Probability and statistics
著者
書誌事項
Probability and statistics
(Pearson modern classic)
Pearson, c2019
4th ed
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注記
Includes bibliographical references (p. 879-883) and index
内容説明・目次
内容説明
Probability & Statistics, 4th Edition is a revision of the well-respected text. It presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.
This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price.
目次
Brief Contents
Introduction to Probability
Conditional Probability
Random Variables and Distributions
Expectation
Special Distributions
Large Random Samples
Estimation
Sampling Distributions of Estimators
Testing Hypotheses
Categorical Data and Nonparametric Methods
Linear Statistical Models
Simulation
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