0. Why Study Statistics The Science of Intuition The Statistical Inference Procedure Problem Solving With a Little Help From Technology 1. An Introduction to Statistics and Statistical Inference 1.1 Statistics Today 1.2 Populations, Samples, Probability, and Statistics 1.3 Experiments and Random Samples 2. Tables and Graphs for Summarizing Data 2.1 Types of Data 2.2 Bar Charts and Pie Charts 2.3 Stem-and-Leaf Plots 2.4 Frequency Distributions and Histograms 3. Numerical Summary Measures 3.1 Measures of Central Tendency 3.2 Measures of Variability 3.3 The Empirical Rule and Measures of Relative Standing 3.4 Five-Number Summary and Box Plots 4 Probability 4.1 Experiments, Sample Spaces, and Events 4.2 An Introduction to Probability 4.3 Counting Techniques 4.4 Conditional Probability 4.5 Independence 5. Random Variables and Discrete Probability Distributions 5.1 Random Variables 5.2 Probability Distributions for Discrete Random Variables 5.3 Mean, Variance, and Standard Deviation for a Discrete Random Variable 5.4 The Binomial Distribution 5.5 Other Discrete Distributions 6. Continuous Probability Distributions 6.1 Probability Distributions for Continuous Random Variables 6.2 The Normal Distribution 6.3 Checking the Normality Assumption 6.4 The Exponential Distribution 7. Sampling Distributions 7.1 Statistics, Parameters, and Sampling Distributions 7.2 The Sampling Distribution of the Sample Mean and the Central Limit Theorem 7.3 The Distribution of the Sample Proportion 8. Confidence Intervals Based on a Single Sample 8.1 Point Estimation 8.2 A Confidence Interval for a Population Mean when s Is Known 8.3 A Confidence Interval for a Population Mean when s Is Unknown 8.4 A Large-Sample Confidence Interval for a Population Proportion 8.5 A Confidence Interval for a Population Variance 9. Hypothesis Tests Based on a Single Sample 9.1 The Parts of a Hypothesis Test and Choosing the Alternative Hypothesis 9.2 Hypothesis Test Errors 9.3 Hypothesis Tests Concerning a Population Mean when s Is Known 9.4 p Values 9.5 Hypothesis Tests Concerning a Population Mean when s Is Unknown 9.6 Large-Sample Hypothesis Tests Concerning a Population Proportion 9.7 Hypothesis Tests Concerning a Population Variance or Standard Deviation 10. Confidence Intervals and Hypothesis Tests Based on Two Samples or Treatments 10.1 Comparing Two Population Means Using Independent Samples when Population Variances Are Known 10.2 Comparing Two Population Means Using Independent Samples from Normal Populations 10.3 Paired Data 10.4 Comparing Two Population Proportions Using Large Samples 10.5 Comparing Two Population Variances or Standard Deviations 11. The Analysis of Variance 11.1 One-Way ANOVA 11.2 Isolating Differences 11.3 Two-Way ANOVA 12. Correlation and Linear Regression 12.1 Simple Linear Regression 12.2 Hypothesis Tests and Correlation 12.3 Inferences Concerning the Mean Value and an Observed Value of Y for x 5 x* 12.4 Regression Diagnostics 12.5 Multiple Linear Regression 13. Categorical Data and Frequency Tables 13.1 Univariate Categorical Data, Goodness-of-Fit Tests 13.2 Bivariate Categorical Data, Tests for Homogeneity and Independence 14. Nonparametric Statistics 14.1 The Sign Test 14.2 The Signed-Rank Test 14.3 The Rank-Sum Test 14.4 The Kruskal–Wallis Test 14.5 The Runs Test 14.6 Spearman’s Rank Correlation Notes and Data Sources Tables Appendix Answers to Odd-Numbered Exercises Index Optional Online Sections Section 6.5 The Normal Approximation to the Binomial Distribution Section 12.6 The Polynomial and Qualitative Predictor Models Section 12.7 Model Selection Procedures