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Contents

*Introductory Statistics 10th Edition Weiss eBook Details*

*Introductory Statistics 10th Edition Weiss eBook Details*

: Introductory Statistics, 10th Edition**Book Name**: Neil A. Weiss**Author**: 9780321989178**ISBN**:**Published***2016*:**Pages****File Format**: 11 MB**File Size**

## Weiss Introductory Statistics 10th Edition PDF Book Description

*For one- or two-semester courses in statistics.*

**Statistically Significant**

Weiss’s ** Introductory Statistics, Tenth Edition,** is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. Comprehensive in its coverage, Weiss’s meticulous style offers 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.

This text contains 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.

## Weiss Introductory Statistics 10th Edition PDF

See Also:Mann Introductory Statistics 9th Edition PDF eBook

## Introductory Statistics Neil Weiss 10th Edition PDF Book 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

Photo Credits

*About the Author(s)*

*About the Author(s)*

**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 has 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 has also been 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 ensures that his texts are mathematically and statistically accurate, as well as pedagogically sound.

In addition to his numerous research publications, Dr. Weiss is the author of *A Course in Probability *(Addison-Wesley, 2006). He has also authored or coauthored books in finite mathematics, statistics, and real analysis, and is currently working on a new book on applied regression analysis and the analysis of variance. His texts–well known for their precision, readability, and pedagogical excellence–are used worldwide.

Dr. Weiss is a pioneer of the integration of statistical software into textbooks and the classroom, first providing such integration in the book *Introductory Statistics *(Addison-Wesley, 1982). He and Pearson Education continue that pioneering spirit to this day.

In his spare time, Dr. Weiss enjoys walking, studying and practicing meditation, and playing hold ’em poker. He is married and has two sons.

See Also:

Mann Introductory Statistics 9th Edition PDF eBook

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