About the Book :
This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. Proven, accurate, and lauded for its excellent examples, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 8e, evidences Jay Devores reputation as an outstanding author and leader in the academic community. Devore emphasizes concepts, models, methodology, and applications as opposed to rigorous mathematical development and derivations. Aided by his lively and realistic examples, students go beyond simply learning about statisticsthey also learn how to put statistical methods to use.
About the Author :
Jay Devore earned his undergraduate degree in Engineering Science from the University of California at Berkeley, spent a year at the University of Sheffield in England, and finished his Ph.D. in statistics at Stanford University. He previously taught at the University of Florida and at Oberlin College and has had visiting appointments at Stanford, Harvard, the University of Washington, New York University, and Columbia University. From 1998 to 2006, Jay served as Chair of the Statistics Department at California Polytechnic State University, San Luis Obispo, which has an international reputation for activities in statistics education. In addition to this book, Jay has written several widely used engineering statistics texts and a book in applied mathematical statistics. He is currently collaborating on a business statistics text, and also serves as an Associate Editor for Reviews for several statistics journals. He is the recipient of a distinguished teaching award from Cal Poly and is a Fellow of the American Statistical Association. In his spare time, he enjoys reading, cooking and eating good food, tennis, and travel to faraway places. He is especially proud of his wife, Carol, a retired elementary school teacher, his daughter Allison, the executive director of a nonprofit organization in New York City, and his daughter Teresa, an ESL teacher in New York City.
1.Overview And Descriptive Statistics. 2. Probability. 3. Discrete Random Variables And Probability. 4. Continuous Random Variables And Probability Distributions. 5. Joint Probability Distributions And Random Samples. 6. Point Estimation. 7. Statistical Intervals Based On A Single Sample. 8. Tests Of Hypotheses Based On A Single Sample. 9. Inferences Based On Two Samples. 10. The Analysis Of Variance. 11. Multifactor Analysis Of Variance. 12. Simple Linear Regression And Correlation. 13. Nonlinear And Multiple Regression. 14. Goodness-Of-Fit Tests And Categorical Data Analysis. 15. Distribution-Free Procedures16. Quality Control Methods.