About the Book
Making statistics—and statistical software—accessible and rewarding
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.
Table of Contents:
About the Authors
Preface
Acknowledgments
Introduction
Chapter 1: An Introduction to Statistics & Quantitative Methods
Chapter 2: An Introduction to IBM® SPSS® Statistics and Stata
Chapter 3: Descriptive Statistics
Chapter 4: Pearson′s r, Chi-square, t-Test, and ANOVA
Chapter 5: Linear Regression
Chapter 6: Logistic, Ordered, Multinomial, Negative Binomial, and Poisson Regression
Chapter 7: Factor Analysis
Chapter 8: Time-Series Analysis
Chapter 9: Hierarchical Linear Modeling
Chapter 10: Structural Equation Modeling
Appendix A: Selecting the Appropriate Test
Appendix B: Tables of Significance
Appendix C: Additional Statistical Tests and Equations
Glossary
Index
Review :
This is a hurried and poorly executed book which gives a very superficial treatment to the subject matter. Moreover, given the cover price, I would have expected a little more finesse with the final look of the tables/charts. There were countless mistakes which just made me think it hadn′t been edited thoroughly, which is both down to the author and the editor.
Good easy book to understand and helpful for students
Some errors in numbers.
Explanations are short,not detailed.
Example are a few.
too advanced for my students
I find this book good as a resource for using SPSS and other statistical software. It provides step-by-step instructions about how to run each statistical test and provides graphical displays for each step. This book is useful as a supplement to the main text. I′m adopting it for the doctoral research class and I′m considering it also for my intro stats class.
The book is an excellent source for my Management doctoral students working on applied research involving regression. I partcilarly liked the exposition of difficult concepts using to the point phrases followed by easy to comprehend mathematical notaion and/or formulae. Excellent reference textbook!
Useful but not to be essential text as it doesn′t have enough detail.
Kremelberg′s Practical Statistics makes simplicity out of complex; a must have book for doctoral students who need to understand SPSS.
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!
good explanations, too simplistic for doctoral level work.
Although I use both qualitative and quantitative methods in my research and reporting, the statistics aspects have never quite come easily. Yes, I do have a collection of statistics guides on my shelf, but still found myself seeking something a little more ‘fundamental.’ I found Kremelberg’s text very easy to read, and the step-by-step approach quickly proved to be invaluable. Providing some background on the statistical tests, and then giving examples for different statistical packages was excellent, although sometimes the multitude of pictures on a page can appear a little ‘clunky’. This book could be used at the undergraduate level much more often that the complex textbooks that I usually see.
Price
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.
very good
This is an excellent book for non-mathematicians who wish to learn the basics of statistics and want to be able to easily implement the acquired knowledge. The author provides the reader with very detailed instructions for the implementation of every statistical tool given in the book. Chapter 2 is particularly useful since it gives an easy to follow introduction to SPSS and STATA, the two statistical packages used throughout the book.
The book is biased towards statistics used in the social sciences but it covers most of the basics for an introductory statistics course. Specifically, descriptive statistics is covered and illustrated using both packages, followed by the basic statistical tests. The fifth chapter is concerned with linear regression while generalised linear modelling follows in the next chapter. The final four chapters centre on more advanced statistical models and contain factor analysis, time-series analysis, mixed models and structural equation modelling.
One potential amendment to the book structure would be the inclusion of non-parametric tests in the main body of the book. Also, ANOVA is considered almost separately from (hierarchical) linear regression. Some discussion of the connections among the two methods and a more extensive coverage of linear mixed models would be desirable, particularly for general biostatistical applications. Finally, I would add a small section at the end of each chapter including the mathematical derivation of the methods described in each chapter, directed to the more mathematically inclined reader.
In conclusion, this is a concise introductory book on applied statistics which students and practitioners who intend to use quantitative methods shall find helpful, particularly those interested in social sciences.
Nikos Demiris
Agricultural University of Athens
This book can be adopted as an essential book for the course in Econometrics, Stata course or Applied Statistics. It has a moderate amount of necessary formulas, gives the codes for Stata programs and its′ outcomes (with print screens). The contents is logical, starting from simple tests, linear regression and going to multiple, with a discussion of time series and structural equation model.
A very useful text - makes understanding SPSS really simple!
SPSS support, cheap. Good suitability as a supporting textbook.
I selected another Sage book--Salkind′s Statistics for People Who (think) They Hate Statistics. However, this textbook was a close second.
Not at appropriate level.
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.
A little too complex
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,
The fact that it approaches statistical analyses on two fronts( SPSS and STATA) makes it handy for students who want to learn both at the same time. It is brilliant 2 in 1 book.
this book explains factor analysis with excellent way
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.
book will be supplemental for those proceeding their analysis with SPSS. a very nice and comprehensive book. the other way around some confusing because of the content regarding STATA. so therefore it didn′t reach the status of adoption for essential reading
A very useful textbook to understand basic statistics
A very good guide for basic practics in statistical methods with a main focus to SPSS, but also to STATA. My students preffered it (even if it is written not in their native language, german) because the usage of the statistical procedures is described with easy to understand screen-shots that can be recognised during their own work.
An excellent basic statistics text.
A good, clear introduction to 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
This book is essential for students who wish to study SPSS in a more detailed way.
Too broad for students
Course did not run.
