Preface Index of Applications 1. Introduction to Data Case Study–Deadly Cell Phones? 1.1 What Are Data? 1.2 Classifying and Storing Data 1.3 Organizing Categorical Data 1.4 Collecting Data to Understand Causality Exploring Statistics–Collecting a Table of Different Kinds of Data 2. Picturing Variation with Graphs Case Study–Student-to-Teacher Ratio at Colleges 2.1 Visualizing Variation in Numerical Data 2.2 Summarizing Important Features of a Numerical Distribution 2.3 Visualizing Variation in Categorical Variables 2.4 Summarizing Categorical Distributions 2.5 Interpreting Graphs Exploring Statistics–Personal Distance 3. Numerical Summaries of Center and Variation Case Study–Living in a Risky World 3.1 Summaries for Symmetric Distributions 3.2 What’s Unusual? The Empirical Rule and z-Scores 3.3 Summaries for Skewed Distributions 3.4 Comparing Measures of Center 3.5 Using Boxplots for Displaying Summaries Exploring Statistics–Does Reaction Distance Depend on Gender? 4. Regression Analysis: Exploring Associations between Variables Case Study–Catching Meter Thieves 4.1 Visualizing Variability with a Scatterplot 4.2 Measuring Strength of Association with Correlation 4.3 Modeling Linear Trends 4.4 Evaluating the Linear Model Exploring Statistics–Guessing the Age of Famous People 5. Modeling Variation with Probability Case Study–SIDS or Murder? 5.1 What Is Randomness? 5.2 Finding Theoretical Probabilities 5.3 Associations in Categorical Variables 5.4 Finding Empirical Probabilities Exploring Statistics–Let’s Make a Deal: Stay or Switch? 6. Modeling Random Events: The Normal and Binomial Models Case Study–You Sometimes Get More Than You Pay For 6.1 Probability Distributions Are Models of Random Experiments 6.2 The Normal Model 6.3 The Binomial Model (optional) Exploring Statistics–ESP with Coin Flipping 7. Survey Sampling and Inference Case Study–Spring Break Fever: Just What the Doctors Ordered? 7.1 Learning about the World through Surveys 7.2 Measuring the Quality of a Survey 7.3 The Central Limit Theorem for Sample Proportions 7.4 Estimating the Population Proportion with Confidence Intervals 7.5 Comparing Two Population Proportions with Confidence Exploring Statistics–Simple Random Sampling Prevents Bias 8. Hypothesis Testing for Population Proportions Case Study–Dodging the Question 8.1 The Essential Ingredients of Hypothesis Testing 8.2 Hypothesis Testing in Four Steps 8.3 Hypothesis Tests in Detail 8.4 Comparing Proportions from Two Populations Exploring Statistics–Identifying Flavors of Gum through Smell 9. Inferring Population Means Case Study–Epilepsy Drugs and Children 9.1 Sample Means of Random Samples 9.2 The Central Limit Theorem for Sample Means 9.3 Answering Questions about the Mean of a Population 9.4 Hypothesis Testing for Means 9.5 Comparing Two Population

The writing style is relaxed and conversational, engaging readers using language they can understand. Student guidance features appear throughout every chapter, ensuring that readers are following the material and making connections to their everyday lives: Snapshots go beyond a definition by breaking down the statistical concepts introduced in the text discussion, quickly summarising the concept or procedure, and indicating when and how it should be used. A Theme opens each chapter, setting the tone and introducing the chapter's concepts. A Case Study opens each chapter, showing a real-world application of the concepts. At the end of the chapter, the case study is revisited to show how the statistical techniques covered in the chapter help solve the problem presented. Margin Notes draw attention to details that enhance learning and reading comprehension. Caution notes provide warnings about common mistakes or misconceptions. Looking Back reminders refer students to earlier coverage of a topic. Details clarify or expand on a concept. Key Points highlight essential concepts within the text to draw special attention to them. Understanding these concepts is essential for progress. The Chapter Review that concludes each chapter provides a list of important new terms, student learning objectives, a quick summary of the concepts and methods discussed, and sources for data, articles, and graphics referred to in the chapter. Technology integration emphasises the use of statistical software, which allows readers to focus on learning the concepts rather than being bogged down with unnecessarily time-consuming number crunching. Check Your Tech shows students how to calculate a problem by hand, using formulas, and get the same result as statistical software. TechTips outline steps for performing calculations using TI-83/84-Plus® graphing calculators, Excel®, Minitab®, and StatCrunch®. Whenever a new method or procedure is introduced, an icon refers students to the TechTips section at the end of the chapter. Mathematical formulas are limited throughout the book, and are introduced only when necessary to understand a concept. An active learning focus keeps students engaged in the material. NEW AND UPDATED examples appear in each chapter, with current topics such as views of stem cell research (Chapter 7) and online classes (Chapter 10). Many examples were also revised for a more thorough integration of technology. NEW! A wealth of exercises—including more than 400 new, revised, and updated exercises—appears at the end of each chapter, most using real data. Output from a range of statistical software is often included to acclimate students to interpreting results, regardless of which technology generated them. Guided Exercises step students through solving a problem if they need extra help while doing homework. These exercises are marked with an icon to indicate that step-by-step instruction is available in the Guided Exercises section at the end of the chapter. End-of-chapter exercises are organised by section and level of difficulty. Challenging exercises, identified with an asterisk, ask open-ended questions and sometimes require students to perform a complete statistical analysis. An abundance of

New and Updated Features in the Book NEW AND UPDATED examples appear in each chapter, with current topics such as views of stem cell research (Chapter 7) and online classes (Chapter 10). Many examples were also revised for a more thorough integration of technology.NEW! A wealth of exercises—including more than 400 new, revised, and updated exercises—appears at the end of each chapter, most using real data. Output from a range of statistical software is often included to acclimate students to interpreting results, regardless of which technology generated them. Guided Exercises step students through solving a problem if they need extra help while doing homework. These exercises are marked with an icon to indicate that step-by-step instruction is available in the Guided Exercises section at the end of the chapter.End-of-chapter exercises are organized by section and level of difficulty. Challenging exercises, identified with an asterisk, ask open-ended questions and sometimes require students to perform a complete statistical analysis. MyStatLabTM not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyStatLab from Pearson is the world’s leading online resource for teaching and learning statistics, integrating interactive homework, assessment, and media in a flexible, easy-to-use format. MyStatLab is a course management system that delivers improving results in helping individual students succeed. Chapter Review Videos walk students through solving a selection of the more complex problems posed in each chapter, providing a review of the chapter's key concepts and offering students support where they most need it.Student PowerPoint® slides provide an overview of each chapter, stressing important definitions and offering additional examples. These slides are an excellent resource for both traditional and online students. These are available in MyStatLab.Increased data-driven exercise coverage gives students more opportunities to practice the material. A goal of this revision is to improve learning outcomes for students. To help achieve this goal, we analyzed aggregated student usage and performance data from the first edition's MyStatLab course. The results of this analysis yielded specific improvements to this edition, including:Adjusted difficulty levels—we analyzed the easiest and most challenging exercises in the text to see whether adjustments needed to be made to those exercises or to the instruction in the text that supports them.Added or adjusted content—We analyzed exercise usage data to determine where content might need to be added to this text and its MyStatLab course. We also analyzed exercise and eText usage data to determine whether content that was seldom used, might be covered more succinctly.Data Cycle in Everyday Things videos bring real-world situations to life. Students are introduced to the concept of a data cycle, showing how statistics and data don’t necessarily have a "start and stop" point or a “yes or no” answer. Statistics is an exploration in data where we ask questions, collect data, analyze findings, interpret meaning, and repeat!Learning CatalyticsTM Integration: Learning Catalytics is a web-based engagement and assessment tool. As a "bring-your-own-device" direct response syste