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Probability and Statistics (2nd Edition) Hardcover – January, 1986

ISBN-13: 978-0201113662 ISBN-10: 020111366X Edition: 2 Sub

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Probability and Statistics (4th Edition)
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Product Details

  • Hardcover: 723 pages
  • Publisher: Addison Wesley Publishing Company; 2 Sub edition (January 1986)
  • Language: English
  • ISBN-10: 020111366X
  • ISBN-13: 978-0201113662
  • Product Dimensions: 9.5 x 6.7 x 1.3 inches
  • Shipping Weight: 2.4 pounds
  • Average Customer Review: 3.8 out of 5 stars  See all reviews (26 customer reviews)
  • Amazon Best Sellers Rank: #377,840 in Books (See Top 100 in Books)

Customer Reviews

If you want to learn like this, go ahead and buy this book.
The book also has lots of great examples that clarify the theory and show how the theory can be applied.
Philip Ostromogolsky
I can strongly recommend this book as a text for upper level courses in probability and statistics.
Charles Ashbacher

Most Helpful Customer Reviews

90 of 93 people found the following review helpful By "self-study" on April 25, 2003
This is an introductory book. It also fits in introductory level of Mathematical Statistics. The prerequisites are introductory calculus and linear algebra. Most theorems are proved in calculus style but there are some gIt can be shownsh that are not proved. So some readers may not be satisfied with the book, especially Math majors.
Logical steps are shown in detail; else logical gaps are contained within a level such that a first time reader can fill in the gap with a pencil and paper. Occasional mix with Bayesian perspective is also a feature. Answers to odd-numbered exercises are provided except ones that ask derivations and proofs. Exercises that require some tricks are provided with hints. In these respects, this textbook is suitable for self-study.
Upon completion of the entire material, I feel concepts are developed well up to Hypothesis testing Chapter 8 where the presentation of material reaches climax and its level of exposition is somewhat higher than other chapters. Thereafter, simple linear regression is treated in detail, but coverage and detail of materials seem to deteriorate from the following general regression section, nonparametrics and thereafter. Kolmogorov-Smirnov Tests section is treated nicely though. Anova section lacks in coverage. The new simulation chapter is presented more like a demonstration rather than an introduction.
I have never seen the previous 2nd edition (unfortunately Dr. Degroot is no longer with us), but according to the preface of this 3rd edition, Dr. Schervish describes 8 major changes from the previous edition.
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53 of 59 people found the following review helpful By Daniel Ventosa S on April 3, 2001
Format: Hardcover
As a social science student (economics), statistics are crucial in a large array of topics of interest. During my studies, I have bought many probabilities and statistical manuals in order to understand the underlying theory I study (econometrics). So far, no one is better than this one (Mendelhall, Monfort among others). As someone said, probability is not an easy topic; sometimes it's pretty hard to understand particularly abstract concepts. Nevertheless, the author teaches you through an impressive quantity of examples. You don't need to be a genius in math's to understand him, because he explains pretty well. The equations are all understandable and the author's doesn't use I high level of sophistication to present complex problems. The content is pretty impressive; besides the classical probability theory (basic concepts, conditional probability, random variables, expectation...), there is an extensive section dealing with estimation techniques (maximum of likelihood, OLS, and Bayesian estimators) there is a chapter dealing with statistical tests and another with non-parametrical methods. The latter is somehow oldie and there are no explanations of the kernel density estimation or kernel regression. The other objection I can raise is that there are no explanations neither of sigma-algebras, a concept used in advanced probability. Of course, it's an introductory book, thus such drawbacks are understandable. This book should be in your library.
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64 of 73 people found the following review helpful By Deep Roy on December 9, 2005
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After having used this book in a graduate level probability/statistics course and having the opportunity to poll students who took that class over the past 3 years, I found out that the probability of getting a good grade, and achieving understanding with DeGroot, was small.

To my joy, the university now uses Fredrick Solomon's book entitled "Probability and Stochastic Processes" for their 4000 level course.

After reading Solomon's book, I found myself getting unconfused and after having studied Jim Pitman's Probability book and Freedman's Statistic's book, I can now get into DeGroot's book. I am also going to get Feller's book, volume 1. What I needed, and DeGroot didn't offer, was a better feeling of "number sense" or what I think of as the "physics of numbers." I also wanted to know about the connections between things (concept maps) and DeGroot didn't do this, initially, for me.

I agree with the other reviewers that DeGroot's book is interesting but I don't believe that DeGroot sequenced the information well or had the desire to bring out a lot of the hidden details. Of course, after I read the other books I mentioned, I am beginning to see how wonderful DeGroot is for the advanced learner because he puts things together in interesting ways. However, to get to that level of appreciation, and see the "deeper connections," I really needed a stronger foundation on which I could appreciate DeGroot's heavy dose of algebra and matter of fact presentation.

In short, I found this book to be "the exam," but not "the course."
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15 of 15 people found the following review helpful By Donald M. Hourican on March 1, 2001
Format: Hardcover
This was my first stats book in college. I really liked it a lot, and maybe it is why it helped me appreciate stats. This book is very versatile and somehow explains sophisticated concepts with the greatest of ease. It has great examples, and I learn better with those. This book was used not only in my undergrad courses (Stats I and II, back mid-'70's) but also in my MBA curriculum (as a later edition) 10 years later. I have yet to run into a better book for someone studying stats for the first time. Also good at probability, which is one of the most obtuse, counter-intuitive subjects for humans to understand.
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