Table of Contents

1. The Role of Statistics in Engineering. 2. Data Summary and Presentation. 3. Random Variables and Probability Distributions. 4. Decision Making for a Single Sample. 5. Decision Making for Two Samples. 6. Building Empirical Models. 7. Design of Engineering Experiments. 8. Statistical Quality Control. Appendices Index.

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.