Probability and Statistics (4th Edition)

The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. This fourth edition has contemporary statistical methods integrated into the text. Other new features include a chapter on simulation, a section on Gibbs sampling, what you should know boxes and remarks to highlight difficult concepts