Probability and Statistical Inference, Second Edition
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Summary
This text presents the rigorous theory of probability and statistical inference using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. Beginning with the basic ideas and techniques of probability theory and progressing to more rigorous topics, the author covers all of the topics typically addressed in a two-semester graduate or upper-level undergraduate course in probability and statistical inference, including hypothesis testing, Bayesian analysis, and sample-size determination. He reinforces important ideas and special techniques with drills and boxed summaries.
Table of Contents
Notions of probability; expectations of functions of random variables; multivariate random variables; transformations and sampling distributions; notions of stochastic convergence; sufficiency, completeness and ancillarity; point estimation; tests of hypotheses; confidence interval estimation; Bayesian methods; likelihood ratio and other tests; large-sample inference; sample size determination - two-stage procedures. Appendices: abbreviations and notation; celebration of statistics - selected biographical notes; selected statistical tables.
Editorial Reviews
Praise for the First Edition
...the book contains unique features throughout. Examples are the moment problem, which is clarified through a nice example, the role of the probability generating functions, and the central limit theorem for the sample variance. Techniques and concepts are typically illustrated through a series of examples. Within a box is routinely summarized what it is that has been accomplished or where to go from that point. At the end of each chapter a long list of exercises is arranged according the sections.
—Zentralblatt MATH, 2000
…a marvelous book for students.
—Statistical Papers
…a handy reference as well as a good textbook.
—ISI Short Book Reviews
