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.