This text is designed for undergraduate mathematics students or graduate students in the sciences. Each chapter corresponds to a fifty-minute lecture. LECTURES IN ELEMENTARY PROBABILITY THEORY AND STOCHASTIC PROCESSES can be used in a prerequisite course for Statistics (for math majors) or Mathematical Modeling. The first eighteen chapters could be used in a one-quarter course, and the entire text is appropriate for a one-semester course.
1 Preliminaries
2 Sample Space and Events
3 Probability and Area
4 Probability Measures
5 Basic Rules of Probability Calculus
6 Sampling
7 Counting Subsets
8 Discrete Distributions
9 Conditional Probabilities
10 Independence and Bayes Theorem
11 The Principle of Maximum Likelihood
12 Random Variables
13 Distribution Functions
14 Continuous Random Variables
15 Expectation and Moments
16 Covariance and Correlation
17 The Law of Large Numbers
18 Moment Generating Functions
19 Multivariate Distributions
20 Bivariate Normal Distributions
21 Finite Markov Chains, Basic Concepts
22 Homogeneous Markov Chains
23 Random Walks
24 Poisson Processes
Solutions and Hints for Selected Problems
Glossary of Symbols
Index
Bibliography