Description
Mathematical Statistics: Old School covers three main areas: The mathematics needed as a basis for work in statistics; the mathematical methods for carrying out statistical inference; and the theoretical approaches for analyzing the efficacy of various procedures. The author, John Marden, developed this material over the last thirty years teaching various configurations of mathematical statistics and decision theory courses. It is intended as a graduate-level text. Topics include distribution theory, asymptotic convergence, frequentist and Bayesian inference (estimation, hypothesis testing, confidence intervals, model selection), exponential families, linear regression, likelihood methods, bootstrap and randomization methods, and statistical decision theory.
