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Introduction to Probability Theory with Contemporary Applications
by Lester L. Helms
This introduction to probability theory transforms a highly abstract subject into a series of coherent concepts. Its extensive discussions and clear examples, written in plain language, expose students to the rules and methods of probability. Suitable for an introductory probability course, this volume requires abstract and conceptual thinking skills and a background in calculus.
Topics include classical probability, set theory, axioms, probability functions, random and independent random variables, expected values, and covariance and correlations. Additional subjects include stochastic processes, continuous random variables, expectation and conditional expectation, and continuous parameter Markov processes. Numerous exercises foster the development of problem-solving skills, and all problems feature step-by-step solutions
Table of Contents for Introduction to Probability Theory with Contemporary Applications
| Preface | | Errata | | 1. Classical Probability | | 2. Axioms of Probability | | 3. Random Variables | | 4. Expectation | | 5. Stochastic processes | | 6. Continous Random Variables | | 7. Expectation Revisited | | 8. Continous Parameter Markov Processes | | Solutions to Exercises | | Standard Normal Distribution Function | | Symbols | | Index |
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