Contents (each chapter concludes with Vocabulary, Review Exercises, and a Quiz)
Chapter 1. The Nature of Statistics
Case Study: Does Friday the 13th Change Human Behavior?
1.1 Data Stories: The People Behind the Numbers
1.2 An Introduction to Statistics
1.3 Gathering Data
Chapter 2. Describing Data Using Graphs and Tables
Case Study: The Caesar Cipher
2.1 Graphs and Tables for Categorical Data
2.2 Graphs and Tables for Quantitative Data
2.3 Further Graphs and Tables for Quantitative Data
2.4 Graphical Misrepresentations of Data
Chapter 3. Describing Data Numerically
Case Study: Can the Financial Experts Beat the Darts?
3.1 Measures of Center
3.2 Measures of Variability
3.3 Working with Grouped Data
3.4 Measures of Position and Outliers
3.5 Five-Number Summary and Boxplots
3.6 Chebyshev’s Rule and the Empirical Rule
Chapter 4. Correlation and Regression
Case Study: Female Literacy and Fertility Worldwide
4.1 Scatterplots and Correlation
4.2 Introduction to Regression
4.3 Further Topics in Regression Analysis
Chapter 5. Probability
Case Study: The ELISA Test for the Presence of HIV
5.1 Introducing Probability
5.2 Combining Events
5.3 Conditional Probability
5.4 Counting Methods
Chapter 6. Probability Distributions
Case Study: Be Careful What You Assume: National Football League Salaries
6.1 Discrete Random Variables
6.2 Binomial Probability Distribution
6.3 Poisson Probability Distribution
6.4 Continuous Random Variables and the Normal Probability Distribution
6.5 Standard Normal Distribution
6.6 Applications of the Normal Distribution
6.7 Normal Approximation to the Binomial Probability Distribution
Chapter 7. Sampling Distributions
Case Study: Trial of the Pyx: How Much Gold Is in Your Gold
7.1 Introduction to Sampling Distributions
7.2 Central Limit Theorem for Means
7.3 Central Limit Theorem for Proportions
Chapter 8. Confidence Intervals
Case Study Health Effects of the Deepwater Horizon Oil Spill
8.1 Z Interval for the Population Mean
8.2 t Interval for the Population Mean
8.3 Z Interval for the Population Proportion
8.4 Confidence Intervals for the Population Variance and Standard Deviation
Chapter 9. Hypothesis Testing
Case Study: The Golden Ratio
9.1 Introduction to Hypothesis Testing
9.2 Z Test for the Population Mean: Critical-Value Method
9.3 Test for the Population Mean: p-Value Method
9.4 t Test for the Population Mean
9.5 Z Test for the Population Proportion
9.6 Chi-Square Test for the Population Standard Deviation
9.7 Probability of Type II Error and the Power of a Hypothesis Test
Chapter 10. Two-Sample Inference
Case Study: Do Prior Student Evaluations Influence Students’ Ratings of Professors?
10.1 Inference for Mean Difference—Dependent Samples
10.2 Inference for Two Independent Means
10.3 Inference for Two Independent Proportions
10.4 Inference for Two Independent Standard Deviations
Chapter 11. Categorical Data Analysis
Case Study: Online Dating
11.1 Goodness of Fit Test
11.2 Tests for Independence and for Homogeneity of Proportions
Chapter 12. Analysis of Variance
Case Study: Professors on Facebook
12.1 One-Way Analysis of Variance (ANOVA)
12.2 Multiple Comparisons
12.3 Randomized Block Design
12.4 Two-Way ANOVA
Chapter 13. Inference in Regression
Case Study: How Fair Is Scoring in Scrabble?
13.1 Inference About the Slope of the Regression Line
13.2 Confidence Intervals and Prediction Intervals
13.3 Multiple Regression
Chapter 14. Nonparametric Statistics
Case Study: Has Median Gas Mileage Increased?
14.1 Introduction to Nonparametric Statistics
14.2 Sign Test
14.3 Wilcoxon Signed Rank Test for Matched-Pair Data
14.4 Wilcoxon Rank Sum Test for Two Independent Samples
14.5 Kruskal-Wallis Test
Answers to Exercises and Chapter Quizzes
Tables Appendix
Table A: Random numbers
Table B: Binomial distribution
Table C: Standard normal distribution
Table D: t-Distribution
Table E: Chi-square (?2 ) distribution
Table F: F-Distribution critical values
Table G: Critical values for correlation coefficient
Table H: Critical values for Tukey’s test
Notes and Data Sources
Index