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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.
Chapter 2. One-Dimensional Random Variables.
Chapter 3. Functions of One Random Variable and Expectation.
Chapter 4. Joint Probability Distributions.
Chapter 5. Some Important Discrete Distributions.
Chapter 6. Some Important Continuous Distributions.
Chapter 7. The Normal Distribution.
Chapter 8. Introduction to Statistics and Data Description.
Chapter 9. Random Samples and Sampling Distributions.
Chapter 10. Parameter Estimation.
Chapter 11. Tests of Hypotheses.
Chapter 12. Design and Analysis of Single-Factor Experiments: The Analysis of Variance.
Chapter 13. Design of Experiments with Several Factors.
Chapter 14. Simple Linear Regression and Correlation.
Chapter 15. Multiple Regression.
Chapter 16. Nonparametric Statistics.
Chapter 17. Statistical Quality Control and Reliability Engineering.
Chapter 18. Stochastic Processes and Queueing.
Chapter 19. Computer Simulation.
Answers to Selected Exercises.