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Modern Mathematical Statistics with Applications (with CD-ROM), by Jay L. Devore, Kenneth N. Berk
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Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without emphasizing contemporary statistical practice. MODERN MATHEMATICAL STATISTICS WITH APPLICATIONS strikes a balance between mathematical foundations and statistical practice. Accomplished authors Jay Devore and Ken Berk first engage students with real-life problems and scenarios and then provide them with both foundational context and theory. This book follows the spirit of the Committee on the Undergraduate Program in Mathematics (CUPM) recommendation that every math student should study statistics and probability with an emphasis on data analysis.
- Sales Rank: #117631 in Books
- Brand: Brand: Cengage Learning
- Published on: 2006-01-06
- Original language: English
- Number of items: 1
- Dimensions: 1.13" h x 7.48" w x 9.22" l, 2.91 pounds
- Binding: Hardcover
- 848 pages
- Used Book in Good Condition
Review
From the book reviews:
“The text by Devore and Berk is a worthy entry into the collection of texts designed for the typical undergraduate mathematical statistics course. … there is more than enough material in the book for a one-year course. … the book would be a very solid choice for a year-long mathematical statistics course.” (R. T. Smythe, Mathematical Reviews, December, 2014)
"The authors made a good revision in this edition. The format is standard, however it showcases many statistical ideas in a clear manner, for a smooth grasp of the material. The chapters are well structured, presented, and motivated. The main strength of the book is that it still offers a good number of worked examples that are based on real datasets emerging from a variety of fields. It is a good candidate for adoption as a textbook for a senior level undergraduate course." (Ahmed, Technometrics, November, 2014)
From the Back Cover
Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data.
The 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.
Other features include:
- An extensive range of applications that will appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and business, economics, and quantitative social science students.
- Nearly 1,500 exercises to help students master the material and better understand sophisticated concepts and arguments.
- An emphasis on the importance of statistical software, including output from the statistical software packages Minitab, R, and SAS.
About the Author
Jay Devore is Professor Emeritus of Statistics at California Polytechnic State University. He 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. Jay 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, he served as Chair of the Statistics Department. In addition to this book, Jay has written several widely used engineering statistics texts and a book in applied mathematical statistics. He recently coauthored a text in probability and stochastic processes. He is the recipient of a distinguished teaching award from Cal Poly, is a Fellow of the American Statistical Association , and has served several terms as an Associate Editor of the "Journal 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, who has held several high-level positions in nonprofit organizations in Boston and New York City, and his daughter Teresa, an ESL teacher in New York City.
Ken Berk has a BS in Physics from Carnegie Tech (now Carnegie Mellon) and a PhD in Mathematics from 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 and the book Data Analysis with Microsoft Excel (with Patrick Carey).
Most helpful customer reviews
0 of 0 people found the following review helpful.
Four Stars
By Lionel Tchadji
Good
7 of 7 people found the following review helpful.
My all-time favorite text book
By MissTab
I think this is an excellent book. I used it for two semesters of mathematical statistics in my senior year of undergrad. I was an applied math major, so I really appreciated the way this book is organized. It doesn't get too theoretical or include tons of unnecessary proofs. Also, I found the book to be very user-friendly. It includes all necessary formulas, several examples, and many many practice problems with solutions to the odd problems in the back. Overall, I think it is well-written and very readable. I often referred back to this book in graduate school.
3 of 3 people found the following review helpful.
Good Entry Point.
By Walter
Modern Mathematical Statistics by Devore and Berk is an excellent place to start your exploration of probability and statistics. While probability is a branch of mathematics, statistics is its own separate entity that is partially an outgrowth of probability. The authors choose to focus this book on the fundamental ideas of probability and statistics and the application of these ideas to many real life problems. I support this approach since it highlights the ever increasing need to know this material, while not obscuring what is actually going on with complicated math. A student only needs a year of calculus to understand the bulk of the book. Even with this restriction the authors manage to show the important results covered in any entry level book on probability or math stat.
The book is ideal for self study the since authors give many example problems, clear exposition, and a student solution manual. The authors use minitab, a statistical program, to highlight the role that statistical computing plays in data analysis. I like that a statistical program is used, but I have never seen minitab used anywhere in real life.
If I had to teach a class on these topics, I would use this book. Classes like probability and mathematical statistics are often comprised of a diverse audience. Not only will you have math and stat majors, but students from the physical and social sciences. The low amount of prerequisite math should give everyone a chance to succeed. If an instructor wants to examine a topic in more depth than what is presented here, he or she can always assign additional readings from a book like Rice, which shares the same basic philosophy, but presents the material at a higher level.
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