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Chapter 4 covers discrete and continuous random variables, mathematical expectation, and Chebyshev's Inequality . Probability Theory: A Concise Course
Chapter 5 focuses on Bernoulli trials, the binomial and Poisson distributions, and the De Moivre-Laplace theorem . If you are looking to purchase or use
While rigorous, it requires no prior knowledge of measure theory , making it accessible to undergraduate students with a basic background in calculus. Critical Reception While rigorous, it requires no prior knowledge of
The final chapters (7–8) provide a detailed treatment of Markov chains (transition and limiting probabilities) and continuous Markov processes. Practical Features
The book is structured into eight chapters that guide the reader from elementary foundations to advanced stochastic processes: