Introductory Statistics, MyLab Revision, Global Edition

About our author The late Neil A. Weiss received his Ph.D. from UCLA and subsequently accepted an assistant professor position at Arizona State University (ASU), where he was ultimately promoted to the rank of full professor. Dr. Weiss taught statistics, probability, and mathematics, from the freshman level to the advanced graduate level, for more than 30 years.In recognition of his excellence in teaching, Dr. Weiss received the Dean's Quality Teaching Award from the ASU College of Liberal Arts and Sciences. He also was runner-up twice for the Charles Wexler Teaching Award in the ASU School of Mathematical and Statistical Sciences. Dr. Weiss's comprehensive knowledge and experience ensure that his texts are mathematically and statistically accurate, as well as pedagogically sound.In addition to his numerous research publications, Dr. Weiss was the author of A Course in Probability (Addison-Wesley, 2006). He also authored or coauthored books in finite mathematics, statistics and real analysis. His texts, well known for their precision, readability and pedagogical excellence, are used worldwide.Dr. Weiss was a pioneer of the integration of statistical software into textbooks and the classroom, first providing such integration in the book Introductory Statistics (AddisonWesley,1982). Since this first publication, Neil Weiss's work continues to inspire future statisticians and current students of statistics alike.

• * Indicates optional material.** Indicates optional material on the WeissStats site.PART I: INTRODUCTION 1. The Nature of Statistics Case Study: Top Films of All Time1.1 Statistics Basics1.2 Simple Random Sampling1.3 Other Sampling Designs*1.4 Experimental Designs*Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography PART II: DESCRIPTIVE STATISTICS 2. Organizing Data Case Study: World's Richest People2.1 Variables and Data2.2 Organizing Qualitative Data2.3 Organizing Quantitative Data2.4 Distribution Shapes2.5 Misleading Graphs*Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 3. Descriptive Measures Case Study: The Beatles' Song Length3.1 Measures of Center3.2 Measures of Variation3.3 Chebyshev's Rule and the Empirical Rule*3.4 The Five-Number Summary; Boxplots3.5 Descriptive Measures for Populations; Use of SamplesChapter in ReviewReview ProblemsFocusing on DataAnalysisCase Study DiscussionBiography PART III: PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS 4. Probability Concepts Case Study: Texas Hold'em4.1 Probability Basics4.2 Events4.3 Some Rules of Probability4.4 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 ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 5. Discrete Random Variables* Case Study: Aces Wild on the Sixth at Oak Hill5.1 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 ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 6. The Normal Distribution Case Study: Chest Sizes of Scottish Militiamen6.1 Introducing Normally Distributed Variables6.2 Areas under the Standard Normal Curve6.3 Working with Normally Distributed Variables6.4 Assessing Normality; Normal Probability Plots6.5 Normal Approximation to the Binomial Distribution*Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 7. The Sampling Distribution of the Sample Mean Case Study: The Chesapeake and Ohio Freight Study7.1 Sampling Error; the Need for Sampling Distributions7.2 The Mean and Standard Deviation of the Sample Mean7.3 The Sampling Distribution of the Sample MeanChapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography PART IV: INFERENTIAL STATISTICS 8. Confidence Intervals for One Population Mean Case Study: Bank Robberies: A Statistical Analysis8.1 Estimating a Population Mean8.2 Confidence Intervals for One Population Mean When σ Is Known8.3 Confidence Intervals for One Population Mean When σ Is UnknownChapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 9. Hypothesis Tests for One Population Mean Case Study: Gender and Sense of Direction9.1 The Nature of Hypothesis Testing9.2 Critical-Value Approach to Hypothesis Testing9.3 P-Value Approach to Hypothesis Testing9.4 Hypothesis Tests for One Population Mean When σ Is Known9.5 Hypothesis Tests for One Population Mean When σ Is Unknown9.6 The Wilcoxon Signed-Rank Test*9.7 Type II Error Probabilities; Power*9.8 Which Procedure Should Be Used?**Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 10. Inferences for Two Population Means Case Study: Dexamethasone Therapy and IQ10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal10.4 The Mann - Whitney Test*10.5 Inferences for Two Population Means, Using Paired Samples10.6 The Paired Wilcoxon Signed-Rank Test*10.7 Which Procedure Should Be Used?**Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 11. Inferences for Population Standard Deviations* Case Study: Speaker Woofer Driver Manufacturing11.1 Inferences for One Population Standard Deviation*11.2 Inferences for Two Population Standard Deviations, Using Independent Samples*Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 12. Inferences for Population Proportions Case Study: Arrested Youths12.1 Confidence Intervals for One Population Proportion12.2 Hypothesis Tests for One Population Proportion12.3 Inferences for Two Population ProportionsChapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 13. Chi-Square Procedures Case Study: Eye and Hair Color13.1 The Chi-Square Distribution13.2 Chi-Square Goodness-of-Fit Test13.3 Contingency Tables; Association13.4 Chi-Square Independence Test13.5 Chi-Square Homogeneity TestChapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography PART V: REGRESSION, CORRELATION, AND ANOVA 14. Descriptive Methods in Regression and Correlation Case Study: Healthcare: Spending and Outcomes14.1 Linear Equations with One Independent Variable14.2 The Regression Equation14.3 The Coefficient of Determination14.4 Linear CorrelationChapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 15. Inferential Methods in Regression and Correlation Case Study: Shoe Size and Height15.1 The Regression Model; Analysis of Residuals15.2 Inferences for the Slope of the Population Regression Line15.3 Estimation and Prediction15.4 Inferences in Correlation15.5 Testing for Normality**Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography 16. Analysis of Variance (ANOVA) Case Study: Self-Perception and Physical Activity16.1 The F-Distribution16.2 One-Way ANOVA: The Logic16.3 One-Way ANOVA: The Procedure16.4 Multiple Comparisons*16.5 The Kruskal - Wallis Test*Chapter in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionBiography PART VI: MULTIPLE REGRESSION AND MODEL BUILDING; EXPERIMENTAL DESIGN AND ANOVA** MODULE A: Multiple Regression Analysis Case Study: Automobile Insurance RatesA.1 The Multiple Linear Regression ModelA.2 Estimation of the Regression ParametersA.3 Inferences Concerning the Utility of the Regression ModelA.4 Inferences Concerning the Utility of Particular Predictor VariablesA.5 Confidence Intervals for Mean Response; Prediction Intervals for ResponseA.6 Checking Model Assumptions and Residual AnalysisModule in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionAnswers to Selected ExercisesIndex MODULE B: Model Building in Regression Case Study: Automobile Insurance Rates RevisitedB.1 Transformations to Remedy Model ViolationsB.2 Polynomial Regression ModelB.3 Qualitative PredictorB.4 MulticollinearityB.5 Model Selection: Stepwise RegressionB.6 Model Selection: All-Subsets RegressionB.7 Pitfalls and WarningsModule in ReviewReview ProblemsFocusing on Data AnalysisCase Study DiscussionAnswers to Selected ExercisesIndex MODULE C: Design of Experiments and Analysis of Variance Case Study: Dental Hygiene: Which Toothbrush?C.1 Factorial DesignsC.2 Two-Way ANOVA: The LogicC.3 Two-Way ANOVA: The ProcedureC.4 Two-Way ANOVA: Multiple ComparisonsC.5 Randomized Block DesignsC.6 Randomized Block ANOVA: The LogicC.7 Randomized Block ANOVA: The ProcedureC.8 Randomized Block ANOVA: Multiple ComparisonsC.9 Friedman's Nonparametric Test for the Randomized Block DesignModule in ReviewReview ProblemsFocusing on Data AnalysisCase Study Discussion Answers to Selected Exercises Index Appendices A: Statistical TablesB: Answers to Selected ExercisesIndex Photo Credits * Indicates optional material.** Indicates optional material on the WeissStats site.