Description
Roussas's Introduction to Probability features exceptionally clear explanations of the mathematics of probability theory and explores its diverse applications through numerous interesting and motivational examples. It provides a thorough introduction to the subject for professionals and advanced students taking their first course in probability. The content is based on the introductory chapters of Roussas's book, An Intoduction to Probability and Statistical Inference, with additional chapters and revisions.
Readership
This one-semester basic probability textbook is written for students in mathematics, physics, engineering, statistics, actuarial science, operations research, and computer science with a background in elementary calculus taking upper level or graduate level introduction to probability courses.
Introduction to Probability, 1st Edition
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
Tables
Some Notation and Abbreviations
Answers to the Even-numbered Exercises
