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Introduction to the Practice of Statistics (9th Edition)

Author(s):
Publisher:

WH Freeman

Pages: 814
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Flyer

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Hardcover - 9781319153977

06 January 2017

€74.99

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Access Card - 9781319013653

15 December 2016

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Pack - 9781352001105

27 July 2017

€78.99

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Introduction to the Practice of Statistics is the classic textbook for teaching statistics. This textbook shows students how to produce and interpret data from real-world contexts, guiding them through the type of data...

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Introduction to the Practice of Statistics is the classic textbook for teaching statistics. This textbook shows students how to produce and interpret data from real-world contexts, guiding them through the type of data gathering and analysis that working statisticians do every day. With this phenomenally successful approach developed by David Moore and George McCabe, statistics is more than just a collection of techniques and formulas. Instead, students develop a way of thinking about data with a focus on problem-solving that helps them understand concepts and master statistical reasoning.

Part of the best-selling Moore family of statistics books, Introduction to the Practice of Statistics is designed for a two-semester ‘introduction to statistics’ course and offers a rigorous introduction to the subject. This textbook is available on LaunchPad, which combines an interactive ebook with multimedia content and assessment tools, including LearningCurve adaptive quizzing. See ‘Instructor Resources’ and ‘Student Resources’ for further information.

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  • Available on LaunchPad - an innovative online teaching tool with interactive elements and adaptive questions. 
  • Textbook examines the nature of modern statistics, focusing on the production and analysis of data as well as the traditional topics of probability and inference.
  • Inference is treated as a tool that helps statisticians draw conclusions from data in an appropriate way.
  • Real examples drive the exposition so students learn the conceptual ties between regression and correlation and the importance of looking for influential observations.
  • Beyond the Basics sections give quick overviews of topics such as density estimation, scatterplot smoothers, data mining, nonlinear regression, and meta-analysis. 
  • Objectives at the beginning of each section help to identify what students will learn by the end of the section.

  • Over 30% of the 1700 exercises are new or revised, and over 30% of the 430 examples are new or revised.
  • Coverage of mosaic plots as a visual tool for relationships between two categorical variables has been added to Chapters 2 and 9.
  • Coverage of equivalence testing has been added to Chapter 7.
  • Greater emphasis on sample size determination using software in Chapters 7 and 8.

1.1 Data.-


1.2 Displaying Distributions with Graphs.-


1.3 Describing Distributions with Numbers.-


1.4 Density Curves and Normal Distributions.-


2.1 Relationships.-


2.2 Scatterplots.-


2.3 Correlation.-


2.4 Least-Squares Regression.-


2.5 Cautions about Correlation and Regression.-


<2.6 Data Analysis for Two-Way Tables.-


2.7 The Question of Causation.-


3.1 Sources of Data.-


3.2 Design of Experiments


3.3 Sampling Design.-


3.4 Ethics.-


4.1 Randomness.-


4.2 Probability Models.-


4.3 Random Variables.-


4.4 Means and Variances of Random Variables.-


4.5 General Probability Rules.-

 

5.1 Toward Statistical Inference.-


5.2 The Sampling Distribution of a Sample Mean.-


5.3 Sampling Distributions for Counts and Proportions.-

 

6.1 Estimating with Confidence.-


6.2 Tests of Significance.-


6.3 Use and Abuse of Tests.-


6.4 Power and Inference as a Decision 

Power.-


7.1 Inference for the Mean of a Population.-


7.2 Comparing Two Means.-


7.3 Additional Topics on Inference.-

 

8.1 Inference for a Single Proportion.-


8.2 Comparing Two Proportions.-


9.1 Inference for Two-Way Tables.-


10.1 Simple Linear Regression.-


10.2 More Detail about Simple Linear Regression.-


11.1 Inference for Multiple Regression.-

 

11.2 A Case Study.-


12.1 Inference for One-Way Analysis of Variance.-


12.2 Comparing the Means.-

 

13.1 The Two-Way ANOVA Model.-


14.1 The Logistic Regression Model.-


14.2 Inference for Logistic Regression.-


15.1 The Wilcoxon Rank Sum Test.-


15.2 The Wilcoxon Signed Rank Test.-


15.3 The Kruskal-Wallis Test.-


16.1 The Bootstrap Idea.-


16.2 First Steps in Using the Bootstrap.-


16.3 How Accurate Is a Bootstrap Distribution?.-


16.4 Bootstrap Confidence Intervals.-


16.5 Significance Testing Using Permutation Tests.-


17.1 Processes and Statistical Process Control.-


17.2 Using Control Charts.-


17.3 Process Capability Indexes.-


17.4 Control Charts for Sample Proportions.-

Introduction to the Practice of Statistics is available on LaunchPad. With LaunchPad, you’ll have access to an interactive eBook with multimedia content. You’ll also be able to benefit from its adaptive quizzing and learning tools which will help you succeed in your course. Purchase your LaunchPad access card or print and LaunchPad bundle above. 

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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. 


George P. McCabe is the Associate Dean for Academic Affairs in the College of Science and a Professor of Statistics at Purdue University.

Bruce A. Craig is Professor of Statistics and Director of the Statistical Consulting Service at Purdue University. He is an active member of the American Statistical Association and was chair of its section on Statistical Consulting in 2009.

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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. 


George P. McCabe is the Associate Dean for Academic Affairs in the College of Science and a Professor of Statistics at Purdue University.

Bruce A. Craig is Professor of Statistics and Director of the Statistical Consulting Service at Purdue University. He is an active member of the American Statistical Association and was chair of its section on Statistical Consulting in 2009.

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