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Examples and Problems in Mathematical Statistics, by Shelemyahu Zacks
PDF Download Examples and Problems in Mathematical Statistics, by Shelemyahu Zacks
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Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises
With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results.
Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features:
- Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving
- More than 430 unique exercises with select solutions
- Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis
Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.
- Sales Rank: #2911485 in Books
- Published on: 2014-02-18
- Original language: English
- Number of items: 1
- Dimensions: 9.50" h x 1.25" w x 6.40" l, .0 pounds
- Binding: Hardcover
- 652 pages
From the Back Cover
Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises
With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory and application and presents numerous problem-solving examples that illustrate the related notations and proven results.
Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features:
- Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving
- More than 430 unique exercises with select solutions
- Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis
Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.
About the Author
SHELEMYAHU ZACKS, PhD, is Distinguished Professor in the Department of Mathematical Sciences at Binghamton University. He has published several books and more than 170 journal articles on the design and analysis of experiments, statistical control of stochastic processes, statistical decision theory, sequential analysis, reliability, statistical methods in logistics, and sampling from finite populations. A Fellow of the American Statistical Association, Institute of Mathematical Sciences, and American Association for the Advancement of Sciences, Dr. Zacks is the author of Stage-Wise Adaptive Designs, also published by Wiley.
Most helpful customer reviews
3 of 3 people found the following review helpful.
For a Limited Audience
By B.L.
I think that the vast majority of the people who end up buying this are probably not going to even really be asking whether they should, because it'll be something that was assigned as part of a course. It's very heavy on examples and calculations, which is good for the fact that it provides plenty of practice.
It's at a high enough level, though, that the number of people who'd be studying this kind of thing on their own is very very small. It does seem like it was written with the assumption that there'd be a professor involved who'd probably walk you through some of the gaps. I could definitely also see someone buying it as a supplementary book for a class in the topic, to get a lot more practice questions in case you're struggling and want to make sure you have the subject really nailed down.
If you're just looking for something to teach you about statistics, on the other hand, this is not what you're looking for. When I looked at the description initially I was thinking it meant something more at an undergrad level, but this is definitely intended to be somewhere around advanced undergrad to grad school.
2 of 2 people found the following review helpful.
Good High Level Review of Math Stats with Emphasis on Examples and Problems
By Dan Sherman
I liked this book a lot in that it lays out what would be covered in a year-long graduate mathematical statistics course over about 600 pages and 9 chapters, and covers most basic results that one would see in this type of course. What I likes a lot about the book is that after laying out theory (probably about 1/2 of the test), each chapter than has worked out examples, along with problems to which solutions are presented. This is not an easy book and certainly requires good mathematical and statistical training. It could certainly be used as a text; the examples and problems are well chosen and solutions are well presented. For me (a PhD in economics), the book is a good reference as I read statistical work (index is good) - I find looking at a problem (and solution) as a useful way to make sure I understand the material. and problems are useful to make sure I understand the material.
A very good book, but necessarily pretty difficult going given its content. Recommended as a reference and possible text (or study companion).
1 of 1 people found the following review helpful.
Excellent Textbook for Advanced Mathematical Statistics Course
By William L. Brown
This book is a textbook that is geared toward use in upper-level courses in advanced mathematical statistics. It covers basic probability theory, statistical distributions, sufficient statistics and the information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory for estimation and testing, Bayesian analysis in testing and estimation, and advanced topics in estimation theory.
The description on the cover indicates that this book “[p]rovides the necessary skills to solve problems in mathematical statistics” and that it is a “clear … approach to the fundamentals of statistical theory.” This led me initially to think that it was an entry-level treatise on practical aspects of statistics that would help me in my research and evaluation work.
In over 600 pages of complicated equations and higher level mathematics, the author provides proofs and examples of numerous statistical theories. A highly skilled and adept mathematician would undoubtedly find the information of great interest in strengthening their knowledge of mathematical statistics.
The author is a Distinguished Professor in the Department of Mathematical Sciences at Binghamton (New York) University. His accomplishments in the fields of statistics and probability are numerous, including several books and over 170 journal articles on the design and analysis of experiments. As such, he is clearly a foremost expert in the field.
At over $100, the book is not inexpensive, and the average statistics user is unlikely to find much of practical application therein. A more basic approach would be Methods of Mathematics Applied to Calculus, Probability, and Statistics (Dover Books on Mathematics) by R. W. Hamming. Although Hamming’s work currently appears in a 1985 edition, readers have consistently given it high marks for its clarity and utility, and as of this writing it is still available from Amazon.
I suspect that Zacks’s book will reach only a very limited audience, primarily very accomplished mathematicians. It is definitely not basic or fundamental, except in the most restricted senses of these terms.
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