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Full Description
An introduction to the field of statistics, which assumes some prior knowledge of mathematics, but not of probability or statistics. The text is organized into three parts: part one covers the core of the probability topic; part two covers the foundations of statistical inference; and part three covers special topics. This edition has been updated to include problems, examples and figures. Its features include: over 350 worked examples; coverage of minimal sufficient statistics; and presentation of the theory of confidence intervals.
Contents
Probability; Random Variables and Their Probability Distributions; Moments and Generating Functions; Multiple Random Variables; Some Special Distributions; Limit Theorems; Sample Moments and Their Distributions; Parametric Point Estimation; Neyman-Pearson Theory of Testing of Hypotheses; Some Further Results on Hypotheses Testing; Confidence Estimation; The General Linear Hypothesis; Nonparametric Statistical Inference.