Introduction -- Preliminaries -- Some common probability distributions -- Distributions related to the Gaussian -- Sampling -- Distributions of sample statistics -- Bayes' theorem and maximum likelihood -- Confidence intervals -- Hypothesis testing -- The theory of maximum likelihood estimators -- Least squares fitting for linear models -- Hypothesis testing in the linear model -- Rank correlation coefficients -- Tests of fit -- Robust tests for means
Summary
Aimed at readers without a specialist scientific background, this monograph describes the theory underlying classical statistical methods. Readers with some familiarity of the standard tests will learn more about their strengths, weaknesses and domains of applicability
Bibliography
Includes bibliographical references (p. 130-131) and indexes
Notes
Description based on print version record and CIP data provided by publisher; resource not viewed
