Practical Statistics
A Quick and Easy Guide to IBM® SPSS® Statistics, STATA, and Other Statistical Software
- David Kremelberg - DK Statistical Consulting Inc.
This book provides readers with step-by-step guidance on running a wide variety of statistical analyses in IBM® SPSS® Statistics, Stata, and other programs. Author David Kremelberg begins his user-friendly text by covering charts and graphs through regression, time-series analysis, and factor analysis. He provides a background of the method, then explains how to run these tests in IBM SPSS and Stata. He then progresses to more advanced kinds of statistics such as HLM and SEM, where he describes the tests and explains how to run these tests in their appropriate software including HLM and AMOS.
This is an invaluable guide for upper-level undergraduate and graduate students across the social and behavioral sciences who need assistance in understanding the various statistical packages.
This is a basic overview which may be useful to students that need a more general refresher of SPSS or STATA. Overall, a really clear and concise text.
While this textbook is meant as a guide for statistical software, I appreciate the fact that the authors do attempt to present students with the mathematics behind some of the methods.
Price
Kremelberg's Practical Statistics makes simplicity out of complex; a must have book for doctoral students who need to understand SPSS.
The following review regards the book “Practical statistics a quick and easy guide to IBM SPSS, Stata and other Statistical Software”, by David Kremelberg.
There are many textbooks about statistics. The first question we should answer is whether this book was necessary or not. To my point of view the answer is YES and I will explain why.
Reading the book was really pleasant and Dr. Kremelberg is clear in explaining the concepts in the text. There is a certain quantity of math formulas but they are always supported with examples: numbers take place into the formulas and the reader can better understand what it is going on. Moreover, for those how are “allergic” to formulas, there is the possibility to skip them, without any problem, and to conduct the analysis using SPSS and/or STATA. Both these software are very known and user friendly. They are easy to use because of the possibility to have menu and windows in the selection of the data analysis.
Dr Kremelberg explains how to conduct the analysis, step by step, with the support of a lot of pictures taken during the use of SPSS and STATA. The reader sees selections and procedures as they should appear conducting the analysis. In the book it is refereed also to other statistical software/tools which may be useful as well.
The examples presented in the book guide the reader in experiencing, what it is said in the text in an efficient way. The reader gets skilled in conducting analysis and becomes more confident with statistic.
All the chapters have a nice but short introduction that makes the reader more confident of what it is expected to find in the following pages. Theory is introduced before the practical use of the statistical techniques with SPSS and STATA. At the end of each chapter there is a brief summary which stresses the most important concepts met.
Chapter 10 is a nice introduction to “Structural Equation Modeling” (SEM) and in the use of AMOS, a program for conducting analysis using structural equation modeling. SEM is preferred in situations where it is necessary to run a model that can not be run using simpler methods such as regression.
The glossary provides an easy access to definition that sometime can be “obscure” or cause uncertainly. Readers could benefit from it when they need to revise the definition of a concept, for example when they read a paper and statistical terms are presented.
At the end, I consider this book very useful especially for students who need a practical approach to statistical analysis using SPSS and/or STATA.
There are some suggestions the Author could consider for improvements in future revisions:
1) To add some extra chapters regarding: Roc curves, Pannel data analysis, Introduction to non-linear model.
2) To add summary tables or diagrams which help the reader in the choice of a technique instead of another.
Dr. Gabriele Messina
Research Professor of Public Health
University of Siena
very good
It is a good guide to SPSS. Students feel that it is easy to read it and operate SPSS step-by-step according to the illustration of this ook.
An excellent basic statistics text.
Great introduction to entry level graduate statistics using both SPSS and Stata. Should be accessible for most beginning graduate students and provide them with a solid quantitative foundation,
This is a very interesting and easy-to-read book. One of the best on "surface-teaching" or intuitive teaching of stats (i.e. the book does not present complex mathematical formulas but relies instead on statistical software outputs). I will strongly recommand the book to any graduate student using stats in their master's degree thesis and will add it to my course outline.
Thanks for putting together this great book!
