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Mathematical Statistics with Applications

By Dennis Wackerly, William Mendenhall, Richard L. Scheaffer

7th Edition © 2008
Discipline:Statistics
Course:Intermediate/Advanced Statistics
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In their bestselling title MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. This updated edition now includes simulation activities with interactive applets, a complete R appendix, and an updated WebAssign product.

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About this product

In their bestselling title MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. This updated edition now includes simulation activities with interactive applets, a complete R appendix, and an updated WebAssign product.

WebAssign, the market-leading online homework and assessment courseware, includes over 1200 textbook exercises, featuring algorithmically-randomized values and automatically graded answers, is available to support MATHEMATICAL STATISTICS WITH APPLICATIONS. Ideal for homework, practice, or testing, WebAssign includes the fully-interactive eTextbook, complete with new R appendix.

The authors efficiently use mathematics as a necessary tool to promote a firm understanding of statistical techniques.

Stressing connectivity, the authors explain not only how major topics play a role in statistical inference but also how the topics are related to one another. These integrating discussions appear most frequently in chapter introductions and conclusions.

This text takes a practical approach in both the exercises throughout and the useful topics in statistical methodology covered in the last five chapters.

Table of contents

Chapters

Cover Page
Title Page
Copyright Page
Preface
Acknowledgments
Note to the Student
Chapter 1. What Is Statistics?*Preview this chapter
Chapter 2. Probability
Chapter 3. Discrete Random Variables and Their Probability Distributions
Chapter 4. Continuous Variables and Their Probability Distributions
Chapter 5. Multivariate Probability Distributions
Chapter 6. Functions of Random Variables
Chapter 7. Sampling Distributions and the Central Limit Theorem
Chapter 8. Estimation
Chapter 9. Properties of Point Estimators and Methods of Estimation
Chapter 10. Hypothesis Testing
Chapter 11. Linear Models and Estimation by Least Squares
Chapter 12. Considerations in Designing Experiments
Chapter 13. The Analysis of Variance
Chapter 14. Analysis of Categorical Data
Chapter 15. Nonparametric Statistics
Chapter 16. Introduction to Bayesian Methods for Inference
Appendix 1. Matrices and Other Useful Mathematical Results
Appendix 2. Common Probability Distributions, Means, Variances, and Moment-Generating Functions
Appendix 3. Tables
Appendix R
Show more

Chapter 1. What Is Statistics?Preview this chapter ↗

1.1
Introduction
Preview this section ↗
Exercises ↗
1.2
Characterizing a Set of Measurements: Graphical Methods
Preview this section ↗
Exercises ↗
1.3
Characterizing a Set of Measurements: Numerical Methods
Preview this section ↗
Characterizing a Set of Measurements Using R ↗
Exercises ↗
1.4
How Inferences Are Made ↗
1.5
Theory and Reality ↗
1.6
Summary ↗
References and Further Readings ↗
Supplementary Exercises ↗

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