- Clearly written;
- Tough subjects are made understandable even for beginners;
- Classical results are presented rigorously after a bunch of examples;
- Many exercises, well posed, whose solutions are found in the end of the book (just even exercises).

This books has been long without a revision and we can see easily that it is much better. The main improvement is the computational treatment of Statistics in terms of theory and exercises. And, of course, it is visually more pleasant.

You may think this is little, though. But, a classical is so well done that there is not much more to do. This is the case. So the second author adds what was difficult when DeGroot first wrote it (computational stuff, as I said) and suppress what is out of fashion or has been overcome.

I think it is still the best option to start out to learn Statistics.


Good intro for self-study   April 25, 2003
 72 out of 75 found this review helpful

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 shownsh 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. Notable are some material removed from the previous (likelihood principle, Gauss-Markov theorem, and stepwise regression), some added (lognormal distribution, quantiles, prediction and prediction intervals, improper priors, Bayes test, power functions, M-estimators, residual plots in linear models and Bayesian analysis of simple linear regression), more exercises and examples, special notes, introduction and summary to each section, and so on. I find the last in the list is somewhat disturbing, especially introduction parts that are often redundant with the very next paragraph. On the other hand, I find that special notes provide good insights.

I wish they included introduction to Statistical Decision theory, full coverage of regression analysis to be usable such as diagnosis, transformation and variable selection, coverage of Multivariate Normal distribution, more coverage and depth in nonparametrics and simulation, and lists of recommended readings for further study at the end of each section with comments.

There are a noticeable number of typos as of this first printing I have. I sent suggestions for typos and was impressed that Dr. Schervish updated errata list within a few days at his homepage. I wish all authors were like him being responsible.


Great stats book   January 15, 2003
 8 out of 9 found this review helpful

I used to hate statistics, but this book is pretty clear and concise, and gets the idea across very quickly and easily. The exercise questions were of reasonable difficulty, and are put forth in a clear manner, unlike other books which present the questions in round-about manner. The examples tend to follow on or build upon from the earlier chapters, so it is best to tackle the book in the order as prescribed by the chapters.


best introduction to the field   October 24, 2002
 9 out of 11 found this review helpful

I have looked at many introductory books to probability and statistics and this one is definitely the best. It is very clear and readable and yet gets to pretty advanced stuff.


what's the point of the intro and summaries?   October 14, 2002
 10 out of 14 found this review helpful

I used this book as a reference for my graduate level statistics course and I found it to be an excellent book to learn from. However, I have compared the first and third editions and I noticed that Prof. Schervish's additions; notably, the introduction and summary to each section, served very little; or if not, no purpose. The writing of the book is wordy enough, so these additions only made the book thicker, ...