Preface   PART ONE: GATHERING AND EXPLORING DATA   1. Statistics: The Art and Science of Learning from Data 1.1 Using Data to Answer Statistical Questions 1.2 Sample Versus Population 1.3 Using Calculators and Computers             Chapter Summary             Chapter Problems   2. Exploring Data with Graphs and Numerical Summaries 2.1 Different Types of Data 2.2 Graphical Summaries of Data 2.3 Measuring the Center of Quantitative Data 2.4 Measuring the Variability of Quantitative Data 2.5 Using Measures of Position to Describe Variability 2.6 Recognizing and Avoiding Misuses of Graphical Summaries             Chapter Summary             Chapter Problems   3. Association: Contingency, Correlation, and Regression 3.1 The Association Between Two Categorical Variables 3.2 The Association Between Two Quantitative Variables 3.3 Predicting the Outcome of a Variable 3.4 Cautions in Analyzing Associations             Chapter Summary             Chapter Problems   4. Gathering Data 4.1 Experimental and Observational Studies 4.2 Good and Poor Ways to Sample 4.3 Good and Poor Ways to Experiment 4.4 Other Ways to Conduct Experimental and Nonexperimental Studies             Chapter Summary             Chapter Problems               Part Review 1 (ONLINE)   PART TWO: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLING DISTRIBUTIONS   5. Probability in Our Daily Lives 5.1 How Probability Quantifies Randomness 5.2 Finding Probabilities 5.3 Conditional Probability 5.4 Applying the Probability Rules             Chapter Summary             Chapter Problems   6. Probability Distributions 6.1 Summarizing Possible Outcomes and Their Probabilities 6.2 Probabilities for Bell-Shaped Distributions 6.3 Probabilities When Each Observation Has Two Possible Outcomes             Chapter Summary             Chapter Problems   7. Sampling Distributions 7.1 How Sample Proportions Vary Around the Population Proportion 7.2 How Sample Means Vary Around the Population Mean             Chapter Summary             Chapter Problems               Part Review 2 (ONLINE)   PART THREE: INFERENTIAL STATISTICS   8. Statistical Inference: Confidence Intervals 8.1 Point and Interval Estimates of Population Parameters 8.2 Constructing a Confidence Interval to Estimate a Population Proportion 8.3 Constructing a Confidence Interval to Estimate a Population Mean 8.4 Choosing the Sample Size for a Study 8.5 Using Computers to Make New Estimation Methods Possible             Chapter Summary             Chapter Problems   9. Statistical Inference: Significance Tests About Hypotheses 9.1 Steps for Performing a Significance Test 9.2 Significance Tests About Proportions 9.3 Significance Tests About Means 9.4 Decisions and Types of Errors in Significance Tests 9.5 Limitations of Significance Tests 9.6 The Likelihood of a Type II Error             Chapter Summary             Chapter Problems   10. Comparing Two Groups 10.1 Categorical Response: Comparing Two Proportions 10.2 Quantitative Response: Comparing Two Means 10.3 Other Ways of Comparing Means and Comparing Proportions 10.4 Analyzing Dependent Samples 10.5 Adjusting for the Effects of Other Variables             Chapter Summary             Chapter Problems               Part Review 3 (ONLINE)   PART FOUR: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS   11. Analyzing the Association Between Categorical Variables 11.1 Independence and Dependence (Association) 11.2 Testing Categorical Variables for Independence 11.3 Determining the Strength of the Association 11.4 Using Residuals to Reveal the Pattern of Association 11.5 Fisher’s Exact and Permutation Tests             Chapter Summary             Chapter Problems   12. Analyzing the Association Between Quantitative Variables: Regression Analysis 12.1 Modeling How Two Variables Are Related 12.2 Inference About Model Parameters and the Association 12.3 Describing the Strength of Association 12.4 How the Data Vary Around the Regression Line 12.5 Exponential Regression: A Model for Nonlinearity             Chapter Summary             Chapter Problems   13. Multiple Regression 13.1 Using Several Variables to Predict a Response 13.2 Extending the Correlation and R2 for Multiple Regression 13.3 Using Multiple Regression to Make Inferences 13.4 Checking a Regression Model Using Residual Plots 13.5 Regression and Categorical Predictors 13.6 Modeling a Categorical Response             Chapter Summary             Chapter Problems   14. Comparing Groups: Analysis of Variance Methods 14.1 One-Way ANOVA: Comparing Several Means 14.2 Estimating Differences in Groups for a Single Factor 14.3 Two-Way ANOVA             Chapter Summary             Chapter Problems   15. Nonparametric Statistics 15.1 Compare Two Groups by Ranking 15.2 Nonparametric Methods for Several Groups and for Matched Pairs             Chapter Summary             Chapter Problems             Part Review 4 (ONLINE)   Tables Answers Index Index of Applications Photo Credits

About the Book NEW! Topical coverage reflecting the latest trends in statistical education, including: Measures of association for categorical variables in Chapter 3 Permutation testing in Chapters 10 and 11 Updated coverage of McNemar's test in Chapter 10 (previously Chapter 11) Promoting Student Learning: these features were created to motivate students to think about the material presented, ask interesting questions, and develop good problem-solving skills. In Words summarizes complicated symbolic notation and formal definitions in a non-technical, less formal way to help students understand “what it really means.” New Caution margin boxes appear at appropriate places to help students avoid common mistakes. Recall margin boxes direct students back to previous presentations in the text to review definitions and formulas, and to reinforce key concepts in context. Did You Know margin boxes provide information that helps with the contextual understanding of the statistical questions. Annotated figures feature labels to identify noteworthy aspects in each illustration that may not be obvious to inexperienced students; many captions include questions designed to challenge students to think more about the information being presented. Active learning is encouraged through the use of simulations and hands-on activities via Learning Catalytics. Learning Catalytics is a web-based engagement and assessment tool. As a "bring-your-own-device" direct response system, Learning Catalytics offers a diverse library of dynamic question types that allow students to interact with and think critically about statistical concepts. As a real-time resource, instructors can take advantage of critical teaching moments both in the classroom or through assignable and gradable homework. Real-World Connections Chapter-opening examples include a high-interest example that raises questions and establishes a chapter theme. Opening examples use real-world data from a variety of applications. In Practice boxes alert students to the way statisticians actually analyze data in the real world. Exercises and Examples incorporate real data and focus on intriguing topics that appeal to students. Examples emphasize thinking about and understanding statistics through analysis of current real data. The unique five-step format encourages students to model the thought processes required to examine issues in statistics. Picture the Scenario presents background information so that students can understand the context of the data. Questions to Explore show students the appropriate questions to ask about the scenario and focus on what students should learn from the example. Think It Through is the heart of each example, as the Questions to Explore are investigated and answered using the appropriate statistical methods. Insight clarifies the central ideas investigated in the example and places them in a broader context that states the conclusions in less technical terms. This step also connects concepts from other sections in the book. A Try Exercise directs students to an end-of-section exercise that allows immediate practice of the concept. Concept tags are included with each example so that students can easily identify the concept demonstrated in the example. NEW and updated example videos are available in MyStatLab for students to watch as they work through in-text examples. A plethora of chapter exercises test student comprehension through interesting real-data problems. Exercises, divided into three categories, address relevant and thought-provoking topics, such as cell phone usage, cancer, and public support for the death penalty. Practicing the Basics reinforce basic applications of methods. Concepts and Investigations require students to explore the theory and concepts presented in the chapter through real data sets. Student Activities are appropriate for individual or group work and often make use of the web apps that accompany the text. “Part” organization divides the book into four Parts. Each Part has a corresponding Part Review in MyStatLab to help students understand the “big picture” and solve exercises that review the key concepts, ideas, and techniques. Included are Summary Questions, Summary Examples, and Part Exercises. Technology Integration Modern technological techniques are used to develop concepts and analyze data. Output from computer software (Minitab®, StatCrunch, Microsoft Excel®) and the TI-83/84 Plus graphing calculator is used to illustrate many concepts. Activities and Web Apps referred to in the text are found within MyStatLab or at the Companion Website (www.pearsonhighered.com/AFK). The use of web apps offers a way to show students certain concepts visually. Helpful instructor features Chapter-specific Instructor Notes appear in the Annotated Instructor’s Edition. These time-saving notes give insights into the authors’ approach to the material, suggestions for additional classroom examples and activities, learning objectives, and other helpful teaching tips. UPDATED! Instructor-to-Instructor videos feature the authors’ perspectives on chapters and helpful suggestions for how to teach from the book. The videos can be accessed through a link in Pearson’s Instructor Resource Center and through MyStatLab.   Also available with MyStatLab MyStatLab™ is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. For this edition, new web apps with complementary exercises, a tightly integrated video program, and strong exercise coverage enhance student learning. NEW! Increased exercise coverage on 60% of the book's exercises, gives instructors even more options when creating assignments. NEW! Web Apps—delivered through examples, exercises, and simulations—allow students to interact with key statistical concepts and techniques, including permutation tests, bootstrapping, and sampling distributions. Students can explore the consequences of changing parameters and carry out statistical inference. UPDATED! Technology Instruction Videos provide step-by-step instructions on how to perform statistical procedures using Excel®, Minitab®, StatCrunch, and the TI Graphing Calculator. StatCrunch is integrated within the eBook. With a single click, the data set on the page opens in StatCrunch, allowing point-of-use data analysis. Conceptual Question Library: In addition to algorithmically regenerated questions that are aligned with the textbook, there is also a library of 1,000 Conceptual Questions that focus on student understanding of statistical concepts. Getting Ready for Statistics: A library of questions focusing on developmental math topics is available. These can be assigned as a prerequisite to other assignments, if desired. NEW! Learning Catalytics is a web-based engagement and assessment tool. As a "bring-your-own-device" direct response system, Learning Catalytics offers a diverse library of dynamic question types that allow students to interact with and think critically about statistical concepts. As a real-time resource, instructors can take advantage of critical teaching moments both in the classroom or through assignable and gradable homework.

About the Book NEW! Topical coverage reflecting the latest trends in statistical education, including: Measures of association for categorical variables in Chapter 3 Permutation testing in Chapters 10 and 11 Updated coverage of McNemar's test in Chapter 10 (previously Chapter 11) New Caution margin boxes appear at appropriate places to help students avoid common mistakes.   Also available with MyStatLab MyStatLab™ is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. For this edition, new web apps with complementary exercises, a tightly integrated video program, and strong exercise coverage enhance student learning. Increased exercise coverage on 60% of the book's exercises, gives instructors even more options when creating assignments. Web Apps—delivered through examples, exercises, and simulations—allow students to interact with key statistical concepts and techniques, including permutation tests, bootstrapping, and sampling distributions. Students can explore the consequences of changing parameters and carry out statistical inference. UPDATED! Technology Instruction Videos provide step-by-step instructions on how to perform statistical procedures using Excel®, Minitab®, StatCrunch, and the TI Graphing Calculator. UPDATED! Instructor-to-Instructor videos feature the authors’ perspectives on chapters and helpful suggestions for how to teach from the book. The videos can be accessed through a link in Pearson’s Instructor Resource Center and through MyStatLab. Learning Catalytics is a web-based engagement and assessment tool. As a "bring-your-own-device" direct response system, Learning Catalytics offers a diverse library of dynamic question types that allow students to interact with and think critically about statistical concepts. As a real-time resource, instructors can take advantage of critical teaching moments both in the classroom or through assignable and gradable homework.