Introduction to the Practice of Statistics

Introduction to the Practice of Statistics pdf epub mobi txt 电子书 下载 2026

出版者:W. H. Freeman
作者:David S. Moore
出品人:
页数:694
译者:
出版时间:2010-11-19
价格:USD 140.00
装帧:Hardcover
isbn号码:9781429240321
丛书系列:
图书标签:
  • 统计学
  • 教材
  • 统计
  • Textbook
  • Statistics
  • 文学青年
  • 数据处理
  • 数学
  • 统计学
  • 概率论
  • 数据分析
  • 统计推断
  • 实验设计
  • 统计方法
  • 统计学教材
  • 入门
  • 统计实践
  • R语言
想要找书就要到 小哈图书下载中心
立刻按 ctrl+D收藏本页
你会得到大惊喜!!

具体描述

The new Seventh Edition brings the acclaimed IPS approach to a new generation, with a number of enhancements in the text and with breakthrough media tools for instructors and students. It demonstrates how statistical techniques are used to solve real-world problems, combining real data and applications with innovative pedagogy, both in the text and via electronic media.

New Format Options

Introduction to the Practice of Statistics, Seventh Edition is available as:

• A core book containing the first 13 chapters in hardcover (1-4292-4032-6) or paperback (1-4292-7433-6). Companion chapters 14-17 are available on the book’s CD and web site.

• Extended Version (hardcover; includes chapters 1-15): 1-4292-7434-4; Companion chapters 16-17 are available on the book’s CD and web site.

http://www.whfreeman.com/Catalog/product/introductiontothepracticeofstatistics-seventhedition-moore

作者简介

David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University and was 1998 president of the American Statistical Association. He received his A.B. from Princeton and his Ph.D. from Cornell, both in mathematics. He has written many research papers in statistical theory and served on the editorial boards of several major journals. Professor Moore is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He has served as program director for statistics and probability at the National Science Foundation. In recent years, Professor Moore has devoted his attention to the teaching of statistics. He was the content developer for the Annenberg/Corporation for Public Broadcasting college-level telecourse Against All Odds: Inside Statistics and for the series of video modules Statistics: Decisions through Data, intended to aid the teaching of statistics in schools. He is the author of influential articles on statistics education and of several leading texts. Professor Moore has served as president of the International Association for Statistical Education and has received the Mathematical Association of America’s national award for distinguished college or university teaching of mathematics.

George P. McCabe is the Associate Dean for Academic Affairs in the College of Science and a Professor of Statistics at Purdue University. In 1966, he received a B.S. degree in mathematics from Providence College, and in 1970 a Ph.D. in mathematical statistics from Columbia University. His entire professional career has been spent at Purdue with sabbaticals at Princeton, the Commonwealth Scientific and Industrial Research Organization in Melbourne (Australia); the University of Berne (Switzerland); the National Institute of Standards and Technology (Boulder, Colorado); and the National University of Ireland in Galway. Professor McCabe is an elected fellow of the American Association for the Advancement of Science and of the American Statistical Association; he was 1998 Chair of its section on Statistical Consulting. From 2008 to 2010, he served on the Institute of Medicine Committee on Nutrition Standards for the National School Lunch and Breakfast Programs. He has served on the editorial boards of several statistics journals, has consulted with many major corporations, and has testified as an expert witness on the use of statistics. Professor McCabe’s research has focused on applications of statistics. Much of his recent work has been on problems of nutrition, including nutrient requirements, calcium metabolism, and bone health. He is author or coauthor of more than 160 publications in many different journals.

Bruce A. Craig is Professor of Statistics and Director of the Statistical Consulting Service at Purdue University. He received his B.S. in mathematics and economics from Washington University in St. Louis and his PhD in statistics from the University of Wisconsin–Madison. He is an active member of the American Statistical Association and was chair of its section on Statistical Consulting in 2009. He also is an active member of the Eastern North American Region of the International Biometrics Society and aws elected by the voting membership to the Regional Committee from 2003 to 2006. Professor Craig has served on the editorial board of several statistical journals and has been a member of several data and safety monitoring boards, including Purdue's IRB. Professor Craig's research interests focus on the development of novel statistical methodology to address research questions in the life sciences. Areas of current interest are protein structure determination, diagnostic testing, and animal abundance estimation. In 2005, he was named Purdue University Faculty Scholar.

http://www.whfreeman.com/Catalog/product/introductiontothepracticeofstatistics-seventhedition-moore

目录信息

PART I: Looking at Data
CHAPTER 1: Looking at Data—Distributions
CHAPTER 2: Looking at Data—Relationships
CHAPTER 3: Producing Data
PART II: Probability and Inference
CHAPTER 4: Probability: The Study of Randomness
CHAPTER 5: Sampling Distributions
CHAPTER 6: Introduction to Inference
CHAPTER 7: Inference for Distributions
CHAPTER 8: Inference for Proportions
PART III: Topics in Inference
CHAPTER 9: Analysis of Two-Way Tables
CHAPTER 10: Inference for Regression
CHAPTER 11: Multiple Regression
CHAPTER 12: One-Way Analysis of Variance
CHAPTER 13: Two-Way Analysis of Variance
Companion Chapters on CD-ROM and the Book Companion Site
CHAPTER 14: Logistic Regression
CHAPTER 15: Nonparametric Tests
CHAPTER 16: Bootstrap Methods and Permutation Tests
CHAPTER 17: Statistics for Quality: Control and Capability
· · · · · · (收起)

读后感

评分

评分

评分

评分

评分

用户评价

评分

读完这本书,我感觉自己的统计学思维得到了**一次彻底的重塑**。以往我对统计的理解仅仅停留在计算Z分数和P值上,总觉得这门学科是用来“证明”某个结论的工具。然而,这本书的视角更为深刻和批判性。它花了很多篇幅讨论**统计推断的局限性、抽样的偏差、以及如何正确地解读P值背后的概率含义**。作者非常警惕那些“一刀切”的结论,反复告诫读者要考虑情境和背景。比如,在讨论因果推断时,他们详细剖析了混杂变量的作用,并介绍了如何通过更高级的实验设计来尽量隔离效应。这种**强调科学审慎性和对不确定性的坦诚接纳**,是这本书最宝贵的财富。它教给我的不是“如何做计算”,而是“如何像一个严谨的统计学家一样思考”。对于那些追求学术深度和对统计伦理有高要求的读者,这本书提供的哲学层面的引导是无价的。它让我不再盲目相信任何图表,而是开始质疑其背后的数据来源和模型假设。

评分

这本书简直是统计学领域的**实战指南**!我当初拿到它的时候,还担心又是那种枯燥的教科书,里面塞满了晦涩难懂的公式和理论。但翻开第一章,我就被吸引住了。作者的叙述方式非常注重**实际应用**,仿佛手把手地教你如何在真实世界的问题中应用统计思维。他们没有直接抛出复杂的假设检验框架,而是先用一个引人入胜的案例,比如市场调研中的客户偏好分析,让你直观感受到“为什么我们需要统计学”。接着,每引入一个新概念,比如概率分布或者置信区间,都会紧密地和具体的工作场景结合起来。我特别喜欢书中对**数据清洗和探索性分析**的强调,这部分内容在很多理论导向的书里经常被一带而过,但这本书把它放在了核心位置,强调了“好数据的重要性”。阅读体验非常流畅,章节之间的过渡自然得像是听一位经验丰富的同事在分享他的工作心得。对于那些希望学完就能立刻上手处理真实数据集的人来说,这本书提供了坚实的桥梁,从理论的彼岸,顺利抵达实践的此岸。

评分

如果你是那种**需要大量视觉辅助**才能理解抽象概念的读者,这本书绝对不会让你失望。它的排版设计和图表呈现达到了教科书级别的专业水准,但又远超普通教材的枯燥感。色彩的运用非常克制但有效,关键的公式和定义被巧妙地用不同颜色的边框或背景突出显示,确保了重点的突出。更令人称赞的是,几乎每一个核心统计检验方法,都会配有**清晰的流程图和详细的计算步骤分解**。我个人对卡方检验和回归分析那几章印象特别深刻,作者用一系列逐步展开的图示,将复杂的矩阵运算和系数解释过程可视化了。这不仅仅是好看,而是实实在在地帮助我将抽象的代数语言转化为直观的几何或流程概念。对于那些在学习过程中容易被纯文字淹没的读者,这本书就像一个贴心的视觉向导,让统计学习不再是一场孤独的数字迷宫探险。

评分

这本书在**软件工具的结合应用**方面做得非常出色,体现了现代统计实践的真实面貌。它并没有固守理论的象牙塔,而是非常务实地介绍了如何利用主流统计软件(虽然我个人主要用的是R语言,但书中的SPSS和Excel的案例也都很通用)来执行分析。它不仅仅是告诉你“点击菜单上的这个选项”,而是深入解释了**软件后台运行的统计过程**,以及在不同软件环境中输入数据格式的细微差异。特别是关于**数据可视化和报告生成**的部分,提供了大量实用技巧,教会我们如何将分析结果转化为具有说服力的演示文稿或报告。这种对“从数据输入到结果输出”全流程的覆盖,极大地弥补了许多传统教材只关注理论推导的不足。对于希望将所学知识立即转化为工作产出的职场人士来说,这种实用性是决定性的加分项。

评分

坦白说,这本书的**深度和广度**都令人印象深刻。它涵盖的统计主题非常全面,从最基础的描述性统计,到中级的推断性统计,甚至触及了一些高级的主题,例如非参数检验和基础的时间序列分析概念。但最难得的是,它在保持这种广度的同时,并没有牺牲对细节的关注。例如,在讲解方差分析(ANOVA)时,它不仅介绍了单因素和双因素,还细致地讨论了重复测量设计的特殊考量。对于一个**渴望全面构建知识体系**的学习者而言,这本书提供了一个非常可靠的路线图。我发现,当我遇到一些专业文献中出现的较少见的方法时,回过头来查阅本书的相关章节,总能找到清晰、易懂的解释和适用的场景界定。这就像一个随身携带的、随时可以查阅的统计工具箱,结构清晰,用料扎实,经得起反复敲打和检验。

评分

这学期学完这本么也就拉倒了 千万别让我下学期还要学统计 姐念社科的,不是统计!!!!!

评分

耶鲁大学原版社会科学统计学入门教材,深入浅出,对词汇量要求不大,读几章后可无障碍阅读,举例较多,帮助理解统计理论,是不可多得的优质统计学教材。强烈推荐。

评分

为神马我们要用这本书!!!看不出编排哪里好!

评分

耶鲁大学原版社会科学统计学入门教材,深入浅出,对词汇量要求不大,读几章后可无障碍阅读,举例较多,帮助理解统计理论,是不可多得的优质统计学教材。强烈推荐。

评分

浅出浅出

本站所有内容均为互联网搜索引擎提供的公开搜索信息,本站不存储任何数据与内容,任何内容与数据均与本站无关,如有需要请联系相关搜索引擎包括但不限于百度google,bing,sogou

© 2026 qciss.net All Rights Reserved. 小哈图书下载中心 版权所有