Probability and statistics
Author(s)
Bibliographic Information
Probability and statistics
Pearson Education, c2012
4th ed
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Note
Includes bibliographical references (p. 879-883) and index
Description and Table of Contents
Description
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.
Table of Contents
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
by "Nielsen BookData"
