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Engineering Statistics
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Engineering Statistics
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?
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Description
Montgomery, Runger, and Hubele's Engineering Statistics, 5th Edition provides modern coverage of engineering statistics by focusing on how statistical tools are integrated into the engineering problem-solving process. All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, statistical tests and confidence intervals for one and two samples, building regression models, designing and analysing engineering experiments, and statistical process control.
This edition features new introductions and revised content to help students better understand ANOVA. Additionally, it includes new examples to assist with calculating probability and approximately 80 new exercises.
Book Details
INFORMATION
ISBN: 9780470631478
Publisher: John Wiley and Sons Ltd
Format: Hardback
Date Published: 20 December 2010
Country: United Kingdom
Imprint: John Wiley & Sons Ltd
Edition: 5th Revised edition
Illustration: Photos: 0 B&W, 0 Color; Drawings: 0 B&W, 0 Color
Audience: Tertiary education
DIMENSIONS
Spine width: 25.0mm
Width: 211.0mm
Height: 257.0mm
Weight: 1134g
Pages: 544
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. He has been a faculty member of the School of Industrial and Systems Engineering at the Georgia Institute of Technology and a professor of mechanical engineering and director of the Program in Industrial Engineering at the University of Washington, where he held the John M. Fluke Distinguished Chair of Manufacturing Engineering. The recipient of numerous awards including the Deming Lecture Award from the American Statistical Association, Shewhart Medal of the American Society for Quality, the George Box medal from EENBIS, the Greenfield medal from the Royal Statistical Society, the Brumbaugh Award, the Lloyd S. Nelson Award, the William G. Hunter Award, and two Shewell Awards from the ASQ. He is 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 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 Emeritus of Engineering and Statistics at Arizona State University, and formerly Director of Strategic Initiatives for the Ira A. Fulton School of Engineering, holds degrees in mathematics, operations research, statistics and computer and systems engineering. She is co-owner of the metallurgical processing and statistical consulting company Refrac Systems in Chandler, Arizona. She is on the editorial board of the Journal of Quality Technology and Quality Technology & Quantity Management, as a founding member. Her specializations include capability analysis, transportation safety, and statistics in litigation.
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