Introduction to probability for computing
- Cambridge : Cambridge University Press, 2024
- xx, 550 p. ; ill. (some col.), 25 cm.
Includes bibliographical references and index.
A rigorous, yet accessible, textbook for computer science students learning probability. It covers topics of interest to computer scientists, including randomized algorithms, simulation, statistical inference, and stochastic systems modeling. Replete with engaging real-world examples, exercises, and full-color illustrations.
9781009309073 hbk.
Stationary distribution Z-transform Randomized algorithms Poisson process Pareto distribution MAP estimaotr MAP estimator Laplace transform Fermat Primality Test Exponential distribution Discrete random variables Continuous random variables Confidence interval Chernoff bound