Title: Probability and Statistics in Engineering and Management Science, 3rd Edition
Publisher: Wiley
Publication Date: 1990
Language: English
ISBN 10: 0471600903
ISBN 13: 9780471600909
Binding: Hardcover
Edition: 3rd Edition
Condition: Fair
Dust Jacket Condition: No Jacket
Weight: 2.4 pounds

About this title

Synopsis

Providing an introduction to probability and statistics, this text covers statistical quality control and reliability, topics that other books often leave out. Emphasizing quality and essential material for all engineers, it features chapters on decision theory and stochastic models as well as a discussion of computer programs for multiple regression analysis giving a broader range of subject matter. Also incorporated are examples of real data allowing students and instructors to appreciate the reality and practicality of real data as opposed to artificially manipulated data.

From the Back Cover

Now with even more examples with real data, real–world applications, and computer exercise, the Fourth Edition of this accessible text prepares you for situations you′re likely to encounter as a professionakl engineer.

Together with new co–authors David Goldsman and Connie Borror, William Hines and Douglas Montgomery have refined their highly effective pedagogical framework to make their text even more user friendly. This Fourth Edition also features a new chapter on statistical methods for computer situation, as well exceptionally clear statistical coverage, expanded discussions of quiality control, experimental design, and different types of interval estimation, and coverage of such special topics as nonparametric statistics, p–values in hypothetical testing, and residual analysis.

Highlights of the Fourth Edition:

∗ New examples and applications provide a real–world perspective on how engineers use probability and statistics in professional practice.
∗ Over 600 exercises, including many new computation problems, provide opportunities for hands–on learning.
∗ An entirely new chapter on statistical methods for computer simulation methods covers Monte Carlo experimentation, random number and variate generation, and simulation output data analysis.
∗ New chapter organization starts with probability theory and progresses through random variables, discrete and continuous distributions, and normal distribution, before introducing statistics and data description techniques.
∗ Each chapter starts with an introduction that describes the importance of the topic and features interesting historical information related to the topic.
∗ End–of–chapter summaries reinforce the main topics and goals of the chapter.

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