Focusing on how statistical tools are integrated into the engineering problem–solving process, this book provides modern coverage of engineering statistics. It presents a wide range of techniques and methods that engineers will find useful in professional practice. All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, building regression models, designing and analyzing engineering experiments, and more.

About the Author

Douglas C. Montgomery , Regents Professor of Industrial Engineering and Statistics at Arizona State University, received his B.S., M.S., and Ph.D. degrees in engineering from Virginia Polytechnic Institute, the editor of Quality and Reliability Engineering International and a former editor of the Journal of Quality Technology . George C. Runger, Ph.D., is a Professor in the department of Industrial Engineering at Arizona State University. His research is on data mining, real–time monitoring and control, and other data–analysis methods with a focus on large, complex, multivariate data streams. His work is funded by grants from the National Science Foundation and corporations. In addition to academic work, he was a senior engineer at IBM. He holds degrees in industrial engineering and statistics. Norma Faris Hubele, Professor of Engineering and Statistics at Arizona State University, and Director of Strategic Initiatives for the Ira A. Fulton School of Engineering, has taught and done research at the University level and with industry for over 20 years. Her cutting edge educational research has been supported by the National Science Foundation and is reflected in this textbook.

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