Jay L. DevoreKenneth N. BerkDecember 7, 2011

Springer Science & Business MediaThe main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings.

This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

Jay Devore received a B.S. in Engineering Science from the University of California, Berkeley, and a Ph.D. in Statistics from Stanford University. He previously taught at the University of Florida and Oberlin College, and has had visiting positions at Stanford, Harvard, the University of Washington, New York University, and Columbia. He has been at California Polytechnic State University, San Luis Obispo, since 1977, where he was chair of the Department of Statistics for seven years and recently achieved the exalted status of Professor Emeritus.

Jay has previously authored or coauthored five other books, including *Probability and Statistics for Engineering and the Sciences*, which won a McGuffey Longevity Award from the Text and Academic Authors Association for demonstrated excellence over time . He is a Fellow of the American Statistical Association, has been an associate editor for both the *Journal of the American Statistical Association* and *The American Statistician*, and received the Distinguished Teaching Award from Cal Poly in 1991. His recreational interests include reading, playing tennis, traveling, and cooking and eating good food.

Ken Berk has a B.S. in Physics from Carnegie Tech (now Carnegie Mellon) and a Ph.D. in Mathematics from the University of Minnesota. He is Professor Emeritus of Mathematics at Illinois State University and a Fellow of the American Statistical Association. He founded the Software Reviews section of *The American Statistician* and edited it for six years. He served as secretary/treasurer, program chair, and chair of the Statistical Computing Section of the American Statistical Association, and he twice co-chaired the Interface Symposium, the main annual meeting in statistical computing. His published work includes papers on time series, statistical computing, regression analysis, and statistical graphics, as well as the book *Data Analysis with Microsoft Excel* (with Patrick Carey).

Publisher

Springer Science & Business Media

Published on

Dec 7, 2011

Pages

845

ISBN

9781461403913

Language

English

Genres

Mathematics / Probability & Statistics / General

Mathematics / Probability & Statistics / Stochastic Processes

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