This book provides an excellent step-by-step approach to learning how to use SPSS to conduct statistical analyses. The book begins with a description of the Basics of SPSS: opening the program, opening files, printing, saving, etc. The authors then cover, through examples, the running of descriptive stastics, graphing, and inferential statistics, including t tests, one-way ANOVA, correlation, regression, and Chi-square. The book is filled with illustrations which the authors have designed utilizing the data sets that come with the SPSS package. The authors not only cover the procedures for running the statistical tests in SPSS, but they also discuss the research questions that may be addressed with each statistic, i.e. the "When?" and "Why?" questions

As a mathematics Ph.d student with some statistical knowledge and knowledge of how to work in a Windows environment I needed to know basics of SAS. Tried various other books and couldn't figure out how to start. This book is wonderful. In one day you can learn a lot. Can go home feeling great that you learnt something useful.

Very good introduction to Real Analysis!!! I highly recommend it to those starting to study the subject.

This book was out of print for a few years, but Cambridge Univ Press has issued a revised edition. This is my favorite book for real analysis, measure theory, and probability theory. The book is very self-contained and rigorous, and develops probability theory abstractly enough for advanced work in the field. If you are interested in empirical process theory, this text can be followed by Dudley's book on Uniform Central Limit Theorems.

In the acknowledgements to the first edition of Numerical Recipes in Fortran, Wm. Press et al write "We also wish to ackowledge two individuals we have never met: Forman Acton, whose 1970 textbook Numerical Methods That Work has surely left its stylistic mark on us...." (The second being Donald Knuth) In Real Computing, Acton expands in greater detail upon the theme of the earlier work, which is that good computing routines are problem-specific. That insight and understanding are called-for; recipes and black box routines are insufficient. In the fifties, with powerful mainframes few and far between, engineers farmed out their computations to a computing center. There you could find the guys who knew intelligent machine computing. When the IBM 370 came along, every university had its own machine, and computations became in-house. The expertise you found in the old centers wasn't there. Acton worked in one of those centers, and this book is written to guide the reader in acquiring some of the old magic.

Hosking and Wallis have succeeded in their book to give a complete overview of the methodology for doing a regional frequency analysis with estimation methods based on L-Moments. They have subdivided the methodology in 4 parts: screening data (using the Wilks discordancy measure), formation of homogeneous regions (using grouping methods with fine tuning by a heterogeneity measure), and selection and estimation of a regional frequency distribution (using a goodness-of-fit measure). In all 4 steps the L-Moments of the available data sets are used for parameter estimation and for deciding on discordancy, heterogeneity and goodness-of-fit. H&W have shown (in their 1980 to 1996 papers and summarizing it in this book) that the approach works well and that it is robust against intersite dependence (certainly present between neighboring sites), robust against small heterogeneity between the sites, and robust against a possible misspecification of the regional distribution. Two large case studies show the methodology in practice. This book will be appreciated by hydrologists and civil engineers in general, because the whole RFA-methodology is contained in one single book (224 pages) added with lots of references for the interested reader. I am sure that H&W may expect quite a number of citations to this work in the near future (they will have mine...)!

Freund & Wilson have taken a classical statistical procedure and breathed new life into it. Covering the basics at an understandable level, the text covers all current and traditional topic areas. From Multipe Regression to PCA regression with a tinge of Ridge Regression. Traditional trouble areas are adequately dealt with. The novice reader will have no trouble in getting up to speed and not have any of the formula hemmoraging normally associated with MRA. For you mathematicians take a break and go do a derivative elsewhere. A Dummies book for the rest of us. 5 stars and 6 bottles of beer for this one. Good job fellas!

This is the consummate regression book. It is ideal for grad work in stats. In particular the examples used are relevant and on target. A must for every social scientist's library.

This is one of a series of books Dennis Cook has written on regression graphics. This is the most theoretical of the three. It is a companion to the recent book with Sandy Weisberg. The other book emphasizes applications while this provides some theory to support a complete regression analysis through graphical methods. It provides a modern and up-to-date treatment. This work was summarized in a recent tutorial I attended that Cook gave at the Deming Conference last year. It includes several examples and covers asymptotic theory for such topics as sliced inverse regression. It is a great reference source also.

The book may be considered an update of Weyl's classic from 1946 "The classical groups, their invariants and representations". Naturally the theory has developed immensly since then and a new comprehensive presentation has been urgently overdue. Goodman and Wallach are not only among the most qualified to write this next "classic" on the subject, they also put a phantastic effort into making it comprehensive, readable, and pleasant to use. I found it easy to find needed results and concrete formulae on decompositions of tensors and harmonics, duailty groups and centralizer algebras, mulitiplicity formulae, branching laws, etc.. The results are systematically organized - almost in an "encyclopedial" style. The book also contains rather modern results, such as, for example, new proofs of the Kostant Rallis Theorem or the relations between invariant theory and the Jones knot polynomial.

This new "classic" sets the standard and foundations for any mathematician working in the field. I consider it especially useful also for mathematician from other fields as well as theoretical physicists who want to apply invariant theory in a variety of concrete settings.