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# Introduction to Probability

• Hardback
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## Description

Introduction to Probability, Second Edition, discusses probability theory in a mathematically rigorous, yet accessible way. This one-semester basic probability textbook explains important concepts of probability while providing useful exercises and examples of real world applications for students to consider.

This edition demonstrates the applicability of probability to many human activities with examples and illustrations. After introducing fundamental probability concepts, the book proceeds to topics including conditional probability and independence; numerical characteristics of a random variable; special distributions; joint probability density function of two random variables and related quantities; joint moment generating function, covariance and correlation coefficient of two random variables; transformation of random variables; the Weak Law of Large Numbers; the Central Limit Theorem; and statistical inference. Each section provides relevant proofs, followed by exercises and useful hints. Answers to even-numbered exercises are given and detailed answers to all exercises are available to instructors on the book companion site.

This book will be of interest to upper level undergraduate students and graduate level students in statistics, mathematics, engineering, computer science, operations research, actuarial science, biological sciences, economics, physics, and some of the social sciences.

## Product details

• Hardback | 546 pages
• 195.58 x 236.22 x 25.4mm | 839.14g
• San Diego, United States
• English
• 2nd edition
• Illustrated; Illustrations, unspecified
• 0128000414
• 9780128000410

Preface
1. Some Motivating Examples
2. Some Fundamental Concepts
3. The Concept of Probability and Basic Results
4. Conditional Probability and Independence
5. Numerical Characteristics of a Random Variable
6. Some Special Distributions
7. Joint Probability Density Function of Two Random Variables and Related Quantities
8. Joint Moment Generating Function, Covariance and Correlation Coefficient of Two Random Variables
9. Some Generalizations to k Random Variables, and Three Multivariate Distributions
10. Independence of Random Variables and Some Applications
11. Transformation of Random Variables
12. Two Modes of Convergence, the Weak Law of Large Numbers, the Central Limit Theorem, and Further Results
13. An Overview of Statistical Inference
Appendix
Some Notation and Abbreviations
Index

## Review Text

"...a very traditional mathematics text on the topic of probability. Readers should be comfortable with multiple integrals and, in spots, a little linear algebra. The writing is clear and concise." -- MAA.org , August 18 2014

## Review quote

"...the first seven chapters can be used as one term undergraduate course in probability. I am satisfied with the topics covered in each chapter and the order in which they are presented. Numerous solved examples and exercises are provided in each chapter. They support concepts well, and they are of high quality. The examples and exercises are carefully selected and are even better than many texts currently available in the market...I would be happy to adopt this book."
-Subash Bagui Univ of West Florida

"I feel this book covers the topics better and in a more easy to understand way with the conversational tone. There are a lot more examples and I like that the exercises are not too technologically dependent. I would definitely adopt this for my Intro Probability course. The first eight chapters are a perfect fit."
-Pat Goeters Auburn University