Introductory Statistics, 10th Edition By Neil A. Weiss eBook [PDF]

eBook for Introductory Statistics, 10th Edition By Neil A. Weiss Get all 16 Chapters eBook PDF. Table of Contents PART I: Introduction 1. The Nature of Statistics Case Study: Top Films of All Time 1.1 Statistics Basics 1.2 Simple Random Sampling 1.3 Other Sampling Designs∗ 1.4 Experimental Designs∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography PART II: Descriptive Statistics 2. Organizing Data Case Study: World’s Richest People 2.1 Variables and Data 2.2 Organizing Qualitative Data 2.3 Organizing Quantitative Data 2.4 Distribution Shapes 2.5 Misleading Graphs∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 3. Descriptive Measures Case Study: The Beatles’ Song Length 3.1 Measures of Center 3.2 Measures of Variation 3.3 Chebyshev’s Rule and the Empirical Rule∗ 3.4 The Five-Number Summary; Boxplots 3.5 Descriptive Measures for Populations; Use of Samples Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography PART III: Probability, Random Variables, and Sampling Distributions 4. Probability Concepts Case Study: Texas Hold’em 4.1 Probability Basics 4.2 Events 4.3 Some Rules of Probability 4.4 Contingency Tables; Joint and Marginal Probabilities∗ 4.5 Conditional Probability∗ 4.6 The Multiplication Rule; Independence∗ 4.7 Bayes’s Rule∗ 4.8 Counting Rules∗ Chapter in Review 218 Review Problems Focusing on Data Analysis Case Study Discussion Biography 5. Discrete Random Variables∗ Case Study: Aces Wild on the Sixth at Oak Hill 5.1 Discrete Random Variables and Probability Distributions∗ 5.2 The Mean and Standard Deviation of a Discrete Random Variable∗ 5.3 The Binomial Distribution∗ 5.4 The Poisson Distribution∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 6. The Normal Distribution Case Study: Chest Sizes of Scottish Militiamen 6.1 Introducing Normally Distributed Variables 6.2 Areas under the Standard Normal Curve 6.3 Working with Normally Distributed Variables 6.4 Assessing Normality; Normal Probability Plots 6.5 Normal Approximation to the Binomial Distribution∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 7. The Sampling Distribution of the Sample Mean Case Study: The Chesapeake and Ohio Freight Study 7.1 Sampling Error; the Need for Sampling Distributions 7.2 The Mean and Standard Deviation of the Sample Mean 7.3 The Sampling Distribution of the Sample Mean Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography PART IV: Inferential Statistics 8. Confidence Intervals for One Population Mean Case Study: Bank Robberies: A Statistical Analysis 8.1 Estimating a Population Mean 8.2 Confidence Intervals for One Population Mean When σ Is Known 8.3 Confidence Intervals for One Population Mean When σ Is Unknown Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 9. Hypothesis Tests for One Population Mean Case Study: Gender and Sense of Direction 9.1 The Nature of Hypothesis Testing 9.2 Critical-Value Approach to Hypothesis Testing 9.3 P-Value Approach to Hypothesis Testing 9.4 Hypothesis Tests for One Population Mean When σ Is Known 9.5 Hypothesis Tests for One Population Mean When σ Is Unknown 9.6 The Wilcoxon Signed-Rank Test∗ 9.7 Type II Error Probabilities; Power∗ 9.8 Which Procedure Should Be Used?∗∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 10. Inferences for Two Population Means Case Study: Dexamethasone Therapy and IQ 10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal 10.4 The Mann—Whitney Test∗ 10.5 Inferences for Two Population Means, Using Paired Samples 10.6 The Paired Wilcoxon Signed-Rank Test∗ 10.7 Which Procedure Should Be Used?∗∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 11. Inferences for Population Standard Deviations∗ Case Study: Speaker Woofer Driver Manufacturing 11.1 Inferences for One Population Standard Deviation∗ 11.2 Inferences for Two Population Standard Deviations, Using Independent Samples∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 12. Inferences for Population Proportions Case Study: Arrested Youths 12.1 Confidence Intervals for One Population Proportion 12.2 Hypothesis Tests for One Population Proportion 12.3 Inferences for Two Population Proportions Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 13. Chi-Square Procedures Case Study: Eye and Hair Color 13.1 The Chi-Square Distribution 13.2 Chi-Square Goodness-of-Fit Test 13.3 Contingency Tables; Association 13.4 Chi-Square Independence Test 13.5 Chi-Square Homogeneity Test Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography PART V: Regression, Correlation, and ANOVA 14. Descriptive Methods in Regression and Correlation Case Study: Healthcare: Spending and Outcomes 14.1 Linear Equations with One Independent Variable 14.2 The Regression Equation 14.3 The Coefficient of Determination 14.4 Linear Correlation Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 15. Inferential Methods in Regression and Correlation Case Study: Shoe Size and Height 15.1 The Regression Model; Analysis of Residuals 15.2 Inferences for the Slope of the Population Regression Line 15.3 Estimation and Prediction 15.4 Inferences in Correlation 15.5 Testing for Normality∗∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography 16. Analysis of Variance (ANOVA) Case Study: Self-Perception and Physical Activity 16.1 The F-Distribution 16.2 One-Way ANOVA: The Logic 16.3 One-Way ANOVA: The Procedure 16.4 Multiple Comparisons∗ 16.5 The Kruskal—Wallis Test∗ Chapter in Review Review Problems Focusing on Data Analysis Case Study Discussion Biography PART VI: Multiple Regression and Model Building; Experimental Design and ANOVA∗∗ MODULE A: Multiple Regression Analysis Case Study: Automobile Insurance Rates A.1 The Multiple Linear Regression Model A.2 Estimation of the Regression Parameters A.3 Inferences Concerning the Utility of the Regression Model A.4 Inferences Concerning the Utility of Particular Predictor Variables A.5 Confidence Intervals for Mean Response; Prediction Intervals for Response A.6 Checking Model Assumptions and Residual Analysis Module in Review Review Problems Focusing on Data Analysis Case Study Discussion Answers to Selected Exercises Index MODULE B: Model Building in Regression Case Study: Automobile Insurance Rates–Revisited B.1 Transformations to Remedy Model Violations B.2 Polynomial Regression Model B.3 Qualitative Predictor B.4 Multicollinearity B.5 Model Selection: Stepwise Regression B.6 Model Selection: All-Subsets Regression B.7 Pitfalls and Warnings Module in Review Review Problems Focusing on Data Analysis Case Study Discussion Answers to Selected Exercises Index MODULE C: Design of Experiments and Analysis of Variance Case Study: Dental Hygiene: Which Toothbrush? C.1 Factorial Designs C.2 Two-Way ANOVA: The Logic C.3 Two-Way ANOVA: The Procedure C.4 Two-Way ANOVA: Multiple Comparisons C.5 Randomized Block Designs C.6 Randomized Block ANOVA: The Logic C.7 Randomized Block ANOVA: The Procedure C.8 Randomized Block ANOVA: Multiple Comparisons C.9 Friedman’s Nonparametric Test for the Randomized Block Design Module in Review Review Problems Focusing on Data Analysis Case Study Discussion Answers to Selected Exercises Index Appendix A: Statistical Tables Appendix B: Answers to Selected Exercises Index