Books like Introduction to counting and probability by David Patrick

A comprehensive introductory text that explains probability theory with clear examples and challenging problem sets.

Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probability. Probability and Measure provides thorough coverage of probability, measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes. The Third Edition features an improved treatment of Brownian motion and the replacement of queuing theory with ergodic theory. Like the previous editions, this new edition will be well received by students of mathematics, statistics, economics, and a wide variety of disciplines that require a solid understanding of probability theory. --back cover

A foundational guide for undergraduate students that introduces elementary probability theory and stochastic processes, and demonstrates their application across engineering, computer science, management science, and the physical and social sciences.

The leading reference on probabilistic methods in combinatorics-now expanded and updated When it was first published in 1991, The Probabilistic Method became instantly the standard reference on one of the most powerful and widely used tools in combinatorics. Still without competition nearly a decade later, this new edition brings you up to speed on recent developments, while adding useful exercises and over 30% new material. It continues to emphasize the basic elements of the methodology, discussing in a remarkably clear and informal style both algorithmic and classical methods as well as modern applications. The Probabilistic Method, Second Edition begins with basic techniques that use expectation and variance, as well as the more recent martingales and correlation inequalities, then explores areas where probabilistic techniques proved successful, including discrepancy and random graphs as well as cutting-edge topics in theoretical computer science. A series of proofs, or "probabilistic lenses," are interspersed throughout the book, offering added insight into the application of the probabilistic approach. New and revised coverage includes: Several improved as well as new results A continuous approach to discrete probabilistic problems Talagrand's Inequality and other novel concentration results A discussion of the connection between discrepancy and VC-dimension Several combinatorial applications of the entropy function and its properties A new section on the life and work of Paul Erd's-the developer of the probabilistic method

Revised edition of DeGroot’s classic, blending classical and Bayesian statistics with new chapters on simulation—MCMC and Bootstrap—and enhanced residual analysis for linear models, all illustrated with real‑world data.

A book introducing mathematical concepts through a story about a wolf trying to find the pigs.