Mathematical Statistics and Data Analysis 2nd Edition

by John A. Rice (Author)

35 ratings

ISBN-13: 978-0534209346

ISBN-10: 0534209343

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This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.

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Editorial Reviews

About the Author

Ph.D. University of California Berkeley

Product details

Publisher ‏ : ‎ Duxbury Press; 2nd edition (June 1, 1994)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 672 pages
ISBN-10 ‏ : ‎ 0534209343
ISBN-13 ‏ : ‎ 978-0534209346
Item Weight ‏ : ‎ 2.75 pounds
Dimensions ‏ : ‎ 1 x 7.75 x 9.5 inches

Best Sellers Rank: #964,718 in Books (See Top 100 in Books)
- #1,742 in Statistics (Books)
- #2,756 in Probability & Statistics (Books)

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35 ratings

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5 star		56%
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3 star		5%
2 star		13%
1 star		10%

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Sitong Peng

Top Notch Applied Statistics Text, Great Explanations

Reviewed in the United States on September 7, 2009

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Most of the reviews are rather heavy on the opposite ends of the spectrum.

I used this book for a second semester undergrad course on statistical inference/methods. So I mainly used the later chapters on estimation, testing, anova, regression.. Most of the negative reviews on Amazon gripe about how this book is not an introductory text on statistics, which I can't say much against since I myself didn't use it as an intro text. I read pitman's probability text (great book) first. However, I would still urge you to be wary of those reviews because many people, even statisticians, have trouble with the trickiness of probability - much less people diving into mathematical statistics for the first time.

The chapters in the later half of the book are really just amazing. Rice writes in very clear, albeit sometimes lengthy, terms. There are enough proofs in this book to satisfy those looking to bypass the English, and there are enough explanations and examples to give students a firm understanding of the subject. Really! The explanations are very very clear and cover a variety of situations you may face in the field when working with stats (in private industry or econometric research alike). The graphical depictions in this book are really priceless.

I have frequently referenced this book and pitman's probability. Honestly, with maybe 3-4 hours of quiet study time, I can easily review all the basic probability and statistics topics one needs to do well in any statistics class at the undergrad and the lower grad level.

The only con is that the solutions aren't worked out in the book. If you need solutions, you can go to [...]and purchase monthly subscriptions to access their user worked out answers for this book. They have maybe 2/3 of the problems worked out, with perhaps a 90% accuracy rate.

Great 2nd mathematical intro to stats book!

5 people found this helpful

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Person

Unclear and inconsistent

Reviewed in the United States on February 23, 2012

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I recently completed courses in calculus (limits, differentiation, integration, sequences and series) and linear algebra (with some sets and logic). I picked this book up to learn basic probability and mathematical statistics on my own.
This book is incredibly confusing. The material is not that hard, but the author muddies the waters by using inconsistent terms and by omitting important logical steps. Omitting important steps is OK as long as you tell your reader that you're doing it. This saves your reader from re-reading the sentences to see if he/she missed something.
In Chapter 1, a sample space is sometimes denoted with a capital letter; however at times an event within that space is also denoted with a capital letter.
The grammar is even more confusing. The author does not indicate if an important logical step is omitted. For example, instead of saying "by the associative law ..." he uses words like "clearly..." and "logically..." without pointing to the rules being applied.
The problems are not challenging in my opinion. They are simply poorly worded and confusing. I have been able to look back at the examples and piece together the missing parts from the practice problems.
I'm going to try something else. I am disappointed because I spent a great deal of money and the book was recommended to me by peers (who clearly haven't read it).

2 people found this helpful

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M. Nguyen

great book

Reviewed in the United States on June 24, 2014

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This is a great book, very detailed explanations and proofs. I used it for an upper-division undergrad stat course at UC Berkeley

3 people found this helpful

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Dandan Chen

Good book to start learning stat.

Reviewed in the United States on June 1, 2013

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This book was recommended to me by a friend when I decided to learn some stat. I find it easy to read with many understandable examples. They also have a review on Probability, although I didn't use it. But it is convenient when you have a question, you can always go back to check the theorems.

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Kunpeng Liu

Five Stars

Reviewed in the United States on February 14, 2015

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Really useful

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Robert E. Froese

Is there an ideal text that non-statisticians will love?

Reviewed in the United States on April 2, 2001

Teaching statistics is a tough business because it is quantitative, rigourous, and often abstract. Most importantly teaching statistics is tough because the majority of students most professors face take statistics because the need to, not because they want to. To make matters worse, they face instructors who not only grasp the theory, but enjoy it, and who are all the while empowered to deliver no more than little snippets of higher level stuff their students can apply.
Rice tries to bridge the gap between theory and application, delivering enough theory that the student understands the logical foundation of the applied aspects they may have already discovered in previous courses. In my mind, this is the central theme of Rice's text - avoiding unnecessary and often pedantic details better left to graduate majors in statistics while filling in the background material that often left students of statistics uncertain about the amount of confidence to place in their analyses. Rice's text is not for those who fear rigour and logic. His introductions to new concepts are compact, impersonal, and often followed by terse propositions, definitions and laws that build logically as the text progresses. He includes numerous examples that are similarly terse; however, he never failed my litmus test for logical works, which is a demonstrable linkage between each example and some proposition, law or definition previously introduced.
The text commences with the most basic review of probability, progressing quickly to random variables, distributions, expected values and important derived distributions like the t, F and Chi-square. Students will discover how the tests they applied in the past are related to theory. This theme culminates in the section on Survey Sampling, in which sampling estimators and their assumptions are derived.
Rice has weaknesses that deserve mention. Some of the problems are tough, and Rice's impersonal approach emphasizes concepts over technique. I spent many hours reading and re-reading sections in the text before a useful approach to a problem came to me. Sections on least squares and ANOVA are the least useful; they are too compact to achieve the goal of bridging theory and application. This material is much better covered elsewhere. The decision theory and Baesian inference section suffers similarly, but given how little exposure most stats students get to this material is nevertheless useful.
If you're interested in learning the rigourous application of statistics but not theory, then Rice isn't for you. No matter what, you mustn't be afraid of challenges; Rice is impersonal and compact and won't make any excuses for you. If you want to understand the assumptions and limitations of the applied statistics you've already been practicing, however, I recommend Rice enthusiastically. He won't explain the assumptions, but he will arm you with the knowledge to do it yourself.

65 people found this helpful

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