Introductory Statistics: Exploring the World Through Data, 4th edition

Index of Applications

1. Introduction to Data

• Case Study: Dangerous Habit?
• 1.1 What Are Data?
• 1.2 Classifying and Storing Data
• 1.3 Investigating Data
• 1.4 Organizing Categorical Data
• 1.5 Collecting Data to Understand Causality
• Data Project: Introduction: Importing 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
• Data Project: The Bare Bones: Data Types

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
• Data Project: The W’s and One H: Asking Interrogative Questions

4. Regression Analysis: Exploring Associations between Variables

• Case Study: Forecasting Home Prices
• 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
• Data Project: Get It Sorted: Sorting Data

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
• Data Project: Ask Good Questions: Posing Statistical Investigative Questions

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)
• Data Project: Transformations for a Better Analysis

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
• Data Project: Make it Smaller: Subsetting Data

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
• Data Project: On and Off, and Off and On: Working with Binary Variables

9. Inferring Population Means

• Case Study: You Look Sick! Are You Sick?
• 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 Means
• 9.6 Overview of Analyzing Means
• Data Project: Non-binary Coding: Creating Multi-valued Categorical Variables

10. Associations between Categorical Variables

• Case Study: Popping Better Popcorn
• 10.1 The Basic Ingredients for Testing with Categorical Variables
• 10.2 The Chi-Square Test for Goodness of Fit
• 10.3 Chi-Square Tests for Associations between Categorical Variables
• 10.4 Hypothesis Tests When Sample Sizes Are Small
• Data Project: Dating Yourself: Creating New Variables from Dates

11. Multiple Comparisons and Analysis of Variance

• Case Study: Seeing Red
• 11.1 Multiple Comparisons
• 11.2 The Analysis of Variance
• 11.3 The ANOVA Test
• 11.4 Post-Hoc Procedures
• Data Project: What’s in a Name: Splitting and Merging Columns

12. Experimental Design: Controlling Variation

• Case Study: Does Stretching Improve Athletic Performance?
• 12.1 Variation Out of Control
• 12.2 Controlling Variation in Surveys
• 12.3 Reading Research Papers
• Data Project: Making Stacks: Stacking and Unstacking Data

13. Inference without Normality

• Case Study: Contagious Yawns
• 13.1 Transforming Data
• 13.2 The Sign Test for Paired Data
• 13.3 Mann-Whitney Test for Two Independent Groups
• 13.4 Randomization Tests
• Data Project: Breathe Deeply: Prepare a Data Set for Analysis

14. Inference for Regression

• Case Study: Another Reason to Stand at Your Desk?
• 14.1 The Linear Regression Model
• 14.2 Using the Linear Model
• 14.3 Predicting Values and Estimating Means
• Data Project: Is the Pen Mightier than the Keyboard?

Appendices

• A: Tables
• B: Answers to Odd-Numbered Exercises
• C: Credits

Index