Probability and Statistics for Engineering and the Sciences, Enhanced Review Edition

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Cengage Learning, Jan 29, 2008 - Mathematics - 768 pages
3 Reviews
This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. This proven, accurate book and its excellent examples evidence 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. Through the use of lively and realistic examples, students go beyond simply learning about statistics-they actually put the methods to use.
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this book can teach you nothing. basically it's a workbook & assume that you know all the theory shit

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This book is probably one of the worst books to learn statistics from. The author uses the same examples over and over again and simple things are written in overly complicated ways.


Overview and Descriptive Statistics
Discrete Random Variables and Probability Distributions
Continuous Random Variables and Probability Distributions
Joint Probability Distributions and Random Samples
Point Estimation
Statistical Intervals Based on a Single Sample
Tests of Hypotheses Based on a Single Sample
Simple Linear Regression and Correlation
Nonlinear and Multiple Regression
GoodnessofFit Tests and Categorical Data Analysis
DistributionFree Procedures
Quality Control Methods
Appendix Tables
Answers to Selected OddNumbered Exercises

Inferences Based on Two Samples
The Analysis of Variance
Multifactor Analysis of Variance

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About the author (2008)

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.

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