Probability and Statistics in Engineering and Management Science

The Third Edition of this engineering management text retains the pedagogical strengths that made the previous editions so popular, including the use of real data in the examples. There is a new chapter on nonparametric statistics, a new section on p-values in hypothetical testing, new coverage of residual analysis, and more material on quality control and experiment design. Provides chapter introductions, including interesting historical information, and there are more illustrations and many new problems. Contains enough material for a two-term course and the broad coverage permits instructors flexibility in choice of topics.

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.