Preface Index of Applications   Part I. Exploring and Understanding Data   1. Stats Starts Here! 1.1 What Is Statistics? 1.2 Data 1.3 Variables   2. Displaying and Describing Categorical Data 2.1 Summarizing and Displaying a Single Categorical Variable 2.2 Exploring the Relationship Between Two Categorical Variables   3. Displaying and Summarizing Quantitative Data 3.1 Displaying Quantitative Variables 3.2 Shape 3.3 Center 3.4 Spread 3.5 Boxplots and 5-Number Summaries 3.6 The Center of Symmetric Distributions: The Mean 3.7 The Spread of Symmetric Distributions: The Standard Deviation 3.8 Summary—What to Tell About a Quantitative Variable   4. Understanding and Comparing Distributions 4.1 Comparing Groups with Histograms 4.2 Comparing Groups with Boxplots 4.3 Outliers 4.4 Timeplots: Order, Please! 4.5 Re-expressing Data: A First Look   5. The Standard Deviation as a Ruler and the Normal Model 5.1 Standardizing with z-Scores 5.2 Shifting and Scaling 5.3 Normal Models 5.4 Finding Normal Percentiles 5.5 Normal Probability Plots   Review of Part I: Exploring and Understanding Data   Part II. Exploring Relationships Between Variables   6. Scatterplots, Association, and Correlation 6.1 Scatterplots 6.2 Correlation 6.3 Warning: Correlation ≠ Causation 6.4 Straightening Scatterplots   7. Linear Regression 7.1 Least Squares: The Line of "Best Fit" 7.2 The Linear Model 7.3 Finding the Least Squares Line 7.4 Regression to the Mean 7.5 Examining the Residuals 7.6 R2—The Variation Accounted for by the Model 7.7 Regression Assumptions and Conditions   8. Regression Wisdom 8.1 Examining Residuals 8.2 Extrapolation: Reaching Beyond the Data 8.3 Outliers, Leverage, and Influence 8.4 Lurking Variables and Causation 8.5 Working with Summary Values   Review of Part II: Exploring Relationships Between Variables   Part III. Gathering Data   9. Understanding Randomness 9.1 What is Randomness? 9.2 Simulating By Hand   10. Sample Surveys 10.1 The Three Big Ideas of Sampling 10.2 Populations and Parameters 10.3 Simple Random Samples 10.4 Other Sampling Designs 10.5 From the Population to the Sample: You Can't Always Get What You Want 10.6 The Valid Survey 10.7 Common Sampling Mistakes, or How to Sample Badly   11. Experiments and Observational Studies 11.1 Observational Studies 11.2 Randomized, Comparative Experiments 11.3 The Four Principles of Experimental Design 11.4 Control Treatments 11.5 Blocking 11.6 Confounding   Review of Part III: Gathering Data   Part IV. Randomness and Probability   12. From Randomness to Probability 12.1 Random Phenomena 12.2 Modeling Probability 12.3 Formal Probability   13. Probability Rules! 13.1 The General Addition Rule 13.2   Conditional Probability and the General Multiplication Rule 13.3 Independence 13.4 Picturing Probability: Tables, Venn Diagrams and Trees 13.5 Reversing the Conditioning and Bayes' Rule   14. Random Variables and Probability Models 14.1 Expected Value: Center 14.2 Standard Deviation 14.3 Combining Random Variables 14.4 The Binomial Model 14.5 Modelin

Road Map to Success—from the familiar writing style to the helpful features included at key points of each chapter, the author team gives students the tools they need to succeed. Readability: the authors use a colloquial and informal style to engage students to actually read the book.Where Are We Going? chapter openers give a context for the work students are about to begin within the broader course.NEW! Chapter outlines have been added to each chapter opener to call out major topics.What Have We Learned? summaries conclude each chapterInnovative What Can Go Wrong? sections highlight the most common mistakes and misconceptions about statistics, arming students with the tools to detect statistical errors.By Hand boxes break calculations down into simple steps.A Reality Check asks students to think about whether their answers make sense before interpreting their results.Notation Alerts appear whenever special notation is introduced.Connections feature links key terms and concepts with previous discussions. Building an Understanding—to guide students in mastering the objectives presented in each chapter, the authors consistently model examples and provide opportunities for students to test their comprehension as they progress through the course. For Example appears after each important concept is introduced, applying that concept in a focused example—often with real and updated data. Many For Examples carry the discussion through the chapter.Step-by-Step examples repeat the mantra of Think, Show, and Tell in every chapter. These longer, worked examples guide students through the process of analysing a problem with the general explanation on the left and the worked-out problem on the right. They emphasise the importance of thinking about a statistics question and reporting the findings (the Tell step). The Show step contains the mechanics of calculating results. In the 4th edition, the authors have updated Think/Show/Tell Step-by-Step examples with new applications and data.Just Checking questions throughout the chapter encourage students to pause and think about what they’ve just read. Just Checking answers are at the end of the exercise sets so students can easily assess themselves.Exercises have been updated with the most recent data. Many are based on news stories and recent research articles.NEW! Single-concept exercises have been added at the beginning of each exercise set so students can be sure they have a clear understanding of important topics in every section before working comprehensive exercises.

Revised sections throughout the book are clearer and more interesting for readers.Rewritten examples with real and updated data open many chapters, motivating students to delve into the analyses that follow.A number of new organizational features make it even easier for students to connect the concepts Section heads are reorganized and reworded to be clearer and more specific.Chapter study materials now include Learning Objectives as well as key terms.Single-concept exercises have been added for each major section to assess students’ knowledge of the chapter’s basic concepts.A redesigned text layout clarifies the purpose of each element.The content has been reorganized to shorten the book from 27 to 23 chapters. Each chapter is still a focused discussion. Topics have been combined that are conceptually similar to reduce time spent on secondary topics.StatTalk Videos: 24 Conceptual Videos to Help You Actually Understand Statistics. Fun-loving statistician Andrew Vickers takes to the streets of Brooklyn, NY to demonstrate important statistical concepts through interesting stories and real-life events. These fun and engaging videos, available through the accompanying MyStatLab course, will help students actually understand statistical concepts. Available with an instructors user guide and assessment questions. Content changes: Chapter 1 now gets down to business immediately rather than just providing an introduction to the book’s features.The discussion of Randomness is now in Chapter 9—two chapters earlier than the previous edition.The discussions of probability and random variables are more concise—and a chapter shorter.The discussion of inference for means is now earlier. Although the discussion still opens with inference for proportions (for reasons explained in the Instructors Resource Guide), it now turns immediately to inference for means so students can see the methods side-by-side. Students can then also see that the reasoning is really the same.The discussion of paired samples and blocks is also earlier as it builds naturally on inference for means.Most exercises that use real data have been updated.