合是它本身的子集\n3.  真子集的概念\n> 若集合，存在元素，则称集合A是集合B的真子集\n（proper subset）。记作：A\n![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image17.png)\nB（或B![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image18.png)\nheight=\"0.11458333333333333in\"} A），读作：A真包含于B（或B真包含A）\n> 举例（由学生举例，共同辨析）\n4.  空集的概念\n> 我们知道方程x^2^+1=0没有实数根，所以方程x^2^+1=0的实数根组成的集合中就\n没有元素。我们把这种不含有任何元素的集合称为空集（empty set），记作：\n规定：空集是任何集合的子集，\n思考1：P7思考题：你能举出几个空集的例子吗？\n5.  结论：\n> 任何一个集合是它本身的自己\n对于集合A,B,C,如果，且，那么\n思考2：你还能得出哪些结论？\n答：空集是任何非空集合的真子集。\n6.  例题\n> （1）写出集合{a，b}的所有的子集，并指出其中哪些是它的真子集。/\n>", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-76b5f00835079a99481b0353878f5cf3", "__created_at__": 1754880286, "content": "空集的例子吗？\n5.  结论：\n> 任何一个集合是它本身的自己\n对于集合A,B,C,如果，且，那么\n思考2：你还能得出哪些结论？\n答：空集是任何非空集合的真子集。\n6.  例题\n> （1）写出集合{a，b}的所有的子集，并指出其中哪些是它的真子集。/\n> （2）化简集合A={x/|x-3/>2},B={x/|x5}，并表示A、B的关系；\n7.  课堂练习2、P7练习题第二，三题\n8.  归纳小结，强化思想\n> 两个集合之间的基本关系只有\"包含\"与\"相等\"两种，可类比两个实数间的大小关系，同时还要注意区别\"属于\"与\"包含\"两种关系及其表示方法；\n9.  作业布置\n```{=html}\n<!-- -->\n```\n1.  书面作业：习题1.1 第5题\n2.  提高作业：\n> 已知集合，≥，且满足，求实数的取值范围。\n>\n> 设集合，\n>\n> ，试用Venn图表示它们之间的关系。\n板书设计：\n课后反馈：\n/\n课题：§1.1.3集合的基本运算\n教材分析：本小节介绍了集合的三种基本运算，以及全集的概念\n> 与前一小节类似，教科书强调了集合的基本元素与实数的基本元素之间的类比。第9页给出的思考，是让学生从实数的加法运算出发，通过类比的方法，联想集合的某种运算。在此基础上，教科书以两个实例为载体引入了集合的运算。对于集合的并集，交集，补集的理解，不仅要会用自然语言描述，还要学会用符号表示，以及图形表示。\n>\n> 在教授并集，交集，补集的概念时，要充分发挥引例的作用以及对引例的变形处理。第9页的思考不仅可以加深学生对集合元素\"互异性\"的理解，体会空集的意义，而且可以让学生关注集合运算的特殊性。\n>\n> 集合的补集是在全集的概念后介绍的。在数学研究中，明确在什么范围内讨论问题是非常重要的，这才是学习全集概念的意义。在教学时可以让学生分别在有理数范围和实属范围内解方程，然后问学生，不同的研究范围对问题的结果有什么影响？以使学生体会到全集的含义。\n>\n> 例题4可以让学生用Venn图表示结果，这样不仅加强了主观性，还可以为后面学习交集做准备，同时也让学生体会Venn图表示集合的直观性。\n>\n> 例题5中用数轴表示是为了直观的表示集合的并运算的过程，也为以后用数轴求集合的并，补做准备。\n例题6可以根据教学班级的实际情况加以改编，\n例题7没有什么实际的价值，可以换掉\n> 例题8可以让学生自己完成，还可以进一步的让学生用Venn图表示A与,B与。\n>\n> 例题9中还可以让学生求与，这样可以使学生更加深刻的理解和体会补集的意义\n>\n> 练习第1，2，3题可结合例题6，7进行，第4题可以结合例题8进行。习题1.1A组的第1，2，5，6可在课堂上选作练习题，其余问题可供课后作业选用。\n课 时：一课时\n课 型：新授课\n教学重点：集合的交集与并集、补集的概念；\n教学难点：集合的交集与并集、补集\"是什么\"，\"为什么\"，\"怎样做\"；\n教学关键：相对于并集与交集两个概念，补集是较难理解的。因此，教学时宜多采用Venn图的直观性帮助学生理解\n教学流程：\n教具准备：\n教学过程：\n1.  引入课题\n我们两个实数除了可以比较大小外，还可以进行加法运算，类比实数的加法运算，两个集合是否也可以\"相加\"呢？\n引入并集概念。\n思考：考察下列各个集合，你能说出集合C与集合A,B之间的关系吗？\n（1）A={1,3,5},B={2,4,6},C={1,2,3,4,5,6};\n（2）A={x/|x是有理数}，B={x/|x是无理数}，C＝{x/|x是实数}\n二、新课教学\n在上述两个问题中，集合A,B与集合C之间都具有这样一种关系：集合C是由所有属于集合A或属于集合B的元素组成的。\n1.  并集\n> 一般地，由所有属于集合A或属于集合B的元素所组成的集合，称为集合A与B的并集（Union）\n>\n> 记作：A∪B", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-393fbdbc5656139ebb55f2afcc93ece5", "__created_at__": 1754880286, "content": "＝{x/|x是实数}\n二、新课教学\n在上述两个问题中，集合A,B与集合C之间都具有这样一种关系：集合C是由所有属于集合A或属于集合B的元素组成的。\n1.  并集\n> 一般地，由所有属于集合A或属于集合B的元素所组成的集合，称为集合A与B的并集（Union）\n>\n> 记作：A∪B 读作：\"A并B\"\n>\n> 即： A∪B={x/|x∈A，或x∈B}\n>\n> Venn图表示：\n>\n> 说明：两个集合求并集，结果还是一个集合，是由集合A与B的所有元素组成的集合（重复元素只看成一个元素）。\n>\n> 例题（P~8-9~例4、例5）\n>\n> 例题4、设A={4,5,6,8},B＝{3，5，7，8}，求A∪B.\n>\n> 例题5、设集合A＝{x/|-1/<x/<2},集合B={x/|1/<x/<3}\n>\n> 说明：连续的（用不等式表示的）实数集合可以用数轴上的一段封闭曲线来表示。\n>\n> 问题：在上图中我们除了研究集合A与B的并集外，它们的公共部分（即问号部分）还应是我们所关心的，我们称其为集合A与B的交集。\n2.  交集\n> 一般地，由属于集合A且属于集合B的元素所组成的集合，叫做集合A与B的交集（intersection）。\n>\n> 记作：A∩B 读作：\"A交B\"\n>\n> 即： A∩B={x/|∈A，且x∈B}\n>\n> 交集的Venn图表示\n>\n> ![](static/Images/c72af4bdba1f454fa890bc6d35622724/media/image33.emf){width=\"2.7604166666666665in\"\n> height=\"1.7520833333333334in\"}\n>\n> 说明：两个集合求交集，结果还是一个集合，是由集合A与B的公共元素组成的集合。\n>\n> 例题（P~9-10~例6、例7）\n>\n> 拓展：求下列各图中集合A与B的并集与交集\n>\n> 说明：当两个集合没有公共元素时，两个集合的交集是空集，而不能说两个集合没有交集\n3.  补集\n> 全集：一般地，如果一个集合含有我们所研究问题中所涉及的所有元素，那么就称这个集合为全集（Universe），通常记作U。\n>\n> 补集：对于全集U的一个子集A，由全集U中所有不属于集合A的所有元素组成的集合称为集合A相对于全集U的补集（complementary\n> set）,简称为集合A的补集，\n>\n> 记作：C~U~A\n>\n> 即：C~U~A={x/|x∈U且x∈A}\n>\n> 补集的Venn图表示\n>\n> ![](static/Images/c72af4bdba1f454fa890bc6d35622724/media/image34.emf){width=\"2.390277777777778in\"\n> height=\"1.5173611111111112in\"}\n>\n> 说明：补集的概念必须要有全集的限制\n>\n> 例题（P~12~例8、例9）\n4.  求集合的并、交、补是集合间的基本运算，运算结果仍然还是集合，区分交集与并集的关键是\"且\"与\"或\"，在处理有关交集与并集的问题时，常常从这两个字眼出发去揭示、挖掘题设条件，结合Venn图或数轴进而用集合语言表达，增强数形结合的思想方法。\n5.  集合基本运算的一些结论：\n> A∩BA，A∩BB，A∩A=A，A∩=,A∩B=B∩A\n>\n> AA∪B，BA∪B，A∪A=A，A∪=A,A∪B=B∪A\n>\n> （C~U~A）∪A=U，（C~U~A）∩A=\n>\n> 若A∩B=A，则AB，反之也成立\n>\n> 若A∪B=B，则AB，反之也成立\n>\n> 若x∈（A∩B），则x∈A且x∈B\n>\n> 若x∈（A∪B），则x∈A，或x∈B\n6.  课堂练习/\n（1）设A={奇数}、B={偶数}，则A∩Z=A，B∩Z=B，A∩B=/\n（2）设A={奇数}、B={偶数}，则A∪Z=Z，B∪Z=Z，A∪B=Z\n```{=html}\n<!-- -->\n```\n2.  归纳小结（略）\n3.", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-c79e119380a9cf921c9ff71b72d0121d", "__created_at__": 1754880286, "content": "课堂练习/\n（1）设A={奇数}、B={偶数}，则A∩Z=A，B∩Z=B，A∩B=/\n（2）设A={奇数}、B={偶数}，则A∪Z=Z，B∪Z=Z，A∪B=Z\n```{=html}\n<!-- -->\n```\n2.  归纳小结（略）\n3.  作业布置\n1.  书面作业：P~13~习题1.1，第6-10题\n2.  提高内容：\n```{=html}\n<!-- -->\n```\n1.  已知X={x/|x2+px+q=0，p2-4q/>0},A={1,3,5,7,9},B={1,4,7,10}，且\n> ，试求p、q；\n2.  集合A={x/|x2+px-2=0},B={x/|x2-x+q=0},若AB={-2，0，1}，求p、q；\n3.  A={2，3，a2+4a+2}，B={0，7，a2+4a-2，2-a}，且AB ={3，7}，求B\n板书设计：\n课后反馈：\n/\n课题：§1.2.1函数的概念\n教材分析：函数是描述客观世界变化规律的重要数学模型．高中阶段不仅把函数看成变量之间的依赖关系，同时还用集合与对应的语言刻画函数，高中阶段更注重函数模型化的思想．\n函数是高中数学的重要内容。在学生学习用集合与对应的语言刻画函数之前，学生已经会把函数看成变量之间的依赖关系，同时，虽然函数概念比较抽象，但函数现象大量存在于学生的周围。因此，教科书采用了从实际例子中抽象概括出用集合与对应的语言定义函数的方式介绍函数概念。这样不仅为学生理解函数概念打了感性基础，而且注重培养学生的抽象概括能力，启发学生运用函数模型表述、思考和解决现实世界中蕴涵的规律，逐渐形成善于提出问题的习惯，学会数学表达和交流，发展数学应用意识。\n本节函数概念的引入是采用从三个背景实例入手，在体会两个变量之间依赖关系的基础上，引导学生运用集合与对应的语言刻画函数概念。继而，通过例题，思考，探究，练习中的问题从三个层次理解函数概念：函数定义，函数符号函数三要素，并与初中定义相比较。\n教科书的引例选自运动，自然界，经济生活中用三种不同方法表示的函数，既可以让学生感受函数在许多方面的广泛应用，又可以使学生意识到对应关系不仅仅可以是明确的解析式（实例1），也可以是形象直观的曲线（实例2）或者表格（实例3），这三个实例的自变量的取值范围都是有限制的，事实上，大多数现实世界中的函数问题和今后研究的函数的自变量的取值范围都是有限制的，可以通过学生的多动让他们认识到这点。学完每个背景引例后，可以让学生讨论它们的共性：都涉及两个数集；两个数集间都有一种确定的对应关系。运用集合与对应的语言，采用统一的符号，就得到函数的一般概念。\n例题1教会学生求简单函数的定义域；对于用解析式表示的函数，会由给定的自变量与函数的解析式计算函数值；进一步体会函数记号的含义，能区别f（3）、f（a）与f（x）\n例题2使学生通过判断函数相等认识到函数的整体性。值得注意的是，三要素中，由于值域是由定义域和对应关系决定的，所以只要两个函数定义域和对应法则完全一致，这两个函数就相等。例题2还可以进一步加深学生对函数概念的理解。\n课 时：一课时\n教学目的：（1）通过丰富实例，进一步体会函数是描述变量之间的依赖关系的重要数学模型，在此基础上学习用集合与对应的语言来刻画函数，体会对应关系在刻画函数概念中的作用；\n> （2）了解构成函数的要素；\n>\n> （3）会求一些简单函数的定义域和值域；\n>\n> （4）能够正确使用\"区间\"的符号表示某些函数的定义域；\n教学重点：理解函数的模型化思想，用合与对应的语言来刻画函数；\n教学难点：符号\"y=f(x)\"的含义，函数定义域和值域的区间表示；\n教学关键：对函数概念，应是学生明确三点：\n1.  定义域，值域和对应关系是决定函数的三要素，这是一个整体。\n2.  函数记号y=f（x）的内涵。同时也应用具体的函数说明符号\"y=f（x）\"为\"y是关于x的函数\"这句话的数学表达，它只是一个数学符号，并不表示\"y等于f与x的乘积", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-35599dfd96278bbad81823e459b68e95", "__created_at__": 1754880286, "content": "关键：对函数概念，应是学生明确三点：\n1.  定义域，值域和对应关系是决定函数的三要素，这是一个整体。\n2.  函数记号y=f（x）的内涵。同时也应用具体的函数说明符号\"y=f（x）\"为\"y是关于x的函数\"这句话的数学表达，它只是一个数学符号，并不表示\"y等于f与x的乘积\"。\n3.  符号f（a）与f（x）的区别与联系。\n教学流程：\n教具准备：投影\n教学过程：\n1.  引入课题\n```{=html}\n<!-- -->\n```\n1.  复习初中所学函数的概念，强调函数的模型化思想；\n2.  阅读课本引例，体会函数是描述客观事物变化规律的数学模型的思想：\n> （1）炮弹的射高与时间的变化关系问题；\n>\n> （2）南极臭氧空洞面积与时间的变化关系问题；\n>\n> （3）\"八五\"计划以来我国城镇居民的恩格尔系数与时间的变化关系问题\n>\n> 备用实例：\n>\n> （4）我国2003年4月份非典疫情统计：\n---------------- ----- ----- ---- ----- ----- ----- ---- ----- -----\n日 期            22    23    24   25    26    27    28   29    30\n新增确诊病例数   106   105   89   103   113   126   98   152   101\n---------------- ----- ----- ---- ----- ----- ----- ---- ----- -----\n3.  引导学生应用集合与对应的语言描述各个实例中两个变量间的依赖关系；\n4.  根据初中所学函数的概念，判断各个实例中的两个变量间的关系是否是函数关系．\n```{=html}\n<!-- -->\n```\n2.  新课教学\n（一）函数的有关概念\n1．函数的概念：\n设A、B是非空的数集，如果按照某个确定的对应关系f，使对于集合A中的任意一个数x，在集合B中都有唯一确定的数f(x)和它对应，那么就称f：A→B为从集合A到集合B的一个函数（function）．\n记作： y=f(x)，x∈A．\n其中，x叫做自变量，x的取值范围A叫做函数的定义域（domain）；与x的值相对应的y值叫做函数值，函数值的集合{f(x)/|\nx∈A }叫做函数的值域（range）．\n注意：\n\"y=f(x)\"是函数符号，可以用任意的字母表示，如\"y=g(x)\"；\n函数符号\"y=f(x)\"中的f(x)表示与x对应的函数值，一个数，而不是f乘x．\n2.  构成函数的三要素：\n> 定义域、对应关系和值域 同一函数定义\n3．一次函数、二次函数、反比例函数的定义域和值域讨论\n（由学生完成，师生共同分析讲评）\n4．区间的概念\n（1）区间的分类：开区间、闭区间、半开半闭区间；\n（2）无穷区间；\n（3）区间的数轴表示．\n（二）典型例题\n1．求函数定义域\n课本p17例1\n解：（略）\n说明：\n函数的定义域通常由问题的实际背景确定，如课前三个实例；\n如果只给出解析式y=f(x)，而没有指明它的定义域，则函数的定义域即是指能使这个式子有意义的实数的集合；\n函数的定义域、值域要写成集合或区间的形式．\n巩固练习：课本P19第1题\n2．判断两个函数是否为同一函数\n课本P~18~例2\n解：（略）\n说明：\n构成函数三个要素是定义域、对应关系和值域．由于值域是由定义域和对应关系决定的，所以，如果两个函数的定义域和对应关系完全一致，即称这两个函数相等（或为同一函数）\n两个函数相等当且仅当它们的定义域和对应关系完全一致，而与表示自变量和函数值的字母无关。\n巩固练习：\n课本P~19~第2，3题\n判断下列函数f（x）与g（x）是否表示同一个函数，说明理由？\n（1）f ( x ) = (x －1) ^0^；g ( x ) = 1\n（2）f ( x ) = x； g ( x ) =\n（3）f ( x ) = x ^2^；f ( x ) = (x + 1) ^2^\n（4）f ( x ) = /| x /| ；g ( x ) =\n（三）课堂练习\n求下列函数的定义域\n（1）\n（2）\n（3）\n（4）\n（5）\n（6）\n3.  归纳小结，强化思想\n从具体实例引入了函数的的概念，用集合与对应的语言描述了函数的定义及其相关概念，介绍了求函数定义域和判断同一函数的典", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-cd7a1b3a945d4592a28b560b224d5eac", "__created_at__": 1754880286, "content": "x ) = /| x /| ；g ( x ) =\n（三）课堂练习\n求下列函数的定义域\n（1）\n（2）\n（3）\n（4）\n（5）\n（6）\n3.  归纳小结，强化思想\n从具体实例引入了函数的的概念，用集合与对应的语言描述了函数的定义及其相关概念，介绍了求函数定义域和判断同一函数的典型题目，引入了区间的概念来表示集合。\n4.  作业布置\n课本P~24~ 习题1．2（A组） 第1，2，3，4，5题\n板书设计：\n课后反馈：\n/\n课题：§1.2.2函数的表示法\n教材分析：学习函数的表示，不仅是研究函数本身和应用函数解决实际问题所必需涉及的问题，而且是加深理解函数概念的过程。同时，基于高中阶段所接触的许多函数均可以用多种不同的方式表示，因而使得学习函数的表示也是向学生渗透数形结合方法的重要过程。\n初中已经接触过函数的三种表示法：解析法、例表法和图像法。高中阶段是让学生在了解三种表示法各自优点的基础上，重点在于使学生面对实际情景时，会根据不同的需要选择恰当的方法表示函数。\n解析法有两个优点：一是简明、全面的概括了变量间的关系；二是可以通过解析式求出任意一个变量的值所对应的函数值。\n> 图像法的优点：直观形象，很容易通过自变量的变化，看到函数值的变化情况。\n>\n> 列表法的优点：不需要计算就可以看到自变量的值和它对应函数值。\n>\n> 教科书第19页的例题3介绍了一个可以用三种表示方法表示的函数，通过这个例子可以使学生体会到三种表示方法各自的优点，还可以使学生看到函数的图像可以是一些分散的点，这与学生以前接触的一次函数，二次函数，反比例函数的图像都是连续的曲线有很大的差别，教学时要考虑学生的认知基础，强调y=5x（x∈R）是连续的直线，但是y=5x(x∈{1,2,3,4,5})却是5个离散的点，由此有可以让学生看到，函数概念中，对应关系，定义域，值域是一个整体。\n>\n> 函数图像既可以是连续的曲线，也可以是直线，折线，离散的点。例题3边框中的问题，讨论后的结论应该是\"平行于y轴的直线（或y轴）与图像至多一个交点\"。\n>\n> 例题4利用表格给出了四个函数分别表示王伟，张城，赵磊的各次考试成绩及各次考试的班级平均分。由表格区分三位同学的成绩高低不直观，所以教科书选择了图像法表示。教学时要培养学生根据需要选择恰当的函数表示法的能力。要注意的是图像当中的虚线不是函数图像的组成部分，之所以用虚线连接起来，主要是为了区别这三个函数，并且让三个函数的图像具有整体性，以方便比较。教学时要引导学生观察图像，学习如何从图像上获取有用信息，为分析每一位同学的学习情况提供依据。\n>\n> 例题5使学生进一步体会数形结合在理解函数中的重要作用，为介绍分段函数做准备。\n>\n> 例题6是为了使学生尝试用数学表达式去表达实际问题，学习分段函数及其表示，同时使学生有意识的注意到\"在数学模型中全面反映问题的实际意义\"\n>\n> 由于分段函数学生初次接触，比较难学，但它又是一类重要的函数，因此教科书专门做了介绍。教学中不必要求学生一次完成认识，可以根据具体情况，采取不同要求。\n课 时：一课时\n教学目的：（1）明确函数的三种表示方法；会画简单的分段函数的图像\n> （2）在实际情境中，会根据不同的需要选择恰当的方法表示函数；\n>\n> （3）通过具体实例，了解简单的分段函数，并能简单应用；\n>\n> （4）纠正认为\"y=f(x)\"就是函数的解析式的片面错误认识．\n教学重点：函数的三种表示方法，分段函数的概念．\n教学难点：根据不同的需要选择恰当的方法表示函数，什么才算\"恰当\"？分段函数的表示及其图象．\n教学关键：运用信息技术，为学生创设丰富的数形结合环境，帮助学生更深刻的理解函数概念及其表示\n教学流程：\n教具准备：多媒体，电脑，三角板\n教学过程：\n1.  引入课题\n师：在初中的时候，我们已经学习过一些简单的函数，有一次函数，二次函数，反比例函数等，大家还知道函数作图的步骤吗？\n生：知道。函数作图有三步", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-76b781b54c9c49df537fdc108a9eee02", "__created_at__": 1754880286, "content": "技术，为学生创设丰富的数形结合环境，帮助学生更深刻的理解函数概念及其表示\n教学流程：\n教具准备：多媒体，电脑，三角板\n教学过程：\n1.  引入课题\n师：在初中的时候，我们已经学习过一些简单的函数，有一次函数，二次函数，反比例函数等，大家还知道函数作图的步骤吗？\n生：知道。函数作图有三步：一是列表，二是描点，三是作图。\n![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image48.png)\nheight=\"1.5833333333333333in\"}师：各位同学，你们知道吗？你们在作图的过程中已经接触到了函数的三种不同表示方法了，通过大家的预习，大家说说看，是哪三种函数的表达呢？\n二、新课讲解\n生：解析式法，列表法，图像法。\n师：对，非常正确。那么，如果给出一个函数的一种表示，如右图，已知某函数的图像，你们能得出它的另外的两种表示吗？\n生：能。（学生写出函数的解析式和列表表示）\n师：很好，大部分同学都能写出来。不会的同学一定要再努努力啊，争取下次也能也出来。通过这个例子，我们可以发现函数的三种表示法之间是可以相互转化的，它们实际上就是同一个事物的不同表达。就如同我们在前面学习集合一样，同一个集合也是有多种不同的表示（例举法，描述法，图示法等等），但实际上它们是一样的类比集合的这三种常见的表示法，我们想想函数的三种表示法各自的优缺点好吗？这也是我们为什么要学习函数的三种表示法而不是一种的原因。\n生：解析法有两个优点：一是简明、全面的概括了变量间的关系；二是可以通过解析式求出任意一个变量的值所对应的函数值。\n图像法的优点：直观形象，很容易通过自变量的变化，看到函数值的变化情况。\n列表法的优点：不需要计算就可以看到自变量的值和它对应函数值。\n3.  例题练讲\n例1．某种笔记本的单价是5元，买x\n(x∈{1，2，3，4，5})个笔记本需要y元．试用三种表示法表示函数y=f(x) ．\n分析：注意本例的设问，此处\"y=f(x)\"有三种含义，它可以是解析表达式，可以是图象，也可以是对应值表．\n解：（略）\n注意：\n函数图象既可以是连续的曲线，也可以是直线、折线、离散的点等等，注意判断一个图形是否是函数图象的依据；\n解析法：必须注明函数的定义域；\n图象法：是否连线；\n列表法：选取的自变量要有代表性，应能反映定义域的特征．\n> 巩固练习：\n课本P~27~练习第1题\n例2．下表是某校高一（1）班三位同学在高一学年度几次数学测试的成绩及班级及班级平均分表：\n---------- -------- -------- -------- -------- -------- --------\n第一次   第二次   第三次   第四次   第五次   第六次\n王 伟      98       87       91       92       88       95\n张 城      90       76       88       75       86       80\n赵 磊      68       65       73       72       75       82\n班平均分   88．2    78．3    85．4    80．3    75．7    82．6\n---------- -------- -------- -------- -------- -------- --------\n> 请你对这三位同学在高一学年度的数学学习情况做一个分析．\n>\n> 分析：本例应引导学生分析题目要求，做学情分析，具体要分析什么？怎么分析？借助什么工具？\n>\n> 解：（略）\n>\n> 注意：\n>\n> 本例为了研究学生的学习情况，将离散的点用虚线连接，这样更便于研究成绩的变化特点；\n>\n> 本例能否用解析法？为什么？\n>\n> 巩固练习：\n>\n> 课本P~27~练习第2题\n>\n> 例3．画出函数y = /| x /| ．\n>\n> 解：（略）\n>\n> 巩固练习：课本P~27~练习第3题\n>\n> 拓展练习：\n>\n> 任意画一个函数y=f(x)的图象，然后作出y=/|f(x)/| 和 y=f (/|x/|)\n> 的图象，并尝试简要说明三者（图象）之间的关系．\n>\n> 课本P~27~练习第3题\n>\n> 例4．某市郊空调公共汽车的票价按下列规则制定：\n>\n> （1） 乘坐汽车5公里以内，票价2元；\n>\n> （2", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-0610d91e749f063330ef67659ad2b763", "__created_at__": 1754880286, "content": "象，然后作出y=/|f(x)/| 和 y=f (/|x/|)\n> 的图象，并尝试简要说明三者（图象）之间的关系．\n>\n> 课本P~27~练习第3题\n>\n> 例4．某市郊空调公共汽车的票价按下列规则制定：\n>\n> （1） 乘坐汽车5公里以内，票价2元；\n>\n> （2） 5公里以上，每增加5公里，票价增加1元（不足5公里按5公里计算）．\n已知两个相邻的公共汽车站间相距约为1公里，如果沿途（包括起点站和终点站）设20个汽车站，请根据题意，写出票价与里程之间的函数解析式，并画出函数的图象．\n分析：本例是一个实际问题，有具体的实际意义．根据实际情况公共汽车到站才能停车，所以行车里程只能取整数值．\n解：设票价为y元，里程为x公里，同根据题意，\n如果某空调汽车运行路线中设20个汽车站（包括起点站和终点站），那么汽车行驶的里程约为19公里，所以自变量x的取值范围是{x∈N^/*^/|\nx≤19}．\n由空调汽车票价制定的规定，可得到以下函数解析式：\n> ()\n根据这个函数解析式，可画出函数图象，如下图所示：\n![](static/Images/c72af4bdba1f454fa890bc6d35622724/media/image52.emf){width=\"4.15in\"\n注意：\n本例具有实际背景，所以解题时应考虑其实际意义；\n本题可否用列表法表示函数，如果可以，应怎样列表？\n实践与拓展：\n请你设计一张乘车价目表，让售票员和乘客非常容易地知道任意两站之间的票价．（可以实地考查一下某公交车线路）\n说明：我们把例题1，例题2这样的函数叫做分段函数。在现实生活中，有很多可以用分段函数描述的实际问题，同学们可以试着自己举出一些这样的例子。\n注意：分段函数的解析式不能写成几个不同的方程，而就写函数值几种不同的表达式并用一个左大括号括起来，并分别注明各部分的自变量的取值情况．\n四、归纳小结，强化思想\n理解函数的三种表示方法，在具体的实际问题中能够选用恰当的表示法来表示函数，注意分段函数的表示方法及其图象的画法．\n五、作业布置\n课本P~24~ 习题1．2（A组） 第7，8，9题 （B组）第2、3题\n板书设计：\n课后反馈：\n/\n课题：§1.2.2映射\n教材分析：本小节的最后部分是在函数的基础上介绍映射的概念。教科书把映射作为函数的推广来处理，能很好的体现从特殊到一般的认知规律。教学时需要注意以下几点：\n> （1）函数推广到映射，只是把函数中的两个数集推广到两个任意的集合；\n>\n> （2）对于映射f：A/-/--/>B，我们通常把集合A中的元素叫做原象，把集合B中与之对应的元素叫做象。所以集合A叫做原象集，集合B叫做象象所在的集（集合B中可以有元素不是象）\n>\n> （3）映射只要求\"对于集合A中的任何一个元素，在集合B中都有唯一确定的元素与之对应\"，即对于集合A中的每个原象在B中都有象，至于集合B中的元素在A中是否有原象，以及有原象时原象是否唯一等问题不需要考虑的。\n>\n> 在实际的教学时，宜多举学生身边的实际例子帮助理解。\n>\n> 教科书第22页例题7的（1）（2）是以后经常用到的映射，教学时需要引导学生认真理解。对于（3），（4）可以进行变式训练。另外，对于（4）还可以与例题7后面的思考进行比较，让学生进一步体会映射是讲顺序的，即f：A-B与f：B-A是不同的，并且它们中可能都不是映射，也可能有一个是映射，也有可能都是映射。\n课 时：一课时\n教学目的：（1）了解映射的概念及表示方法，了解象、原象的概念；\n（2）结合简单的对应图示，了解一一映射的概念．\n教学重点：映射的概念．\n教学难点：映射的概念．\n教学关键：象与原象的理解\n教学流程：\n教具准备：\n教学过程：\n一、引入课题\n复习初中已经遇到过的对应：\n1.  对于任何一个实数a，数轴上都有唯一的点P和它对应；（数与点的对应）\n2.  对于坐标平面内任何一个点A，都有唯一的有序实数对(x,y)和它对应；（数对与点的对应）\n3.  对于任意一个三角形，都有", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-3b497a1af583da9f3e0b2d4ffced3b77", "__created_at__": 1754880286, "content": "：\n一、引入课题\n复习初中已经遇到过的对应：\n1.  对于任何一个实数a，数轴上都有唯一的点P和它对应；（数与点的对应）\n2.  对于坐标平面内任何一个点A，都有唯一的有序实数对(x,y)和它对应；（数对与点的对应）\n3.  对于任意一个三角形，都有唯一确定的面积和它对应；（图形与数字）\n4.  某影院的某场电影的每一张电影票有唯一确定的座位与它对应；(物与物对应)\n5． 函数的概念．（数与数对应）\n6/. 同学们与自己的座位对应（人与物对应）\n二、新课教学\n1.  很容易的我们可以发现，以上的例子都是对应，而我们所学习的函数只是数与数之间的对应，仅仅是以上这些对应中的一种。现实生活中还有许许多多类似于这些的对应。所以我们有必要对函数这种对应做一个进一步的推广。下面，我们看着函数的概念，想想我们能不能通过修改函数的概念达到这个目的。\n2.  我们已经知道，函数是建立在两个非空数集间的一种对应，若将其中的条件\"非空数集\"弱化为\"任意两个非空集合\"，按照某种法则可以建立起更为普通的元素之间的对应关系，这种的对应就叫映射（mapping）．\n3.  什么叫做映射？\n一般地，设A、B是两个非空的集合，如果按某一个确定的对应法则f，使对于集合A中的任意一个元素x，在集合B中都有唯一确定的元素y与之对应，那么就称对应f：AB为从集合A到集合B的一个映射（mapping）．记作\"f：AB\"\n说明：（1）这两个集合有先后顺序，A到B的映射与B到A的映射是截然不同的．其中f表示具体的对应法则，可以用汉字叙述．\n（2）\"都有唯一\"什么意思？\n包含两层意思：一是必有一个；二是只有一个，也就是说有且只有一个的意思\n三、例题分析\n例题1、下列哪些对应是从集合A到集合B的映射？\n（1）A={P /|\nP是数轴上的点}，B=R，对应关系f：数轴上的点与它所代表的实数对应；\n（2）A={ P /| P是平面直角体系中的点}，B={（x，y）/|\nx∈R，y∈R}，对应关系f：平面直角体系中的点与它的坐标对应；\n（3）A={三角形}，B={x /|\nx是圆}，对应关系f：每一个三角形都对应它的内切圆；\n（4）A={x /| x是新华中学的班级}，B={x /|\nx是新华中学的学生}，对应关系f：每一个班级都对应班里的学生．\n思考：将（3）中的对应关系f改为：每一个圆都对应它的内接三角形；（4）中的对应关系f改为：每一个学生都对应他的班级，那么对应f：\nBA是从集合B到集合A的映射吗？\n四、课本练习\nP23练习4\n五、作业布置\nP24习题1.2 第10题\n补充题：\n板书设计：\n课后反馈：\n/\n课题：§1.3.1函数的单调性\n教材分析：教科书以学生熟悉的一次函数，二次函数为例，给出函数的图像，让学生从图像中获得\"上升\"\"下降\"的整体认识。针对二次函数给出数据表，结合数据表，用自然语言描述图像特征\"上升\"\"下降\"，即图像在y轴左侧\"下降\"，也就是在区间上，随着x的增大，相应的f（x）（函数）的值在减小；图像在y轴的右侧\"上升\"，即在区间上，随着x的增大，相应的f（x）的值也在增大。\n对于例题1，学生很可能会提出这样的一个问题：在两个区间的公共端点处，比如点x=-2处，这个函数是增函数还是减函数？这里需要向学生说明，函数的单调性是对定义域内的某个连续区间而言的。其一，对于单独的一点，由于它的函数值是唯一确定的常数，因而没有增减变化，所以不存在单调性问题。其二，虽然f（x）在区间，上都是减函数，但不能说f（x）在区间上是减函数。其三，有些函数在整个定义域内具有单调性，例如一次函数；有些函数在定义域内的某些区间上是增函数，而在另一些区间上是减函数，例如二次函数；有些函数没有单调区间，例如函数y=1；有的函数的定义域根本就不是区间，例如1.2.2小节例题3中的函数y=5x，x∈{", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-a0811701b65b95ce47491b09e44ff2a6", "__created_at__": 1754880286, "content": "减函数。其三，有些函数在整个定义域内具有单调性，例如一次函数；有些函数在定义域内的某些区间上是增函数，而在另一些区间上是减函数，例如二次函数；有些函数没有单调区间，例如函数y=1；有的函数的定义域根本就不是区间，例如1.2.2小节例题3中的函数y=5x，x∈{1，2，3，4，5}。\n例题2有两个目的，一是利用函数的单调性证明物理里面的玻意耳定律，让学生感受到函数单调性的初步应用；二是表明用函数单调性定义证明函数在某个区间上单调性的基本步骤。其后的\"探究\"，可以让学生进一步理解函数单调性中的\"任意性\"。同时启发学生获得旁注所给的认识。\n课 时：一课时\n教学目的：（1）通过已学过的函数特别是二次函数，理解函数的单调性及其几何意义；\n> （2）学会运用函数图象理解和研究函数的性质；\n>\n> （3）能够熟练应用定义判断数在某区间上的的单调性．\n教学重点：函数的单调性及其几何意义．\n教学难点：利用函数的单调性定义判断、证明函数的单调性．\n教学关键：运用符号语言将自然语言的描述提升到形式化的定义。教学时让学生任意在取两个不同的自变量的值，计算对应的函数值，使学生自己发现自变量越大的函数值越小。同样的让学生在任取两个不同的自变量的值，计算对应的函数值，使学生自己发现自变量越大函数值也越大。最后归纳出增函数，减函数的定义。\n利用函数的单调性的定义来判断函数的单调性是难点，其主要原因在于学生比较大小的能力不足，因此要对函数的复杂程度加以控制，同时要帮助学生建立判断函数单调性的基本步骤。\n教学流程：\n教具准备：电脑，多媒体，大三角板\n教学过程：\n1.  引入课题\n```{=html}\n<!-- -->\n```\n1.  观察下列各个函数的图象，并说说它们分别反映了相应函数的哪些变化规律：\n随x的增大，y的值有什么变化？\n能否看出函数的最大、最小值？\n函数图象是否具有某种对称性？\n2.  画出下列函数的图象，观察其变化规律：\n> （1）f(x) = x\n>\n> 从左至右图象上升还是下降 /_/_/_/_/_/_?\n>\n> 在区间 /_/_/_/_/_/_/_/_/_/_/_/_ 上，随着x的增\n>\n> 大，f(x)的值随着 /_/_/_/_/_/_/_/_ ．\n>\n> （2）f(x) = -2x+1\n>\n> 从左至右图象上升还是下降 /_/_/_/_/_/_?\n>\n> 在区间 /_/_/_/_/_/_/_/_/_/_/_/_ 上，随着x的增\n>\n> 大，f(x)的值随着 /_/_/_/_/_/_/_/_ ．\n>\n> （3）f(x) = x^2^\n>\n> 在区间 /_/_/_/_/_/_/_/_/_/_/_/_ 上，f(x)的值随着x的增大而\n> /_/_/_/_/_/_/_/_ ．\n>\n> 在区间 /_/_/_/_/_/_/_/_/_/_/_/_ 上，f(x)的值随\n>\n> 着x的增大而 /_/_/_/_/_/_/_/_ ．\n2.  新课教学\n（一）函数单调性定义\n1．增函数\n一般地，设函数y=f(x)的定义域为I，\n如果对于定义域I内的某个区间D内的任意两个自变量x~1~，x~2~，当x~1~/<x~2~时，都有f(x~1~)/<f(x~2~)，那么就说f(x)在区间D上是增函数（increasing\nfunction）．\n思考：仿照增函数的定义说出减函数的定义．（学生活动）\n注意：\n函数的单调性是在定义域内的某个区间上的性质，是函数的局部性质；\n必须是对于区间D内的任意两个自变量x~1~，x~2~；当x~1~/<x~2~时，总有f(x~1~)/<f(x~2~)\n．\n2．函数的单调性定义\n> 如果函数y=f(x)在某个区间上是增函数或是减函数，那么就说函数y=f(x)在这一区间具有（严格的）单调性，区间D叫做y=f(x)的单调区间：\n3．判断函数单调性的方法步骤\n利用定义证明函数f(x)在给定的区间D上的单调性的一般步骤：\n取值（任取x~1~，x~2~∈D，且x~1~/<x~2~）\n作差（f(x~1~)－f", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-f3312a397171b6e8223ca85189b1ab44", "__created_at__": 1754880286, "content": "在这一区间具有（严格的）单调性，区间D叫做y=f(x)的单调区间：\n3．判断函数单调性的方法步骤\n利用定义证明函数f(x)在给定的区间D上的单调性的一般步骤：\n取值（任取x~1~，x~2~∈D，且x~1~/<x~2~）\n作差（f(x~1~)－f(x~2~)）；\n> 变形（通常是因式分解和配方）；\n>\n> 定号（即判断差f(x~1~)－f(x~2~)的正负）；\n>\n> 下结论（即指出函数f(x)在给定的区间D上的单调性）．\n（二）典型例题\n> 例1．（教材P~29~例1）根据函数图象说明函数的单调性．\n>\n> 解：（略）\n>\n> 巩固练习：课本P~32~练习第1、2题\n>\n> 例2．（教材P~29~例2）根据函数单调性定义证明函数的单调性．\n>\n> 解：（略）\n巩固练习：\n> 课本P~32~练习第3题；\n证明函数在（1，+∞）上为增函数．\n> 例3．作出函数y =－x^2^ +2 /| x /| + 3的图象并指出它的的单调区间．\n>\n> 解：（略）\n>\n> 思考：画出反比例函数的图象．\n>\n> 这个函数的定义域是什么？\n>\n> 它在定义域*I*上的单调性怎样？证明你的结论．\n>\n> 说明：本例可利用几何画板、函数图象生成软件等作出函数图象．\n3.  归纳小结，强化思想\n函数的单调性一般是先根据图象判断，再利用定义证明．画函数图象通常借助计算机，求函数的单调区间时必须要注意函数的定义域，单调性的证明一般分五步：\n取 值 → 作 差 → 变 形 → 定 号 → 下结论\n4.  作业布置\n```{=html}\n<!-- -->\n```\n1.  书面作业：课本P~39~ 习题1．3（A组） 第1，2，3题．\n2.  提高作业：设f(x)是定义在*R*上的增函数，f(xy)=f(x)+f(y)，\n> 求f(0)、f(1)的值；\n>\n> 若f(3)=1，求不等式f(x)+f(x-2)/>1的解集．\n板书设计：\n课后反馈：\n/\n课题：§1.3.1函数的最大（小）值\n教材分析：函数的最大（小）值的定义是借助于二次函数及其图像引出的，概念的出现任然遵循从特殊到一般的原则。第30页给出了两个\"思考\"，前一个是给学生提供尝试的机会，也为引出最大值的概念做个准备。后一个是让学生学会用类比的方法独立获得最小值的概念。\n例题3是一个实际应用问题，教学时也可以用信息技术作出函数图像，然后通过追踪点坐标的变化，观察和体会问题的实际意义。\n例题4表明，高一阶段利用函数的单调性求函数的最大（小）值是常用方法。同时，又一次让学生体会用函数的单调性定义证明函数的单调性的方法。\n课 时：一课时\n教学目的：（1）理解函数的最大（小）值及其几何意义；\n> （2）学会运用函数图象理解和研究函数的性质；\n教学重点：函数的最大（小）值及其几何意义．\n教学难点：利用函数的单调性求函数的最大（小）值．\n教学关键：\n教学流程：\n教具准备：电脑，多媒体\n教学过程：\n1.  引入课题\n画出下列函数的图象，并根据图象解答下列问题：\n> 说出y=f(x)的单调区间，以及在各单调区间上的单调性；\n>\n> 指出图象的最高点或最低点，并说明它能体现函数的什么特征？\n>\n> （1） （2）\n>\n> （3） （4）\n二、新课教学\n（一）函数最大（小）值定义\n1．最大值\n一般地，设函数y=f(x)的定义域为*I*，如果存在实数M满足：\n（1）对于任意的x∈*I*，都有f(x)≤M；\n（2）存在x~0~∈*I*，使得f(x~0~) = M\n那么，称M是函数y=f(x)的最大值（Maximum Value）．\n思考：仿照函数最大值的定义，给出函数y=f(x)的最小值（Minimum\nValue）的定义．（学生活动）\n注意：\n函数最大（小）首先应该是某一个函数值，即存在x~0~∈*I", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-812f88b18c5a553bddb13fe3bbf4293c", "__created_at__": 1754880286, "content": "存在x~0~∈*I*，使得f(x~0~) = M\n那么，称M是函数y=f(x)的最大值（Maximum Value）．\n思考：仿照函数最大值的定义，给出函数y=f(x)的最小值（Minimum\nValue）的定义．（学生活动）\n注意：\n函数最大（小）首先应该是某一个函数值，即存在x~0~∈*I*，使得f(x~0~) =\nM；\n函数最大（小）应该是所有函数值中最大（小）的，即对于任意的x∈*I*，都有f(x)≤M（f(x)≥M）．\n2．利用函数单调性的判断函数的最大（小）值的方法\n利用二次函数的性质（配方法）求函数的最大（小）值\n利用图象求函数的最大（小）值\n利用函数单调性的判断函数的最大（小）值\n如果函数y=f(x)在区间/[a，b/]上单调递增，在区间/[b，c/]上单调递减则函数y=f(x)在x=b处有最大值f(b)；\n如果函数y=f(x)在区间/[a，b/]上单调递减，在区间/[b，c/]上单调递增则函数y=f(x)在x=b处有最小值f(b)；\n（二）典型例题\n> 例1．（教材P~30~例3）利用二次函数的性质确定函数的最大（小）值．\n>\n> 解：（略）\n说明：对于具有实际背景的问题，首先要仔细审清题意，适当设出变量，建立适当的函数模型，然后利用二次函数的性质或利用图象确定函数的最大（小）值．\n> 巩固练习：如图，把截面半径为\n>\n> 25cm的圆形木头锯成矩形木料，\n>\n> 如果矩形一边长为x，面积为y\n>\n> 试将y表示成x的函数，并画出\n>\n> 函数的大致图象，并判断怎样锯\n>\n> 才能使得截面面积最大？\n>\n> 例2．（新题讲解）\n>\n> 旅 馆 定 价\n>\n> 一个星级旅馆有150个标准房，经过一段时间的经营，经理得到一些定价和住房率的数据如下：\n------------ -------------\n房价（元）   住房率（%）\n160          55\n140          65\n120          75\n100          85\n------------ -------------\n> 欲使每天的的营业额最高，应如何定价？\n>\n> 解：根据已知数据，可假设该客房的最高价为160元，并假设在各价位之间，房价与住房率之间存在线性关系．\n>\n> 设为旅馆一天的客房总收入，为与房价160相比降低的房价，因此当房价为元时，住房率为，于是得\n>\n> =150··．\n>\n> 由于≤1，可知0≤≤90．\n>\n> 因此问题转化为：当0≤≤90时，求的最大值的问题．\n>\n> 将的两边同除以一个常数0.75，得~1~=－^2^＋50＋17600．\n>\n> 由于二次函数~1~在=25时取得最大值，可知也在=25时取得最大值，此时房价定位应是160－25=135（元），相应的住房率为67.5%，最大住房总收入为13668.75（元）．\n>\n> 所以该客房定价应为135元．（当然为了便于管理，定价140元也是比较合理的）\n>\n> 例3．（教材P~37~例4）求函数在区间/[2，6/]上的最大值和最小值．\n>\n> 解：（略）\n>\n> 注意：利用函数的单调性求函数的最大（小）值的方法与格式．\n巩固练习：（教材P~38~练习4）\n1.  归纳小结，强化思想\n函数的单调性一般是先根据图象判断，再利用定义证明．画函数图象通常借助计算机，求函数的单调区间时必须要注意函数的定义域，单调性的证明一般分五步：\n取 值 → 作 差 → 变 形 → 定 号 → 下结论\n2.  作业布置\n```{=html}\n<!-- -->\n```\n1.  书面作业：课本P~39~ 习题1．3（A组） 第5题；（B组）第1，2题\n> 提高作业：快艇和轮船分别从A地和C地同时开出，如下图，各沿箭头方向航行，快艇和轮船的速度分别是45\n> km/h和15\n> km/h，已知AC=150km，经过多少时间后，快艇和轮船之间的距离最短？\n板书设计：\n课后反馈：\n/\n课题：§1.3.2函数的奇偶性\n教材分析：教科书在处理函数的奇偶性的时候，沿用了处理函数单调性的方法，即", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-020ba4f8f874cd610a64eabbae8b4a5a", "__created_at__": 1754880286, "content": "，各沿箭头方向航行，快艇和轮船的速度分别是45\n> km/h和15\n> km/h，已知AC=150km，经过多少时间后，快艇和轮船之间的距离最短？\n板书设计：\n课后反馈：\n/\n课题：§1.3.2函数的奇偶性\n教材分析：教科书在处理函数的奇偶性的时候，沿用了处理函数单调性的方法，即先给出几个特殊的函数图像，让学生通过图像获取函数奇偶性的认识，然后利用表格探究数量变化特征，通过代数运算，验证发现的数量特征对定义域中的\"任意\"值都成立，最后在这个基础上建立奇偶函数的概念。\n对于奇函数，教科书在给出的表格中留下了大部分空格，旨在让学生自己动手计算填写数据，仿照偶函数概念建立的过程，独立的去经历发现，猜想与证明的全过程，从而建立奇函数的概念。\n教科书第35页上的思考2，意在让学生利用函数的奇偶性画函数的图像。教学时可将练习的第1题与之配合。奇函数的图像关于原点对称，偶函数的图像关于y轴对称，所以，奇偶函数有一个很重要的性质，就是X轴上表示函数定义域的线段一定关于原点对称。\n教学时，可以通过具体的例子引导学生认识，并不是所有的函数都具有奇偶性，如函数既不是奇函数也不是偶函数，这可以从图像上看出，也可以由定义去说明，以为它的定义域是，即x取负值时函数无意义，所以不满足奇函数与偶函数的定义。\n例题5的教学可以与练习的第1题结合进行，主要目的是让学生学会用奇偶函数的定义去判断函数的奇偶性。判断一个函数是奇函数，或者是偶函数，或者既不是奇函数也不是偶函数，叫做判断函数的奇偶性。这是在研究函数的性质时应予考察的一个重要方面。对于一个奇函数或偶函数，根据它的图像关于原点或y轴对称的特性，就可由自变量取正时的图像和性质，来推断它在整个定义域内的图像和性质。\n课 时：一课时\n教学目的：（1）理解函数的奇偶性及其几何意义；\n> （2）学会运用函数图象理解和研究函数的性质；\n>\n> （3）学会判断函数的奇偶性．\n教学重点：函数的奇偶性及其几何意义．\n教学难点：判断函数的奇偶性的方法与格式．\n教学关键：函数奇偶性定义的引入要与函数奇偶性定义相结合，概念分析要到位，板演要严谨，示范性要强。归纳出判断或证明函数奇偶性的步骤和关键\n教学流程：\n教具准备：电脑，多媒体\n教学过程：\n1.  引入课题\n1/. 用列表法作出下列函数的图像：\n（1）f（x）=x^2^ （2）f（x）=/|x/| （3）f（x）=2x （4）f（x）=x^3^\n2．观察所作出的图形，思考并讨论以下的问题：\n（1）大家能不能把这四个图像分成两类呢？为什么这样分类？\n答：前面两个函数的图像关于y轴对称，后面两个函数图像关于原点对称。所以前两个函数一类，后两个函数一类\n（2）在第一类函数和第二类函数中，互为相反数的两个自变量的值对应的函数值有什么关系呢？\n答：第一类中对应的函数值相等，第二类中对应的函数值互为相反数。\n二、新课教学\n（一）函数的奇偶性定义\n象前面两个函数，图象关于y轴对称，我们称之为偶函数，像后两个函数，图象关于原点对称的，我们称之为奇函数．\n下面请同学们根据引例的第2题第2问的提示，从函数自变量和因变量的角度来叙述奇函数与偶函数的定义。\n1．偶函数（even function）\n一般地，对于函数f(x)的定义域内的任意一个x，都有f(－x)=f(x)，那么f(x)就叫做偶函数．\n（学生活动）：仿照偶函数的定义给出奇函数的定义\n2．奇函数（odd function）\n一般地，对于函数f(x)的定义域内的任意一个x，都有f(－x)=-f(x)，那么f(x)就叫做奇函数．\n注意：\n函数是奇函数或是偶函数称为函数的奇偶性，函数的奇偶性是函数的整体性质；\n由函数的奇偶性定义可知，函数具有奇偶性的一个必要条件是，对于定义域内的任意一个x，则－x也一定是定义域内的一个自变量（即定义域关于原点对称）．\n（二）具有奇偶性的函数的图象的特征\n偶函数的图象关于y轴对称；", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-de9f61d61d6c384cd79b8d441dee412f", "__created_at__": 1754880286, "content": "是偶函数称为函数的奇偶性，函数的奇偶性是函数的整体性质；\n由函数的奇偶性定义可知，函数具有奇偶性的一个必要条件是，对于定义域内的任意一个x，则－x也一定是定义域内的一个自变量（即定义域关于原点对称）．\n（二）具有奇偶性的函数的图象的特征\n偶函数的图象关于y轴对称；\n奇函数的图象关于原点对称．\n（三）典型例题\n1．判断函数的奇偶性\n> 例1．作出函数f（x）=x^2^，的图像，并判断此函数的奇偶性。\n>\n> 解：（略）\n>\n> 说明：函数具有奇偶性的首要条件是\"定义域关于原点对称\"，所以判断函数的奇偶性应应首先判断函数的定义域是否关于原点对称，若不是即可断定函数是非奇非偶函数．\n>\n> 选题说明：此题是为后面用函数奇偶性的定义判断或证明函数奇偶性做铺垫工作的，解决在判断或证明函数奇偶性时为什么要先判断函数定义域是否关于原点对称，然后再判断或证明函数的奇偶性的问题。\n>\n> 例2．（教材P~35~例题5）判断下列函数的奇偶性\n>\n> （1）f（x）=x^4^ （2）f（x）=x^5^ （3）f（x）= （4）\n>\n> 解：（1）对于函数f（x）=x^4^，其定义域为\n>\n> 因为对定义域内的每一个x，都有\n>\n> 所以，函数f（x）=x^4^为偶函数\n（（2）（3）（4）略）\n总结：利用定义判断函数奇偶性的格式步骤：\n> 首先确定函数的定义域，并判断其定义域是否关于原点对称；\n>\n> 确定f(－x)与f(x)的关系；\n>\n> 作出相应结论：\n>\n> 若f(－x) = f(x) 或 f(－x)－f(x) = 0，则f(x)是偶函数；\n>\n> 若f(－x) =－f(x) 或 f(－x)＋f(x) = 0，则f(x)是奇函数．\n>\n> 巩固练习：（教材P~36~练习第1题）\n2．利用函数的奇偶性补全函数的图象\n> （教材P~35~思考题）\n>\n> 规律：偶函数的图象关于y轴对称；\n>\n> 奇函数的图象关于原点对称．\n说明：这也可以作为判断函数奇偶性的依据．\n> 巩固练习：（教材P~36~练习2）\n3．函数的奇偶性与单调性的关系\n（学生活动）举几个简单的奇函数和偶函数的例子，并画出其图象，根据图象判断奇函数和偶函数的单调性具有什么特殊的特征．\n> 例3．已知f(x)是奇函数，在(0，＋∞)上是增函数，证明：f(x)在(－∞，0)上也是增函数\n>\n> 解：(由一名学生板演，然后师生共同评析，规范格式与步骤)\n>\n> 规律：偶函数在关于原点对称的区间上单调性相反；\n>\n> 奇函数在关于原点对称的区间上单调性一致．\n2.  归纳小结，强化思想\n本节主要学习了函数的奇偶性，判断函数的奇偶性通常有两种方法，即定义法和图象法，用定义法判断函数的奇偶性时，必须注意首先判断函数的定义域是否关于原点对称．单调性与奇偶性的综合应用是本节的一个难点，需要同学们结合函数的图象充分理解好单调性和奇偶性这两个性质．\n3.  作业布置\n```{=html}\n<!-- -->\n```\n3.  书面作业：课本P~39~ 习题1．3（A组） 第6题， B组第3题．\n2．补充作业：判断下列函数的奇偶性：\n> ；\n>\n> ；\n>\n> （）\n3.  课后思考：\n> 已知是定义在R上的函数，\n>\n> 设，\n>\n> 试判断的奇偶性；\n>\n> 试判断的关系；\n>\n> 由此你能猜想得出什么样的结论，并说明理由．\n板书设计：\n课后反馈：\n/\n课题：§2.1.1指数与指数幂的运算\n教材分析：为了让学生在学习之初感受到指数函数的实际背景，教科书先给出了两个实际例子：GDP的增长问题，碳14的衰减问题。前一个问题，既让学生回顾了初中已学的整数指数幂，也让学生感受其中的函数模型，并且还有思想教育价值；后一个问题，让学生体会其中的函数模型的同时，激发学生探究分数指数幂、无理指数�", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-36d41d083bbdc150d8446ea9a43d8080", "__created_at__": 1754880286, "content": "学习之初感受到指数函数的实际背景，教科书先给出了两个实际例子：GDP的增长问题，碳14的衰减问题。前一个问题，既让学生回顾了初中已学的整数指数幂，也让学生感受其中的函数模型，并且还有思想教育价值；后一个问题，让学生体会其中的函数模型的同时，激发学生探究分数指数幂、无理指数幂的兴趣和欲望，为新知识的学习做了铺垫。\n本节安排的内容蕴涵了许多重要的数学思想方法，如推广的思想（指数幂运算律的推广）。逼近的思想（有理指数幂逼近无理指数幂）。\n教科书从问题2中得到，，，。。。。，它们分别表示生物死亡了6000年，10000年，100000年，。。。。。后体内碳14的含量。那么，它们的含义到底是什么呢？这正是需要学习的。教学时可让学生由此体会引进分数指数幂的必要性。\n课 时：一课时\n教学目的：（1）掌握根式的概念；\n> （2）规定分数指数幂的意义；\n>\n> （3）学会根式与分数指数幂之间的相互转化；\n>\n> （4）理解有理指数幂的含义及其运算性质；\n>\n> （5）了解无理数指数幂的意义\n教学重点：分数指数幂的意义，根式与分数指数幂之间的相互转化，有理指数幂的运算性质\n教学难点：根式的概念，根式与分数指数幂之间的相互转化，了解无理数指数幂．\n教学关键：根式的概念是教学的难点，在突破这个难点时，需注意以下几点：\n1.  以具体例子为载体，如2^4^=16，3^5^=243，类比平方根、立方根的定义，给出n次方根的定义\"如果x^n^=a，那么x叫做a的n次方根，其中n/>1，n∈N^/*^\"。教学时，可以在给出定义前，让学生类比平方根，立方根举例。\n2.  在将平方根和立方根的性质推广到n次方根的性质时，除了教科书上的例子，应再为学生提供更多的实例，经过比较得出结论：与立方根的情况一样，奇次方根有下列性质：在实数范围内，正数的奇次方根是一个正数，负数的奇次方根是一个负数；正数的偶次方根是两个绝对值相等，符号相反的数；负数的偶次方根没有意义。\n3.  对于结论\"零的任何次方根都是零\"，要启发学生用n次方根的定义去理解，即因为0^n^=0（n∈N^/*^），所以零的任何次方根都是零，即奇次方根，偶次方根都是零。\n教学流程：\n教具准备：投影\n教学过程：\n2.  引入课题\n```{=html}\n<!-- -->\n```\n1.  以折纸问题引入，激发学生的求知欲望和学习指数概念的积极性\n2.  由实例引入，了解指数指数概念提出的背景，体会引入指数的必要性；\n3.  复习初中整数指数幂的运算性质；\n4.  初中根式的概念；\n> 如果一个数的平方等于a，那么这个数叫做a的平方根，如果一个数的立方等于a，那么这个数叫做a的立方根；\n二、新课教学\n（一）指数与指数幂的运算\n1．根式的概念\n一般地，如果，那么叫做的次方根（n th root），其中/>1，且∈^/*^．\n当是奇数时，正数的次方根是一个正数，负数的次方根是一个负数．此时，的次方根用符号表示．\n式子叫做根式（radical），这里叫做根指数（radical\nexponent），叫做被开方数（radicand）．\n当是偶数时，正数的次方根有两个，这两个数互为相反数．此时，正数的正的次方根用符号表示，负的次方根用符号－表示．正的次方根与负的次方根可以合并成±（/>0）．\n由此可得：负数没有偶次方根；0的任何次方根都是0，记作．\n思考：（课本P~50~探究问题）=一定成立吗？．（学生活动）\n> 结论：当是奇数时，\n>\n> 当是偶数时，\n>\n> 例1．（教材P~50~例1）求下列各式的值：\n>\n> （1） (2) (3) (4)\n>\n> 解：（略）\n巩固练习：（教材P~54~练习1）\n2．", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-a45ce9fee716d4c88933e11700484366", "__created_at__": 1754880286, "content": "课本P~50~探究问题）=一定成立吗？．（学生活动）\n> 结论：当是奇数时，\n>\n> 当是偶数时，\n>\n> 例1．（教材P~50~例1）求下列各式的值：\n>\n> （1） (2) (3) (4)\n>\n> 解：（略）\n巩固练习：（教材P~54~练习1）\n2．分数指数幂\n我们看下面的例子。根据n次方根的定义和数的运算，\n这就是说当根式的被开方数的指数能被根指数整除时，根式可以表示为分数指数幂的形式。\n那么，当根式的被开方数的指数不能被根指数整除时，根式是否也可以表示为分数指数幂的形式呢？例如能否把能否写成？\n我们规定正数的正分数指数幂的意义是\n> 正数的负分数指数幂是：\n0的正分数指数幂等于0，0的负分数指数幂没有意义\n特别指出：规定了分数指数幂的意义后，指数的概念就从整数指数推广到了有理数指数，那么整数指数幂的运算性质也同样可以推广到有理数指数幂．\n3．有理指数幂的运算性质\n（1）· ；\n（2） ；\n（3） ．\n引导学生解决本课开头实例问题\n> 例2．（教材P~51~例2、例3、例4、例5）\n>\n> 说明：让学生熟练掌握根式与分数指数幂的互化和有理指数幂的运算性质运用．\n巩固练习：（教材P~54~练习1，2，3）\n4.  无理指数幂\n> 结合教材P~62~实例利用逼近的思想理解无理指数幂的意义．\n指出：一般地，无理数指数幂是一个确定的实数．有理数指数幂的运算性质同样适用于无理数指数幂．\n思考：（教材P~63~练习4）\n巩固练习思考：：（教材P~62~思考题）\n> 例3．（新题讲解）从盛满1升纯酒精的容器中倒出升，然后用水填满，再倒出升，又用水填满，这样进行5次，则容器中剩下的纯酒精的升数为多少？\n>\n> 解：（略）\n>\n> 点评：本题还可以进一步推广，说明可以用指数的运算来解决生活中的实际问题．\n4.  归纳小结，强化思想\n本节主要学习了根式与分数指数幂以及指数幂的运算，分数指数幂是根式的另一种表示形式，根式与分数指数幂可以进行互化．在进行指数幂的运算时，一般地，化指数为正指数，化根式为分数指数幂，化小数为分数进行运算，便于进行乘除、乘方、开方运算，以达到化繁为简的目的，对含有指数式或根式的乘除运算，还要善于利用幂的运算法则．\n5.  作业布置\n```{=html}\n<!-- -->\n```\n4.  必做题：教材P~59~习题2．1（A组） 第1，2，4题．\n5.  选做题：教材P~60~习题2．1（B组） 第2题．\n板书设计：（略）\n课后反馈：\n/\n课题：§2.1.2指数函数及其性质\n教材分析：本小节内容是在实数指数幂及其运算性质等知识基础上，进一步学习指数函数的概念、图像和性质，及初步运用。\n教科书通过比较本节开始时的问题1和问题2引入的指数函数，以利于学生体会指数函数的概念来自于实践。教学时，要让学生体会到所引入的两个函数所具有的共同的形式特征。从而引出指数函数定义域。在教学指数函数的定义时，可以让学生根据分数指数幂的概念与运算性质思考为什么\"规定a/>0,且a≠1\"，例如在中，指数x取就没有意义。\n函数图像是研究函数性质的直观工具。可利用信息技术，建议让学生亲自操作，通过改变底数a的值获得多个指数函数的图像。教科书第55页的\"思考\"意在让学生获得\"函数的图像与函数的图像关于y轴对称\"的结论，由此体会可以用已知函数的图像及对称性来作新的函数图像。这样做，可以引导学生用联系的观点看问题，通过逻辑推理获得数学结论。\n利用指数函数的图像获取指数函数的性质是本小节的重点。利用函数的图像便于学生发现、概括、记忆函数的性质。在学习指数函数时，建议尽可能的引导学生通过观察图像，自己归纳概括。\n例题6", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-444995e8a08f4b2eed7d78a6bcc97a7a", "__created_at__": 1754880286, "content": "函数的图像及对称性来作新的函数图像。这样做，可以引导学生用联系的观点看问题，通过逻辑推理获得数学结论。\n利用指数函数的图像获取指数函数的性质是本小节的重点。利用函数的图像便于学生发现、概括、记忆函数的性质。在学习指数函数时，建议尽可能的引导学生通过观察图像，自己归纳概括。\n例题6不仅可以使学生在此熟悉函数值的记法，而且还可以让学生学习待定系数法求底数a的值\n例题7的主要目的是应用指数函数的单调性\"比较两个数的大小\"，熟悉指数函数的性质。教学时也可以让学生采用不同的方法解决这个问题。而应用函数单调性判断大小关系的意义在于使学生形成用函数观点解决问题的意识。\n课 时：一课时\n教学任务：（1）使学生了解指数函数模型的实际背景，认识数学与现实生活及其他学科的联系；\n> （2）理解指数函数的的概念和意义，能画出具体指数函数的图象，探索并理解指数函数的单调性和特殊点；\n>\n> （3）在学习的过程中体会研究具体函数及其性质的过程和方法，如具体到一般的过程、数形结合的方法等．\n教学重点：指数函数的的概念和性质．\n教学难点：用数形结合的方法从具体到一般地探索、概括指数函数的性质．\n教学关键：利用信息技术，改变底数a的值获得多个指数函数的图像，总结规律，形成结论\n教学流程：\n教具准备：多媒体\n教学过程：\n3.  引入课题\n> （备选引例）\n5.  （合作讨论）人口问题是全球性问题，由于全球人口迅猛增加，已引起全世界关注．世界人口2000年大约是60亿，而且以每年1.3%的增长率增长，按照这种增长速度，到2050年世界人口将达到100多亿，大有\"人口爆炸\"的趋势．为此，全球范围内敲起了人口警钟，并把每年的7月11日定为\"世界人口日\"，呼吁各国要控制人口增长．为了控制人口过快增长，许多国家都实行了计划生育．\n> 我国人口问题更为突出，在耕地面积只占世界7%的国土上，却养育着22%的世界人口．因此，中国的人口问题是公认的社会问题．2000年第五次人口普查，中国人口已达到13亿，年增长率约为1%．为了有效地控制人口过快增长，实行计划生育成为我国一项基本国策．\n>\n> 按照上述材料中的1%的增长率，从2000年起，x年后我国的人口将达到2000年的多少倍？\n>\n> 到2050年我国的人口将达到多少？\n>\n> 你认为人口的过快增长会给社会的发展带来什么样的影响？\n6.  上一节中GDP问题中时间x与GDP值y的对应关系y=1.073^x^（x∈N^/*^，x≤20）能否构成函数？\n7.  一种放射性物质不断变化成其他物质，每经过一年的残留量是原来的84%，那么以时间x年为自变量，残留量y的函数关系式是什么？\n8.  上面的几个函数有什么共同特征？\n二、 新课教学\n（一）指数函数的概念\n一般地，函数叫做指数函数（exponential\nfunction），其中x是自变量，函数的定义域为R．\n注意： 指数函数的定义是一个形式定义，要引导学生辨析；\n> 注意指数函数的底数的取值范围，引导学生分析底数为什么不能是负数、零和1．\n（二）指数函数的图象和性质\n> 问题：你能类比前面讨论函数性质时的思路，提出研究指数函数性质的内容和方法吗？\n>\n> 研究方法：画出函数的图象，结合图象研究函数的性质．\n>\n> 研究内容：定义域、值域、特殊点、单调性、最大（小）值、奇偶性．\n>\n> 探索研究：\n1．![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image130.png)\n> （1）\n>\n> （2）\n>\n> （3）\n>\n> （4）\n>\n> （5）\n>\n> 2．从画出的图象中你能发现函数的图象和函数的图象有什么关系？可否利用的图象画出的图象？\n>\n> 3．从画出的图象（、和）中，你能发现函数的图象与其底数之间有什么样的规律？\n4．你能根据指数函数的图象的特征归纳出指数函数的性质吗？\n+----------------+----------------+----------------+----------------+\n| 图象特征       | 函数性质       |                |                |\n+----------------+----------------+----------------+----------------+\n|                |                |                |                |\n+----------------+----------------+----------------+----------------+\n| 向x、y轴正     | 函             |                |                |\n| 负方向无限延伸 | 数的定义域为R", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-7975c355bb5c4bac44c6caa13e0b627b", "__created_at__": 1754880286, "content": "的图象的特征归纳出指数函数的性质吗？\n+----------------+----------------+----------------+----------------+\n| 图象特征       | 函数性质       |                |                |\n+----------------+----------------+----------------+----------------+\n|                |                |                |                |\n+----------------+----------------+----------------+----------------+\n| 向x、y轴正     | 函             |                |                |\n| 负方向无限延伸 | 数的定义域为R  |                |                |\n+----------------+----------------+----------------+----------------+\n| 图象关于原     | 非奇非偶函数   |                |                |\n| 点和y轴不对称  |                |                |                |\n+----------------+----------------+----------------+----------------+\n| 函数图         | 函             |                |                |\n| 象都在x轴上方  | 数的值域为R^+^ |                |                |\n+----------------+----------------+----------------+----------------+\n| 函数图象都     |                |                |                |\n| 过定点（0，1） |                |                |                |\n+----------------+----------------+----------------+----------------+\n| 自左向右看，   | 自左向右看，   | 增函数         | 减函数         |\n|                |                |                |                |\n| 图象逐渐上升   | 图象逐渐下降   |                |                |\n+----------------+----------------+----------------+----------------+\n| 在第           | 在第           |                |                |\n| 一象限内的图象 | 一象限内的图象 |                |                |\n| 纵坐标都大于1  | 纵坐标都小于1  |                |                |\n+----------------+----------------+----------------+----------------+\n| 在第           | 在第           |                |                |\n| 二象限内的图象 | 二象限内的图象 |                |                |\n| 纵坐标都小于1  | 纵坐标都大于1  |                |                |\n+----------------+----------------+----------------+----------------+\n| 图象上升       | 图象上升       | 函数           | 函数           |\n| 趋势是越来越陡 | 趋势是越来越缓 | 值开始增长较慢 | 值开始减小极快 |\n|                |                | ，到了某一值后 | ，到了某一值后 |\n|                |                | 增长速度极快； | 减小速度较慢； |\n+----------------+----------------+----------------+----------------+\n> 5.利用函数的单调性，结合图象还可以看出：/\n> （1）在/[a，b/]上，值域是或；/\n> （2）若，则；取遍所有正数当且仅当；/\n> （3）对于指数函数，总有；/\n> （4）当时，若，则；\n（三）典型例题\n> 例1．（教材P~56~例6）已知指数函数的图像经过点（3，），求f（0），f（1），f（-3）的值。\n>\n> 解：（略）\n>\n> 问题：你能根据本例说出确定一个指数函数需要几个条件吗？\n>\n> 例2．（教材P~57~例7）比较下列各题中两个值的大小：\n>\n> （1） （2） （3）\n>\n> 解：（略）\n>\n> 问题：你能根据本例说明怎样利用指数函数的性质判断两个幂的大小？\n>\n> 说明：规范利用指数函数的性质判断两个幂的大小方法、步骤与格式．\n巩固练习：（教材P~59~习题A组第5，7，8题单号题）\n三、归纳小结，强化思想\n本节主要学习了指数函数的图象，及利用图象研究函数性质的方法．\n四、作业布置\n1.  必做题：教材P~59~习题2．1（A组） 第5、7，8的双号题以及第6题，第9题．\n2.  选做题：教材P~70~习题2．1（B组） 第1，3，4题．\n板书设计：（略）\n课后反馈：\n/\n课题：§2.2.1对数\n教材分析：本小节包括对数的定义，对数式与指数式互化，对数的运算性质及对数的初步应用。\n第62页的思考的目的是让学生从人口问题感受到对数的现实背景，并引出对数的概念。在给出对数概念后，建议让学生就具体的对数进行表述，特别是将人口问题中的时间用对数来表示。对于常用对数和自然对数，只要让学生掌握这两个对数的定义和它们的符号即可。\n由对数的定义可以得到对数与指数之间的关系：\n教学时，引导学生利用这个关系和已经学习的指数幂的相关知识解决如下问题：\n（1）说明为何在对数中要规定。\n（2）指数式，对数式中各个符号的名称是什么？要让学生认清对数式的含义：明确a，N，b相对于指数式是什么，并找出它们之间的关系；其次要掌握各数的名称和式子的读法。\n（3）为什么负数", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-3c87a4a6f14c93c0119974dff81ea620", "__created_at__": 1754880286, "content": "导学生利用这个关系和已经学习的指数幂的相关知识解决如下问题：\n（1）说明为何在对数中要规定。\n（2）指数式，对数式中各个符号的名称是什么？要让学生认清对数式的含义：明确a，N，b相对于指数式是什么，并找出它们之间的关系；其次要掌握各数的名称和式子的读法。\n（3）为什么负数和零没有对数。在中，必须N/>0，这是由于在实数范围内，正数的任何次幂都是正数。因而中N总是正数。\n（4）推导\n例题1，2的目的是让学生通过实例进一步熟悉对数式与指数式的互化，以及加深对式中各字母意义的理解。教学时，可让学生课堂完成随后配备的练习。\n课 时：一课时\n教学目的：（1）理解对数的概念；\n> （2）能够说明对数与指数的关系；\n>\n> （3）掌握对数式与指数式的相互转化．\n教学重点：对数的概念，对数式与指数式的相互转化\n教学难点：对数概念的理解．\n教学关键：\n教学流程：\n教具准备：无\n教学过程：\n1.  引入课题\n1.  （对数的起源）介绍对数产生的历史背景与概念的形成过程，体会引入对数的必要性；\n> 设计意图：激发学生学习对数的兴趣，培养对数学习的科学研究精神．\n2.  尝试解决本小节开始提出的问题．\n```{=html}\n<!-- -->\n```\n2.  新课教学\n1．对数的概念\n一般地，如果，那么数叫做以为底的对数（Logarithm），记作：\n--- 底数，--- 真数，--- 对数式\n说明： 注意底数的限制，且；\n> ；\n>\n> 注意对数的书写格式．\n思考： 为什么对数的定义中要求底数，且；\n> 是否是所有的实数都有对数呢？\n设计意图：正确理解对数定义中底数的限制，为以后对数型函数定义域的确定作准备．\n两个重要对数：\n> 常用对数（common logarithm）：以10为底的对数；\n>\n> 自然对数（natural logarithm）：以无理数为底的对数的对数．\n2.  对数式与指数式的互化\n> 对数式 指数式\n>\n> 对数底数 ← → 幂底数\n>\n> 对数 ← → 指数\n>\n> 真数 ← → 幂\n例题1、（教材P~63~例1）将下列指数函数化为对数式，对数式化为指数式：\n（1）5^4^=625 （2）2^-6^= （3） （4）\n（5） （6）ln10=2.303\n巩固练习：（教材P~64~练习1、2）\n设计意图：熟练对数式与指数式的相互转化，加深理解对数概念．\n说明：本例题和练习均让学生独立阅读思考完成，并指出对数式与指数式的互化中应注意哪些问题．\n3.  对数的性质\n> （学生活动）\n阅读教材P~63~例2，指出其中求的依据；\n例题2、求下列各式中x的值：\n> /(1/) (2)\n>\n> (3)lg100=x (4)\n独立思考完成教材P~64~练习3、4，指出其中蕴含的结论\n> 对数的性质\n>\n> （1）负数和零没有对数；\n>\n> （2）1的对数是零：；\n>\n> （3）底数的对数是1：；\n>\n> （4）对数恒等式：；\n>\n> （5）．\n巩固练习：（教材P~64~练习3、4）\n3.  归纳小结，强化思想\n> 引入对数的必要性；\n>\n> 指数与对数的关系；\n>\n> 对数的基本性质．\n4.  作业布置\n> 教材P~74~习题2．2（A组） 第1、2题。\n板书设计：（略）\n课后反馈：\n/\n课题：§2.2.1对数的运算性质\n教材分析：对数的运算性质是进行对数运算的重要依据，是本小节的重点之一。教科书的思路是根据指数与对数的关系及指数运算性质，推出对数运算的性质。教科书给出了性质1的推导过程，这是一个纯粹的数学推理过程。另两个运算性质可以让学生自己推导，以进一步理解对数与指数间的关系。\n教学时，要注意将指数与对数的运算性质进行对照加以复习和巩固。对数的换底公式是进行对数运算的重要基础，这里只要求学生知道换底公式并利用它将对数转化为常用对数或自然对数来计算，因此教科书把换底公式的证明", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-be507672e78029fa6f4609b59a3c3430", "__created_at__": 1754880286, "content": "。另两个运算性质可以让学生自己推导，以进一步理解对数与指数间的关系。\n教学时，要注意将指数与对数的运算性质进行对照加以复习和巩固。对数的换底公式是进行对数运算的重要基础，这里只要求学生知道换底公式并利用它将对数转化为常用对数或自然对数来计算，因此教科书把换底公式的证明作为学生的\"探究\"活动。学生了解换底公式后，第一个应用就是解决引入对数概念时人口问题中的设问。\n例题3和例题4的目的是让学生熟悉对数的运算性质，了解简单对数的计算及对数式的化简。教学时，可让学生结合例题3和例题4的学习课堂完成配备的练习。\n课 时：一课时\n教学目的：（1）理解对数的运算性质；\n> （2）知道用换底公式能将一般对数转化成自然对数或常用对数；\n>\n> （3）通过阅读材料，了解对数的发现历史以及对简化运算的作用．\n教学重点：对数的运算性质，用换底公式将一般对数转化成自然对数或常用对数\n教学难点：对数的运算性质和换底公式的熟练运用．\n教学关键：\n教学流程：\n教具准备：无\n教学过程：\n1.  引入课题\n1.  对数的定义：；\n2.  对数恒等式：；\n二、新课教学\n1．对数的运算性质\n提出问题：根据对数的定义及对数与指数的关系解答下列问题：\n> 设，，求；\n>\n> 设，，试利用、表示·．\n（学生独立思考完成解答，教师组织学生讨论评析，进行归纳总结概括得出对数的运算性质１，并引导学生仿此推导其余运算性质）\n运算性质：\n如果，且，，，那么：\n·＋；\n－；\n．\n（引导学生用自然语言叙述上面的三个运算性质）\n学生活动：\n> 阅读教材Ｐ~65~例3、4，；\n设计意图：在应用过程中进一步理解和掌握对数的运算性质．\n> 完成教材Ｐ~68~练习1/~3\n设计意图：在练习中反馈学生对对数运算性质掌握的情况，巩固所学知识．\n> 2．利用科学计算器求常用对数和自然对数的值\n设计意图：学会利用计算器、计算机求常用对数值和自然对数值的方法．\n思考：对于本小节开始的问题中，可否利用计算器求解的值？从而引入换底公式．\n3.换底公式\n> （，且；，且；）．\n>\n> 学生活动\n>\n> 根据对数的定义推导对数的换底公式．\n设计意图：了解换底公式的推导过程与思想方法，深刻理解指数与对数的关系．\n> 思考完成教材P~62~问题（即本小节开始提出的问题）；\n>\n> 利用换底公式推导下面的结论\n>\n> （1）；\n>\n> （2）．\n设计意图：进一步体会并熟练掌握换底公式的应用．\n说明：利用换底公式解题时常常换成常用对数，但有时还要根据具体题目确定底数．\n4.课堂练习\n> 教材Ｐ68练习3，4\n>\n> 已知\n>\n> 试求：的值。（对换5与2，再试一试）\n>\n> 设,，试用、表示\n三、归纳小结，强化思想\n本节主要学习了对数的运算性质和换底公式的推导与应用，在教学中应用多给学生创造尝试、思考、交流、讨论、表达的机会，更应注重渗透转化的思想方法．\n四、作业布置\n1.  基础题：教材P~74~习题2．2（A组） 第3 /~5、11题；\n2.  提高题：\n> 设,，试用、表示；\n>\n> 设,，试用、表示；\n>\n> 设、、为正数，且，求证：．\n3.  课外思考题：\n> 设正整数、、（≤≤）和实数、、、满足：\n>\n> ，，\n>\n> 求、、的值．\n板书设计：\n课后反馈：\n/\n课题：§2.2.2对数函数（一）\n教材分析：对数函数的图像与性质的研究过程和方法与指数函数是一样的，所以教学时，可以类比指数函数图像和性质的研究，引导学生自己研究对数函数的性质，最后获得对数函数的图像特征和函数性质对应表。\n对数函数的图像和性质是本小节的重点，也是教学的一个难点。突破难点的关键在于认识底数a对函数值变化的影响，而学生对研究过程的参与又是关键，所以，教学时应鼓励学生积极主动的参与获得性质的过程。\n在教学时，应充分", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-112e15435abd28d4152f76a0d727d41c", "__created_at__": 1754880286, "content": "性质的研究，引导学生自己研究对数函数的性质，最后获得对数函数的图像特征和函数性质对应表。\n对数函数的图像和性质是本小节的重点，也是教学的一个难点。突破难点的关键在于认识底数a对函数值变化的影响，而学生对研究过程的参与又是关键，所以，教学时应鼓励学生积极主动的参与获得性质的过程。\n在教学时，应充分利用信息技术。例如，对对数函数中的底数a，在作出函数图像的过程中取为可变量，以便于清楚的看到底数a是如何影响对数函数的。\n例题7的目的是使学生通过求函数的定义域加深对对数函数的理解，重点并非求函数的定义域，建议教学时不要加大这部分的难度。\n例题8的主要目的是应用对数函数的单调性\"比较两个数的大小\"，熟悉对数函数的性质。\n例题9的难点是让学生理解题意，把具体的实际问题化归为数学问题。教学中，还应特别引导，启发学生用所获得的结果去解释实际现象。\n本小节练习的处理：第1题结合绘制对数函数的图像完成，第2题结合例题7完成，第3题结合例题8完成。\n课 时：一课时\n教学任务：（1）通过具体实例，直观了解对数函数模型所刻画的数量关系，初步理解对数函数的概念，体会对数函数是一类重要的函数模型；\n> （2）能借助计算器或计算机画出具体对数函数的图象，探索并了解对数函数的单调性与特殊点；\n>\n> （3）通过比较、对照的方法，引导学生结合图象类比指数函数，探索研究对数函数的性质，培养学生数形结合的思想方法，学会研究函数性质的方法．\n教学重点：掌握对数函数的图象和性质．\n教学难点：对数函数的定义，对数函数的图象和性质及应用．\n教学关键：认识底数a对函数值变化的影响，而学生对研究过程的参与又是关键，所以，教学时应鼓励学生积极主动的参与获得性质的过程。\n教学流程：\n教具准备：\n教学过程：\n1.  引入课题\n> 1．（知识方法准备）\n>\n> 学习指数函数时，对其性质研究了哪些内容，采取怎样的方法？\n设计意图：结合指数函数，让学生熟知对于函数性质的研究内容，熟练研究函数性质的方法------借助图象研究性质．\n对数的定义及其对底数的限制．\n设计意图：为讲解对数函数时对底数的限制做准备．\n> 2．（引例）\n>\n> 教材P~70~引例\n>\n> 处理建议：在教学时，可以让学生利用计算器填写下表：\n--------------- ----- ----- ----- ------ -------\n碳14的含量P     0.5   0.3   0.1   0.01   0.001\n生物死亡年数t\n--------------- ----- ----- ----- ------ -------\n> 然后引导学生观察上表，体会\"对每一个碳14的含量P的取值，通过对应关系，生物死亡年数t都有唯一的值与之对应，从而t是P的函数\"\n> ．（进而引入对数函数的概念）\n2.  新课教学\n（一）对数函数的概念\n1．定义：函数，且叫做对数函数（logarithmic function）\n> 其中是自变量，函数的定义域是（0，+∞）．\n注意： 对数函数的定义与指数函数类似，都是形式定义，注意辨别．如：，\n都不是对数函数，而只能称其为对数型函数．\n> 对数函数对底数的限制：，且．\n（二）对数函数的图象和性质\n> 问题：你能类比前面讨论指数函数性质的思路，提出研究对数函数性质的内容和方法吗？\n>\n> 研究方法：画出函数的图象，结合图象研究函数的性质．\n>\n> 研究内容：定义域、值域、特殊点、单调性、最大（小）值、奇偶性．\n探索研究：\n在同一坐标系中画出下列对数函数的图象；（可用描点法，也可借助科学计算器或计算机）\n（1） （2）\n（3） （4）\n> ![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image250.png)\n> height=\"2.113888888888889in\"}\n>\n> 类比指数函数图象和性质的研究，研究对数函数的性质并填写如下表格：\n+-----------------------------+-----------------------------+--------+--------+\n| 对数函数图象特征            | 对数函数性质                |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n|                             |                             |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 函数图象都在y轴右侧         | 函数的定义域为（0，＋∞）    |        |        |\n+-----------------------------+-----------------------------+--------+", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-f1d9a9a21eb036b8ea381cd534afb066", "__created_at__": 1754880286, "content": "-----------------------------+--------+--------+\n| 对数函数图象特征            | 对数函数性质                |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n|                             |                             |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 函数图象都在y轴右侧         | 函数的定义域为（0，＋∞）    |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 图象关于原点和y轴不对称     | 非奇非偶函数                |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 向y轴正负方向无限延伸       | 函数的值域为R           |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 函数图象都过定点（1，0）    |                             |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 自左向右看，                | 自左向右看，                | 增函数 | 减函数 |\n|                             |                             |        |        |\n| 图象逐渐上升                | 图象逐渐下降                |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 第一象限的图象纵坐标都大于0 | 第一象限的图象纵坐标都大于0 |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n| 第二象限的图象纵坐标都小于0 | 第二象限的图象纵坐标都小于0 |        |        |\n+-----------------------------+-----------------------------+--------+--------+\n思考底数是如何影响函数的．（学生独立思考，师生共同总结）\n规律：在第一象限内，自左向右，图象对应的对数函数的底数逐渐变大．\n（三）典型例题\n> 例1．（教材P~71~例7）．\n>\n> 解：（略）\n>\n> 说明：本例主要考察学生对对数函数定义中底数和定义域的限制，加深对对数函数的理解．\n>\n> 巩固练习：（教材P~73~练习2）．\n>\n> 例2．（教材P~72~例8）比较下列各组数中值的大小：\n>\n> （1） （2）\n>\n> （3） （a/>0,且a≠1）\n>\n> 解：（略）\n>\n> 说明：本例主要考察学生利用对数函数的单调性\"比较两个数的大小\"的方法，熟悉对数函数的性质，渗透应用函数的观点解决问题的思想方法．\n>\n> 注意：本例应着重强调利用对数函数的单调性比较两个对数值的大小的方法，规范解题格式．\n巩固练习：（教材P~73~练习3）．\n> 例3．（教材P~72~例9）\n>\n> 解：（略）\n>\n> 说明：本例主要考察学生对实际问题题意的理解，把具体的实际问题化归为数学问题．\n>\n> 注意：本例在教学中，还应特别启发学生用所获得的结果去解释实际现象．\n巩固练习：（教材P~74~习题2．2 A组第6题）．\n3.  归纳小结，强化思想\n本小节的目的要求是掌握对数函数的概念、图象和性质．在理解对数函数的定义的基础上，掌握对数函数的图象和性质是本小节的重点．\n4.  作业布置\n> 教材P~74~习题2．2（A组） 第7、8、9、12题．\n板书设计：\n课后反馈：\n/\n课题：§2.2.2对数函数及其性质（二）\n教材分析：\n课 时：一课时\n教学任务：（1）进一步理解对数函数的图象和性质；\n> （2）熟练应用对数函数的图象和性质，解决一些综合问题；\n>\n> （3）通过例题和练习的讲解与演练，培养学生分析问题和解决问题的能力．\n教学重点：对数函数的图象和性质．\n教学难点：对对数函数的性质的综合运用．\n教学关键：对对数函数图像和性质的理解\n教学流程：\n教具准备：\n教学过程：\n1.  回顾与总结\n```{=html}\n<!-- -->\n```\n1.  函数的图象如图所示，回答下列问题．\n![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image261.png)\nheight=\"1.6916666666666667in\"}（1）说明哪个函数对应于哪个图象，并解释为什么？\n（2）函数与\n且有什么关系？图象之间 又有什么特殊的关系？\n（3）以的图象为基础，在同一坐标系中画出的图象．\n![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image268.png)\nheight=\"1.475in\"}（4）已知函数的图象，则底数之间的关系： ．\n2.  完成下表（对", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-42fd5d01bea98c6aae2bcf62fa951658", "__created_at__": 1754880286, "content": "与\n且有什么关系？图象之间 又有什么特殊的关系？\n（3）以的图象为基础，在同一坐标系中画出的图象．\n![](/static/Images/c72af4bdba1f454fa890bc6d35622724/media/image268.png)\nheight=\"1.475in\"}（4）已知函数的图象，则底数之间的关系： ．\n2.  完成下表（对数函数且的图象和性质）\n+--------+---+---+\n|        |   |   |\n+--------+---+---+\n| 图     |   |   |\n|        |   |   |\n| 象     |   |   |\n+--------+---+---+\n| 定义域 |   |   |\n+--------+---+---+\n| 值域   |   |   |\n+--------+---+---+\n| 性     |   |   |\n|        |   |   |\n| 质     |   |   |\n+--------+---+---+\n3.  根据对数函数的图象和性质填空．\n> 已知函数，则当时， ；当时， ；当时， ；当时， ．\n>\n> 已知函数，则当时， ；当时， ；当时， ；当时， ；当时， ．\n2.  应用举例\n```{=html}\n<!-- -->\n```\n1.  比较大小： ，且；\n> ，．\n>\n> 解：（略）\n>\n> 例2．已知恒为正数，求的取值范围．\n>\n> 解：（略）\n>\n> /[总结点评/]：（由学生独立思考，师生共同归纳概括）．\n．\n> 例3．求函数的定义域及值域．\n>\n> 解：（略）\n>\n> 注意：函数值域的求法．\n>\n> 例4．（1）函数在/[2，4/]上的最大值比最小值大1，求的值；\n>\n> （2）求函数的最小值．\n>\n> 解：（略）\n>\n> 注意：利用函数单调性求函数最值的方法，复合函数最值的求法．\n>\n> 例5．（2003年上海高考题）已知函数，求函数的定义域，并讨论它的奇偶性和单调性．\n>\n> 解：（略）\n>\n> 注意：判断函数奇偶性和单调性的方法，规范判断函数奇偶性和单调性的步骤．\n>\n> 例6．求函数的单调区间．\n>\n> 解：（略）\n>\n> 注意：复合函数单调性的求法及规律：\"同增异减\"．\n>\n> 练习：求函数的单调区间．\n3.  作业布置\n考试卷一套\n板书设计：\n课后反馈：\n/\n课题：§2.2.2对数函数及其性质（三）\n教材分析：教科书只要求学生知道底数相同的对数函数与指数函数互为反函数，不要求学生讨论形式化的反函数定义，也不要求学生求已知函数的反函数。\n第73页\"探究\"的目的是要学生知道\"按照对应关系，x是y的函数\"，并由此说明同底的指数函数与对数函数互为反函数。教科书从\"过y轴正半轴上任意一点作x轴的平行线，与的图像有且只有一个交点\"及\"对于任意一个y∈（0，+∞），通过式子，x在R中都有唯一确定的值和它对应\"两个方面说明\"（\ny∈（0，+∞））是函数（x∈R）的反函数\"，前者可以让学生从图像上获得直观认识，后者可以回到函数的定义上，前者为后者作了铺垫。\n互为反函数的对数函数和指数函数的图像之间的关系，教科书是以\"探究与发现\"的形式出现的，供有兴趣的学生学习，并不做一般要求。\n完成指数函数，对数函数的教学后，应引导学生回顾，对比这两类函数，对它们形成整体认识，教学时，可以让学生完成指数函数与对数函数的对照表。\n课 时：一课时\n教学目标：\n知识与技能\n理解指数函数与对数函数的依赖关系，了解反函数的概念，加深对函数的模型化思想的理解．\n过程与方法 通过作图，体会两种函数的单调性的异同．\n情感、态度、价值观 对体会指数函数与对数函数内在的对称统一．\n教学重点：两种函数的内在联系，反函数的概念．\n教学难点：反函数的概念．\n教学关键：\n教学流程：\n教具准备：多媒体\n教学过程：\n+----------+----------------------------+----------------------------+\n| 环节     | 呈现教学材料               | 师生互动设计               |\n+----------+----------------------------+----------------------------+\n| 创       | 材料一：                   | 生：独立思考完成，         |\n|          |                            | 讨论展示并分析自己的结果． |\n| 设       | 当生物                     |                            |\n|          | 死亡后，它机体", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-370fdb117fad7ea7877fc6113ccb83d4", "__created_at__": 1754880286, "content": "多媒体\n教学过程：\n+----------+----------------------------+----------------------------+\n| 环节     | 呈现教学材料               | 师生互动设计               |\n+----------+----------------------------+----------------------------+\n| 创       | 材料一：                   | 生：独立思考完成，         |\n|          |                            | 讨论展示并分析自己的结果． |\n| 设       | 当生物                     |                            |\n|          | 死亡后，它机体内原有的碳14 | 师：引导学生分             |\n| 情       | 会按确定的规律衰减，大约每 | 析归纳，总结概括得出结论： |\n|          | 经过5730年衰减为原来的一半 |                            |\n| 境       | ，这个时间称为\"半衰期\"．根 | （1）P和t                  |\n|          | 据这个规律，人们获得了生物 | 之间的对应关系是一一对应； |\n|          | 体碳14含量P与生物死亡年数t |                            |\n|          | 之间的关系．回答下列问题： | （2）P关于t是指数函数；    |\n|          |                            |                            |\n|          | > （1）                    | t关于P是对数函数，它们的   |\n|          | 求生物死亡t年后它机体内的  | 底数相同，所描述的都是碳1  |\n|          | 碳14的含量P，并用函数的观  | 4的衰变过程中，碳14含量P与 |\n|          | 点来解释P和t之间的关系，指 | 死亡年数t之间的对应关系；  |\n|          | 出是我们所学过的何种函数？ |                            |\n|          |                            | （3）本问                  |\n|          | （2）已知一生物体内碳      | 题中的同底数的指数函数和对 |\n|          | 14的残留量为P，试求该生物  | 数函数，是描述同一种关系（ |\n|          | 死亡的年数t，并用函数的观  | 碳14含量P与死亡年数t之间的 |\n|          | 点来解释P和t之间的关系，指 | 对应关系）的不同数学模型． |\n|          | 出是我们所学过的何种函数？ |                            |\n|          |                            |                            |\n|          | （3）这                    |                            |\n|          | 两个函数有什么特殊的关系？ |                            |\n|          |                            |                            |\n|          | （4）                      |                            |\n|          | 用映射的观点来解释P和t之间 |                            |\n|          | 的对应关系是何种对应关系？ |                            |\n|          |                            |                            |\n|          | （5                        |                            |\n|          | ）由此你能获得怎样的启示？ |                            |\n+----------+----------------------------+----------------------------+\n|          | 材料二：由对数函数的定     |                            |\n|          | 义可知，对数函数是把指数函 |                            |\n|          | 数中的自变量与因变量对调位 |                            |\n|          | 置而得出的，在列表画的图象 |                            |\n|          | 时，也是把指数函数的对应值 |                            |\n|          | 表里的和的数值对换，而得到 |                            |\n|          | 对数函数的对应值表，如下： |                            |\n|          |                            |                            |\n|          | 表一 ．                    |                            |\n|          |                            |                            |\n|          |   -- ----- ---- ----       |                            |\n|          | ---- --- --- --- --- ----- |                            |\n|          |      ...   -3   -2         |                            |\n|          |   -1   0   1   2   3   ... |                            |\n|          |      ...                   |                            |\n|          |        1   2   4   8   ... |                            |\n|          |   -- ----- ---- ----       |                            |\n|          | ---- --- --- --- --- ----- |                            |\n+----------+----------------------------+----------------------------+\n| 环节     | 呈现教学材料               | 师生互动设计               |\n+----------+----------------------------+----------------------------+\n|          | 表二 ．                    | 生：                       |\n|          |                            | 仿照材料一分析：与的关系． |\n|          |   -- ----- ---- ----       |                            |\n|          | ---- --- --- --- --- ----- | 师                         |\n|          |      ...   -3   -2         | ：引导学生分析，讲评得出结 |\n|          |   -1   0   1   2   3   ... | 论，进而引出反函数的概念． |\n|          |      ...                   |                            |\n|          |        1   2   4   8   ... |                            |\n|          |   -- ----- ---- ----       |                            |\n|          | ---- --- --- --- --- ----- |                            |\n|          |                            |                            |\n|          | 在同一坐                   |                            |\n|          | 标系中，用描点法画出图象． |                            |\n+----------+----------------------------+----------------------------+\n| 组织探究 | 材料一：反函数的概念：     | 师：说明：                 |\n|", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-d87a45165f2f79023a603c1954ee0753", "__created_at__": 1754880286, "content": "|                            |\n|          |   -- ----- ---- ----       |                            |\n|          | ---- --- --- --- --- ----- |                            |\n|          |                            |                            |\n|          | 在同一坐                   |                            |\n|          | 标系中，用描点法画出图象． |                            |\n+----------+----------------------------+----------------------------+\n| 组织探究 | 材料一：反函数的概念：     | 师：说明：                 |\n|          |                            |                            |\n|          | 当一个函数是               | （1）互为反函数的两个      |\n|          | 一一映射时，可以把这个函数 | 函数是定义域、值域相互交换 |\n|          | 的因变量作为一个新的函数的 | ，对应法则互逆的两个函数； |\n|          | 自变量，而把这个函数的自变 |                            |\n|          | 量作为新的函数的因变量，我 | （2）由反函数的概念可      |\n|          | 们称这两个函数互为反函数． | 知\"单调函数一定有反函数\"； |\n|          |                            |                            |\n|          | 由反函                     | （3）互为反函数的两个      |\n|          | 数的概念可知，同底数的指数 | 函数是描述同一变化过程中两 |\n|          | 函数和对数函数互为反函数． | 个变量关系的不同数学模型． |\n|          |                            |                            |\n|          | 材料二：以与为例研         | 师                         |\n|          | 究互为反函数的两个函数的图 | ：引导学生探索研究材料二． |\n|          | 象和性质有什么特殊的联系？ |                            |\n|          |                            | 生：分组讨                 |\n|          |                            | 论材料二，选出代表阐述各自 |\n|          |                            | 的结论，师生共同评析归纳． |\n+----------+----------------------------+----------------------------+\n| 尝试练习 | > 求下列函数的反函数：     | 生：独立完成．             |\n|          | >                          |                            |\n|          | > （1）； （2）            |                            |\n+----------+----------------------------+----------------------------+\n| 巩固反思 | 从宏观性、关联性角度       |                            |\n|          | 试着给指数函数、对数函数的 |                            |\n|          | 定义、图象、性质作一小结． |                            |\n+----------+----------------------------+----------------------------+\n| 作业反馈 | 1.  求下列函数的反函数：   | 答案：                     |\n|          |                            |                            |\n|          |   -- --- --- --- ---       | 1．互换、的数值．          |\n|          |      1   2   3   4         |                            |\n|          |      3   5   7   9         | 2．略．                    |\n|          |   -- --- --- --- ---       |                            |\n|          |                            |                            |\n|          | 2                          |                            |\n|          | ．（1）试着举几个满足\"对定 |                            |\n|          | 义域内任意实数a、b，都有f  |                            |\n|          | (a·b) = f ( a ) + f ( b )  |                            |\n|          | ．\"的函数实例，你能说出这  |                            |\n|          | 些函数具有哪些共同性质吗？ |                            |\n|          |                            |                            |\n|          | （2）试着举几个满足\"对定   |                            |\n|          | 义域内任意实数a、b，都有f  |                            |\n|          | (a + b) = f ( a )·f ( b )  |                            |\n|          | ．\"的函数实例，你能说出这  |                            |\n|          | 些函数具有哪些共同性质吗？ |                            |\n+----------+----------------------------+----------------------------+\n| 课外活动 | 我们知道                   | 结论：                     |\n|          | ，指数函数，且与对数函数， |                            |\n|          | 且互为反函数，那么，它们的 | 互为反函数的两             |\n|          | 图象有什么关系呢？运用所学 | 个函数的图象关于直线对称． |\n|          | 的数学知识，探索下面几个问 |                            |\n|          | 题，亲自发现其中的奥秘吧！ |                            |\n|          |                            |                            |\n|          | 问题1                      |                            |\n|          | 在同一平面直角坐标系中     |                            |\n|          | ，画出指数函数及其反函数的 |                            |\n|          | 图象，你能发现这两个函数的 |                            |\n|          | 图象有什么特殊的对称性吗？ |                            |\n|          |                            |                            |\n|          | 问题2                      |                            |\n|          | 取图象                     |                            |\n|          | 上的几个点，说出它们关于直 |                            |\n|          | 线的对称点的坐标，并判断它 |                            |\n|          | 们是否在的图象上，为什么？ |                            |\n|          |                            |                            |\n|          | 问题3                      |                            |\n|          | 如果P~0~", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-21b24e4dc123c93d8c93c9c7dbedf55a", "__created_at__": 1754880286, "content": "|\n|          | 问题2                      |                            |\n|          | 取图象                     |                            |\n|          | 上的几个点，说出它们关于直 |                            |\n|          | 线的对称点的坐标，并判断它 |                            |\n|          | 们是否在的图象上，为什么？ |                            |\n|          |                            |                            |\n|          | 问题3                      |                            |\n|          | 如果P~0~（                 |                            |\n|          | x~0~，y~0~）在函数的图象上 |                            |\n|          | ，那么P~0~关于直线的对称点 |                            |\n|          | 在函数的图象上吗，为什么？ |                            |\n|          |                            |                            |\n|          | 问题4                      |                            |\n|          | 由上述                     |                            |\n|          | 探究过程可以得到什么结论？ |                            |\n|          |                            |                            |\n|          | 问题5 上述结论对于指数函数 |                            |\n|          |                            |                            |\n|          | ，且及其反                 |                            |\n|          | 函数，且也成立吗？为什么？ |                            |\n+----------+----------------------------+----------------------------+\n|          |                            |                            |\n+----------+----------------------------+----------------------------+\n板书设计：\n课后反馈：\n/\n课题：§2.3幂函数\n教材分析：教科书从实际问题得到五个常用的幂函数，从而引出幂函数的概念。教学时只需要对它们的图像与基本性质进行认识，不必在一般的幂函数上做引伸和过多的介绍。\n教科书首先给出5个实际问题，目的是引出5个常用的幂函数，并由此概括它们的共性，获得幂函数的定义。五个幂函数y=x，y=x^2^，y=x^3^，y=x^-1^，y=中，y=x，y=x^2^，y=x^-1^的图像是学生熟悉的，对于y=x^3^，y=两个幂函数。可以用描点法做出函数的图像，也可以借助计算机作出函数的图像加以认识。当然，五个幂函数的图像可以通过计算机在同一个坐标系当中作出。\n教学中，可以让学生通过观察上述图像，自己尝试归纳五个幂函数的基本性质，然后完成教科书中的表格。在归纳五个幂函数的基本性质时，应注意引导学生类比前面研究一般的函数，指数函数，对数函数等过程的思想方法，对研究这些函数的思路作出引导。\n课 时：一课时\n教学目标：1、通过具体实例了解幂函数的图象和性质，并能进行简单的应用．\n2、能够类比研究一般函数、指数函数、对数函数的过程与方法，来研究幂函数的图象和性质．\n3、体会幂函数的变化规律及蕴含其中的对称性．\n教学重点：从五个具体幂函数中认识幂函数的一些性质．\n教学难点：画五个具体幂函数的图象并由图象概括其性质，体会图象的变化规律．\n教学关键：通过指数函数，对数函数，幂函数的图像对比，总结归纳出幂函数的性质\n教学流程：\n教具准备：\n教学过程：\n+----------+----------------------------+----------------------------+\n| 环节     | 教学内容设计               | 师生双边互动               |\n+----------+----------------------------+----------------------------+\n| 创       | 阅读教材P~77~的具体实例（  | 生：独立思考完成引例．     |\n|          | 1）/~（5），思考下列问题： |                            |\n| 设       |                            | 师：引导                   |\n|          | > 1．                      | 学生分析归纳概括得出结论． |\n| 情       | 它们的对应法则分别是什么？ |                            |\n|          | >                          | 师生：共同辨析这           |\n| 境       | > 2．以上问                | 种新函数与指数函数的异同． |\n|          | 题中的函数有什么共同特征？ |                            |\n|          | >                          |                            |\n|          | > （答案）                 |                            |\n|          | >                          |                            |\n|          | > 1．                      |                            |\n|          | （1）乘以1；（2）求平方；  |                            |\n|          | （3）求立方；（4）开方；（ |                            |\n|          | 5）取倒数（或求－1次方）． |                            |\n|          | >                          |                            |\n|          | > 2．上述问题中            |                            |\n|          | 涉及到的函数，都是形如的函 |                            |\n|          | 数，其中是自变量，是常数． |                            |\n+----------+----------------------------+----------------------------+\n| 组       | 材                         | 师：说明：                 |\n|          | 料一：幂函数定义及其图象． |                            |\n| 织       |                            | 幂函数的定义来             |\n|          | 一般地，", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-96ddb2e7376dbb23b609be36089124d6", "__created_at__": 1754880286, "content": "|\n|          | 涉及到的函数，都是形如的函 |                            |\n|          | 数，其中是自变量，是常数． |                            |\n+----------+----------------------------+----------------------------+\n| 组       | 材                         | 师：说明：                 |\n|          | 料一：幂函数定义及其图象． |                            |\n| 织       |                            | 幂函数的定义来             |\n|          | 一般地，形如               | 自于实践，它同指数函数、对 |\n| 探       |                            | 数函数一样，也是基本初等函 |\n|          | 的函                       | 数，同样也是一种\"形式定义\" |\n| 究       | 数称为幂函数，其中为常数． | 的函数，引导学生注意辨析． |\n|          |                            |                            |\n|          | 下面我们举                 | 生：利用                   |\n|          | 例学习这类函数的一些性质． | 所学知识和方法尝试作出五个 |\n|          |                            | 具体幂函数的图象，观察所图 |\n|          | 作出下列函数的图象：       | 象，体会幂函数的变化规律． |\n|          |                            |                            |\n|          | （1）；（2）；（3）；      | 师：                       |\n|          |                            | 引导学生应用画函数的性质画 |\n|          | （4）；（5）．             | 图象，如：定义域、奇偶性． |\n|          |                            |                            |\n|          | /[解/] 列表（略）          | 师生共同分                 |\n|          |                            | 析，强调画图象易犯的错误． |\n|          | 图象                       |                            |\n+----------+----------------------------+----------------------------+\n| 环节     | 教学内容设计               | 师生双边互动               |\n+----------+----------------------------+----------------------------+\n| 组       | 材料二：幂函数性质归纳．   | 师：引导                   |\n|          |                            | 学生观察图象，归纳概括幂函 |\n| 织       | （1）所有的                | 数的的性质及图象变化规律． |\n|          | 幂函数在（0，+∞）都有定义  |                            |\n| 探       | ，并且图象都过点（1，1）； | 生：观察图象，分组         |\n|          |                            | 讨论，探究幂函数的性质和图 |\n| 究       | （2）                      | 象的变化规律，并展示各自的 |\n|          | 时，幂函数的图象通过原点， | 结论进行交流评析，并填表． |\n|          | 并且在区间上是增函数．特别 |                            |\n|          | 地，当时，幂函数的图象下凸 |                            |\n|          | ；当时，幂函数的图象上凸； |                            |\n|          |                            |                            |\n|          | （3）时，幂函数的          |                            |\n|          | 图象在区间上是减函数．在第 |                            |\n|          | 一象限内，当从右边趋向原点 |                            |\n|          | 时，图象在轴右方无限地逼近 |                            |\n|          | 轴正半轴，当趋于时，图象在 |                            |\n|          | 轴上方无限地逼近轴正半轴． |                            |\n+----------+----------------------------+----------------------------+\n|          | 材料三：观察与思考         |                            |\n|          |                            |                            |\n|          | 观察图象，总结填写下表：   |                            |\n|          |                            |                            |\n|          |   -------- -- -- -- -- --  |                            |\n|          |                            |                            |\n|          |   定义域                   |                            |\n|          |   值域                     |                            |\n|          |   奇偶性                   |                            |\n|          |   单调性                   |                            |\n|          |   定点                     |                            |\n|          |   -------- -- -- -- -- --  |                            |\n+----------+----------------------------+----------------------------+\n|          | 材料五：例题               | 师：                       |\n|          |                            | 引导学生回顾讨论函数性质的 |\n|          | /[例1/]（                  | 方法，规范解题格式与步骤． |\n|          | 教材P~78~例题）证明幂函数  |                            |\n|          |                            | 并指出函                   |\n|          | 在(0,+∞)上是增函数.        | 数单调性是判别大小的重要工 |\n|          |                            | 具，幂函数的图象可以在单调 |\n|          | /[例2/]                    | 性、奇偶性基础上较快描出． |\n|          |                            |                            |\n|          | 比较下列两个代数值的大小： | 生：独立思考，             |\n|          |                            | 给出解答，共同讨论、评析． |\n|          | （1），                    |                            |\n|          |                            |                            |\n|          | （2），                    |                            |\n|          |                            |                            |\n|          | /[例3/]                    |                            |\n|          | 讨论函数的定义域           |                            |\n|          | 、奇偶性，", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-ef434f4acf2785c731a49c20fa787b93", "__created_at__": 1754880286, "content": "代数值的大小： | 生：独立思考，             |\n|          |                            | 给出解答，共同讨论、评析． |\n|          | （1），                    |                            |\n|          |                            |                            |\n|          | （2），                    |                            |\n|          |                            |                            |\n|          | /[例3/]                    |                            |\n|          | 讨论函数的定义域           |                            |\n|          | 、奇偶性，作出它的图象，并 |                            |\n|          | 根据图象说明函数的单调性． |                            |\n+----------+----------------------------+----------------------------+\n| 环节     | 呈现教学材料               | 师生互动设计               |\n+----------+----------------------------+----------------------------+\n| 尝       | 1                          |                            |\n|          | ．利用幂函数的性质，比较下 |                            |\n| 试       | 列各题中两个幂的值的大小： |                            |\n|          |                            |                            |\n| 练       | （1），；                  |                            |\n|          |                            |                            |\n| 习       | （2），；                  |                            |\n|          |                            |                            |\n|          | （3），；                  |                            |\n|          |                            |                            |\n|          | （4），．                  |                            |\n|          |                            |                            |\n|          | 2．作出函数                |                            |\n|          | 的图象，根据图象讨论这个函 |                            |\n|          | 数有哪些性质，并给出证明． |                            |\n|          |                            |                            |\n|          | 3．作                      |                            |\n|          | 出函数和函数的图象，求这两 |                            |\n|          | 个函数的定义域和单调区间． |                            |\n|          |                            |                            |\n|          | 4．用图象法解方程：        |                            |\n|          |                            |                            |\n|          | （1）； （2）．            |                            |\n+----------+----------------------------+----------------------------+\n| 探       | ![](static/Images/c72      | 规律1：在第一象限，作      |\n|          | af4bdba1f454fa890bc6d35622 | 直线，它同各幂函数图象相交 |\n| 究       | 724/media/image359.png)1． | ，按交点从下到上的顺序，幂 |\n|          | 如图所示，曲线是幂函数在第 | 指数按从小到大的顺序排列． |\n| 与       | 一象限内的图象，已知分别取 |                            |\n|          | 四个值，则相应图象依次为： | 规律2：幂                  |\n| 发       | ．                         | 指数互为倒数的幂函数在第一 |\n|          |                            | 象限内的图象关于直线对称． |\n| 现       | 2．在                      |                            |\n|          | 同一坐标系内，作出下列函数 |                            |\n|          | 的图象，你能发现什么规律？ |                            |\n|          |                            |                            |\n|          | （1）和；                  |                            |\n|          |                            |                            |\n|          | （2）和．                  |                            |\n+----------+----------------------------+----------------------------+\n| 作业回馈 | 1．                        |                            |\n|          | 在函数中，幂函数的个数为： |                            |\n|          |                            |                            |\n|          | A．0 B．1 C．2 D．3        |                            |\n+----------+----------------------------+----------------------------+\n| 环节     | 呈现教学材料               | 师生互动设计               |\n+----------+----------------------------+----------------------------+\n|          | 2．已知幂函数的图象过点    |                            |\n|          | ，试求出这个函数的解析式． |                            |\n|          |                            |                            |\n|          | 3．在固定压力差（压        |                            |\n|          | 力差为常数）下，当气体通过 |                            |\n|          | 圆形管道时，其流量速率R与  |                            |\n|          | 管道半径r的四次方成正比．  |                            |\n|          |                            |                            |\n|          | （1）写出函数解析式；      |                            |\n|          |                            |                            |\n|          | （                         |                            |\n|          | 2）若气体在半径为3cm的管道 |                            |\n|          | 中，流量速率为400cm^3^/s， |                            |\n|          | 求该气体通过半径为r的管道  |                            |\n|          | 时，其流量速率R的表达式；  |                            |\n|          |                            |                            |\n|          | （3）已知（2）             |                            |\n|          | 中的气体通过的管道半径为5  |                            |\n|          | cm，计算该气体的流量速率． |                            |\n|          |                            |                            |\n|          | 4．1992年底世界            |                            |\n|          | 人口达到54．8亿，若人口的  |                            |\n|          | 平均增长率为x%，2008年底世 |                            |\n|          | 界人口数为y（亿），写出：  |                            |\n|", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-ed7d58f8e26610adfefbbcdb761bf588", "__created_at__": 1754880286, "content": "5  |                            |\n|          | cm，计算该气体的流量速率． |                            |\n|          |                            |                            |\n|          | 4．1992年底世界            |                            |\n|          | 人口达到54．8亿，若人口的  |                            |\n|          | 平均增长率为x%，2008年底世 |                            |\n|          | 界人口数为y（亿），写出：  |                            |\n|          |                            |                            |\n|          | （1）1993年底、1994年      |                            |\n|          | 底、2000年底的世界人口数； |                            |\n|          |                            |                            |\n|          | （2）2008年底的世          |                            |\n|          | 界人口数y与x的函数解析式． |                            |\n+----------+----------------------------+----------------------------+\n| 课       | 利用图形计算器探索一般     |                            |\n|          | 幂函数的图象随的变化规律． |                            |\n| 外       |                            |                            |\n|          |                            |                            |\n| 活       |                            |                            |\n|          |                            |                            |\n| 动       |                            |                            |\n+----------+----------------------------+----------------------------+\n| 收       | 1．谈谈五个基本幂          |                            |\n|          | 函数的定义域与对应幂函数的 |                            |\n| 获       | 奇偶性、单调性之间的关系？ |                            |\n|          |                            |                            |\n| 与       | 2．幂函数与指数函数的      |                            |\n|          | 不同点主要表现在哪些方面？ |                            |\n| 体       |                            |                            |\n|          |                            |                            |\n| 会       |                            |                            |\n+----------+----------------------------+----------------------------+\n板书设计：\n课后反馈：\n/\n课题：§3.1.1方程的根与函数的零点\n教材分析：教科书选取探究具体的一元二次方程的根及其对应的一元二次函数与x轴的交点的横坐标之间的关系，作为本节内容的入口，其意图是让学生从熟悉的环境中发现知识，使新知识与原有知识形成联系。教学时，应给学生提供探究情景，让学生自己发现并归纳出结论\"一元二次方程的根就是相应的二次函数的图像与x轴的交点的横坐标。\"\n给出函数零点的概念以后，要让学生明确\"方程的根\"与\"函数的零点\"尽管有密切的联系，但不能将它们混为一谈。之所以介绍通过求函数的零点求方程的根，是因为函数的图像和性质，为理解函数的零点提供了直观认识，并为判定零点是否存在和求出零点提供了支持，这就是使方程的求解与函数的变化形成联系，有利于分析问题的本质。\n教科书通过第87页的探究，让学生观察对应的二次函数在区间端点上的函数值之积的特点，引导学生发现连续函数在某个区间上存在零点的判定方法。教科书上给出了下述结论，要求学生理解并会用，而不要求学生证明。\n如果函数y=f（x）在区间【a，b】上的图像是连续不断的一条曲线，并且有，那么，函数y=f（x）在区间（a，b）内有零点，即存在c∈（a，b），使得f（c）=0，这个c也就是方程f（x）=0的根。\n例题是考察函数零点的个数。通过它要让学生认识到函数图像及其基本性质（特别是函数的单调性）在确定函数零点中的重要作用。\n（1）函数的图像可以让学生利用计算机画出。通过观察教科书上的图3.1-3，发现函数图像与x轴有一个交点，从而对函数有一个零点形成直观认识。\n要说明函数仅有一个零点，除了上述理由外，还必须说明函数在其定义域内是单调的。可以由增（减）函数定义证明函数在（0，+∞）上是增函数。\n第88页的练习可以让学生借助于计算器或计算机在课堂上完成。第1题的2，3，4，要启发学生将\"=\"右边的项移至\"=\"左边，然后将\"=\"左边的代数式设为函数f（x），再探究函数零点得出方程的根的情况。当然，也可以启发学生思考：若将\"=\"左右两边的代数式分别假设为函数f（x），\n> g（x），那么方程的根与函数f（x），g（x）的图像有什么关系？\n课 时：一课时\n教学目标：\n1、理解函数（结合二次函数）零点的概念，领会函数零点与相应方程要的关系，掌握零点存在的判定条件．\n2、零点存在性的判定．\n3、在函数与方程的联系中体验数学中的转化思想的意义和价值．\n教学重点：零点的概念及存在性的判定．\n教学难点：零", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-07269e01563d27d9c31b4f8ce980193a", "__created_at__": 1754880286, "content": "一课时\n教学目标：\n1、理解函数（结合二次函数）零点的概念，领会函数零点与相应方程要的关系，掌握零点存在的判定条件．\n2、零点存在性的判定．\n3、在函数与方程的联系中体验数学中的转化思想的意义和价值．\n教学重点：零点的概念及存在性的判定．\n教学难点：零点的确定．\n教学关键：处理好函数与方程的关系，方程的根与函数图像与坐标轴的交点之间的关系，让学生自己动手，寻找这两个关系\n教学流程：\n教具准备：\n教学过程：\n+------+------------------------------+------------------------------+\n| 环节 | 教学内容设置                 | 师生双边互动                 |\n+------+------------------------------+------------------------------+\n| 创   | 先来                         | 师                           |\n|      | 观察几个具体的一元二次方程的 | ：引导学生解方程，画函数图象 |\n| 设   | 根及其相应的二次函数的图象： | ，分析方程的根与图象和轴交点 |\n|      |                              | 坐标的关系，引出零点的概念． |\n| 情   | 方程与函数                   |                              |\n|      |                              | 生：独立思                   |\n| 境   | 方程与函数                   | 考完成解答，观察、思考、总结 |\n|      |                              | 、概括得出结论，并进行交流． |\n|      | 方程与函数                   |                              |\n|      |                              | 师：上述结论推广到一般的一   |\n|      |                              | 元二次方程和二次函数又怎样？ |\n+------+------------------------------+------------------------------+\n| 组织 | 函数零点的概念：             | 师：引导学生仔细体会左边的这 |\n|      |                              | 段文字，感悟其中的思想方法． |\n| 探究 | 对于函数，把                 |                              |\n|      | 使成立的实数叫做函数的零点． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 教学内容设置                 | 师生双边互动                 |\n+------+------------------------------+------------------------------+\n| 组   | 函数零点的意义：             | 生：                         |\n|      |                              | 认真理解函数零点的意义，并根 |\n| 织   | 函                           | 据函数零点的意义探索其求法： |\n|      | 数的零点就是方程实数根，亦即 |                              |\n| 探   | 函数的图象与轴交点的横坐标． | 　代数法；                   |\n|      |                              |                              |\n| 究   | 即：                         | 　几何法．                   |\n|      |                              |                              |\n|      | 方程有实数根函数             |                              |\n|      | 的图象与轴有交点函数有零点． |                              |\n|      |                              |                              |\n|      | 函数零点的求法：             |                              |\n|      |                              |                              |\n|      | 求函数的零点：               |                              |\n|      |                              |                              |\n|      | > （代数法）求方程的实数根； |                              |\n|      |                              |                              |\n|      | （几何法                     |                              |\n|      | ）对于不能用求根公式的方程， |                              |\n|      | 可以将它与函数的图象联系起来 |                              |\n|      | ，并利用函数的性质找出零点． |                              |\n+------+------------------------------+------------------------------+\n|      | 二次函数的零点：             | 师：引导学生运用函数零点的   |\n|      |                              | 意义探索二次函数零点的情况． |\n|      | 二次函数                     |                              |\n|      |                              |                              |\n|      | 　　　　　．                 |                              |\n|      |                              |                              |\n|      | １）△＞０，方程有两不等      |                              |\n+------+------------------------------+------------------------------+\n|      | >                            | 生：根据函数零点的意义探     |\n|      | 实根，二次函数的图象与轴有两 | 索研究二次函数的零点情况，并 |\n|      | 个交点，二次函数有两个零点． | 进行交流，总结概括形成结论． |\n|      | >                            |                              |\n|      | > ２）△＝０，方程有两        |                              |\n|      | 相等实根（二重根），二次函数 |                              |\n|      | 的图象与轴有一个交点，二次函 |                              |\n|      | 数有一个二重零点或二阶零点． |                              |\n|      | >                            |                              |\n|      | > ３）△＜０                  |                              |\n|      | ，方程无实根，二次函数的图象 |                              |\n|      | 与轴无交点，二次函数无零点． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 零点存在性的探索：           | 生：分析函数，按提示         |\n|      |                              | 探索，完成解答，并认真思考． |", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-9378348396d55b16846cdb282e0e4a31", "__created_at__": 1754880286, "content": "|      | > ３）△＜０                  |                              |\n|      | ，方程无实根，二次函数的图象 |                              |\n|      | 与轴无交点，二次函数无零点． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 零点存在性的探索：           | 生：分析函数，按提示         |\n|      |                              | 探索，完成解答，并认真思考． |\n|      | （Ⅰ）观察二次函数的图象：    |                              |\n|      |                              | 师：引导学生                 |\n|      | >                            | 结合函数图象，分析函数在区间 |\n|      | 在区间上有零点/_/_/_/_/_/_； | 端点上的函数值的符号情况，与 |\n|      | >                            | 函数零点是否存在之间的关系． |\n|      | > /_/                        |                              |\n|      | _/_/_/_/_/_，/_/_/_/_/_/_/_, | 生：结合函数图象，思考、     |\n|      | >                            | 讨论、总结归纳得出函数零点存 |\n|      | > ·/_/_/_/_/_0（＜或＞）．   | 在的条件，并进行交流、评析． |\n|      | >                            |                              |\n|      | >                            | 师：引导学生理解函数零点存在 |\n|      | 在区间上有零点/_/_/_/_/_/_； | 定理，分析其中各条件的作用． |\n|      | >                            |                              |\n|      | > ·/_/_/_/_0（＜或＞）．     |                              |\n|      | >                            |                              |\n|      | > （Ⅱ）观察下面函数的图象    |                              |\n|      | >                            |                              |\n|      | > 在区间                     |                              |\n|      | 上/_/_/_/_/_/_(有/无)零点；  |                              |\n|      | >                            |                              |\n|      | > ·/_/_/_/_/_0（＜或＞）．   |                              |\n|      | >                            |                              |\n|      | > 在区间                     |                              |\n|      | 上/_/_/_/_/_/_(有/无)零点；  |                              |\n|      | >                            |                              |\n|      | > ·/_/_/_/_/_0（＜或＞）．   |                              |\n|      | >                            |                              |\n|      | > 在区间                     |                              |\n|      | 上/_/_/_/_/_/_(有/无)零点；  |                              |\n|      | >                            |                              |\n|      | > ·/_/_/_/_/_0（＜或＞）．   |                              |\n|      | >                            |                              |\n|      | > 由以上两步探               |                              |\n|      | 索，你可以得出什么样的结论？ |                              |\n|      |                              |                              |\n|      | 怎样利用                     |                              |\n|      | 函数零点存在性定理，断定函数 |                              |\n|      | 在某给定区间上是否存在零点． |                              |\n+------+------------------------------+------------------------------+\n| 例   | 例1．求函数的零点个数．      | 师：引                       |\n|      |                              | 导学生探索判断函数零点的方法 |\n| 题   | 问题：                       | ，指出可以借助计算机或计算器 |\n|      |                              | 来画函数的图象，结合图象对函 |\n| 研   | 1）你可以想到                | 数有一个零点形成直观的认识． |\n|      | 什么方法来判断函数零点个数？ |                              |\n| 究   |                              | 生：借助计算机或             |\n|      | 2）判断                      | 计算器画出函数的图象，结合图 |\n|      | 函数的单调性，由单调性你能得 | 象确定零点所在的区间，然后利 |\n|      | 该函数的单调性具有什么特性？ | 用函数单调性判断零点的个数． |\n|      |                              |                              |\n|      | 例2．                        |                              |\n|      | 求函数，并画出它的大致图象． |                              |\n+------+------------------------------+------------------------------+\n| 尝   | 1．利用函数图象判断          | 师：结合图                   |\n|      | 下列方程有没有根，有几个根： | 象考察零点所在的大致区间与个 |\n| 试   |                              | 数，结合函数的单调性说明零点 |\n|      | （1）；                      | 的个数；让学生认识到函数的图 |\n| 练   |                              | 象及基本性质（特别是单调性） |\n|      | （2）；                      | 在确定函数零点中的重要作用． |\n| 习   |                              |                              |\n|      | （3）；                      |                              |\n|      |                              |                              |\n|      | （4）．                      |                              |\n|      |                              |                              |\n|      | 2．利用函数的图象，指出      |                              |\n|      | 下列函数零点所在的大致区间： |                              |\n|      |                              |                              |\n|      | （1）；                      |                              |\n|      |                              |                              |\n|      | （2", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-eff8aa2e1993d2953f6afcaa5e0183dc", "__created_at__": 1754880286, "content": "|\n|      | （3）；                      |                              |\n|      |                              |                              |\n|      | （4）．                      |                              |\n|      |                              |                              |\n|      | 2．利用函数的图象，指出      |                              |\n|      | 下列函数零点所在的大致区间： |                              |\n|      |                              |                              |\n|      | （1）；                      |                              |\n|      |                              |                              |\n|      | （2）；                      |                              |\n|      |                              |                              |\n|      | （3）；                      |                              |\n|      |                              |                              |\n|      | （4）．                      |                              |\n+------+------------------------------+------------------------------+\n| 探   | 1．已知，请探究方程的根．    |                              |\n|      | 如果方程有根，指出每个根所在 |                              |\n| 究   | 的区间（区间长度不超过1）．  |                              |\n|      |                              |                              |\n| 与   | 2．设函数．                  |                              |\n|      |                              |                              |\n| 发   | （1）利用计                  |                              |\n|      | 算机探求和时函数的零点个数； |                              |\n| 现   |                              |                              |\n|      | （2）当                      |                              |\n|      | 时，函数的零点是怎样分布的？ |                              |\n+------+------------------------------+------------------------------+\n| 作   | 1.  教材P~                   |                              |\n|      | 92~习题3．1（A组）第1、2题； |                              |\n| 业   |                              |                              |\n|      | 2.  求下列函数的零点：       |                              |\n| 回   |                              |                              |\n|      | > （1）；                    |                              |\n| 馈   | >                            |                              |\n|      | > （2）；                    |                              |\n|      | >                            |                              |\n|      | > （3）                      |                              |\n|      | >                            |                              |\n|      | > ．                         |                              |\n|      |                              |                              |\n|      | 3.  求下列函数的零点         |                              |\n|      | ，图象顶点的坐标，画出各自的 |                              |\n|      | 简图，并指出函数值在哪些区间 |                              |\n|      | 上大于零，哪些区间上小于零： |                              |\n|      |                              |                              |\n|      | > （1）；                    |                              |\n|      | >                            |                              |\n|      | > （2）．                    |                              |\n|      |                              |                              |\n|      | 4.  已知：                   |                              |\n|      |                              |                              |\n|      | > （1）为何值时              |                              |\n|      | ，函数的图象与轴有两个零点； |                              |\n|      | >                            |                              |\n|      | > （2）如果函数至少有        |                              |\n|      | 一个零点在原点右侧，求的值． |                              |\n|      |                              |                              |\n|      | 5.  求下列函数的定义域：     |                              |\n|      |                              |                              |\n|      | > （1）；                    |                              |\n|      | >                            |                              |\n|      | > （2）；                    |                              |\n|      | >                            |                              |\n|      | > （3）                      |                              |\n+------+------------------------------+------------------------------+\n| 课   | 研究，，                     | 考虑                         |\n|      |                              | 列表，建议画出图象帮助分析． |\n| 外   | ，                           |                              |\n|      | 的相互关系，以零点作为研究出 |                              |\n| 活   | 发点，并将研究结果尝试用一种 |                              |\n|      | 系统的、简洁的方式总结表达． |                              |\n| 动   |                              |                              |\n+------+------------------------------+------------------------------+\n| 收   | 说说方程的根与函数           |                              |\n|      | 的零点的关系，并给出判定方程 |                              |\n| 获   | 在某个区产存在根的基本步骤． |                              |\n|      |                              |                              |\n| 与   |                              |                              |\n|      |                              |                              |\n| 体   |                              |                              |\n|      |                              |                              |\n| 会   |                              |                              |\n+------+------------------------------+------------------------------+\n板书设计：\n课后反馈：\n/\n课题：§3.1.2用二分法求方程的近似解\n教材分析：\n课 时：一课时\n教学目标：1、通过具体实例理解二分法的概念及其适用条件，了解二分法是求方程近似解的常用方法，从中体会函数与方程之间的联系及其在实际问题中的应用．\n2、能借助计算器用二分法求方程的近似解，并了解这一数学思想，为学习算法做准备．\n3、体会数学逼近过程，感受精确与近似的相对统一．\n教学重点：\n通过用二分法求方程的近似解，体会函数的零点与方程根之间的联系，初步形成用函数观点处理问题的意识．\n教学难点：恰当地使用信息技术工具，利用二分法求给定精确度的方", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-57ba61b4c6dfcb2cda9b14aea9b4f5d5", "__created_at__": 1754880286, "content": "，并了解这一数学思想，为学习算法做准备．\n3、体会数学逼近过程，感受精确与近似的相对统一．\n教学重点：\n通过用二分法求方程的近似解，体会函数的零点与方程根之间的联系，初步形成用函数观点处理问题的意识．\n教学难点：恰当地使用信息技术工具，利用二分法求给定精确度的方程的近似解．\n教学关键：\n教学流程：\n教具准备：\n教学过程：\n+------+------------------------------+------------------------------+\n| 环节 | 教学内容设计                 | 师生双边互动                 |\n+------+------------------------------+------------------------------+\n| 创   | 材料                         | 师：从学生感兴趣的计算机     |\n|      | 一：二分查找(binary-search)  | 编程问题，引导学生分析二分法 |\n| 设   |                              | 的算法思想与方法，引入课题． |\n|      | （第六届全国青少年信         |                              |\n| 情   | 息学（计算机）奥林匹克分区联 | 生                           |\n|      | 赛提高组初赛试题第15题）某数 | ：体会二分查找的思想与方法． |\n| 境   | 列有1000个各不相同的单元，由 |                              |\n|      | 低至高按序排列；现要对该数列 | 师：从高                     |\n|      | 进行二分法检索(binary-search | 次代数方程的解的探索历程，引 |\n|      | )，在最坏的情况下，需检索（  | 导学生认识引入二分法的意义． |\n|      | ）个单元。                   |                              |\n|      |                              |                              |\n|      | Ａ．1000 Ｂ．10   Ｃ．100    |                              |\n|      | Ｄ．500                      |                              |\n|      |                              |                              |\n|      | 二分法检索                   |                              |\n|      | （二分查找或折半查找）演示． |                              |\n|      |                              |                              |\n|      | 材料二：高                   |                              |\n|      | 次多项式方程公式解的探索史料 |                              |\n|      |                              |                              |\n|      | 由于实际问题的               |                              |\n|      | 需要，我们经常需要寻求函数的 |                              |\n|      | 零点（即的根），对于为一次或 |                              |\n|      | 二次函数，我们有熟知的公式解 |                              |\n|      | 法（二次时，称为求根公式）． |                              |\n|      |                              |                              |\n|      | 在十六世纪，已找到了         |                              |\n|      | 三次和四次函数的求根公式，但 |                              |\n|      | 对于高于4次的函数，类似的努  |                              |\n|      | 力却一直没有成功，到了十九世 |                              |\n|      | 纪，根据阿贝尔（Abel）和伽罗 |                              |\n|      | 瓦（Galois）的研究，人们认识 |                              |\n|      | 到高于4次的代数方程不存在求  |                              |\n|      | 根公式，亦即，不存在用四则运 |                              |\n|      | 算及根号表示的一般的公式解． |                              |\n|      | 同时，即使对于3次和4次的代数 |                              |\n|      | 方程，其公式解的表示也相当复 |                              |\n|      | 杂，一般来讲并不适宜作具体计 |                              |\n|      | 算．因此对于高次多项式函数及 |                              |\n|      | 其它的一些函数，有必要寻求其 |                              |\n|      | 零点的近似解的方法，这是一个 |                              |\n|      | 在计算数学中十分重要的课题． |                              |\n+------+------------------------------+------------------------------+\n| 组   | 二分法及步骤：               | 师：阐述                     |\n|      |                              | 二分法的逼近原理，引导学生理 |\n| 织   | 对于在区                     | 解二分法的算法思想，明确二分 |\n|      | 间，上连续不断，且满足·的函  | 法求函数近似零点的具体步骤． |\n| 探   | 数，通过不断地把函数的零点所 |                              |\n|      | 在的区间一分为二，使区间的两 | 分析条件                     |\n| 究   | 个端点逐步逼近零点，进而得到 |                              |\n|      | 零点近似值的方法叫做二分法． | \"·\"、\"精                     |\n|      |                              | 度\"、\"区间中点\"及\"\"的意义．  |\n|      | 给定精度，用二分法求         |                              |\n|      | 函数的零点近似值的步骤如下： |                              |\n|      |                              |                              |\n|      | 1．确                        |                              |\n|      | 定区间，，验证·，给定精度；  |                              |\n|      |                              |                              |\n|      | 2．求区间，的中点；          |                              |\n|      |                              |", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-ec48e58138f8ffd951d624e4f5643fbe", "__created_at__": 1754880286, "content": "给定精度，用二分法求         |                              |\n|      | 函数的零点近似值的步骤如下： |                              |\n|      |                              |                              |\n|      | 1．确                        |                              |\n|      | 定区间，，验证·，给定精度；  |                              |\n|      |                              |                              |\n|      | 2．求区间，的中点；          |                              |\n|      |                              |                              |\n|      | 3．计算：                    |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 呈现教学材料                 | 师生互动设计                 |\n+------+------------------------------+------------------------------+\n| 组   | 若=，则就是函数的零点；      | 生：结合引例\"二分查找\"理解   |\n|      |                              | 二分法的算法思想与计算原理． |\n| 织   | 若·/<，则令=（此时零点）；   |                              |\n|      |                              | 师：引导学生分               |\n| 探   | 若·/<，则令=（此时零点）；   | 析理解求区间，的中点的方法． |\n|      |                              |                              |\n| 究   | 4．判断是否达到精度；        |                              |\n|      |                              |                              |\n|      | 即若，则得到零点零点         |                              |\n|      | 值（或）；否则重复步骤2/~4． |                              |\n+------+------------------------------+------------------------------+\n|      | 例题解析：                   | 师：引导学生利用二分法       |\n|      |                              | 逐步寻求函数零点的近似值，注 |\n|      | 例1．求函                    | 意规范方法、步骤与书写格式． |\n|      | 数的一个正数零点（精确到）． |                              |\n|      |                              | 生：根据                     |\n|      | 分析：首先利用函数性质或借助 | 二分法的思想与步骤独立完成解 |\n|      | 计算机、计算器画出函数图象， | 答，并进行交流、讨论、评析． |\n|      | 确定函数零点大致所在的区间， |                              |\n|      | 然后利用二分法逐步计算解答． | 师：引导学生应用             |\n|      |                              | 函数单调性确定方程解的个数． |\n|      | 解：（略）．                 |                              |\n|      |                              | 生：认真思考，运             |\n|      | 注意：                       | 用所学知识寻求确定方程解的个 |\n|      |                              | 数的方法，并进行、讨论、交流 |\n|      | 第一步                       | 、归纳、概括、评析形成结论． |\n|      | 确定零点所在的大致区间，，可 |                              |\n|      | 利用函数性质，也可借助计算机 |                              |\n|      | 或计算器，但尽量取端点为整数 |                              |\n|      | 的区间，尽量缩短区间长度，通 |                              |\n|      | 常可确定一个长度为1的区间；  |                              |\n|      |                              |                              |\n|      | 建议列表样式如下：           |                              |\n|      |                              |                              |\n|      |   -----------                |                              |\n|      | ---- ------------ ---------- |                              |\n|      |   零点所在区                 |                              |\n|      | 间    中点函数值   区间长度  |                              |\n|      |   /[                         |                              |\n|      | 1，2/]        />0          1 |                              |\n|      |   /[1，                      |                              |\n|      | 1.5/]      /<0          0.5  |                              |\n|      |   /[1.2                      |                              |\n|      | 5，1.5/]   /<0          0.25 |                              |\n|      |   -----------                |                              |\n|      | ---- ------------ ---------- |                              |\n|      |                              |                              |\n|      | 如此列表的优势               |                              |\n|      | ：计算步数明确，区间长度小于 |                              |\n|      | 精度时，即为计算的最后一步． |                              |\n|      |                              |                              |\n|      | 例2．借助                    |                              |\n|      | 计算器或计算机用二分法求方程 |                              |\n|      |                              |                              |\n|      | 的近似解（精确到）．         |                              |\n|      |                              |                              |\n|      | 解：（略）．                 |                              |\n|      |                              |                              |\n|      | 思                           |                              |\n|      | 考：本例除借助计算器或计算机 |                              |\n|      | 确定方程解所在的大致区间和解 |                              |\n|      | 的个数外，你是否还可以想到有 |                              |\n|      | 什么方法确定方程的根的个数？ |                              |\n|      |                              |                              |\n|      | 结论                         |                              |\n|      | ：图象在闭区间，上连续的单调 |                              |\n|      | 函数，在，上至多有一个零点． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | �", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-ce4833f91e73b322d277393cadcbdd12", "__created_at__": 1754880286, "content": "|\n|      | 的个数外，你是否还可以想到有 |                              |\n|      | 什么方法确定方程的根的个数？ |                              |\n|      |                              |                              |\n|      | 结论                         |                              |\n|      | ：图象在闭区间，上连续的单调 |                              |\n|      | 函数，在，上至多有一个零点． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 呈现教学材料                 | 师生互动设计                 |\n+------+------------------------------+------------------------------+\n| 探   | 1.  函数零点的性质           | 师：引导学生从\"数            |\n|      |                              | \"和\"形\"两个角度去体会函数零  |\n| 究   | > 从                         | 点的意义，掌握常见函数零点的 |\n|      | \"数\"的角度看：即是使的实数； | 求法，明确二分法的适用范围． |\n| 与   |                              |                              |\n|      | 从\"形\"的角度看：即是         |                              |\n| 发   | 函数的图象与轴交点的横坐标； |                              |\n|      |                              |                              |\n| 现   | 若函数的图象在处与轴相切     |                              |\n|      | ，则零点通常称为不变号零点； |                              |\n|      |                              |                              |\n|      | 若函数的图象在处与轴相       |                              |\n|      | 交，则零点通常称为变号零点． |                              |\n|      |                              |                              |\n|      | 2.  用二分法求函数的变号零点 |                              |\n|      |                              |                              |\n|      | 二                           |                              |\n|      | 分法的条件·表明用二分法求函  |                              |\n|      | 数的近似零点都是指变号零点． |                              |\n+------+------------------------------+------------------------------+\n| 尝   | 1.  教材P~91~练习1、2题；    |                              |\n|      |                              |                              |\n| 试   | 2.  教材P~                   |                              |\n|      | 92~习题3．1（A组）第1、2题； |                              |\n| 练   |                              |                              |\n|      | 3.  求方程                   |                              |\n| 习   | 的解的个数及其大致所在区间； |                              |\n|      |                              |                              |\n|      | 4.  求方程的实数解的个数；   |                              |\n|      |                              |                              |\n|      | 5.                           |                              |\n|      |   探究函数与函数的图象有无交 |                              |\n|      | 点，如有交点，求出交点，或给 |                              |\n|      | 出一个与交点距离不超过的点． |                              |\n+------+------------------------------+------------------------------+\n| 作   | 1.  教材P~92~习题3．1（A     |                              |\n|      | 组）第3/~6题、（B组）第4题； |                              |\n| 业   |                              |                              |\n|      | 2.  提高作业：               |                              |\n| 回   |                              |                              |\n|      | > 已知函数                   |                              |\n| 馈   | >                            |                              |\n|      | > ．                         |                              |\n|      | >                            |                              |\n|      | > （1）为何值时              |                              |\n|      | ，函数的图象与轴有两个交点？ |                              |\n|      | >                            |                              |\n|      | > （2）如果函                |                              |\n|      | 数的一个零点在原点，求的值． |                              |\n|      | >                            |                              |\n|      | > 借助于计                   |                              |\n|      | 算机或计算器，用二分法求函数 |                              |\n|      | >                            |                              |\n|      | > 的零点（精确到）；         |                              |\n|      | >                            |                              |\n|      | > 用                         |                              |\n|      | 二分法求的近似值（精确到）． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 呈现教学材料                 | 师生互动设计                 |\n+------+------------------------------+------------------------------+\n| 课   | 查找有关系资料或利           |                              |\n|      | 用internet查找有关高次代数方 |                              |\n| 外   | 程的解的研究史料，追寻阿贝尔 |                              |\n|      | （Abel）和伽罗瓦（Galois）， |                              |\n| 活   | 增强探索精神，培养创新意识． |                              |\n|      |                              |                              |\n| 动   |                              |                              |\n+------+------------------------------+------------------------------+\n| 收   | 说说方程的根与函             |                              |\n|      | 数的零点的关系，并给出判定方 |                              |\n| 获   | 程在某个区间存在根的基本步骤 |                              |\n|      | ，及方程根的个数的判定方法； |                              |\n| 与   |                              |                              |\n|", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-eae91de59166ba6f3cf4fbf8c332629c", "__created_at__": 1754880286, "content": "|\n| 动   |                              |                              |\n+------+------------------------------+------------------------------+\n| 收   | 说说方程的根与函             |                              |\n|      | 数的零点的关系，并给出判定方 |                              |\n| 获   | 程在某个区间存在根的基本步骤 |                              |\n|      | ，及方程根的个数的判定方法； |                              |\n| 与   |                              |                              |\n|      | 谈谈通过学                   |                              |\n| 体   | 习求函数的零点和求方程的近似 |                              |\n|      | 解，对数学有了哪些新的认识？ |                              |\n| 会   |                              |                              |\n+------+------------------------------+------------------------------+\n板书设计：（略）\n课后反馈：\n/\n课题：§3.2.1几类不同增长的函数模型\n教材分析：\n课 时：一课时\n教学目标：1、结合实例体会直线上升、指数爆炸、对数增长等不同增长的函数模型意义，理解它们的增长差异性．\n2、能够借助信息技术，利用函数图象及数据表格，对几种常见增长类型的函数的增长状况进行比较，初步体会它们的增长差异性；收集一些社会生活中普遍使用的函数模型（指数函数、对数函数、幂函数、分段函数等），了解函数模型的广泛应用．\n3、体验函数是描述宏观世界变化规律的基本数学模型，体验指数函数、对数函数等函数与现实世界的密切联系及其在刻画现实问题中的作用．\n教学重点：将实际问题转化为函数模型，比较常数函数、一次函数、指数函数、对数函数模型的增长差异，结合实例体会直线上升、指数爆炸、对数增长等不同函数类型增长的含义．\n教学难点：怎样选择数学模型分析解决实际问题．\n教学关键：\n教学流程：\n教具准备：\n教学过程：\n+------+------------------------------+------------------------------+\n| 环节 | 教学内容设计                 | 师生双边互动                 |\n+------+------------------------------+------------------------------+\n| 创   | > 材料：澳大利亚兔子数\"爆炸\" | 师：                         |\n|      |                              | 指出：一般而言，在理想条件（ |\n| 设   | 在教科书第三章的章头图       | 食物或养料充足，空间条件充裕 |\n|      | 中，有一大群喝水、嬉戏的兔子 | ，气候适宜，没有敌害等）下， |\n| 情   | ，但是这群兔子曾使澳大利亚伤 | 种群在一定时期内的增长大致符 |\n|      | 透了脑筋．1859年，有人从欧洲 | 合\"J\"型曲线；在有限环境（空  |\n| 境   | 带进澳洲几只兔子，由于澳洲有 | 间有限，食物有限，有捕食者存 |\n|      | 茂盛的牧草，而且没有兔子的天 | 在等）中，种群增长到一定程度 |\n|      | 敌，兔子数量不断增加，不到1  | 后不增长，曲线呈\"S\"型．可用  |\n|      | 00年，兔子们占领了整个澳大利 | 指数函数描述一个种群的前期增 |\n|      | 亚，数量达到75亿只．可爱的兔 | 长，用对数函数描述后期增长的 |\n|      | 子变得可恶起来，75亿只兔子吃 |                              |\n|      | 掉了相当于75亿只羊所吃的牧草 |                              |\n|      | ，草原的载畜率大大降低，而牛 |                              |\n|      | 羊是澳大利亚的主要牲口．这使 |                              |\n|      | 澳大利亚头痛不已，他们采用各 |                              |\n|      | 种方法消灭这些兔子，直至二十 |                              |\n|      | 世纪五十年代，科学家采用载液 |                              |\n|      | 瘤病毒杀死了百分之九十的野兔 |                              |\n|      | ，澳大利亚人才算松了一口气． |                              |\n+------+------------------------------+------------------------------+\n| 组   | 例1．假设你有一笔资金用      | 师：创设问题情               |\n|      | 于投资，现有三种投资方案供你 | 境，以问题引入能激起学生的热 |\n| 织   | 选择，这三种方案的回报如下： | 情，使课堂里的有效思维增强． |\n|      |                              |                              |\n| 探   | 方案一：每天回报40元；       | 生：阅读题                   |\n|      |                              | 目，理解题意，思考探究问题． |\n| 究   | 方案二：第一天回报10元，     |                              |\n|      | 以后每天比前一天多回报10元； | 师：引导学生分               |\n|      |                              | 析本例中的数量关系，并思考应 |\n|      | 方案三：第一天回报0          | 当选择怎样的函数模型来描述． |\n|      | .4元，以                     |                              |\n|      | 后", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-4770bf1bd50dc26f05e8c6d37f7b4147", "__created_at__": 1754880286, "content": "究   | 方案二：第一天回报10元，     |                              |\n|      | 以后每天比前一天多回报10元； | 师：引导学生分               |\n|      |                              | 析本例中的数量关系，并思考应 |\n|      | 方案三：第一天回报0          | 当选择怎样的函数模型来描述． |\n|      | .4元，以                     |                              |\n|      | 后每天的回报比前一天翻一番． | 生：观察                     |\n|      |                              | 表格，获取信息，体会三种函数 |\n|      | 请问，你会选择哪种投资方案？ | 的增长差异，特别是指数爆炸， |\n|      |                              | 说出自己的发现，并进行交流． |\n|      | 探究：                       |                              |\n|      |                              | 师：引导学生观               |\n|      | 1                            | 察表格中三种方案的数量变化情 |\n|      | ）在本例中涉及哪些数量关系？ | 况，对于\"增加量\"进行比较，体 |\n|      | 如何用函数描述这些数量关系？ | 会\"直线增长\"、\"指数爆炸\"等． |\n|      |                              |                              |\n|      | 2）分析解答（略）            |                              |\n|      |                              |                              |\n|      | 3）根据例1表格中所提供的数据 |                              |\n|      | ，你对三种方案分别表现出的回 |                              |\n|      | 报资金的增长差异有什么认识？ |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 教学内容设计                 | 师生双边互动                 |\n+------+------------------------------+------------------------------+\n| 组   | 4）你能借助计算器或          | 师：引导学生利用函数图象     |\n|      | 计算机作出函数图象，并通过图 | 分析三种方案的不同变化趋势． |\n| 织   | 象描述一下三种方案的特点吗？ |                              |\n|      |                              | 生：                         |\n| 探   | 5）根据以上                  | 对三种方案的不同变化趋势作出 |\n|      | 分析，你认为就作出如何选择？ | 描述，并为方案选择提供依据． |\n| 究   |                              |                              |\n|      |                              | 师：引导学生分析影响方案选   |\n|      |                              | 择的因素，使学生认识到要做出 |\n|      |                              | 正确选择除了考虑每天的收益， |\n|      |                              | 还要考虑一段时间内的总收益． |\n|      |                              |                              |\n|      |                              | 生                           |\n|      |                              | ：通过自主活动，分析整理数据 |\n|      |                              | ，并根据其中的信息做出推理判 |\n|      |                              | 断，获得累计收益并给出本全的 |\n|      |                              | 完整解答，然后全班进行交流． |\n+------+------------------------------+------------------------------+\n|      | 例2．某公司为了              | 师：引导学生分析三种函       |\n|      | 实现1000万元利润的目标，准备 | 数的不同增长情况对于奖励模型 |\n|      | 制定一个激励销售部门的奖励方 | 的影响，使学生明确问题的实质 |\n|      | 案：在销售利润达到10万元时， | 就是比较三个函数的增长情况． |\n|      | 按销售利润进行奖励，且奖金（ |                              |\n|      | 单位：万元）随销售利润（单位 | 生：进一步体会               |\n|      | ：万元）的增加而增加但奖金不 | 三种基本函数模型在实际中的广 |\n|      | 超过5万元，同时奖金不超过利  | 泛应用，体会它们的增长差异． |\n|      | 润的25%．现有三个奖励模型：  |                              |\n|      |                              | 师：引导学生分析             |\n|      | ．                           | 问题使学生得出：要对每一个奖 |\n|      |                              | 励模型的奖金总额是否超出5万  |\n|      | 问：其                       | 元，以及奖励比例是否超过25%  |\n|      | 中哪个模型能符合公司的要求？ | 进行分析，才能做出正确选择． |\n|      |                              |                              |\n|      | 探究：                       |                              |\n|      |                              |                              |\n|      | 1.                           |                              |\n|      |   本例涉及了哪几类函数模型？ |                              |\n|      |                              |                              |\n|      | 本例的实质是什么？           |                              |\n|      |                              |                              |\n|      | 2）你能                      |                              |\n|      | 根据问题中的数据，判定所给的 |                              |\n|      | 奖励模型是否符合公司要求吗？ |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 呈现教学材料                 | 师生互动设计                 |\n+------+------------------------------+------------------------------+\n| 组   | 3）通过对三个函数模型增长    | 生：分析数据特点与作用判定   |\n|      | 差异的比较，写出例2的解答．  | 每一个奖励模型是否符合要求． |\n| 织   |                              |                              |\n|", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-ba7e1c2cf2958b9ab2cf964a9e18d54a", "__created_at__": 1754880286, "content": "|\n+------+------------------------------+------------------------------+\n| 环节 | 呈现教学材料                 | 师生互动设计                 |\n+------+------------------------------+------------------------------+\n| 组   | 3）通过对三个函数模型增长    | 生：分析数据特点与作用判定   |\n|      | 差异的比较，写出例2的解答．  | 每一个奖励模型是否符合要求． |\n| 织   |                              |                              |\n|      |                              | 师：                         |\n| 探   |                              | 引导学生利用解析式，结合图象 |\n|      |                              | ，对三个模型的增长情况进行分 |\n| 究   |                              | 析比较，写出完整的解答过程． |\n|      |                              |                              |\n|      |                              | 生                           |\n|      |                              | ：进一步认识三个函数模型的增 |\n|      |                              | 长差异，对问题作出具体解答． |\n+------+------------------------------+------------------------------+\n| 探   | 幂函数、指数函               | 师：引                       |\n|      | 数、对数函数的增长差异分析： | 导学生仿照前面例题的探究方法 |\n| 究   |                              | ，选用具体函数进行比较分析． |\n|      | 你能                         |                              |\n| 与   | 否仿照前面例题使用的方法，探 | 生：仿照例题的探究方法，选用 |\n|      | 索研究幂函数、指数函数、对数 | 具体函数进行研究、论证，并进 |\n| 发   | 函数在区间上的增长差异，并进 | 行交流总结，形成结论性报告． |\n|      | 行交流、讨论、概括总结，形成 |                              |\n| 现   | 较为准确、详尽的结论性报告． | 师：对学生的结论进行评析，借 |\n|      |                              | 助信息技术手段进行验证演示． |\n+------+------------------------------+------------------------------+\n| 巩   | 尝试练习：                   | 生：通过尝试练习             |\n|      |                              | 进一步体会三种不同增长的函数 |\n| 固   | 1.  教材P~101~练习1、2；     | 模型的增长差异及其实际应用． |\n|      |                              |                              |\n| 与   | 2.  教材P~101~练习3．        | 师：培养学生对数学学科的     |\n|      |                              | 深刻认识，体会数学的应用美． |\n| 反   | > 小结与反思：               |                              |\n|      |                              |                              |\n| 思   | 通过实例和计算机作           |                              |\n|      | 图体会、认识直线上升、指数爆 |                              |\n|      | 炸、对数增长等不同函数模型的 |                              |\n|      | 增长的含义，认识数学的价值， |                              |\n|      | 认识数学与现实生活、与其他学 |                              |\n|      | 科的密切联系，从而体会数学的 |                              |\n|      | 实用价值，享受数学的应用美． |                              |\n+------+------------------------------+------------------------------+\n| 环节 | 呈现教学材料                 | 师生互动设计                 |\n+------+------------------------------+------------------------------+\n| 作   | 教材P~107~                   |                              |\n|      |                              |                              |\n| 业   | 习题32（A组）第1/~5题；      |                              |\n|      |                              |                              |\n| 与   | （B组）第1题                 |                              |\n|      |                              |                              |\n| 回   |                              |                              |\n|      |                              |                              |\n| 馈   |                              |                              |\n+------+------------------------------+------------------------------+\n| 课   | 收集一些                     |                              |\n|      | 社会生活中普遍使用的递增的一 |                              |\n| 外   | 次函数、指数函数、对数函数的 |                              |\n|      | 实例，对它们的增长速度进行比 |                              |\n| 活   | 较，了解函数模型的广泛应用； |                              |\n|      |                              |                              |\n| 动   | 有时同一个                   |                              |\n|      | 实际问题可以建立多个函数模型 |                              |\n|      | ．具体应用函数模型时，你认为 |                              |\n|      | 应该怎样选用合理的函数模型？ |                              |\n+------+------------------------------+------------------------------+\n板书设计：（略）\n课后反馈：", "full_doc_id": "高中数学必修一全册教案_3221547.docx", "file_path": "高中数学必修一全册教案_3221547.docx"}, {"__id__": "chunk-d348aeca2b81c773ea452531455253f9", "__created_at__": 1754903684, "content": "常见题型归类\n第一章 集合与函数概念\n1.1集合\n题型1 集合与元素\n题型2 集合的表示\n题型3 空集与 0\n题型4 子集、真子集\n题型5 集合运算\n题型5.1 已知集合，求集合运算\n题型5.2 已知集合运算，求集合\n题型5.3 已知集合运算，求参数\n题型6 \"二维\"集合运算\n题型6 自定义的集合\n1.2函数及其表示\n题型1 映射概念\n题型2 函数概念\n题型3 同一函数\n题型4 函数的表示\n题型5 已知函数解析式求值\n题型6 求解析式\n题型7 定义域\n题型7.1 求函数的定义域\n题型7.2 已知函数的定义域问题\n题型8 值域\n题型8.1 图像法求函数的值域\n题型8.2 转化为二次函数，求函数的值域\n题型8.3 转化为反比例函数，求函数的值域\n题型8.4 利用有界性，求函数的值域\n题型8.5单调性法求函数的值域\n题型8.6 判别式法求函数的值域\n题型8.7 几何法求函数值域\n题型9 已知函数值域，求系数\n1.3函数的基本性质 单调性\n题型1 判断函数的单调区间\n题型2 已知函数的单调区间，求参数\n题型3 已知函数的单调性，比较大小\n题型4 已知函数的单调性，求范围\n1.4函数的基本性质 奇偶性\n题型1 判断函数的奇偶性\n题型2 已知函数的奇偶性，求解析式\n题型3 已知函数的奇偶性，求参数\n题型4 已知函数的奇偶性，求值或解集等\n1.5函数的图像\n题型1 函数图像\n题型2 去绝对值作函数图像\n题型3 利用图像变换作函数图像\n题型4 已知函数解析式判断图像\n题型5 研究函数性质作函数图像\n题型6 函数图像的对称性\n第二章基本初等函数\n2.1指数函数\n题型1 指数运算7\n题型2 指数函数概念\n题型3 指数函数型的定义域、值域\n题型4 指数函数型恒过定点\n题型5 单调性\n题型6 奇偶性\n题型7 图像\n题型8 方程、不等式\n2.2对数函数\n题型1 对数运算\n题型2 对数概念\n题型3 对数函数型的定义域、值域\n题型4 对数函数型的恒过定点\n题型5 奇偶性\n题型5 单调性\n题型6 对数函数型的图像\n题型8 方程、不等式\n2.3幂函数\n题型1 幂函数概念\n题型2 五个重要的幂函数\n题型3 幂函数性质\n题型4 求幂函数\n题型5 比较大小\n第三章 函数的应用\n3.1函数与不等式\n题型1 不等式恒成立、存在问题\n题型2 一元二次不等式\n3.2函数与方程\n题型1 函数的零点\n题型2 存在性定理\n题型3 判断函数的零点个数\n题型4 二分法\n题型5 求函数的零点\n题型6 一元二次方程根的分布\n3.3函数模型应用\n题型1函数模型应用\n第一章 集合与函数概念\n1.1集合\n题型1 集合与元素\n1.下列各项中,不能组成集合的是 (　　)\nA.所有的正整数　　B.等于2的数 C.接近于0的数 D.不等于0的偶数\n2.设集合M={x∈R/|x≤3![](/static/Images/cabd20c81160406e9d570746f63b6662/media/image1.png)\nheight=\"0.17430555555555555in\"},则 (　　)\nA.a∉B.a B.a∈M\nC.{a![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image3.png){width=\"1.0416666666666666e-2in\"\nheight=\"1.3888888888888888e-2in\"}}∈M D.{a}∉M\n3.给出下列关系：①； ②；③ ；④. 其中正确的个数是\nA. 1 B. 2 C. 3 D. 4", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-b593fb9a6a12a4e34bc0da4ba9f8bffd", "__created_at__": 1754903684, "content": "60406e9d570746f63b6662/media/image3.png){width=\"1.0416666666666666e-2in\"\nheight=\"1.3888888888888888e-2in\"}}∈M D.{a}∉M\n3.给出下列关系：①； ②；③ ；④. 其中正确的个数是\nA. 1 B. 2 C. 3 D. 4 ( 　 )\n4.由实数x,－x,｜x｜,所组成的集合，最多含 （ ）\nA.2个元素 B.3个元素\n![学科网(www.zxxk.com)/--国内最大的教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image3.png){width=\"1.0416666666666666e-2in\"\nheight=\"2.2222222222222223e-2in\"}C。4个元素 D.5个元素\n题型2 集合的表示\n1.用适当的方法表示下列集合:\n(1)所有被3整除的整数. [　　　 　　　]{.ul}\n(2)满足方程x=/|x/|的所有x的值构成的集合B. [　　　 　　　]{.ul}\n2.已知集合A={x/|![](/static/Images/cabd20c81160406e9d570746f63b6662/media/image9.png)\nheight=\"0.375in\"}∈N,x∈N},则用列举法表示为[　　　　]{.ul}.\n3.已知集合A={(x,y)/|y=2x+1},B={(x,y)/|y=x+3},a∈A且a∈B,则a为[　　　　　　]{.ul}\n4.某班共30人，其中15人喜爱篮球运动，10人喜爱兵乓球运动，8人对这两项运动都不喜爱，则喜爱篮球运动但不喜爱乒乓球运动的人数为[/_\n/_　　　/_]{.ul}\n题型3 空集与0\n1.下列八个关系式：\n①{0}=; ②=0; ③{}; ④{}; ⑤{0}; ⑥0;\n⑦{0}; ⑧{}.其中正确的个数 （ ）\nA 4 B 5 C 6 D\n题型4 子集、真子集\n1.设A={4,a},B={2,ab},若A=B,则a+b=[　　　　]{.ul}.\n2.设集合，,则 ( )\nA. B. C D\n3/. 设集合，则集合的子集有[　　]{.ul}个；，满足条件的集合有[\n]{.ul}个。\n4.若集合A={x/|-2≤x≤5}，B={x/|m+1≤x≤2m-1}且BA，求m的取值范围。\n题型5 集合运算\n题型5.1 已知集合，求集合运算\n> 1.已知集合A＝{x/|y＝ }，B＝{y/|y＝x^2^－1}，则 等于 (　　)\nA、A B、B C、 D、R\n2.若A={x} B={x },全集U=R，则A=\n题型5.2 已知集合运算，求集合\n![](/static/Images/cabd20c81160406e9d570746f63b6662/media/image34.png)\nheight=\"0.21875in\"}，\n> ![6ec8aac122bd4f6e](static/Images/cabd20c81160406e9d570746f63b6662/media/image37.wmf){width=\"0.8222222222222222in\"\n> height=\"0.21875in\"}，则图中的阴影部分表示的集合为 （ ）\nA．![6ec8aac122bd4f6e](static/Images/cabd20c81160406e9d570746f63b6662/media/image38.wmf){width=\"0.2611111111111111in\"\nB．![6ec8aac122bd4f6e](static/Images/cabd20c81160406e9d570746f63b6662/media/image39.wmf){width=\"0.4048611111111111in\"\nC![6ec8aac122bd4f6e](static/Images/cabd20c81160406e9d570746f63b6662/media/image40.wmf){width=\"0.5006944444444444in\"\nD![6ec8aac122bd4f6e](static/Images/cabd20c81160406e9d570746f63b6662/media/image41.wmf){width=\"0.6777777777777778in\"\n2.全集I={小于9的自然数}，\n> 则A=/_/_/_/_ B= /_/_/_/_\n题型5.3 已知集合运算，求参数\n1.已知,,,,\n,求![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-55249ad8a21d2748432702a8b1014f00", "__created_at__": 1754903684, "content": "d570746f63b6662/media/image41.wmf){width=\"0.6777777777777778in\"\n2.全集I={小于9的自然数}，\n> 则A=/_/_/_/_ B= /_/_/_/_\n题型5.3 已知集合运算，求参数\n1.已知,,,,\n,求![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image60.png){width=\"2.013888888888889e-2in\"\n2.若集合P={x/|+x-6=0}，S={x/|ax+1=0}，且SP，求a的可取值组成的集合.\n3.设A={x,其中xR,如果AB=B，求实数a的取值范围。\n4.已知集合，若，则的取值范围是/_/_/_/_/_/_/_/_/_/_/_。\n5.已知集合![](static/Images/cabd20c81160406e9d570746f63b6662/media/image69.wmf){width=\"2.8965277777777776in\"\n①若求实数m的取值范围；\n②若求实数m的取值范围。\n题型6 \"二维\"集合运算\n1.已知集合![](static/Images/cabd20c81160406e9d570746f63b6662/media/image72.wmf){width=\"3.3645833333333335in\"\nheight=\"0.3229166666666667in\"}求实数b的取值范围。\n> 2.设集合U={（x,y）/|y=2x-1},M={(x,y)/|}, 则CM=/_/_/_/_/_/_\n>\n> 3.，，AB有且仅有一个元素，则取值范围是/_/_/_/_/_/_/_/_/_/_/_/_\n4.集合A={（x,y）},集合B={（x,y）,且0}又A，求实数m的取值范围。\n题型6 自定义的集合\n1.已知集合M,N\n定义M※N=且设集合![](static/Images/cabd20c81160406e9d570746f63b6662/media/image85.wmf){width=\"0.9791666666666666in\"\nheight=\"0.25833333333333336in\"}， 则B※(B※A)= /_/_/_\n1.2函数及其表示\n题型1 映射概念\n1.从集合A＝｛1，2｝到B＝｛a,b，c｝的映射个数为\n2.已知集合P={}，Q={}下列不表示从P到Q的映射是\nA.∶x→y=x B.∶x→y= C.∶x→y= D.∶x→y= （ ）\n3.在映射，，且，则与A中的元素对应的B中的元素为 （ ）\n> A． B． C． D．\n题型2 函数概念\n1.下列各图中可表示函数的图象的只可能是 （ ）\nA B C D\n2.给出下列四个图形，其中能表示从集合*M*到集合*N*的函数关系的有 （ ）\nA．0个 B．1个C．2个 D．3个\n题型3 同一函数\n1.下列各组函数中，函数与表示同一函数的是 ．\n（1）＝，＝； （2）＝3－1，＝3－1；\n（3）＝，＝1； （4）＝，＝；\n（5）＝，＝\n题型4 函数的表示\n1.已知函数＝2＋1，＝＋2，\n(1)叙述的对应关系是 叙述的对应关系是\n(2)则 ； ；\n(3)＝．则\n2.汽车经过启动、加速行驶、匀速行驶、减速行驶之后停车，若把这一过程中汽车的行驶路程![](static/Images/cabd20c81160406e9d570746f63b6662/media/image123.wmf){width=\"0.125in\"\nheight=\"0.16666666666666666in\"}的函数，其图像可能是 （ ）\n3.已知函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image125.wmf){width=\"0.375in\"\nheight=\"0.2222222222222222in\"}分别由下表给出\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image127.emf){width=\"2.75in\"\n> 则（1）![](static/Images/cabd20c81160406e9d570746f63b6662/media/image128.wmf){width=\"0.5416666666666666in\"\n> height=\"0.2222222222222222in\"}的值为\n> ；（2）满足![](static/Images/cabd20c81160406e", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-e53bf8967b037c45280f153d63dd8ed8", "__created_at__": 1754903684, "content": "f63b6662/media/image127.emf){width=\"2.75in\"\n> 则（1）![](static/Images/cabd20c81160406e9d570746f63b6662/media/image128.wmf){width=\"0.5416666666666666in\"\n> height=\"0.2222222222222222in\"}的值为\n> ；（2）满足![](static/Images/cabd20c81160406e9d570746f63b6662/media/image129.wmf){width=\"1.0173611111111112in\"\n> height=\"0.21875in\"}的![](static/Images/cabd20c81160406e9d570746f63b6662/media/image130.wmf){width=\"0.1388888888888889in\"\n> height=\"0.1527777777777778in\"}的值是\n题型5 已知函数解析式求值。\n1.已知＝，则的值是 （ ）\nA. 9； B. 11； C. 44； D. 116．\n2.已知函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image133.wmf){width=\"1.6111111111111112in\"\nheight=\"0.7777777777777778in\"}，\n（1）则((－2))= ；\n（2）如果(a)=3，则实数a= .\n3.函数若，则的取值范围是/_/_/_/_/_/_/_/_.\n题型6 求解析式\n1已知![](static/Images/cabd20c81160406e9d570746f63b6662/media/image138.wmf){width=\"1.1805555555555556in\"\nheight=\"0.22569444444444445in\"}的解析式为 （ ）\nA![](static/Images/cabd20c81160406e9d570746f63b6662/media/image140.wmf){width=\"0.69375in\"\nB.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image141.wmf){width=\"1.101388888888889in\"\nC.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image142.wmf){width=\"1.4652777777777777in\"\nD.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image143.wmf){width=\"1.2777777777777777in\"\n2.已知是一次函数，且满足3－2＝2＋17，\n则\n3.已知二次函数f(x)满足条件f(0)=1及f(x+1)-f(x)=2x。求f(x)的解析式；\n4.已知f(x)是奇函数，g(x)是偶函数，且f(x)+g(x)=\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image149.wmf){width=\"0.375in\"\nheight=\"0.4270833333333333in\"},则f(x)=\n5.若![](static/Images/cabd20c81160406e9d570746f63b6662/media/image150.wmf){width=\"1.1847222222222222in\"\nheight=\"0.2222222222222222in\"}=\n6.设f(x)是定义在（-∞，+∞）上的函数，对一切x∈R均有f(x)+f(x+2)=0，\n当-1/<x≤1时，f(x)=2x-1，求当1/<x≤3时，函数f(x)的解析式。\n题型7 定义域\n题型7.1求函数的定义域\n1.  求下列函数的定义域.\n（1）\n（2）＝＋\n（3）＝；\n2.函数的定义域 ( 　)\nA . B. C. D.\n3.函数*y*＝的定义域是 ( )\nA. B. C. D.\n4.函数的定义域是 （ ）\nA. B. C. D.\n5.函数的定义域是\n6.(1)若函数＝的定义域是/[1，4/]，则＝的定义域是\n(2)若函数＝的定义域是/[1，2/]则＝的定义域是\n题型7.2已知函数的定义域问题\n1.如果函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image176.wmf){width=\"1.44375in\"\nheight=\"0.4305555555555556in\"}的定义域为R，则实数*k*的取值范围是 .\n2.若函数的定义域为，则实数的取值范围是 （ ）\n> A．B． C．D．\n题型8 值域\n题型8.1 图像法求函数的值域\n1.写出函数的值域\n（1） ，值域 ．\n(2)且 值域\n（3） ， 且值域\n2.下列函数中值域为的是 （ ）\n3.函数分别满足下列条件的值域。\n（1）;\n（2）;\n（3）;\n（4）;\n（5）\n4.函数y=的值", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-b0c11efbee3d4a68e99142de2d54e5aa", "__created_at__": 1754903684, "content": "题型8.1 图像法求函数的值域\n1.写出函数的值域\n（1） ，值域 ．\n(2)且 值域\n（3） ， 且值域\n2.下列函数中值域为的是 （ ）\n3.函数分别满足下列条件的值域。\n（1）;\n（2）;\n（3）;\n（4）;\n（5）\n4.函数y=的值域是 （ ）\n(A)(0,2) (B)/[-2,0/] (C)/[-2,2/] (D)(-2,2)\n5.已知\n(Ⅰ)作出函数的图像；\n(Ⅱ)求此函数的定义域和值域。\n6.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image208.wmf){width=\"1.0590277777777777in\"\n（![](static/Images/cabd20c81160406e9d570746f63b6662/media/image210.wmf){width=\"0.375in\"\nheight=\"0.2222222222222222in\"}，\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image212.wmf){width=\"0.2361111111111111in\"\nheight=\"0.2222222222222222in\"}的最小值\n> 7.已知函数，，，\n则函数的最小值。 (　　)\nA．1　 B．2 C．3 D．0\n题型8.2 转化为二次函数，求函数的值域\n1.求函数的值域\n2.求函数 的最大值和最小值。\n题型8.3 转化为反比例函数，求函数的值域\n1.求函数的值域.\n2.求函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image224.wmf){width=\"0.69375in\"\nheight=\"0.4583333333333333in\"}的值域。\n3.求函数 的值域。\n题型8.4 利用有界性，求函数的值域\n1.求函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image224.wmf){width=\"0.69375in\"\nheight=\"0.4583333333333333in\"}的值域\n2.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image226.wmf){width=\"0.7083333333333334in\"\nheight=\"0.4583333333333333in\"}的值域为 （ ）\nA.(－1,1) B./[＋1,1/]\nC.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image227.wmf){width=\"0.4166666666666667in\"\nD.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image228.wmf){width=\"0.4166666666666667in\"\n题型8.5 单调性法求函数的值域\n1.求函数 的最大值和最小值。\n2.求函数的值域\n题型8.6 判别式法求函数的值域\n1.求函数的值域\n2.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image226.wmf){width=\"0.7083333333333334in\"\nheight=\"0.4583333333333333in\"}的值域为 （ ）\nA.(－1,1) B./[＋1,1/]\nC.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image227.wmf){width=\"0.4166666666666667in\"\nD.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image228.wmf){width=\"0.4166666666666667in\"\n3.求函数 的值域。\n题型8.7 几何法求函数值域\n1.求函数的值域。\n题型9 已知函数值域，求系数\n1.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image233.wmf){width=\"0.75in\"\nheight=\"0.4305555555555556in\"}的值域为（－∞，－2）∪（－2，+∞），则实数*a*=\n.\n2.若函数的值域是实数集R，则实数a的取值范围 。\n1.3函数的基本性质 单调性\n题型1 判断函数的单调区间\n1.画出函数 的图象并判断函数的单调性 .\n2.函数y=x∣x-2∣的单调递增区间为/_/_/_/_/_/_/_/_/_/_/_;\n3.判断函数![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image237.wmf){width=\"0.680555555555555", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-b1ebef9a1ecec5f18967ac7a2549cf67", "__created_at__": 1754903684, "content": "单调性 .\n2.函数y=x∣x-2∣的单调递增区间为/_/_/_/_/_/_/_/_/_/_/_;\n3.判断函数![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image237.wmf){width=\"0.6805555555555556in\"\nheight=\"0.2361111111111111in\"}上的单调性\n4.下列函数的单调递减区间\n（1） /_/_/_/_/_/_/_/_/_/_.\n（2）./_/_/_/_/_/_/_/_/_/_/_/_/_/_/_.\n> 5.函数单调递增区间 （ ）\nA B， C. D\n6.下列函数中，既是偶函数又在区间上单调递减的是 (　　)\nA.B.C.D.\n7.若函数 是偶函数，则的单调递增区间是/_ /_．\n8.下列函数中，既是奇函数又在R上为增函数的是 (　　)\nA．*y*＝*x*＋1　　B．*y*＝－*x*^2^ C．*y*＝ D．*y*＝*x*︱*x*︱\n9.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image255.wmf){width=\"0.375in\"\nheight=\"0.19375in\"}时\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image259.wmf){width=\"0.5965277777777778in\"\n> height=\"0.2222222222222222in\"}.\n>\n> /(1/)\n> 求证：![](static/Images/cabd20c81160406e9d570746f63b6662/media/image255.wmf){width=\"0.375in\"\n> height=\"0.2222222222222222in\"}是![](static/Images/cabd20c81160406e9d570746f63b6662/media/image260.wmf){width=\"0.16666666666666666in\"\n> height=\"0.18055555555555555in\"}上的增函数；\n/(2/)\n若![](static/Images/cabd20c81160406e9d570746f63b6662/media/image261.wmf){width=\"0.6111111111111112in\"\n题型2 已知函数的单调区间，求参数。\n1.设二次函数f(x)=x^2^-(2a+1)x+3\n(1)若函数f(x)的单调增区间为![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image263.wmf){width=\"0.5729166666666666in\"\nheight=\"0.19652777777777777in\"}，则实数a的值/_/_/_/_/_/_/_/_/_/_；\n(2)若函数f(x)在区间![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image264.wmf){width=\"0.5729166666666666in\"\nheight=\"0.1798611111111111in\"}内是增函数，则实数a的范围/_/_/_/_/_/_/_/_/_/_；\n> 2.设定义在/[-2，2/]上的偶函数f(x)在区间/[0，2/]上单调递减，若f(1-m)/<f(m)，求实\n>\n> 数m的取值范围。\n3.若函数是上的减函数，求的取值范围/_/_/_/_/_/_/_．\n4.函数上具有单调性,则实数k的取值范围 ( 　)\nA. B．C． D．\n题型3 已知函数的单调性，比较大小。\n1.设函数f(x)在R上为减函数，则下列正确的是 （ ）\nA![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image273.wmf){width=\"0.9583333333333334in\"\nB![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image274.wmf){width=\"0.9583333333333334in\"\nC![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image275.wmf){width=\"1.2083333333333333in\"\nD![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-ecc85f7e2a9521a27b7fb3fdce317e03", "__created_at__": 1754903684, "content": "高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image275.wmf){width=\"1.2083333333333333in\"\nD![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image276.wmf){width=\"1.1666666666666667in\"\n2．已知函数y=f(x)在（0，2）上是增函数，函数f(x+2)是偶函数，则 （ ）\nA．B．C．D。\n题型4 已知函数的单调性，求范围\n1.已知函数是上的增函数，![www.xkb1.com\n新课标第一网不用注册，免费下载！](static/Images/cabd20c81160406e9d570746f63b6662/media/image283.png){width=\"2.013888888888889e-2in\"\nheight=\"2.0833333333333332e-2in\"}，是其图像上的两点，那么 的解集的补集是\n（ ）\nA.\nB![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image3.png){width=\"2.013888888888889e-2in\"\nheight=\"2.5e-2in\"} C. D.\n2.函数是定义在上的奇函数，在上是单调递减且\n若则实数的取值范围是 （ ）\n1.4函数的基本性质 奇偶性\n题型1 判断函数的奇偶性\n1.画出函数 的图象并判断函数的奇偶性 .\n2.判断下列函数的奇偶性\n/(1/)\n/(2/) f(x)= x^3^+5x\n（3）\n（4）\n（5）\n3.判断函数的奇偶性\n4.判断函数的奇偶性\n5.函数的图像关于 （ ）\nA.轴对称 B.原点对称 C.轴对称 D.轴对称\n6.函数是 （ ）\nA、奇函数 B、偶函数 C、既奇又偶函数 D、非奇非偶函数\n7.设函数![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image313.wmf){width=\"0.375in\"\nheight=\"0.2222222222222222in\"}。\n（1）求证：是奇函数；\n> （2）判断函数在![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image320.wmf){width=\"0.7083333333333334in\"\n> height=\"0.2222222222222222in\"}\n> 单调性，并求在![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image320.wmf){width=\"0.7083333333333334in\"\n> height=\"0.2222222222222222in\"}时，![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image313.wmf){width=\"0.375in\"\n> height=\"0.2222222222222222in\"}的最大、最小值。\n题型2 已知函数的奇偶性，求解析式。\n> 1.已知函数为偶函数，且当时，则当时,\n>\n> 的解析式为 。\n2.已知()是R上的奇函数，且当时，，则()的解析式\n为\n题型3 已知函数的奇偶性，求参数。\n1.定义在上的奇函数，则常数/_/_/_/_/_/_,/_/_/_/_/_/_/_/_/_/_/_\n2.若函数＝是偶函数，则实数的值是 ．\n3.若函数是奇函数，则=/_/_/_/_/_/_/_/_/_源:学科网ZXXK/]\n4.已知函数f(x)=ax^2^+bx+3a+b是偶函数，且定义域为/[a-1,2a/]，则a=/_/_/_,b=/_/_/_/_\n> 5.设定义在/[-2，2/]上的偶函数f(x)在区间/[0，2/]上单调递减，若f(1-m)/<f(m)，求实\n>\n> 数m的取值范围。\n题型4 已知函数的奇偶性，求值或解集等。\n1.已知都是奇函数，且在的最大值是8，则在的最 值是 。\n### 2", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-273a4282b2114f237e0221e6de72887a", "__created_at__": 1754903684, "content": "> 5.设定义在/[-2，2/]上的偶函数f(x)在区间/[0，2/]上单调递减，若f(1-m)/<f(m)，求实\n>\n> 数m的取值范围。\n题型4 已知函数的奇偶性，求值或解集等。\n1.已知都是奇函数，且在的最大值是8，则在的最 值是 。\n### 2.若f(x)是奇函数,且在（0,+∞)内是增函数,又f(-3)=0,则xf(x)〈0的解集为/_/_/_/_/_；\n### 则的解集为/_/_/_/_/_/_。\n3.已知是定义在R上的奇函数，，则= 。\n4/. 是定义在上的偶函数，且，则下列各式一定成立的是\nA. B. C. D. （ ）\n5.设是定义在R上的奇函数，且当时,，则()\nA．1 B．－1 C．－ D. （ ）\n6.若在(－∞，0)∪(0，＋∞)上为奇函数，且在(0，＋∞)上为增函数，，则不等式的解集为/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_/_．\n1.5函数的图像\n题型1 函数图像\n1.作函数图象：\n(1);\n（2）且\n（3） ， 且\n题型2 去绝对值作函数图像\n1.作函数图象：\n(1);\n（2）＝＋\n题型3 利用图像变换作函数图像\n1.作函数图象： (草图)\n（1）\n（2）\n（3）\n/(4/)\n/(5/)\n2.已知*f*(*x*)＝/|2*^x^*－1/|，则函数*f*(*x*)的单调区间 ．\n3.函数的图象大致是 （ ）\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image371.emf){width=\"3.125in\"\n4.函数的值域为 （\n![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image373.png){width=\"3.0555555555555555e-2in\"\nheight=\"1.6666666666666666e-2in\"}）\nA．（０，＋） B ．　 C ．（０，２） D．\n5.已知的图象过点（3，2），则函数的图象关于x轴的对称图形定过点 （ ）\nA.（2，-2）B.（2，2）C.（-4，2）D.（4，-2）\n6.把函数的图像沿*x*轴向右平移2个单位，所得的图像为*C*,*C*关于*x*轴对称的图像为的图像，则的函数表达式为\n（ ）\nA. B. C. D.\n7.函数*f*(*x*)的图象向右平移1个单位长度，所得图象与曲线关于对称，则*f*(*x*)=\n(　　)\nA．B． C． D．\n> 8.要得到![学科网(www.zxxk.com)/--国内最大的教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image388.wmf){width=\"0.7638888888888888in\"\n> height=\"0.25in\"}的图像，只需将函数![学科网(www.zxxk.com)/--国内最大的教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image389.wmf){width=\"0.6388888888888888in\"\n> height=\"0.25in\"}的图像 ( )\n>\n> > A．向左平移2个单位\n> > B．向右平移2个C．向左平移1个单位D．向右平移1个单位\n题型4 已知函数解析式判断图象\n1.函数![21世纪教育网 /--\n中国最大型、最专业的中小学教育资源门户网站](static/Images/cabd20c81160406e9d570746f63b6662/media/image390.wmf){width=\"0.8333333333333334in\"\nheight=\"0.4583333333333333in\"}的图像大致为 ( )\nA B C D\n2.函数的图像大致为 ( )\n3.函数*y*＝的大致图象是 (　　)\n![](/static/Images/cabd20c81160406e9d570746f63b6662/media/image392.png)\n题型5 研究", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-0f22f44cf1ecc5142af516e25f5faa4c", "__created_at__": 1754903684, "content": "390.wmf){width=\"0.8333333333333334in\"\nheight=\"0.4583333333333333in\"}的图像大致为 ( )\nA B C D\n2.函数的图像大致为 ( )\n3.函数*y*＝的大致图象是 (　　)\n![](/static/Images/cabd20c81160406e9d570746f63b6662/media/image392.png)\n题型5 研究函数性质作函数图象\n1.利用函数性质画出图像\n题型6 函数图像的对称性\n1.如果函数对任意的实数*x*，都有，那么 （ ）\nA. B.\nC. D.\n2.已知*f(x)＝x^2^*＋*bx*＋*c*且*f(*－1*)＝f(*3*)*，则正确的是 (　　)\nA．*f*(－3)＜*c*＜*f*() B．*f*()＜*c*＜*f*(－3)\nC．*f*()＜*f*(－3)＜*c* D．*c*＜*f*()＜*f*(－3)\n3.设f(x)是(－∞，+∞)上的偶函数，f(x+2)=f(-x)，当0≤x≤1时，f(x)=x，\n> 则 f(7.5)=\nA．1.5 B．－0.5 C．0.5 D．－1.5 （ ）\n4.已知定义在上的函数是奇函数且满足，，\n则 (　　)\nA． B． C． D．\n5．设奇函数的定义域为,当时的图像如图所示，则不等式 的解集是\n6.若直角坐标平面内的两点P，Q满足条件：①P，Q都在函数y＝f(x)的图象上；②P，Q关于原点对称．则称点对/[P，Q/]是函数y＝f(x)的一对\"友好点对\"(点对/[P，Q/]与/[Q，P/]看作同一对\"友好点对\")．已知函数f(x)＝，则此函数的\"友好点对\"有\n(　　)\nA．0对 B．1对 C．2对 D．3对\n7.函数f(x)＝图象的对称中心为 (　　)\nA．(0，0)　 B．(0，1) C．(1，0) D．(1，1)\n8.把函数y＝f(x)＝(x－2)^2^＋2的图象向左平移1个单位，再向上平移1个单位，所得图象对应的函数解析式是\n(　　)\nA．*y*＝(*x*－3)^2^＋3 B．*y*＝(*x*－3)^2^＋1 C．*y*＝(*x*－1)^2^＋3\nD．*y*＝(*x*－1)^2^＋1\n9.已知方程有四个实数根 ，则实数的取值范围是 ( )\n第二章 基本初等函数\n2.1指数函数\n题型1 指数运算\n1.![](static/Images/cabd20c81160406e9d570746f63b6662/media/image424.wmf){width=\"1.5965277777777778in\"\nheight=\"0.7916666666666666in\"}=\n2.计算\n3.化简 =\n4.化简［］的结果为 （ ）\nA．5 B． C．－ D．－5\n题型2 指数函数概念\n1.下列以x为自变量的函数中，是指数函数的是 ( )\nA.y=(-4)^x^ B.y=π^x^ C.y=-4^x^ D.y=a^x+2^(a/>0且a≠1)\n2.已知是指数函数，且，则 。\n3.函数![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image3.png){width=\"2.013888888888889e-2in\"\nheight=\"2.0833333333333332e-2in\"}是指数函数，则a的取值范围是 ( )\nA. B. C. D.\n题型3 指数函数型的定义域、值域\n1.函数的定义域为\n2.函数![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image439.wmf){width=\"0.4722222222222222in\"\nheight=\"0.25in\"}在/[0,1/]上的最大值与最小值的和为3，则a=/_/_/_/_/_\n3.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image440.wmf){width=\"0.6527777777777778in\"\nheight=\"0.277777777", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-d12191880f44fa0494d2dd714869dd81", "__created_at__": 1754903684, "content": "/image439.wmf){width=\"0.4722222222222222in\"\nheight=\"0.25in\"}在/[0,1/]上的最大值与最小值的和为3，则a=/_/_/_/_/_\n3.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image440.wmf){width=\"0.6527777777777778in\"\nheight=\"0.2777777777777778in\"}的定义域为 ，值域为\n4.函数的值域是\n5.已知函数，求其单调区间及值域。\n6.设，求函数的最大值和最小值。\n7.设![](static/Images/cabd20c81160406e9d570746f63b6662/media/image445.wmf){width=\"0.7777777777777778in\"\nheight=\"0.1527777777777778in\"}的值\n题型4 指数函数型恒过定点\n1.函数且的图像必经过点\n2.函数且的图像必经过点\n题型5 单调性\n1.比较下列各组数值的大小：\n（1）![6ec8aac122bd4f6e](static/Images/cabd20c81160406e9d570746f63b6662/media/image453.wmf){width=\"0.375in\"\nheight=\"0.2222222222222222in\"}；\n2.下列不等式0.7^1.3^＜0.7^0.7^2.4^0.1^＜2.4^---0.7^，0.7^1.3^＜1.3^0.7^\n0.7^-0.9^＜1.3^-0.9^\n> 正确的个数是（ ）\nA．0 B．1 C．2 D．3\n3.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image457.wmf){width=\"0.8611111111111112in\"\nheight=\"0.5277777777777778in\"}的递减区间为 ；最大值是\n4.函数的递增区间为 ；最小值是\n题型6 奇偶性\n1.判断的奇偶性\n题型7 图象\n1.设都是不等于的正数，\n> 在同一坐标系中的图像如图所示，则的大小顺序是 （ ）\nA．\nB．\nC．\nD．\n2.若函数的图象![学科网(www.zxxk.com)/--教育资源门户，提供试卷、教案、课件、论文、素材及各类教学资源下载，还有大量而丰富的教学相关资讯！](static/Images/cabd20c81160406e9d570746f63b6662/media/image476.png){width=\"2.013888888888889e-2in\"\nheight=\"2.2222222222222223e-2in\"}在第一、三、四象限内，则 (　　)\nA. B. C.且 D. 且\n3.设![](static/Images/cabd20c81160406e9d570746f63b6662/media/image483.wmf){width=\"0.9305555555555556in\"\nheight=\"0.2222222222222222in\"}，则下列关系式一定成立的是\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image486.wmf){width=\"0.19375in\"\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image487.wmf){width=\"0.4861111111111111in\"\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image488.wmf){width=\"0.19375in\"\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image490.wmf){width=\"0.19375in\"\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image492.wmf){width=\"0.20833333333333334in\"\nheight=\"0.2222222222222222in\"} （ ）\n4.若函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image494.wmf){width=\"1.1388888888888888in\"\nheight=\"0.1527777777777778in\"}的范围是\n5.设，求函数的最大值和最小值。\n题型8 方程、不等式\n1.解方程\n2.不等式![](static/Images/cabd20c81160406e9d570746f63b6662/media/image498.wmf){width=\"0.94375in\"\nheight=\"0.5277777777777778in\"}的解集为\n2.2对数函数\n题型1 对数运算\n1/.\n2.，则的值为 （ ）\nA. B.4 C.1 D.4或1\n3/. 的值等于 (　　)\nA．2＋ B．2 C．2＋ D．1＋\n4.已知 .\n题型2 对数概", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-99adb00804c76c677a02a05160126a18", "__created_at__": 1754903684, "content": ".94375in\"\nheight=\"0.5277777777777778in\"}的解集为\n2.2对数函数\n题型1 对数运算\n1/.\n2.，则的值为 （ ）\nA. B.4 C.1 D.4或1\n3/. 的值等于 (　　)\nA．2＋ B．2 C．2＋ D．1＋\n4.已知 .\n题型2 对数概念\n1.指数函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image505.wmf){width=\"0.4583333333333333in\"\nheight=\"0.25in\"} 且的反函数为 ；它的值域是\n2.下列函数中，当＞＞1时，使＜成立的是\nA B C D\n3.函数 的图像如图所示，则 的大小关系是\n![](static/Images/cabd20c81160406e9d570746f63b6662/media/image517.emf){width=\"1.4583333333333333in\"\nheight=\"1.4895833333333333in\"} （ ）\nA．\nB．\nC.\nD.\n题型3 对数函数型的定义域、值域\n1.函数的定义域是\n2.函数的定义域 。\n3.函数*y*＝的定义域为 (　　)\nA．(－4，－1) B．(－4,1) C．(－1,1) D．(－1,1/]\n4.设函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image524.wmf){width=\"0.9305555555555556in\"\nheight=\"0.4305555555555556in\"}，则a的值\n是\n5.若函数的定义域为实数集R，则实数a的取值范围 .\n6.若函数的值域是实数集R，则实数a的取值范围 。\n7.函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image528.wmf){width=\"1.4583333333333333in\"\nheight=\"0.4027777777777778in\"}的值域是\n8.设函数![](static/Images/cabd20c81160406e9d570746f63b6662/media/image524.wmf){width=\"0.9305555555555556in\"\nheight=\"0.4305555555555556in\"}，则a的值是\n9.已知，，求函数的最大值及相应的的值。\n10.若，求的最大值与最小值。\n11.已知函数，则/_/_/_/_/_．\n12.已知*f*(log~2~*x*)＝*x*，则*f*()＝ (　　)\nA．　　B．　 C．　　D．\n13.求函数的值域。\n14.求函数的最值。\n题型4 对数函数型的恒过定点\n1.已知函数的图象经过定点P，则点P的坐标为(　　)\nA. B. C. (-1,4) D. (-1,3)\n2函数的图象恒过定点,则的坐标是\n题型5 奇偶性\n1.判断函数奇偶性。\n2.函数的图象关于 ( )\nA.*y*轴对称 B．*x*轴对称 C．原点对称 D．直线*y*＝*x*对称\n3.已知是偶函数，它在上是减函数，若则，则实数的取值范围是 ( )\nA、 B、 C、 D、\n4.若函数 则 .\n题型5 单调性\n1.已知![](static/Images/cabd20c81160406e9d570746f63b6662/media/image557.wmf){width=\"1.3055555555555556in\"\nheight=\"0.375in\"}，则 ( )\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image486.wmf){width=\"0.19375in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image558.wmf){width=\"0.6388888888888888in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image488.wmf){width=\"0.19375in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image559.wmf){width=\"0.6388888888888888in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image490.wmf){width=\"0.19375in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image560.wmf){width=\"0.6388888888888888in\"\n> height=\"0.19375in\"}\n> ![](static/", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-256c0afc0f07559c60ea21cf4b2ac865", "__created_at__": 1754903684, "content": "![](static/Images/cabd20c81160406e9d570746f63b6662/media/image490.wmf){width=\"0.19375in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image560.wmf){width=\"0.6388888888888888in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image492.wmf){width=\"0.20833333333333334in\"\n> height=\"0.19375in\"}\n> ![](static/Images/cabd20c81160406e9d570746f63b6662/media/image561.wmf){width=\"0.6388888888888888in\"\n> height=\"0.19375in\"}\n2.，，，的大小关系是\n3.设![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image564.wmf){width=\"2.3333333333333335in\"\nheight=\"0.2777777777777778in\"}，则 ( )\nA. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image565.wmf){width=\"0.625in\"\nheight=\"0.19375in\"} B. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image566.wmf){width=\"0.625in\"\nheight=\"0.19375in\"} C. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image567.wmf){width=\"0.625in\"\nheight=\"0.19375in\"} D. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image568.wmf){width=\"0.625in\"\n4.三个数*a*＝1.2^0.7^，*b*＝log~1.2~0.7，*c*＝log~0.6~0.8大小的顺序是\n(　　)\nA．*a*/>*b*/>*c* B．*a*/>*c*/>*b* C．*b*/>*a*/>*c* D．*c*/>*a*/>*b*\n5.的递增区间为\n6.下列区间中，函数在其上为增函数的是 ( )\nA. B. C. D.\n7.写出函数的单调递减区间\n8.已知y=log~a~(2－ax)在/[0，1/]上是关于x的减函数，则a的取值范围是 （ ）\nA．（0，1）B．（1，2）C．（0，2）D．\n![](/static/Images/cabd20c81160406e9d570746f63b6662/media/image577.png)\nheight=\"0.8694444444444445in\"}题型6 对数函数型的图像\n1.函数*f*(*x*)=1+log~2~*x*与*g*（*x*）=2^-x+1^\n在同一直角坐标系下的图象大致是/_/_/_/_/_/_/_/_/_/_/_.\n2.函数,则的关系为/_/_/_/_/_/_/_/_/_/_/_/_.\n题型8 方程、不等式\n1.，则的取值范围是\n2.方程![](static/Images/cabd20c81160406e9d570746f63b6662/media/image583.wmf){width=\"1.9305555555555556in\"\nheight=\"0.2638888888888889in\"}的解是\n3.log~7~［log~3~（log~2~*x*）］＝0，则等于 （　　）\nA、 B、 C、 D、\n2.3幂函数\n题型1 幂函数概念\n1.函数是一个幂函数，则m= .\n2.如图，图中所示曲线为幂函数![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image594.wmf){width=\"0.4722222222222222in\"\nheight=\"0.25in\"}在第一象限的\n象，则c~1~, c~2~, c~3~, c~4~按从大到小排列为/_/_/_/_/_/_/_/_/_/_/_/_/_\n题型2 五个重要的幂函数\n1.函数y＝x，y＝x^2^，y＝x", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-23ef1d18da0345a1aa2ec56a425daeef", "__created_at__": 1754903684, "content": "6662/media/image594.wmf){width=\"0.4722222222222222in\"\nheight=\"0.25in\"}在第一象限的\n象，则c~1~, c~2~, c~3~, c~4~按从大到小排列为/_/_/_/_/_/_/_/_/_/_/_/_/_\n题型2 五个重要的幂函数\n1.函数y＝x，y＝x^2^，y＝x^3^， 的图象及性质\n2.函数y=与的两个图象之间 （ ）\nA. 关于原点对称 B. 关于x轴对称 C. 关于y轴对称D. 关于直线对称\n题型3 幂函数性质\n1.在函数①y=x^3^②y=x^2^③y=x^-1^④y=中，定义域和值域相同的是 .\n2.函数![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image599.wmf){width=\"0.5555555555555556in\"\nheight=\"0.375in\"}的图象大致是 （ ）\nA. B. C. D.\n题型4 求幂函数\n1.函数是一个反比例函数，则m= .\n2.已知幂函数\n的图象如图，则 （ ）\nA. p为偶数，q为奇数\nB. p为偶数，q为负奇数\nC. p为奇数，q为偶数\nD. p为奇数，q为负偶数\n3.若函数()＝a^x^(a/>0，且a≠1)在/[－1,2/]上的最大值为4，最小值为m，且函数g()＝(1－4m)在/[0，＋∞)上是增函数，求a.\n题型5 比较大小\n1.将![高考资源网(ks5u.com),中国最大的高考网站,您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image604.wmf){width=\"0.5833333333333334in\"\nheight=\"0.34652777777777777in\"}按从小到大进行排列为/_/_/_/_/_/_/_/_\n2.，，的大小关系是 （ ）\nA. B. C. D.\n3.已知幂函数图象过点，则函数是 （ ）\nA.奇函数 B.偶函数 C.非奇非偶函数 D.既是奇函数又是偶函数\n第三章 函数的应用\n3.1函数与不等式\n题型1 不等式恒成立、存在问题\n1.已知对任意恒成立。求实数的取值范围。\n2.已知对任意恒成立。求实数 的取值范围\n题型2一元二次不等式\n1．(1) 不等式的解集为 .\n/(2/) 不等式的解集为 .\n/(3/) 不等式的解集为 .\n/(4/) 不等式的解集为 .\n2.若不等式*ax*^2^+*bx*+2/>0的解集是，则的值是 ．\n3.关于*x*的不等式组的整数解的集合为{－2}，则实数*k*的取值范围是/_/_/_/_/_/_/_/_/_/_/_/_．\n5.已知关于的不等式的解集为．\n（1）求的值；\n（2）当时，解关于的不等式（用表示）．\n6.关于不等式的解是全体实数，求的取值范围 （ ）\n> A． B． C． D．\n7.已知*a*是正实数，函数*f*(*x*)＝*ax*^2^＋2*ax*＋1.若*f*(*m*)＜0，比较大小：\n*f*(*m*＋2)/_/_/_/_/_/_/_/_1.(用\"＜\"或\"＝\"或\"＞\"连接)\n3.2函数与方程\n题型1 函数的零点\n1.函数的图象与轴的交点坐标为 函数的零点为\n题型2 存在性定理\n1.方程lg*x*+*x*=3的解所在区间为 （ ）\nA.(0，1) B.(1，2) C.(2，3) D.(3，+∞)\n2.方程必有一个根的区间是 （ ）\nA． B. C. D.\n3.在下列区间中，函数*f*(*x*)＝e*^x^*＋4*x*－3的零点所在的区间为 (　 )\nA. B. C. D.\n4.已知函数*f*(*x*)＝()*^x^*－log~3~*x*，若*x*~0~是函数*y*＝*f*(*x*)的零点，且0＜*x*~1~＜*x*~0~，则*f*(*x*~1~)的\n值 (　　)\nA．恒为正值 B", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-690b0b881ec3aa9627851d3c7312e9f5", "__created_at__": 1754903684, "content": "间为 (　 )\nA. B. C. D.\n4.已知函数*f*(*x*)＝()*^x^*－log~3~*x*，若*x*~0~是函数*y*＝*f*(*x*)的零点，且0＜*x*~1~＜*x*~0~，则*f*(*x*~1~)的\n值 (　　)\nA．恒为正值 B．等于0 C．恒为负值 D．不大于0\n题型3 判断函数的零点个数\n1.方程的根个数为\n2.设分别是方程的实数根，则\nA. B. C. D. （ ）\n3.函数f(x)＝的零点个数是/_/_/_/_/_/_/_/_．\n4.已知函数f(x)＝若函数g(x)＝f(x)－m有3个零点，则实数m\n的取值范围是/_/_/_/_/_/_/_/_．\n题型4 二分法\n1.若函数![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image650.wmf){width=\"0.4027777777777778in\"\nheight=\"0.2777777777777778in\"}的零点与![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image651.wmf){width=\"1.0416666666666667in\"\nheight=\"0.28125in\"}的零点之差的绝对值不超过0.25，则\n![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image652.wmf){width=\"0.4027777777777778in\"\nheight=\"0.2777777777777778in\"}能是 （ ）\nA.![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image653.wmf){width=\"0.94375in\"\nheight=\"0.2777777777777778in\"}B. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image654.wmf){width=\"1.0277777777777777in\"\nheight=\"0.2777777777777778in\"}C. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image655.wmf){width=\"0.9166666666666666in\"\nheight=\"0.2777777777777778in\"} D. ![高考资源网(\nwww.ks5u.com)，中国最大的高考网站，您身边的高考专家。](static/Images/cabd20c81160406e9d570746f63b6662/media/image656.wmf){width=\"1.2361111111111112in\"\n2/. 函数在区间的零点为/_/_/_/_/_/_/_/_/_/_/_（精确度为0.05）\n2.  下列函数图象与*x*轴均有交点，其中不能用二分法求函数零点的是 （ ）\n4.已知函数f(x)的图象是连续不断的，有如下的x，f(x)的对应表\n---------- -------- -------- -------- ------- ---------- -----------\n*x*        1        2        3        4       5          6\n*f*(*x*)   136.13   15.552   －3.92   10.88   －52.488   －232.064\n---------- -------- -------- -------- ------- ---------- -----------\n则函数*f*(*x*)存在零点的区间有 (　　)\nA．区间/[1，2/]和/[2，3/]\nB．区间/[2，3/]和/[3，4/]\nC．区间/[2，3/]，/[3，4/]和/[4，5/]\nD．区间/[3，4/]，/[4，5/]和/[5，6/]\n题型5 求函数的零点\n1.函数的零点为\n2/. 函数在区间的零点为/_/_/_/_/_/_/_/_/_/_/_（精确度为0.05）\n题型6 一元二次方程根的分布\n1.已知![](static/Images/cabd20c81160406e9d570746f63b6662/media/image660.wmf){width=\"0.13541666666666666in\"\nheight=\"0.15625in\"}的取值范围.\n2.函数*f*(*x*)＝*mx*^2^－2*x*＋1有且仅有一个正实数的零点", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-8a44806f19024847be269bff78a6847e", "__created_at__": 1754903684, "content": "一元二次方程根的分布\n1.已知![](static/Images/cabd20c81160406e9d570746f63b6662/media/image660.wmf){width=\"0.13541666666666666in\"\nheight=\"0.15625in\"}的取值范围.\n2.函数*f*(*x*)＝*mx*^2^－2*x*＋1有且仅有一个正实数的零点，则实数*m*的取值范围是/_/_/_/_/_/_/_/_．\n3.已知关于x的二次方程x^2^＋2mx＋2m＋1＝0.\n> (1)若方程有两根，其中一根在区间(－1，0)内，另一根在区间(1，2)内，求m的取值范围；\n(2)若方程两根均在区间(0，1)内，求m的取值范围。\n3.3函数应用\n题型1函数模型应用\n1.某花店每天以每枝5元的价格从农场购进若干枝玫瑰花，然后以每枝10元的价格出售。如果当天卖不完，剩下的玫瑰花做垃圾处理。若花店一天购进17枝玫瑰花，求当天的利润*y*(单位：元)关于当天需求量*n*（单位：枝，*n*∈N）的函数解析式。\n2.经销商经销某种农产品，在一个销售季度内，每售出It该产品获利润500元，未售出的产品，每It亏损300元.根据历史资料，得到销售季度内市场需求量的频率分布直图，如右图所示.经销商为下一个销售季度购进了130t该农产品.以X（单位：t≤100≤X≤150)表示下一个销售季度内的市场需求量，T(单位:元)表示下一个销售季度内经销该农产品的利润，将T表示为X的函数。\n3.某电视新产品投放市场后第一个月销售100台，第二个月销售200台，第三个月销售400台，第四个月销售790台，则下列函数模型中能较好地反映销量y与投放市场的月数x之间关系的是\n(　　)\nA．y＝100x B．y＝50x^2^－50x＋100 C．y＝50×2^x^ D．y＝100log~2~x＋100\n4.某企业生产一种产品时，固定成本为5\n000元，而每生产100台产品时直接消耗成本要增加2\n500元，市场对此产品的年需求量为500台，销售收入的函数为*R*(*x*)＝5*x*－*x*^2^(万元)(0≤*x*≤5)，其中*x*是产品售出的数量(单位：百台)．\n(1)把利润表示为年产量的函数；\n(2)年产量为多少时，企业所得的利润最大", "full_doc_id": "高中数学必修一常见题型归类_3027455.docx", "file_path": "高中数学必修一常见题型归类_3027455.docx"}, {"__id__": "chunk-24b5971fb37926c19b282f66a64a96d5", "__created_at__": 1754904087, "content": "高一数学教学计划\n杨冬梅 杨莎 吴加璐 王曼玉 李夏颖\n本学期我担任高一数学教学工作。学生的学习能力较差，问题很多。有些学生解方程、解不等式甚至连分数的加减法都不会。这给教学工作带来了一定的难度，要想在这个基础上把教学搞好，任务很艰所以特制定如下教学工作计划。\n一、指导思想\n准确把握《教学大纲》和《考试大纲》的各项基本要求，立足于基础知识和基本技能的教学，注重渗透数学思想和方法。针对学生实际，不断研究数学教学，改进教法，指导学法，奠定立足社会所需要的必备的基础知识、基本技能和基本能力，着力于培养学生的创新精神，运用数学的意识和能力，奠定他们终身学习的基础。\n二、教学建议\n1、深入钻研教材。以教材为核心，深入研究教材中章节知识的内外结构，熟练把握知识的逻辑体系，细致领悟教材改革的精髓，逐步明确教材对教学形式、内容和教学目标的影响。\n2、准确把握新大纲。新大纲修改了部分内容的教学要求层次，准确把握新大纲对知识点的基本要求，防止自觉不自觉地对教材加深加宽。同时，在整体上，要重视数学应用；重视数学思想方法的渗透。如增加阅读材料（开阔学生的视野），以拓宽知识的广度来求得知识的深度。\n3、树立以学生为主体的教育观念。学生的发展是课程实施的出发点和归宿，教师必须面向全体学生因材施教，以学生为主体，构建新的认识体系，营造有利于学生学习的氛围。\n4、发挥教材的多种教学功能。用好章头图，激发学生的学习兴趣；发挥阅读材料的功能，培养学生用数学的意识；组织好研究性课题的教学，让学生感受社会生活之所需；小结和复习是培养学生自学的好材料。\n5、落实课外活动的内容。组织和加强数学兴趣小组的活动内容。\n三、教学内容及课时安排\n第一章  集合与函数概念\n1．通过实例，了解集合的含义，体会元素与集合的\"属于\"关系。\n2．能选择自然语言、图形语言、集合语言（列举法或描述法）描述不同的具体问题，感受集合语言的意义和作用。\n3．理解集合之间包含与相等的含义，能识别给定集合的子集。\n4．在具体情境中，了解全集与空集的含义。\n5．理解两个集合的并集与交集的含义，会求两个简单集合的并集与交集。\n6．理解在给定集合中一个子集的补集的含义，会求给定子集的补集。\n7．能使用Venn图表达集合的关系及运算，体会直观图示对理解抽象概念的作用。\n8．通过丰富实例，进一步体会函数是描述变量之间的依赖关系的重要数学模型，在此基础上学习用集合与对应的语言来刻画函数，体会对应关系在刻画函数概念中的作用；了解构成函数的要素，会求一些简单函数的定义域和值域；了解映射的概念。\n9．在实际情境中，会根据不同的需要选择恰当的方法（如图像法、列表法、解析法）表示函数。\n10．通过具体实例，了解简单的分段函数，并能简单应用。\n11．通过已学过的函数特别是二次函数，理解函数的单调性、最大（小）值及其几何意义；结合具体函数，了解奇偶性的含义。\n12．学会运用函数图象理解和研究函数的性质。\n课时分配（14课时）\n+-------+----------------------+---------+---------+\n| 1.1.1 | 集合的含义与表示     | 约1课时 | 9月1日  |\n+-------+----------------------+---------+---------+\n| 1.1.2 | 集合间的基本关系     | 约1课时 | 9月4日  |\n|       |                      |         |         |\n|       |                      |         | /|      |\n|       |                      |         |         |\n|       |                      |         | /|      |\n|       |                      |         |         |\n|       |                      |         | 9月12日 |\n+-------+----------------------+---------+---------+\n| 1.1.3 | 集合的基本运算       | 约2课时 |         |\n+-------+----------------------+---------+---------+\n|       | 小结与复习           | 约1课时 |         |\n+-------+----------------------+---------+---------+\n| 1.2.1 | 函数的概念           | 约2课时 |         |\n+-------+----------------------+---------+---------+\n| 1.2.2 | 函数的表示法         | 约2课时 | 9月13日 |\n|       |                      |         |         |\n|       |                      |         | /|      |\n|       |", "full_doc_id": "高中数学必修一教学计划_1448630.docx", "file_path": "高中数学必修一教学计划_1448630.docx"}, {"__id__": "chunk-7afed6bec1887e49a8d76a2b54d75d41", "__created_at__": 1754904087, "content": "约1课时 |         |\n+-------+----------------------+---------+---------+\n| 1.2.1 | 函数的概念           | 约2课时 |         |\n+-------+----------------------+---------+---------+\n| 1.2.2 | 函数的表示法         | 约2课时 | 9月13日 |\n|       |                      |         |         |\n|       |                      |         | /|      |\n|       |                      |         |         |\n|       |                      |         | /|      |\n|       |                      |         |         |\n|       |                      |         | 9月25日 |\n+-------+----------------------+---------+---------+\n| 1.3.1 | 单调性与最大（小）值 | 约2课时 |         |\n+-------+----------------------+---------+---------+\n| 1.3.2 | 奇偶性               | 约1课时 |         |\n+-------+----------------------+---------+---------+\n|       | 小结与复习           | 约2课时 |         |\n+-------+----------------------+---------+---------+\n|       |                      |         |         |\n+-------+----------------------+---------+---------+\n第二章  基本初等函数(I)\n1．通过具体实例，了解指数函数模型的实际背景。\n2．理解有理指数幂的含义，通过具体实例了解实数指数幂的意义，掌握幂的运算。\n3.理解指数函数的概念和意义，能借助计算器或计算机画出具体指数函数的图象，探索并理解指数函数的单调性与特殊点。\n4．在解决简单实际问题过程中，体会指数函数是一类重要的函数模型。\n5.理解对数的概念及其运算性质，知道用换底公式能将一般对数转化成自然对数或常用对数；通过阅读材料，了解对数的发现历史以及其对简化运算的作用。\n6.通过具体实例，直观了解对数函数模型所刻画的数量关系，初步理解对数函数的概念，体会对数函数是一类重要的函数模型；能借助计算器或计算机画出具体对数函数的图象，探索并了解对数函数的单调性和特殊点。\n7．通过实例，了解幂函数的概念；结合函数的图象，了解它们的变化情况。\n课时分配（15课时）\n------- -------------------------- --------- -----------------\n2.1.1   引言、指数与指数幂的运算   约3课时   9月27日---30日\n2.1.2   指数函数及其性质           约3课时   10月8日---10日\n2.2.1   对数与对数运算             约3课时   10月11日---14日\n2.2.2   对数函数及其性质           约3课时   10月15日---18日\n2.3     幂函数                     约1课时   10月19日---24日\n小结                       约2课时\n------- -------------------------- --------- -----------------\n第三章  函数的应用\n1.结合二次函数的图象，判断一元二次方程根的存在性及根的个数，从而了解函数的零点与方程根的联系。\n根据具体函数的图象，能够借助计算器用二分法求相应方程的近似解，了解这种方法是求方程近似解的常用方法。\n2.利用计算工具，比较指数函数、对数函数以及幂函数增长差异；结合实例体会直线上升、指数爆炸、对数增长等不同函数类型增长的含义。\n3.收集一些社会生活中普遍使用的函数模型（指数函数、对数函数、幂函数、分段函数等）的实例，了解函数模型的广泛应用。\n4.根据某个主题，收集17世纪前后发生的一些对数学发展起重大作用的历史事件和人物（开普勒、伽利略、笛卡儿、牛顿、莱布尼茨、欧拉等）的有关资料或现实生活中的函数实例，采取小组合作的方式写一篇有关函数概念的形成、发展或应用的文章，在班级中进行交流。\n课时分配（8课时）\n+-------+------------------------+---------+-----------------+\n| 3.1.1 | 方程的根与函数的零点   | 约1课时 | 10月25日        |\n+-------+------------------------+---------+-----------------+\n| 3.1.2 | 用二分法求方程的近似解 | 约2课时 | 10月26日---27日 |\n+-------+------------------------+---------+-----------------+\n| 3.2.1 | 几类不同增长的函数模型 | 约2课时 | 10月30日        |\n|       |                        |         |                 |\n|       |                        |         | /|              |\n|       |                        |         |                 |\n|       |                        |         | 11月3日         |\n+-------+------------------------+---------+-----------------+\n| 3.2.2 | 函数模型的应用实例     | 约2课时 |                 |\n+-------+------------------------+---------", "full_doc_id": "高中数学必修一教学计划_1448630.docx", "file_path": "高中数学必修一教学计划_1448630.docx"}, {"__id__": "chunk-ee86f62ae717a933a77d2ff0717a40ad", "__created_at__": 1754904087, "content": "| 约2课时 | 10月30日        |\n|       |                        |         |                 |\n|       |                        |         | /|              |\n|       |                        |         |                 |\n|       |                        |         | 11月3日         |\n+-------+------------------------+---------+-----------------+\n| 3.2.2 | 函数模型的应用实例     | 约2课时 |                 |\n+-------+------------------------+---------+-----------------+\n|       | 小结                   | 约1课时 |                 |\n+-------+------------------------+---------+-----------------+\n|       |                        |         |                 |\n+-------+------------------------+---------+-----------------+\n继续阅读", "full_doc_id": "高中数学必修一教学计划_1448630.docx", "file_path": "高中数学必修一教学计划_1448630.docx"}, {"__id__": "chunk-395e3fd672628f654b9ce964d4c30e3d", "__created_at__": 1754904278, "content": "高中数学《必修一》讲义\n一．序言\n（一）、为什么要学数学？\n1.提高思维能力，增长聪明才智； 2.学习与实践的基础;\n3.\"高考市场\"的拳头产品\n(二)、数学为什么难学？\n1.高度的抽象性 2.严密的逻辑性 3.应用的广泛性\n(三)、如何学好高中数学？\n1.牢记基础知识; 2.领悟思想方法; 3.把握主干问题; 4.提高运算技能;\n5.注重理性思维; 6.勇于探索创新; 7.加强数学应用; 8.优化心理品质.\n（四）、对数学学习有什么要求？\n1.专注认真; 2.勤思多练; 3.常做笔记;\n4.规范作业; 5.加强交流; 6.反思评价.\n老师寄语：好的开始是成功的一半，新的学期开始了，请大家调整好自己的思想，找到学习的原动力。播种一种思想，收获一种行为；播种一种行为，收获一种习惯；播种一种习惯，收获一种性格；播种一种性格，收获一种命运。愿每位同学都有个好的开始。\n第一讲：集合的含义.表示及集合间的基本关系\n（一）集合的有关概念\n1.  集合理论创始人康托尔称集合为一些确定的、不同的东西的全体，人们\n能意识到这些东西，并且能判断一个给定的东西是否属于这个总体。\n2.  一般地，我们把研究对象统称为元素（element），一些元素组成的总体叫集合（set），也简称集。\n3.  思考1：判断以下元素的全体是否组成集合，并说明理由：\n```{=html}\n<!-- -->\n```\n1.  大于3小于11的偶数；\n2.  我国的小河流；\n3.  非负奇数；\n4.  方程的解；\n5.  某校2007级新生；\n6.  血压很高的人；\n7.  著名的数学家；\n8.  平面直角坐标系内所有第三象限的点\n9.  全班成绩好的学生。\n> 对学生的解答予以讨论、点评，进而讲解下面的问题。\n4.  关于集合的元素的特征\n> （1）确定性：设A是一个给定的集合，x是某一个具体对象，则或者是A的元素，或者不是A的元素，两种情况必有一种且只有一种成立。\n>\n> （2）互异性：一个给定集合中的元素，指属于这个集合的互不相同的个体（对象），因此，同一集合中不应重复出现同一元素。\n>\n> （3）无序性：给定一个集合与集合里面元素的顺序无关。\n>\n> （4）集合相等：构成两个集合的元素完全一样。\n5.  元素与集合的关系；\n> （1）如果a是集合A的元素，就说a属于（belong to）A，记作：a∈A\n>\n> （2）如果a不是集合A的元素，就说a不属于（not belong to）A，记作：aA\n>\n> 例如，我们A表示\"1/~20以内的所有质数\"组成的集合，则有3∈A\n>\n> 4A，等等。\n6．集合与元素的字母表示：\n集合通常用大写的拉丁字母A，B，C...表示，集合的元素用小写的拉丁字母a,b,c,...表示。\n７．常用的数集及记法：\n> 非负整数集（或自然数集），记作N；\n正整数集，记作N^/*^或N~+~；\n整数集，记作Z；\n有理数集，记作Q；\n实数集，记作R；\n例题讲解：\n例1．用\"∈\"或\"\"符号填空：\n（1）8 N； （2）0 N； （3）-3 Z； （4） Q；\n（5）设A为所有亚洲国家组成的集合，则中国 A，美国 A，印度 A，英国 A。\n例2．已知集合P的元素为, 若3∈P且-1P，求实数m的值。\n（二）．集合的表示方法\n我们可以用自然语言和图形语言来描述一个集合，但这将给我们带来很多不便，除此之外还常用列举法和描述法来表示集合。\n> /(1/)\n> 列举法：把集合中的元素一一列举出来，并用花括号\"\"括起来表示集合的方法叫列举法。\n>\n> 如：{1，2，3，4，5}，{x^2^，3x+2，5y^3^-x，x^2^+y^2^}，...；\n>\n> 说明：1．集合中的元素具有无序性，所以用列举法表示集合时不必考\n>\n> 虑元素的顺序。\n>\n> 　　　2．各个元素之间要用逗号隔开；\n>\n> 　　　3．元素不能重复；\n>\n> 4．集合中的元素可以数，点，代数", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-ab80643c40690d15db380223b3bd4910", "__created_at__": 1754904278, "content": "2，5y^3^-x，x^2^+y^2^}，...；\n>\n> 说明：1．集合中的元素具有无序性，所以用列举法表示集合时不必考\n>\n> 虑元素的顺序。\n>\n> 　　　2．各个元素之间要用逗号隔开；\n>\n> 　　　3．元素不能重复；\n>\n> 4．集合中的元素可以数，点，代数式等；\n>\n> 　　　5．对于含有较多元素的集合，用列举法表示时，必须把元素间的规律显示清楚后方能用省略号，象自然数集Ｎ用列举法表示为\n>\n> 例1．用列举法表示下列集合：\n>\n> （1）小于10的所有自然数组成的集合；\n>\n> （2）方程x^2^=x的所有实数根组成的集合；\n>\n> （3）由1到20以内的所有质数组成的集合；\n>\n> （4）方程组的解组成的集合。\n>\n> （2）描述法：把集合中的元素的公共属性描述出来，写在花括号{　}内。\n>\n> 具体方法：在花括号内先写上表示这个集合元素的一般符号及取值（或变化）范围，再画一条竖线，在竖线后写出这个集合中元素所具有的共同特征。\n>\n> 一般格式：\n>\n> 如：{x/|x-3/>2}，{(x,y)/|y=x^2^+1}，{x︳直角三角形}，...；\n>\n> 说明：\n>\n> 描述法表示集合应注意集合的代表元素，[如]{.ul}{(x,y)/|y=\n> x^2^+3x+2}与 {y/|y=\n> x^2^+3x+2}是不同的两个集合，只要不引起误解，集合的代表元素也可省略，例如：{x︳整数}，即代表整数集Z。\n辨析：这里的{\n}已包含\"所有\"的意思，所以不必写{全体整数}。下列写法{实数集}，{R}也是错误的。\n> 例2．试分别用列举法和描述法表示下列集合：\n（1）方程x^2^---2=0的所有实数根组成的集合；\n（2）由大于10小于20的所有整数组成的集合；\n（3）方程组的解。\n说明：列举法与描述法各有优点，应该根据具体问题确定采用哪种表示法，要注意，一般集合中元素较多或有无限个元素时，不宜采用列举法。\n课堂练习：\n1．用适当的方法表示集合：大于0的所有奇数\n2．集合A＝{x/|∈Z，x∈N}，则它的元素是 。\n> 3．已知集合A＝{x/|-3/<x/<3，x∈Z}，B＝{(x,y)/|y＝x+1，x∈A}，则集合B用列举法表示是\n（三）. 子集、空集等概念\n比较下面几个例子，试发现两个集合之间的关系：\n（1），；\n（2）C={/|是第一中学2010年9月入学的高一年级同学}，D={/|是第一中学2010年9月入学的高一年级女同学}.\n（3），\n1.  子集的定义：\n> 对于两个集合A，B，如果集合*A*的任何一个元素都是集合*B*的元素，我们说这两个集合有包含关系，称集合A是集合B的子集（subset）。\n> 记作：\n>\n> 读作：A包含于（is contained in）B，或B包含（contains）A\n当集合A不包含于集合B时，记作\n用Venn图表示两个集合间的\"包含\"关系：\n如：（1）中\n2.  集合相等定义：\n> 如果A是集合B的子集，且集合B是集合A的子集，则集合A与集合B中的元素是一样的，因此集合A与集合B相等，即若，则。\n如（3）中的两集合。\n3.  真子集定义：\n> 若集合，但存在元素，则称集合*A*是集合*B*的真子集（proper\n> subset）。记作：\n>\n> A\n> ![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image25.png)\n> height=\"0.11041666666666666in\"}\n> B（或B![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image26.png)\n> height=\"0.11458333333333333in\"} A）\n>\n> 读作：A真包含于B（或B真包含A）\n如：（1）和（2）中A\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image25.png)\nheight=\"0.11041666666666666in\"} B，C\n![](/static/Images/28bdca7490", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-3ef3ac5b0fd20dd5b71a493210c4abbd", "__created_at__": 1754904278, "content": "=\"0.11458333333333333in\"} A）\n>\n> 读作：A真包含于B（或B真包含A）\n如：（1）和（2）中A\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image25.png)\nheight=\"0.11041666666666666in\"} B，C\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image25.png)\nheight=\"0.11041666666666666in\"} D；\n4.  空集定义：\n不含有任何元素的集合称为空集（empty set），记作：。\n用适当的符号填空：\n； 0 ； ；\n5.  几个重要的结论：\n```{=html}\n<!-- -->\n```\n1.  空集是任何集合的子集；\n2.  空集是任何非空集合的真子集；\n3.  任何一个集合是它本身的子集；\n4.  对于集合A，B，C，如果，且，那么。\n说明：\n1.  注意集合与元素是\"属于\"\"不属于\"的关系，集合与集合是\"包含于\"\"不包含于\"的关系；\n2.  在分析有关集合问题时，要注意空集的地位。\n例题讲解：\n例1．填空：\n（1）． 2 N； N； A;\n（2）．已知集合A＝{x/|x－3x＋2＝0}，B＝{1,2}，C＝{x/|x/<8,x∈N}，则\nA B； A C； {2} C； 2 C\n例2．写出集合的所有子集，并指出哪些是它的真子集。\n例3．若集合 B\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image25.png)\nheight=\"0.11041666666666666in\"} A，求m的值。\n（m=0或）\n例4．已知集合且，\n> 求实数m的取值范围。 （）\n第二讲：集合的基本运算\n（一）. 交集、并集概念及性质\n思考1．考察下列集合，说出集合C与集合A，B之间的关系：\n（1），；\n（2），；\n1.并集的定义：\n一般地，由所有属于集合A或属于集合B的元素所组成的集合，叫做集合A与集合B的并集（union\nset）。记作：A∪B（读作：\"A并B\"），即\n用Venn图表示：\n![未命名](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image43.png){width=\"1.6666666666666667in\"\n这样，在问题（1）（2）中，集合A，B的并集是C，即\n= C\n说明：定义中要注意\"所有\"和\"或\"这两个条件。\n讨论：A∪B与集合A、B有什么特殊的关系？\nA∪A＝ , A∪Ф＝ , A∪B B∪A\nA∪B＝A , A∪B＝B [.]{.ul}\n巩固练习（口答）：\n①．A＝{3,5,6,8}，B＝{4,5,7,8}，则A∪B＝ ;\n②．设A＝{锐角三角形}，B＝{钝角三角形}，则A∪B＝ ;\n③．A＝{x/|x/>3}，B＝{x/|x/<6}，则A∪B＝ 。\n2.交集的定义：\n一般地，由属于集合A且属于集合B的所有元素组成的集合，叫作集合A、B的交集（intersection\nset），记作A∩B（读\"A交B\"）即：\nA∩B＝{x/|x∈A，且x∈B}\n用Venn图表示：（阴影部分即为A与B的交集）\n![未命名](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image46.png){width=\"1.6666666666666667in\"\n常见的五种交集的情况：\n讨论：A∩B与A、B、B∩A的关系？\nA∩A＝ A∩Ф＝ A∩B B∩A\nA∩B＝A A∩B＝B\n巩固练习（口答）：\n①．A＝{3,5,6,8}，B＝{4,5,7,8}，则A∩B＝ ;\n②．A＝{等腰三角形}，B＝{直角三角形}，则A∩B＝ ;\n③．A＝{x/|x/>3}，B＝{x/|x/<6}，则A∩B＝ 。\n例题讲解：\n例1．设集合，求A∪B．\n变式：A＝{x/|-5≤x≤8}\n例2．设平面内直线上点的集合为L~", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-9b0a3ca94c727c8c8a16dbd1721013f9", "__created_at__": 1754904278, "content": "形}，B＝{直角三角形}，则A∩B＝ ;\n③．A＝{x/|x/>3}，B＝{x/|x/<6}，则A∩B＝ 。\n例题讲解：\n例1．设集合，求A∪B．\n变式：A＝{x/|-5≤x≤8}\n例2．设平面内直线上点的集合为L~1~，直线上点的集合为L~2~，试用集合的运算表示，的位置关系。\n例3．已知集合\n是否存在实数m，同时满足\n（m=-2）\n（二）. 全集、补集概念及性质\n1.全集的定义：\n一般地，如果一个集合含有我们所研究问题中涉及的所有元素，那么就称这个集合为全集（universe\nset）,记作U，是相对于所研究问题而言的一个相对概念。\n2.补集的定义：\n对于一个集合A，由全集U中不属于集合A的所有元素组成的集合，叫作集合A相对于全集U的补集（complementary\nset），记作：，\n读作：\"A在U中的补集\"，即\n用Venn图表示：（阴影部分即为A在全集U中的补集）\n![未命名](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image55.png){width=\"1.9270833333333333in\"\n讨论：集合A与之间有什么关系？→借助Venn图分析\n巩固练习（口答）：\n①．U={2,3,4}，A={4,3}，B=φ，则= ，= ；\n②．设U＝{x/|x/<8，且x∈N}，A＝{x/|(x-2)(x-4)(x-5)＝0}，则＝ ；\n③．设U＝{三角形}，A＝{锐角三角形}，则＝ 。\n例题讲解：\n例1．设集，求，．\n例2．设全集，求，\n，。\n（结论：）\n例3．设全集U为R，，若\n，求。\n集合复习\n（一） 集合的基本运算：\n例1：设U=R，A={x/|-5/<x/<5},B={x/|0≤x/<7},求A∩B、A∪B、CA 、CB、\n(CA)∩(CB)、(CA)∪(CB)、C(A∪B)、C(A∩B)。\n说明：不等式的交、并、补集的运算，用数轴进行分析，注意端点。\n例2：全集U={x/|x/<10，x∈N}，AU，BU，且（CB）∩A={1,9}，A∩B={3}，（CA)∩(CB)={4,6,7}，求A、B。\n说明：列举法表示的数集问题用Venn图示法、观察法。\n（二）集合性质的运用：\n例3：A={x/|x+4x=0}，B={x/|x+2(a+1)x＋a－1=0}, 若A∪B=A，求实数a的值。\n说明：注意B为空集可能性；一元二次方程已知根时，用代入法、韦达定理，要注意判别式。\n例4：已知集合A={x/|x/>6或x/<-3}，B={x/|a/<x/<a+3}，若A∪B=A，求实数a的取值范围。\n（三）巩固练习：\n1．已知A={x/|-2/<x/<-1或x/>1}，A∪B={x/|x＋2/>0}，A∩B={x/|1/<x≦3}，求集合B。\n2．P={0,1}，M={x/|xP}，则P与M的关系是 。\n3．已知50名同学参加跳远和铅球两项测验，分别及格人数为40、31人，两项均不及格的为4人，那么两项都及格的为\n人。\n4．满足关系{1,2}A{1,2,3,4,5}的集合A共有 个。\n5．已知集合A∪B＝{x/|x/<8,x∈N}，A＝{1,3,5,6}，A∩B={1,5,6}，则B的子集的集合一共有多少个元素\n6．已知A＝{1,2,a}，B＝{1,a}，A∪B＝{1,2,a}，求所有可能的a值。\n7．设A＝{x/|x－ax＋6＝0}，B＝{x/|x－x＋c＝0}，A∩B＝{2}，求A∪B。\n8．集合A={x/|x2+px-2=0},B={x/|x2-x+q=0},若AB={-2，0，1}，求p、", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-b376e21483a05385d7c126202594c263", "__created_at__": 1754904278, "content": "，求所有可能的a值。\n7．设A＝{x/|x－ax＋6＝0}，B＝{x/|x－x＋c＝0}，A∩B＝{2}，求A∪B。\n8．集合A={x/|x2+px-2=0},B={x/|x2-x+q=0},若AB={-2，0，1}，求p、q。\n9． A={2，3，a2+4a+2}，B={0，7，a2+4a-2，2-a}，且AB ={3，7}，求B。\n10．已知A={x/|x/<-2或x/>3}，B={x/|4x+m/<0}，当AB时，求实数m的取值范围。\n第三讲：函数的概念\n（一）函数的概念：\n思考1：给出三个实例：\nA．一枚炮弹发射，经26秒后落地击中目标，射高为845米，且炮弹距地面高度*h*（米）与时间*t*（秒）的变化规律是。\nB．近几十年，大气层中臭氧迅速减少，因而出现臭氧层空洞问题，图中曲线是南极上空臭氧层空洞面积的变化情况。\nC．国际上常用恩格尔系数（食物支出金额÷总支出金额）反映一个国家人民生活质量的高低。\"八五\"计划以来我们城镇居民的恩格尔系数如下表。\n> 讨论：以上三个实例存在哪些变量变量的变化范围分别是什么两个变量之间存在着怎样的对应关系\n> 三个实例有什么共同点\n>\n> 归纳：三个实例变量之间的关系都可以描述为：对于数集*A*中的每一个*x*，按照某种对应关系*f*，在数集*B*中都与唯一确定的*y*和它对应，记作：\n函数的定义：\n设*A、B*是两个非空的数集，如果按照某种确定的对应关系*f*，使对于集合*A*中的任意一个数*x*，在集合*B*中都有唯一确定的数和它对应，那么称为从集合*A*到集合*B*的一个函数（function），记作：\n其中，x叫自变量，x的取值范围A叫作定义域（domain），与x的值对应的y值叫函数值，函数值的集合叫值域（range）。显然，值域是集合B的子集。\n> （1）一次函数y=ax+b (a≠0)的定义域是R，值域也是R；\n（2）二次函数\n(a≠0)的定义域是R，值域是B；当a/>0时，值域；当a﹤0时，值域。\n（3）反比例函数的定义域是，值域是。\n（二）区间及写法：\n设a、b是两个实数，且a/<b，则：\n1.  满足不等式的实数x的集合叫做闭区间，表示为/[a,b/]；\n2.  满足不等式的实数x的集合叫做开区间，表示为（a,b）；\n3.  满足不等式的实数x的集合叫做半开半闭区间，表示为；\n> 这里的实数a和b都叫做相应区间的端点。（数轴表示见课本P~17~表格）\n符号\"∞\"读\"无穷大\"；\"－∞\"读\"负无穷大\"；\"+∞\"读\"正无穷大\"。我们把满足的实数x的集合分别表示为\n。\n巩固练习：用区间表示R、{x/|x≥1}、{x/|x/>5}、{x/|x≤-1}、{x/|x/<0}\n例题讲解：\n例1．已知函数，求f(0)、f(1)、f(2)、f(－1)的值。\n变式：求函数的值域\n例2．已知函数，\n1.  求的值；\n2.  当a/>0时，求的值。\n课堂练习：\n1． 用区间表示下列集合：\n2． 已知函数f(x)=3x＋5x－2,求f(3)、f(-)、f(a)、f(a+1)的值；\n（二）函数定义域的求法：\n函数的定义域通常由问题的实际背景确定，如果只给出解析式y=f(x)，而没有指明它的定义域，那么函数的定义域就是指能使这个式子有意义的实数的集合。\n例1：求下列函数的定义域（用区间表示）\n⑴ f(x)=； ⑵ f(x)=； ⑶ f(x)=－；\n/*复合函数的定义域求法：\n（1）已知f(x)的定义域为（a,b），求f(g(x))的定义域；\n求法：由a/<x/<b，知a/<g(x)/<b，解得的x的取值范围即是f(g(x))的定义域。\n（2）已知f(g(x))的定义域为（a", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-9588c2c01b7546ba0936d1e2aa735eb3", "__created_at__": 1754904278, "content": "f(x)=； ⑶ f(x)=－；\n/*复合函数的定义域求法：\n（1）已知f(x)的定义域为（a,b），求f(g(x))的定义域；\n求法：由a/<x/<b，知a/<g(x)/<b，解得的x的取值范围即是f(g(x))的定义域。\n（2）已知f(g(x))的定义域为（a,b），求f(x)的定义域；\n求法：由a/<x/<b，得g(x)的取值范围即是f(x)的定义域。\n例2．已知f(x)的定义域为/[0,1/]，求f(x＋1)的定义域。\n例3．已知f(x-1)的定义域为/[-1,0/]，求f(x+1)的定义域。\n巩固练习：\n1．求下列函数定义域：\n（1）； （2）\n2．（1）已知函数f(x)的定义域为/[0，1/]，求的定义域；\n（2）已知函数f(2x-1)的定义域为/[0，1/]，求f(1-3x)的定义域。\n（三）函数相同的判别方法：\n函数是否相同，看定义域和对应法则。\n例5．下列函数中哪个与函数y=x相等？\n（1）； （2）； （3）； （4） 。\n（三）课堂练习： 1．求函数y＝－x＋4x－1 ，x∈/[-1,3) 的值域。\n第四讲：函数的表示法（一）\n（一）函数的三种表示方法：\n解析法：就是用数学表达式表示两个变量之间的对应关系，如的实例（1）；\n优点：简明扼要；给自变量求函数值。\n图象法：就是用图象表示两个变量之间的对应关系，如的实例（2）；\n优点：直观形象，反映两个变量的变化趋势。\n列表法：就是列出表格来表示两个变量之间的对应关系，如的实例（3）；\n优点：不需计算就可看出函数值，如股市走势图； 列车时刻表；银行利率表等。\n例1．某种笔记本的单价是2元，买*x*\n(*x*∈{1，2，3，4，5})个笔记本需要*y*元．试用三种表示法表示函数y=f(x) ．\n> 例2：下表是某校高一（1）班三位同学在高一学年度六次数学测试的成绩及班级平均分表：\n---------- -------- -------- -------- -------- -------- --------\n第一次   第二次   第三次   第四次   第五次   第六次\n甲         98       87       91       92       88       95\n乙         90       76       88       75       86       80\n丙         68       65       73       72       75       82\n班平均分   88．2    78．3    85．4    80．3    75．7    82．6\n---------- -------- -------- -------- -------- -------- --------\n请你对这三们同学在高一学年度的数学学习情况做一个分析．\n（二）分段函数的教学：\n分段函数的定义：\n在函数的定义域内，对于自变量x的不同取值范围，有着不同的对应法则，这样的函数通常叫做分段函数，如以下的例3的函数就是分段函数。\n说明：\n> （1）．分段函数是一个函数而不是几个函数，处理分段函数问题时，首先要确定自变量的数值属于哪个区间段，从而选取相应的对应法则；画分段函数图象时，应根据不同定义域上的不同解析式分别作出；\n（2）．分段函数只是一个函数，只不过x的取值范围不同时，对应法则不相同。\n例3：某市\"招手即停\"公共汽车的票价按下列规则制定：\n（1）5公里以内（含5公里），票价2元；\n（2）5公里以上，每增加5公里，票价增加1元（不足5公里的俺公里计算）。\n> 如果某条线路的总里程为20公里，请根据题意，写出票价与里程之间的函数解析式，并画出函数的图象。\n例4．已知f(x)＝，求f(0)、f/[f(-1)/]的值\n（三）课堂练习：\n1．作业本每本元，买x个作业本的钱数y（元）。试用三种方法表示此实例中的函数。\n> 2．某水果批发店，100kg内单价1元／kg，500kg内、100kg及以上元／kg，500kg及以上元／kg。试用三种方法表示批发x千克与应付的钱数y（元）之间的函数y=f(x)。\n（三） 映射的概念教学：\n定义：\n一般地，设*A*、*B*是两个非空的集合，如果按某一个确定的对应法则*f*，使对于集合*A*中的任意一个元素*x*，在集合*", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-22c241a4b32894d33d1260d2401aaeea", "__created_at__": 1754904278, "content": "100kg及以上元／kg，500kg及以上元／kg。试用三种方法表示批发x千克与应付的钱数y（元）之间的函数y=f(x)。\n（三） 映射的概念教学：\n定义：\n一般地，设*A*、*B*是两个非空的集合，如果按某一个确定的对应法则*f*，使对于集合*A*中的任意一个元素*x*，在集合*B*中都有唯一确定的元素*y*与之对应，那么就称对应为从集合*A*到集合*B*的一个映射（mapping）。记作：\n讨论：映射有哪些对应情况一对多是映射吗\n例1．以下给出的对应是不是从A到集合B的映射？\n1.  集合*A*={*P* /|\nP是数轴上的点}，集合*B*=*R*，对应关系f：数轴上的点与它所代表的实数对应；\n2.  集合*A*={*P* /| P是平面直角坐标系中的点}，*B*= ，对应关系f：\n平面直角坐标系中的点与它的坐标对应；\n3.  集合*A*={*x* /| x是三角形}，集合*B*={*x* /|\nx是圆}，对应关系f：每一个三角形都对应它的内切圆；\n4.  集合*A*={*x* /| x是新华中学的班级}，集合*B*={*x* /|\nx是新华中学的学生}，对应关系：每一个班级都对应班里的学生。\n例2．设集合A={a,b,c}，B={0,1}\n，试问：从A到B的映射一共有几个？并将它们分别表示出来。\n（四）求函数的解析式：\n常见的求函数解析式的方法有待定系数法，换元法，配凑法，消去法。\n例3．已知f(x)是一次函数，且满足3f(x+1)-2f(x-1)=2x+17，求函数f(x)的解析式。\n（待定系数法）\n例4．已知f(2x+1)=3x-2，求函数f(x)的解析式。（配凑法或换元法）\n例5．已知函数f(x)满足，求函数f(x)的解析式。（消去法）\n（三）课堂练习：\n1．已知 ，求函数f(x)的解析式。\n2．已知，求函数f(x)的解析式。\n3．已知，求函数f(x)的解析式。\n第五讲：函数的表示法（二）及函数的复习\n（一）函数的图像\n例1．画出下列各函数的图象：\n（1）\n（2）；\n例2．画出函数的图象。\n例3．设，求函数的解析式，并画出它的图象。\n变式1：求函数的最大值。\n变式2：解不等式。\n例4．当m为何值时，方程有4个互不相等的实数根。\n变式：不等式对恒成立，求m的取值范围。\n课堂练习： 2．画出函数的图象。\n（二）复习总结\n基础习题练习：\n1．说出下列函数的定义域与值域： ； ； ；\n2．已知，求， ， ；\n3．已知，\n（１）作出的图象；\n（２）求的值\n例题：\n例１．已知函数=4x+3，g(x)=x,　求f/[f(x)/]，f/[g(x)/]，g/[f(x)/]，g/[g(x)/]．\n例2．求下列函数的定义域：\n（１）；　　　　　　　　（２）；\n例３．若函数的定义域为Ｒ，求实数a的取值范围．\n例４．\n长沙移动公司开展了两种通讯业务：\"全球通\"，月租50元，每通话1分钟，付费元；\"神州行\"不缴月租，每通话1分钟，付费元.\n若一个月内通话x分钟，两种通讯方式的费用分别为（元）．\n（１）．写出与x之间的函数关系式\n（２）．一个月内通话多少分钟，两种通讯方式的费用相同\n（３）．若某人预计一个月内使用话费200元，应选择哪种通讯方式？\n巩固练习：\n1．已知=xx+3 ，求：f(x+1)， f()的值；\n2．若,求函数的解析式；\n3．设二次函数满足且=0的两实根平方和为10，图象过点(0,3)，求的解析式．\n４．已知函数的定义域为Ｒ，求实数a的取值范围．\n第六讲：单调性与最大（小）值 （一）\n一、复习准备：\n1.引言：函数是描述事物运动变化规律的数学模型，那么能否发现变化中保持不变的特征呢？\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-7d5bbda8b2ef0c9cd07ac163fa248864", "__created_at__": 1754904278, "content": "４．已知函数的定义域为Ｒ，求实数a的取值范围．\n第六讲：单调性与最大（小）值 （一）\n一、复习准备：\n1.引言：函数是描述事物运动变化规律的数学模型，那么能否发现变化中保持不变的特征呢？\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image153.png)\n观察下列各个函数的图象，并探讨下列变化规律：\n①随*x*的增大，*y*的值有什么变化？\n②能否看出函数的最大、最小值？\n③函数图象是否具有某种对称性？\n3/. 画出函数f(x)= x＋2、f(x)=\nx的图像。（小结描点法的步骤：列表→描点→连线）\n二、讲授新课：\n1.教学增函数、减函数、单调性、单调区间等概念：\n①根据f(x)＝3x＋2、 f(x)＝x (x/>0)的图象进行讨论：\n随x的增大，函数值怎样变化 当x/>x时，f(x)与f(x)的大小关系怎样？\n②.一次函数、二次函数和反比例函数，在什么区间函数有怎样的增大或减小的性质？\n③定义增函数：设函数y=f(x)的定义域为I，如果对于定义域I内的某个区间D内的任意两个自变量x~1~，x~2~，当x~1~/<x~2~时，都有f(x~1~)/<f(x~2~)，那么就说f(x)在区间D上是增函数（increasing\nfunction）\n④探讨：仿照增函数的定义说出减函数的定义；→ 区间局部性、取值任意性\n⑤定义：如果函数f(x)在某个区间D上是增函数或减函数，就说f(x)在这一区间上具有（严格的）单调性，区间D叫f(x)的单调区间。\n⑥讨论：图像如何表示单调增、单调减？\n所有函数是不是都具有单调性单调性与单调区间有什么关系\n⑦一次函数、二次函数、反比例函数的单调性\n2.教学增函数、减函数的证明：\n例1．将进货单价40元的商品按50元一个售出时，能卖出500个，若此商品每个涨价1元，其销售量减少10个，为了赚到最大利润，售价应定为多少？\n1.  例题讲解\n例1\n如图是定义在区间/[－5，5/]上的函数y=f(x)，根据图象说出函数的单调区间，以及在每一单调区间上，它是增函数还是减函数？\n![1](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image157.jpeg){width=\"3.220138888888889in\"\n例2：物理学中的玻意耳定律（*k*为正常数），告诉我们对于一定量的气体，当其体积*V*增大时，压强*p*如何变化？试用单调性定义证明.\n例3．判断函数在区间/[2，6/] 上的单调性\n三、巩固练习：\n1.求证f(x)＝x＋的(0,1)上是减函数，在/[1,+∞/]上是增函数。\n2.判断f(x)=/|x/|、y=x的单调性并证明。\n3.讨论f(x)=x－2x的单调性。 推广：二次函数的单调性\n四、小结：\n比较函数值的大小问题，运用比较法而变成判别代数式的符号。\n判断单调性的步骤：设x、x∈给定区间，且x/<x；\n→计算f(x)－f(x)至最简→判断差的符号→下结论。\n第七讲： 单调性与最大（小）值 （二）\n一、复习准备：\n1.指出函数f(x)＝ax＋bx＋c (a/>0)的单调区间及单调性，并进行证明。\n2/. f(x)＝ax＋bx＋c的最小值的情况是怎样的？\n3.知识回顾：增函数、减函数的定义。\n二、讲授新课：\n1.教学函数最大（小）值的概念：\n① 指出下列函数图象的最高点或最低点，→ 能体现函数值有什么特征？\n， ；，\n②\n定义最大值：设函数y=f(x)的定义域为*I*，如果存在实数*M*满足：对于任意的x∈*I*，都有f(x)≤M；存在x~0~∈*I*，使得f(x~0~)\n= *M*. 那么，称*M*是函数y=f(x)的最大值（Maximum Value）\n③ 探讨：仿照最大值定义，给出最小值（Minimum Value）的定义．\n→ 一些什么方法可以求最大（小）值（配方法、图象法", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-90c0c24860ddc364413229e75b692ea2", "__created_at__": 1754904278, "content": "意的x∈*I*，都有f(x)≤M；存在x~0~∈*I*，使得f(x~0~)\n= *M*. 那么，称*M*是函数y=f(x)的最大值（Maximum Value）\n③ 探讨：仿照最大值定义，给出最小值（Minimum Value）的定义．\n→ 一些什么方法可以求最大（小）值（配方法、图象法、单调法） →\n试举例说明方法.\n2.  例题讲解：\n例1．求函数在区间/[2，6/] 上的最大值和最小值．\n例2．求函数的最大值\n探究：的图象与的关系？\n（解法一：单调法； 解法二：换元法）\n三、巩固练习：\n1/. 求下列函数的最大值和最小值：\n（1）；\n（2）\n2.一个星级旅馆有150个标准房，经过一段时间的经营，经理得到一些定价和住房率的数据如右：欲使每天的的营业额最高，应如何定价（分析变化规律→建立函数模型→求解最大值）\n------------ -------------\n房价（元）   住房率（%）\n160          55\n140          65\n120          75\n100          85\n------------ -------------\n3.  求函数的最小值.\n四、小结：\n求函数最值的常用方法有：\n（1）配方法：即将函数解析式化成含有自变量的平方式与常数的和，然后根据变量的取值范围确定函数的最值．\n（2）换元法：通过变量式代换转化为求二次函数在某区间上的最值．\n（3）数形结合法：利用函数图象或几何方法求出最值．\n第八讲：函数的奇偶性\n一、复习准备：\n1.提问：什么叫增函数、减函数？\n2.指出f(x)＝2x－1的单调区间及单调性。 →变题：/|2x－1/|的单调区间\n3.对于f(x)＝x、f(x)＝x、f(x)＝x、f(x)＝x，分别比较f(x)与f(－x)。\n二、讲授新课：\n1.教学奇函数、偶函数的概念：\n①给出两组图象：、、；、.\n发现各组图象的共同特征 → 探究函数解析式在函数值方面的特征\n②\n定义偶函数：一般地，对于函数定义域内的任意一个*x*，都有，那么函数叫偶函数（even\nfunction）.\n③ 探究：仿照偶函数的定义给出奇函数（odd function）的定义.\n（如果对于函数定义域内的任意一个*x*，都有），那么函数叫奇函数。\n④\n讨论：定义域特点与单调性定义的区别图象特点（定义域关于原点对称；整体性）\n⑤ 练习：已知f(x)是偶函数，它在y轴左边的图像如图所示，画出它右边的图像。\n（假如f(x)是奇函数呢）\n1.  教学奇偶性判别：\n例1．判断下列函数是否是偶函数．\n（1）\n（2）\n例2．判断下列函数的奇偶性\n（1） （2） （3） （4）．\n（5） （6）\n4、教学奇偶性与单调性综合的问题：\n①出示例：已知f(x)是奇函数，且在(0,+∞)上是减函数，问f(x)的(-∞,0)上的单调性。\n②找一例子说明判别结果（特例法） →\n按定义求单调性，注意利用奇偶性和已知单调区间上的单调性。\n（小结：设→转化→单调应用→奇偶应用→结论）\n③变题：已知f(x)是偶函数，且在/[a,b/]上是减函数，试判断f(x)在/[-b,-a/]上的单调性，并给出证明。\n三、巩固练习：\n1、判别下列函数的奇偶性：\nf(x)＝/|x＋1/|+/|x－1/| 、f(x)＝、f(x)＝x＋、 f(x)＝、f(x)＝x,x∈/[-2,3/]\n2.设f(x)＝ax＋bx＋5，已知f(－7)＝－17,求f(7)的值。\n3.已知f(x)是奇函数，g(x)是偶函数，且f(x)－g(x)＝，求f(x)、g(x)。\n4.已知函数f(x)，对任意实数x、y，都有f(x+y)＝f(x)＋f(y)，试判别f(x)的奇偶性。(特值代入)\n5.已知f(x)是奇函数，且在/[3,7/]是增函数且最大值为4，那么f(x)在/[-7,-3/]上是（\n）函数，且最 值是 。\n四、小结\n本节主要学习了函数的奇", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-1e310fe13059e9f765812f5cf61e92de", "__created_at__": 1754904278, "content": "任意实数x、y，都有f(x+y)＝f(x)＋f(y)，试判别f(x)的奇偶性。(特值代入)\n5.已知f(x)是奇函数，且在/[3,7/]是增函数且最大值为4，那么f(x)在/[-7,-3/]上是（\n）函数，且最 值是 。\n四、小结\n本节主要学习了函数的奇偶性，判断函数的奇偶性通常有两种方法，即定义法和图象法，用定义法判断函数的奇偶性时，必须注意首先判断函数的定义域是否关于原点对称，单调性与奇偶性的综合应用是本节的一个难点，需要学生结合函数的图象充分理解好单调性和奇偶性这两个性质．\n第九讲：函数的基本性质运用\n一、复习准备：\n1.讨论：如何从图象特征上得到奇函数、偶函数、增函数、减函数、最大值、最小值？\n2.提问：如何从解析式得到奇函数、偶函数、增函数、减函数、最大值、最小值的定义？\n二、教学典型习例:\n1.函数性质综合题型：\n①例1：作出函数y＝x－2/|x/|－3的图像，指出单调区间和单调性。\n分析作法：利用偶函数性质，先作y轴右边的，再对称作。\n思考：y＝/|x－2x－3/|的图像的图像如何作？\n②讨论推广：如何由的图象，得到、的图象？\n③出示例2：已知f(x)是奇函数，在(0，＋∞)上是增函数，证明：f(x)在(－∞，0)上也是增函数\n分析证法 → 教师板演 → 变式训练\n④讨论推广：奇函数或偶函数的单调区间及单调性有何关系？\n（偶函数在关于原点对称的区间上单调性相反；奇函数在关于原点对称的区间上单调性一致）\n2. 教学函数性质的应用：\n①出示例 ：求函数f(x)＝x＋ (x/>0)的值域。\n分析：单调性怎样值域呢→小结：应用单调性求值域。 →\n探究：计算机作图与结论推广\n②出示例：某产品单价是120元，可销售80万件。市场调查后发现规律为降价x元后可多销售2x万件，写出销售金额y(万元)与x的函数关系式，并求当降价多少个元时，销售金额最大最大是多少\n分析：此题的数量关系是怎样的函数呢如何求函数的最大值\n小结：利用函数的单调性（主要是二次函数）解决有关最大值和最大值问题。\n2.基本练习题：\n1、判别下列函数的奇偶性：y＝＋、 y＝\n（变式训练：f(x)偶函数，当x/>0时，f(x)=....，则x/<0时，f(x)= ）\n2、求函数y＝x＋的值域。\n3、判断函数y=单调区间并证明。\n（定义法、图象法； 推广： 的单调性）\n4、讨论y=在/[-1,1/]上的单调性。\n三、巩固练习：\n1.求函数y=为奇函数的时，a、b、c所满足的条件。\n2.已知函数f(x)=ax+bx+3a+b为偶函数，其定义域为/[a-1,2a/]，求函数值域。\n3/. f(x)是定义在(-1,1)上的减函数，如何f(2－a)－f(a－3)/<0。求a的范围。\n4/. 求二次函数f(x)=x－2ax＋2在/[2,4/]上的最大值与最小值。\n第十讲：指数与指数幂的运算\n一.指数函数模型应用背景：\n> 实例1.某市人口平均年增长率为℅，1990年人口数为*a*万，则*x*年后人口数为多少万？\n>\n> 实例2. 给一张报纸，先实验最多可折多少次（8次）\n计算：若报纸长50cm，宽34cm，厚，进行对折*x*次后，问对折后的面积与厚度？\n②问题1.\n国务院发展研究中心在2000年分析，我国未来20年*GDP*（国内生产总值）年平均增长率达℅，\n则*x*年后*GDP*为2000年的多少倍\n问题2.\n生物死亡后，体内碳14每过5730年衰减一半（半衰期），则死亡*t*年后体内碳14的含量*P*与死亡时碳14的关系为.\n探究该式意义？\n③小结：实践中存在着许多指数函数的应用模型，如人口问题、银行存款、生物变化、自然科学.\n二.根式的概念及运算：\n① 复习实例蕴含的概念：,就叫4的平方根；，3", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-49af296beb6db03c8a82602e11d04655", "__created_at__": 1754904278, "content": "半衰期），则死亡*t*年后体内碳14的含量*P*与死亡时碳14的关系为.\n探究该式意义？\n③小结：实践中存在着许多指数函数的应用模型，如人口问题、银行存款、生物变化、自然科学.\n二.根式的概念及运算：\n① 复习实例蕴含的概念：,就叫4的平方根；，3就叫27的立方根.\n探究：,就叫做的？次方根, 依此类推,若,那么叫做的次方根.\n② 定义n次方根：一般地，若,那么叫做的次方根.( th root ),其中,\n简记：. 例如：，则\n③ 讨论：当n为奇数时, n次方根情况如何, 例如: ,,\n记：\n> 当n为偶数时，正数的n次方根情况 例如: ,的4次方根就是, 记：\n强调：负数没有偶次方根,0的任何次方根都是0, 即.\n④ 练习：,则的4次方根为 ； , 则的3次方根为 [.]{.ul}\n⑤ 定义根式：像的式子就叫做根式（radical）, 这里*n*叫做根指数（radical\nexponent）, *a*叫做被开方数（radicand）.\n⑥ 计算、、 → 探究： 、的意义及结果 （特殊到一般）\n结论：. 当是奇数时，；当是偶数时，\n例题讲解\n求下列各式的值\n巩固练习：\n1/. 计算或化简：； （推广：， *a*0）.\n2、 化简： ；\n3、求值化简： ； ； ； （）\n三.分数指数幂概念及运算性质:\n① 引例：*a*/>0时， → ； → .\n1.  定义分数指数幂：\n规定；\n③ 练习：A.将下列根式写成分数指数幂形式：；；\nB. 求值 ； ； ； .\n④ 讨论：0的正分数指数幂 0的负分数指数幂⑤\n指出：规定了分数指数幂的意义后，指数的概念就从整数指数推广到了有理数指数，那么整数指数幂的运算性质也同样可以推广到有理数指数幂．\n指数幂的运算性质：\n·； ； ．\n四、无理指数幂\n的结果？→定义：无理指数幂.\n无理数指数幂是一个确定的实数．\n巩固练习：\n1、求值:; ; ;\n2、化简：；\n3. 计算：的结果\n4. 若\n第十一讲： 指数函数及其性质\n一. 指数函数模型思想及指数函数概念：\n1.  探究两个实例：\n*A*．细胞分裂时，第一次由1个分裂成2个，第2次由2个分裂成4个，第3次由4个分裂成8个，如此下去，如果第*x*次分裂得到*y*个细胞，那么细胞个数*y*与次数*x*的函数关系式是什么？\n*B*．一种放射性物质不断变化成其他物质，每经过一年的残留量是原来的84％，那么以时间*x*年为自变量，残留量*y*的函数关系式是什么？\n2.  讨论：上面的两个函数有什么共同特征底数是什么指数是什么\n③ 定义：一般地，函数叫做指数函数（exponential\nfunction），其中*x*是自变量，函数的定义域为*R*.\n④讨论：为什么规定＞0且≠1呢？否则会出现什么情况呢？\n→ 举例：生活中其它指数模型？\n二. 指数函数的图象和性质：\n①\n讨论：你能类比前面讨论函数性质时的思路，提出研究指数函数性质的内容和方法吗？\n② 回顾：研究方法：画出函数的图象，结合图象研究函数的性质．\n研究内容：定义域、值域、特殊点、单调性、最大（小）值、奇偶性．\n③ 作图：在同一坐标系中画出下列函数图象： ，\n④\n探讨：函数与的图象有什么关系？如何由的图象画出的图象？根据两个函数的图象的特征，归纳出这两个指数函数的性质.\n→ 变底数为3或1/3等后？\n⑤ 根据图象归纳：指数函数的性质\n例题讲解\n例1：已知指数函数（＞0且≠1）的图象过点（3，π），求\n例2：比较下列各题中的个值的大小\n（1） 与 ( 2 )与 ( 3 ) 与 例3：求下列函数的定义域：\n（1） （2）\n三. 指数函数的应用模型：\n①例1：我国人口问题非常突出，在耕地面积只占世界7%的国土上，却养育着22%的世界人口．因此，中国的人口问题是公", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-938b72471a8b33ecefefce797b22a66e", "__created_at__": 1754904278, "content": "（3，π），求\n例2：比较下列各题中的个值的大小\n（1） 与 ( 2 )与 ( 3 ) 与 例3：求下列函数的定义域：\n（1） （2）\n三. 指数函数的应用模型：\n①例1：我国人口问题非常突出，在耕地面积只占世界7%的国土上，却养育着22%的世界人口．因此，中国的人口问题是公认的社会问题．2000年第五次人口普查，中国人口已达到13亿，年增长率约为1%．为了有效地控制人口过快增长，实行计划生育成为我国一项基本国策．\n(Ⅰ)按照上述材料中的1%的增长率，从2000年起，*x*年后我国的人口将达到2000年的多少倍？\n(Ⅱ)从2000年起到2020年我国的人口将达到多少？\n练习： 2010年某镇工业总产值为100亿，计划今后每年平均增长率为8%,\n经过*x*年后的总产值为原来的多少倍\n→ 变式：多少年后产值能达到120亿？\n③\n小结指数函数增长模型：原有量*N*，平均最长率*p*，则经过时间*x*后的总量*y*=\n→一般形式：\n四. 指数形式的函数定义域、值域：\n① 讨论：在/[*m*，*n*/]上，值域？\n②例1. 求下列函数的定义域、值域：; ; .\n②例2. 求函数的定义域和值域.\n讨论：求定义域如何列式 求值域先从那里开始研究\n例题讲解\n例1求函数的定义域和值域，并讨论函数的单调性、奇偶性.\n例2截止到1999年底，我们人口哟13亿，如果今后，能将人口年平均均增长率控制在1%，那么经过20年后，我国人口数最多为多少（精确到亿）\n例3、已知函数，求这个函数的值域\n巩固练习：\n1/. 函数是指数函数，则的值为 .\n2、 比较大小：；\n,.\n； .\n3、探究：在/[*m*，*n*/]上，值域？\n4、\n一片树林中现有木材30000m^3^，如果每年增长5%，经过*x*年树林中有木材*y*m^3^，写出*x，y*间的函数关系式，并利用图象求约经过多少年，木材可以增加到40000m^3^\n第十二讲：对数与对数运算\n一、复习准备：\n1.问题1：庄子：一尺之棰，日取其半，万世不竭![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n（1）取4次，还有多长（2）取多少次，还有尺 （得到：＝，＝=）\n2.问题2：假设2010年我国国民生产总值为*a*亿元，如果每年平均增长8%，那么经过多少年国民生产\n是2010年的2倍 （ 得到：=2*x*= ）\n问题共性：已知底数和幂的值，求指数![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\nheight=\"2.9861111111111113e-2in\"} 怎样求呢？\n例如：由求*x*\n二、讲授新课：\n1.对数的概念：\n① 定义：一般地，如果，那么数 *x*叫做以*a*为底 *N*的对数（logarithm）.\n> 记作\n> ，其中*a*叫做对数的底数，*N*叫做真数![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n> height=\"2.9861111111111113e-2in\"}\n② 定义：我们通常将以10为底的对数叫做常用对数（common\nlogarithm），并把常用对数简记为lg*N*![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n在科学技术中常使用以无理数e=......为底的对数，以e为底的对数叫自然对数，并把自然对数简记作ln*N*![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n→ 认识：lg5 ; ； ln10； ln3\n③ 讨论：指数与对数间的关系 （时，）\n负数与零是否有对数 （原因：在指数式中 *N* /> 0 ）\n，\n④：对数公式，\n2.指数式与对数式的互化：\n①例", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-7d2cf4036aea102e8e381e00d8373b18", "__created_at__": 1754904278, "content": "be6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n→ 认识：lg5 ; ； ln10； ln3\n③ 讨论：指数与对数间的关系 （时，）\n负数与零是否有对数 （原因：在指数式中 *N* /> 0 ）\n，\n④：对数公式，\n2.指数式与对数式的互化：\n①例1. 将下列指数式写成对数式： ；；；\n② 出示例2. 将下列对数式写成指数式：； =-3； ln100=\n例1将下列指数式化为对数式，对数式化为指数式.\n（1）5^4^=645 （2） （3）\n（4） （5） （6）\n例2：求下列各式中*x*的值\n（1） （2） （3） （4）\n3.对数运算性质及推导：\n① 引例：\n由，如何探讨和、![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\nheight=\"2.9861111111111113e-2in\"}之间的关系？\n设,\n，由对数的定义可得：*M*=，*N*=![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n∴*MN*==\n∴*MN*=*p*+*q*，即得*MN*=*M* +\n*N*![](static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image320.emf){width=\"2.9861111111111113e-2in\"\n② 探讨：根据上面的证明，能否得出以下式子？\n如果 *a* /> 0，*a* 1，*M* /> 0， *N* /> 0 ，则\n; ；\n3.  讨论：自然语言如何叙述三条性质 性质的证明思路\n④ 运用换底公式推导下列结论：；\n教学例题：\n例3. 判断下列式子是否正确，（＞0且≠1，＞0且≠1，＞0，＞），\n（1） （2）\n（3） （4）\n（5） （6）\n（7）\n例4：用，，表示出（1）（2）小题，并求出（3）、（4）小题的值.\n（1） （2） （3） （4）\n巩固练习：\n1．计算： ； ；； ； .\n2．求且不等于1，N＞0）.\n3,，试用、表示.\n变式：已知lg２＝，lg３＝，求lg６、lg12、lg的值.\n4计算：； ； .\n5 设、、为正数，且，求证：\n6求的值\n第十三讲：对数函数及其性质\n1.对数函数的图象和性质：\n① 定义：一般地，当*a*＞0且*a*≠1时，函数叫做对数函数(logarithmic\nfunction).自变量是*x*； 函数的定义域是（0，+∞）\n② 辨析： 对数函数定义与指数函数类似，都是形式定义，注意辨别，如：，\n都不是对数函数，而只能称其为对数型函数；对数函数对底数的限制 ，且．\n③\n探究：你能类比前面讨论指数函数性质的思路，提出研究对数函数性质的内容和方法吗？\n研究方法：画出函数的图象，结合图象研究函数的性质．\n研究内容：定义域、值域、特殊点、单调性、最大（小）值、奇偶性．\n④ 练习：同一坐标系中画出下列对数函数的图象 ；\n⑤ 讨论：根据图象，你能归纳出对数函数的哪些性质？\n列表归纳：分类 → 图象 → 由图象观察（定义域、值域、单调性、定点）\n引申：图象的分布规律？\n2、总结出的表格\n+----------------------------------------+----------------------------+\n| 图象的特征                             | 函数的性质                 |\n+----------------------------------------+----------------------------+\n| （1）图象都在轴的右边                  | （1）定义域是（0，+∞）     |\n+----------------------------------------+----------------------------+\n| （2）函数图象都经过（1，0）点          | （2）1的对数是0            |\n+----------------------------------------+----------------------------+\n| （3）从左往右看，当＞1时，             | （3）当＞1时，是增函数，当 |\n| 图象逐渐上升，当0＜＜1时，图象逐渐下降 |                            |\n| .                                  | 0＜＜1时，是减函数.    |\n+----------------------------------------+----------------------------+\n| （4）当＞1时，函                       | （4）当＞1时               |\n| 数图象在（1，0）点右边的纵坐标", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-ab3ae2b2a9b1a8ab8c364d00a5123e3b", "__created_at__": 1754904278, "content": "1时，             | （3）当＞1时，是增函数，当 |\n| 图象逐渐上升，当0＜＜1时，图象逐渐下降 |                            |\n| .                                  | 0＜＜1时，是减函数.    |\n+----------------------------------------+----------------------------+\n| （4）当＞1时，函                       | （4）当＞1时               |\n| 数图象在（1，0）点右边的纵坐标都大于0  |                            |\n| ，在（1，0）点左边的纵坐标都小于0. | ＞1，则＞0                 |\n| 当0＜＜1时，图                         |                            |\n| 象正好相反，在（1，0）点右边的纵坐标都 | 0＜＜1，＜0                |\n| 小于0，在（1，0）点左边的纵坐标都大于0 |                            |\n| .                                  | 当0＜＜1时                 |\n|                                        |                            |\n|                                        | ＞1，则＜0                 |\n|                                        |                            |\n|                                        | 0＜＜1，＜0                |\n+----------------------------------------+----------------------------+\n教学例题\n例1：求下列函数的定义域\n（1） （2） （＞0且≠1）\n例2.比较下列各组数中的两个值大小\n（1） （2）\n2 函数模型思想及应用:\n①例题：溶液酸碱度的测量问题：溶液酸碱度pH的计算公式，其中表示溶液中氢离子的浓度，单位是摩尔/升.\n（Ⅰ）分析溶液酸碱读与溶液中氢离子浓度之间的关系？\n（Ⅱ）纯净水摩尔/升，计算纯净水的酸碱度.\n2.  讨论：抽象出的函数模型 如何应用函数模型解决问题 → 强调数学应用思想\n3反函数的教学:\n① 引言:当一个函数是一一映射时,\n可以把这个函数的因变量作为一个新函数的自变量,\n而把这个函数的自变量新的函数的因变量. 我们称这两个函数为反函数（inverse\nfunction）\n② 探究：如何由求出*x*\n③ 分析：函数由解出，是把指数函数中的自变量与因变量对调位置而得出的.\n习惯上我们通常用*x*表示自变量，*y*表示函数，即写为.\n那么我们就说指数函数与对数函数互为反函数\n④ 在同一平面直角坐标系中，画出指数函数及其反函数图象，发现什么性质？\n⑤\n分析：取图象上的几个点，说出它们关于直线的对称点的坐标，并判断它们是否在的图象上，为什么？\n⑥\n探究：如果在函数的图象上，那么*P*~0~关于直线的对称点在函数的图象上吗，为什么？\n例题讲解\n例3求下列函数的反函数\n（1） （2）\n例4求函数的定义域、值域和单调区间\n巩固练习：\n1求下列函数的定义域： ； .\n2比较下列各题中两个数值的大小：\n； ；\n； ．\n3 已知下列不等式，比较正数*m*、*n*的大小：\n*m*＜*n* ； *m*＞*n* ； *m*＞*n* (*a*＞1)\n4 探究：求定义域；.\n5己知函数的图象过点（1，3）其反函数的图象过（2，0）点，求的表达式.\n第十四讲 ：幂函数\n一、新课引入：\n（1）边长为的正方形面积，这里是的函数；\n（2）面积为的正方形边长，这里是的函数；\n（3）边长为的立方体体积，这里是的函数；\n（4）某人内骑车行进了1，则他骑车的平均速度，这里是的函数；\n（5）购买每本1元的练习本本，则需支付元，这里是的函数.\n观察上述五个函数，有什么共同特征？\n二、讲授新课：\n1、幂函数的图象与性质\n① 给出定义：一般地，形如的函数称为幂函数，其中为常数.\n② 练：判断在函数中，哪几个函数是幂函数？\n③ 作出下列函数的图象：（1）；（2）；（3）；（4）；（5）．\n④观察图象，归纳概括幂函数的的性质及图象变化规律：\n（Ⅰ）所有的幂函数在（0，+∞）都有定义，并且图象都过点（1，1）；\n（Ⅱ）时，幂函数的图象通过原点，并且在区间上是增函数．特别地，当时，幂函数的图象下凸；当时，幂函数的图象上凸；\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image482.png)\n（Ⅲ）时，幂函数的图象在区间上是减函数．在第一象", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}, {"__id__": "chunk-f3898408008c1a2c13c4c732a1533862", "__created_at__": 1754904278, "content": "时，幂函数的图象通过原点，并且在区间上是增函数．特别地，当时，幂函数的图象下凸；当时，幂函数的图象上凸；\n![](/static/Images/28bdca7490d9410983a8afbe6bb74dcd/media/image482.png)\n（Ⅲ）时，幂函数的图象在区间上是减函数．在第一象限内，当从右边趋向原点时，图象在轴右方无限地逼近轴正半轴，当趋于时，图象在轴上方无限地逼近轴正半轴．\n2、教学例题：\n例1．证明幂函数上是增函数\n例2. 比较大小：与；与；与.\n三、巩固练习：\n1、论函数的定义域、奇偶性，作出它的图象，并根据图象说明函数的单调性．\n2/. 比较下列各题中幂值的大小：与；与；与.\n基本初等函数复习\n一、复习准备：\n1.  提问：指数函数、对数函数、幂函数的图象和性质.\n2.  求下列函数的定义域：；；\n3/. 比较下列各组中两个值的大小：；；\n二、典型例题：\n例1：已知＝，54^b^＝3，用的值\n例2、函数的定义域为 .\n例3、函数的单调区间为 .\n例4、已知函数.判断　的奇偶性并予以证明.\n例5、按复利计算利息的一种储蓄，本金为元，每期利率为，设本利和为元，存期为，写出本利和随存期变化的函数解析式.\n如果存入本金1000元，每期利率为%，试计算5期后的本利和是多少（精确到1元）（复利是一种计算利息的方法，即把前一期的利息和本金加在一起算做本金，再计算下一期的利息.\n）\n（小结：掌握指数函数、对数函数、幂函数的图象与性质，会用函数性质解决一些简单的应用问题.\n）\n3.  巩固练习：\n1.函数的定义域为 .，值域为 .\n2/. 函数的单调区间为 .\n3.  若点既在函数的图象上，又在它的反函数的图象上，则=/_/_/_/_/_/_，=/_/_/_/_/_/_/_\n4/. 函数(，且)的图象必经过点 .\n5/. 计算 .\n6/. 求下列函数的值域：\n; ; ;", "full_doc_id": "高中数学必修一讲义_1693010.docx", "file_path": "高中数学必修一讲义_1693010.docx"}], "matrix": 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"}