Probability and statistics in engineering /
William W. Hines ... [et al.].
- 4th ed.
- Hoboken, NJ : Wiley, c2003.
- xii, 655 p. : ill. ; 27 cm.
Includes bibliographical references (p. 637-638) and index.
$a An Introduction to Probability.One-Dimensional Random Variables.Functions of One Random Variable and Expectation.Joint Probability Distributions.Some Important Discrete Distributions.Some Important Continuous Distributions.The Normal Distribution.Introduction to Statistics and Data Description.Random Samples and Sampling Distributions.Parameter Estimation.Tests of Hypotheses.Design and Analysis of Single-Factor Experiments: The Analysis of Variance.Design of Experiments with Several Factors.Simple Linear Regression and Correlation.Multiple Regression.Nonparametric Statistics.Statistical Quality Control and Reliability Engineering.Stochastic Processes and Queueing.Computer Simulation.Appendix.References.Answers to Selected Exercises.Index.
$a 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 professional 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 quality 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 include: new examples and applications that provide a real world perspective on how engineers use probability and statistics in professional practice; and, 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.