Statistical Modeling: A Fresh Approach

by Daniel T. Kaplan

The 2nd edition (green cover) is now available and the first edition (brown cover) is now obsolete. The new edition makes use of the MOSAIC package in R (see www.mosaic-web.org/StatisticalModeling) introduces inference earlier, and incorporates suggestions and corrections offered by readers of the first edition. We continue to make the first edition available for students seeking to match the book used in a class that still uses the first edition. Statistical A Fresh Approach introduces and illuminates the statistical reasoning used in modern research throughout the natural and social sciences, medicine, government, and commerce. It emphasizes the use of models to untangle and quantify variation in observed data. By a deft and concise use of computing coupled with an innovative geometrical presentation of the relationship among variables, A Fresh Approach reveals the logic of statistical inference and empowers the reader to use and understand techniques such as analysis of covariance that are widely used in published research but hardly ever found in introductory texts. Recognizing the essential role the computer plays in modern statistics, A Fresh Approach provides a complete and self-contained introduction to statistical computing using the powerful (and free) statistics package R. Exercises, software and datasets for the book are available at

Genres: Mathematics

440 pages, Paperback

First published January 1, 2009

Reviews

[Terran M · Rating 4 out of 5]

This book offers clear explanations of linear regression and its dependent concepts, which are accessible to those with a weak mathematics background (i.e. no calculus), including some useful geometric intuitions. I admire and appreciate the author's attempt to write an introductory statistics curriculum based primary on fitting models, which is in my experience exactly what students want to do.

Now the drawbacks: it is rather long and verbose relative to the amount of material it covers. It does not introduce concepts which are traditionally considered core in introductory statistics: students using this book will not learn about the law of large numbers, the central limit theorem, or the standard error of the mean. This makes it unsuitable preparation for the study of other books and topics which assume a knowledge of introductory statistics as it is traditionally construed.

[Mihailo Joksimovic · Rating 5 out of 5]

Amazing book! Especially for a guy whose background is Software Engineering and who never had to deal with statistics.

The book is written in amazingly friendly language and author used real-life examples in order to explain concepts that I used to struggle every time I wanted to learn them.

All in all, overall great book for beginners and, probably, intermediates as well.

[Kw Estes · Rating 4 out of 5]

Contains many good theoretical insights regarding statistics--ie should we fetishize certain aspects of the statistical realm as much as we currently do?