This book provides an introduction to probability, stochastic processes, and statistics for students of computer science, electrical/computer engineering, reliability engineering and applied mathematics. It prepares the student for solving practical stochastic modelling problems, and for the more advanced courses on queuing or reliability theory. The text emphasizes on applications, illustrating each theoretical concept by solved examples relating to algorithm analysis or communication related problems.The prerequisites are a knowledge of calculus, a course on introduction to computer programming, and an understanding of computer organization. The book is also suitable for self-study by computer professionals and mathematicians interested in applications.

Introduction. Discrete Random Variables. Continuous Random Variables. Expectation. Conditional Distribution and Conditional Expectation. Stochastic Processes. Discrete-Parameter Markov Chains. Continuous-Parameter Markov Chains. Networks of Queues. Statistical Inference. Regression, Correlation, and Analysis of Variance. Appendices: A_Bibliography. B: Properties of Distributions. C_Statistical Tables. D_Laplace Transforms. E_Program Analysis.