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Designed for post-calculus undergraduate probability courses.
This text thoroughly covers the concepts of probability, random variables, distributions, expected value, and the ramifications and applications of limit theorems. The text focuses on theory motivated by applications, especially in statistical inference and stochastic processes. Numerous examples and exercises accompany the text's accessible expository style. The author carefully builds student understanding by progressively reinforcing concepts and moving from concrete fundamentals to more abstract material. The topics are arranged so key concepts are introduced early. Standard distributions are introduced in the first chapter and are referred to throughout the book. The author's evenhanded treatment of this subject avoids overwhelming students in the first one or two chapters.
Table of contents
1. Probability Models: Definitions and Examples.
2. The Algebra of Events and Probabilities.
3. Probability Distributions.
4. Expected Values.
5. Functions of Random Variables.
6. Normal Distributions and the Central Limit Theorem.
7. Some Important Distributions on the Nonnegative Integers.
8. Some Important Absolutely Continuous Distributions.
9. Conditioning and Baye's Theorem for Random Variables.
Suggested Reading and Bibliography.
Appendix A. Review of Some Topics From Calculus and Set Theory.
Appendix B. Summaries of Commonly-used Distributions.
Appendix C. A Table of the Standard Normal Cumulative Distribution Function.
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Published by Pearson (November 3rd 1993) - Copyright © 1994