Probability and Statistics

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Addison-Wesley, 2002 - Mathematics - 816 pages
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The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a new chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), expanded coverage of residual analysis in linear models, and more examples using real data. Probability & Statisticswas written for a one or two semester probability and statistics course offered primarily at four-year institutions and taken mostly by sophomore and junior level students, majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

 

Introduction to Probability; Conditional Probability; Random Variables and Distribution; Expectation; Special Distributions; Estimation; Sampling Distributions of Estimators; Testing Hypotheses; Categorical Data and Nonparametric Methods; Linear Statistical Models; Simulation

 

For all readers interested in probability and statistics.

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Review: Probability and Statistics

User Review  - Ben - Goodreads

Best book I have read on both subjects. Just the right amount of math for someone that knows calc (doesn't need a hand held), but isn't a mathematicians (very simple proofs). Read full review

Contents

Introduction to Probability
1
Conditional Probability
49
Random Variables and Distributions
97
Copyright

11 other sections not shown

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About the author (2002)

Morris DeGroot (now deceased) was a great statistician and gentleman of the 20th Century. Says friend and coworker Joseph B. ("Jay") Kadane of DeGroot in the Foreword, "He was an institutional builder, as founder of the Statistics Department at Carnegie Mellon University and as first Executive Editor of Statistical Science. He was a wonderful colleague and friend, always ready for a chat about principles, a research problem, a departmental problem, a reference, or personal advice.

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