3 Review(s)

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 Devore’s 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 statistics—they also learn how to put statistical methods to use. Key Features Sample exams help students build confidence and master concepts prior to taking class exams; the glossary of symbols/acronyms, which includes text page references, is another useful study aid. Exclusively from Cengage Learning, Enhanced WebAssign® allows you to assign exercises from this text and ensure that your students receive multimedia tutorial support and immediate feedback as they complete their automatically graded assignments. Several exercises refer to material covered in earlier sections and chapters, allowing students to more easily see the connections between concepts. Virtually every example and exercise has a real world context. Real data in exercises and examples stimulate students'' interest and enhance their comprehension of concepts. Notable content includes a strong emphasis on the role that variation plays in statistics, emphasis on the nature of variation in the slope estimate in simple linear regression, and inclusion of a detailed description of pooled t procedures to provide a balance between unpooled and pooled analyses. "Simulation Experiments" help students gain an understanding of sampling distributions and the insight they provide, especially when a derivation is too complex to carry out. Strong computer coverage, especially with ANOVA and regression, is supported by an abundance of computer output from SAS® and MINITAB® and coverage of computer methods. Inclusion of Java™ Applets from Gary McClelland''s SEEING STATISTICS, specifically designed for this calculus-based text, allows students to experience statistics firsthand. Table of Contents 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 Procedures 16. Quality Control Methods.