Probability and statistics
著者
書誌事項
Probability and statistics
Pearson Education, c2012
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
The revision of this well-respected text 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 assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.
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KEY TOPICS: 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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MARKET: For all readers interested in probability and statistics.
目次
1. Introduction to Probability
2. Conditional Probability
3. Random Variables and Distributions
4. Expectation
5. Special Distributions
6. Large Random Samples
7. Estimation
8. Sampling Distributions of Estimators
9. Testing Hypotheses
10. Categorical Data and Nonparametric Methods
11. Linear Statistical Models
12. Simulation
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