Applied Engineering Statistics

R. RUSSELL RHINEHART is Associate Professor of Chemical Engineering at Texas Tech University, Lubbock, with 13 years of industrial experience in process and product engineering. The author or coauthor of over 30 articles, book chapters, and papers, he is a member of the American Institute of Chemical Engineers, Instrument Society of America, and American Society of Engineering Education. Dr. Rhinehart received the B.S. (1968) and M.S. (1969) degrees from the University of Maryland at College Park, and Ph.D. (1985) from North Carolina State University, Raleigh.ROBERT M. BETHEA is Professor of Chemical Engineering at Texas Tech University, Lubbock. He is the author or coauthor of over 120 articles, papers, book chapters, and reports, and two books, including Statistical Methods for Engineers and Scientists, Second Edition, Revised and Expanded (with Benjamin S. Duran and Thomas L. Boullion) (Marcel Dekker, Inc.). A Diplomate of the American Academy of Environmental Engineers, a Senior Member of the American Institute of Chemical Engineers and American Chemical Society, and a member of the Air and Waste Management Association and American Industrial Hygiene Association, among others, Dr. Bethea received the B.Sc. (1957) degree from Virginia Polytechnic Institute and State University, Blacksburg, and M.S. (1959) and Ph.D. (1964) degrees from Iowa State University of Science and Technology, Ames.

• 1. INTRODUCTION. 2. PROBABILITY. 3. DISTRIBUTIONS. 4. DESCRIPTIVE STATISTICS. 5. STATISTICAL INFERENCE AND ESTIMATIONS. 6. HYPOTHESIS FORMULATION AND TESTING. 7. NONPARAMETRIC TESTS. 8. REPORTING AND PROPAGATING ERROR IN CALCULATIONS. 9. RISK. 10. STOCHASTIC SIMULATION. 11. IMPACT OF RIGHT OR WRONG DECISIONS 12. ANALYSIS OF VARIANCE. 13. STEADY AND TRANSIENT STATE IDENTIFICATION. 14. LINEAR REGRESSION. 15. NONLINEAR REGRESSION. 16. EXPERIMENTAL DESIGN FOR LINEAR STEADY-STATE MODELS – SCREENING DESIGNS. 17. CONCEPTS FOR PHENOMENOLOGICAL MODEL VALIDATION. 18. EXPERIMENTAL DESIGN FOR NONLINEAR MODELS 19. STATISTICAL PROCESS CONTROL. 20. RELIABILITY. 21. CLASSIFICATION ALGORITHMS.