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Statistical Inference
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Binding: Hardcover
Dewey Decimal Number: 519.5
EAN: 9780534243128
Edition: 2
ISBN: 0534243126
Label: Duxbury Press
Manufacturer: Duxbury Press
Number Of Items: 1
Number Of Pages: 688
Publication Date: June 18, 2001
Publisher: Duxbury Press
Studio: Duxbury Press
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Editorial Review:
This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.
Customer Reviews
Average Rating: 
Rating:  - Good introduction, many errors
This text is quite good, with numerous examples, but beware of the many errors or cases of sloppy reasoning. A sampler:
p. 319. The maximum likelihood estimator for the binomial distribution, unknown number of trials, is unique. Not true: n=2, p = .4, sample = (1,6) is a counterexample.
p. 265. If S is the sum of k idd uniform (0,1) random variables, then Prob(S <= t) is t^k over k!. Not true: this would give prob(S <=k) = 1/k!
p. 62, 82, 84: Moments are unique ... Read More
Rating:  - Great textbook.
This is a fantastic book. It is very well written and is a pleasure to read. The problems at the end of each chapter are extensive and help get a very good understanding of the material. This was the required text for a quarter based graduate level course on Statistical Inference. We had an excellent teacher who picked problems very well and that perhaps kept us from getting bogged down. Many of the problems are by no means trivial and require time to solve, which is where a great instructor helps. If ... Read More
Rating:  - Don't believe it!
This book is absolute misery! I would like to echo another review that basically stated if you have to take a class with this book, just drop it now and save yourself the grief. Truer words were never spoken! The Preface states that the prerequisite is 1 year of calculus. That is an outrageous lie! Maybe if you took calculus at Princeton or MIT, you will have a fighting chance. Otherwise you better have the sophistication of writing and understanding proofs that are on par with a real analysis background, ... Read More
Rating: - good text for first graduate course in statistics
This is the second edition of an excellent book. Casella and Berger put together a text that many faculty began choosing for the first graduate course in mathematical statistics. This second edition is improved over the first and puts more emphasis on the algorithms than the asymptotics. It covers modern topics like resampling and is verywell presented.
When I was a graduate student we used Ferguson and Cox and Hinkley and we also used Lehmann's book for hypothesis testing. This book starts with basic ... Read More
Rating:  - Formats are very difficult to read
I find this book very difficult to read. There are no set margins, and the font set is the same for an example, definition or for a Theory. Trying to find what you are looking for is very time consuming. additionally, the examples are predominantly proofs (which are good), but there are few for applied problems, and the explanations are not very thourough. I would recommend Sheldon Ross Introduction to Probability since it covers the same material, is readable with formatting, and has numerous examples. For an even ... Read More
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