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Statistically significant

Introductory Statistics MyLab Revision, 10th Edition is ideal for introductory statistics classes that emphasize statistical reasoning and critical thinking. Weiss’s meticulous and comprehensive coverage includes careful, detailed explanations to ease the learning process. With more than 1,000 data sets and over 3,000 exercises, this text takes a data-driven approach that encourages students to apply their knowledge and develop statistical understanding.

Weiss offers a parallel presentation of critical-value and P-value approaches to hypothesis testing. This unique design allows the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two.

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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 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

Photo Credits

∗Indicates optional material.

∗∗Indicates optional material on the WeissStats site.