This textbook introduces the mathematical concepts and methods that underlie statistics. The course is unified, in the sense that no prior knowledge of probability theory is assumed, being developed as needed. The book is committed to both a high level of mathematical seriousness and to an intimate connection with application. In its teaching style, the book is mathematically complete concrete constructive active. The text is aimed at the upper undergraduate or the beginning Masters program level. It assumes the usual two-year college mathematics sequence, including an introduction to multiple integrals, matrix algebra, and infinite series.

Inhalt

Getting Started.- Structural Models for Data.- Least Squares Methods.- Combinatorial Probability.- Other Probability Models.- Discrete Random Variables I: The Hypergeometric Process.- Discrete Random Variables II: The Bernoulli Process.- Random Vectors and Random Samples.- Maximum Likelihood Estimates for Discrete Models.- Continuous Random Variables I: The Gamma and Beta Families.- Continuous Random Variables II: Expectations and the Normal Family.- Continuous Random Vectors.- Sampling Statistics for the Linear Model.- Representing Distributions.