Probability Theory: A Concise Course May 2026

The final chapters (7–8) provide a detailed treatment of Markov chains (transition and limiting probabilities) and continuous Markov processes. Practical Features

Reviewers often describe it as an excellent "pocket reference" or review tool rather than a comprehensive first-time textbook. Some readers note that its "concise" nature means certain topics, like , are not explicitly covered, and the transition to later, more technical chapters can be steep for beginners. Probability Theory: A Concise Course

While rigorous, it requires no prior knowledge of measure theory , making it accessible to undergraduate students with a basic background in calculus. Critical Reception The final chapters (7–8) provide a detailed treatment

Includes 150 problems with many hints and answers provided, making it suitable for self-study. While rigorous, it requires no prior knowledge of

Chapters 1–3 establish basic concepts such as relative frequency, combinatorial analysis, sample spaces, the addition law, and statistical independence.

Chapter 5 focuses on Bernoulli trials, the binomial and Poisson distributions, and the De Moivre-Laplace theorem .