Probability and Statistics / Edition 4

by Morris H. DeGroot

Overview

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.

Product Details

ISBN-13:	2900321500464
Publisher:	Pearson
Publication date:	01/10/2011
Edition description:	New Edition
Pages:	912
Product dimensions:	8.20(w) x 10.00(h) x 1.40(d)

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