This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.
Presented in full color and written in an accessible way, the text provides a comprehensive and well-balanced introduction to probability
Pedagogical features include numerous examples to illustrate concepts and theory, over 600 exercises of varying levels, and separate 'Finer Points' sections for technical details
Instructor's manual available online with detailed solutions to selected problems and further guidance for using the book in a course
1. Experiments with random outcomes
2. Conditional probability and independence
3. Random variables
4. Approximations of the binomial distribution
5. Transforms and transformations
6. Joint distribution of random variables
7. Sums and symmetry
8. Expectation and variance in the multivariate setting
9. Tail bounds and limit theorems
10. Conditional distribution
Appendix A. Things to know from calculus
Appendix B. Set notation and operations
Appendix C. Counting
Appendix D. Sums, products and series
Appendix E. Table of values for F(x)
Appendix F. Table of common probability distributions.
