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Probability and Statistics,9780321500465
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Probability and Statistics

by ;
Edition:
4th
ISBN13:

9780321500465

ISBN10:
0321500466
Format:
Hardcover
Pub. Date:
12/27/2010
Publisher(s):
Pearson
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Customer Reviews

Great textbook!  July 6, 2011
by


I can strongly recommend this textbook as a text for upper level courses in probability and statistics. It has great examples, and I learn better with those. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. It presents all classical statistical results, formally and intuitively. It is clear and presents the material with lots of accompanying intuitive explanations. This textbook arrived earlier than expected. The quality was great and the price was cheaper than I would have paid in a bookstore.






Probability and Statistics: 4 out of 5 stars based on 1 user reviews.

Summary

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.

Probability & Statistics, Fourth Edition, was written for a one- or two-semester probability and statistics course. This course is offered primarily at four-year institutions and taken mostly by sophomore and junior level students majoring in mathematics or statistics. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.

Features:

-Brief introductions in each technical section give readers a hint about what they are going to encounter, while summaries list the most important ideas.

-In addition to examples using current data, some elementary concepts of probability are illustrated by famous examples such as the birthday problem, the tennis tournament problem, the matching problem, and the collector's problem.

-Special features include sections on Markov chains, the gambler's ruin problem, and utility and preferences among gamblers. These topics are presented in an elementary fashion and can be omitted without loss of continuity.

-Optional sections of the book are indicated by an asterisk in the Table of Contents.

-Chapters 15 are devoted to probability and can serve as the text for a one-semester course on probability. Independence is now introduced after conditional probability.

-Chapters 610 are devoted to statistical inference. Both classical and Bayesian statistical methods are developed in an integrated presentation which will be useful to students when applying the concepts to the real world.

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



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