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The text gives students a strong theoretical foundation balanced with numerous applied and realistic exercises and examples. For flexibility in course contents, advanced or optional topics such as extreme-value distributions, regression and linear models, and reliability and survival distributions are included. This edition has been revised to include more theoretical discussion to provide a solid grounding in theory while giving students an idea of how the subject appliues to the real world.
The text has also been revised to allow for an earlier development of properties of random variables and their distributions. Special probability distributions are placed separately in Chapter 3. Synopsis This book focuses on developing the skills to build probability stochastic models. Lee J. Bain and Max Engelhardt focus on the mathematical development of the subject, with examples and exercises oriented toward applications.
Key features include solid grounding in theory with clear demonstrations of real-world applications, and early development of the properties of random variables and their distributions.
Table of Contents 1. Probability 2. Random Variables and Their Distributions 3. Special Probability Distributions 4. Joint Distributions 5. Properties of Random Variables 6. Functions of Random Variables 7. Limiting Distributions 8. Statistics and Sampling Distributions 9. Point Estimation Sufficiency and Completeness Interval Estimation Tests of Hypotheses Contingency Tables and Goodness-of-Fit Nonparametric Methods Regression and Linear Models Optional
INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS BAIN ENGELHARDT PDF
Introduction to Probability & Mathematical Statistics