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A Conceptual Guide to Statistics Using SPSS
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A Conceptual Guide to Statistics Using SPSS



April 2011 | 312 pages | SAGE Publications, Inc
This book helps students develop a conceptual understanding of a variety of statistical tests by linking the statistics with the computational steps and output from SPSS. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. For example, seeing exactly how the concept of variance is used in SPSS-how it is converted into a number based on real data, which other concepts it is associated with, and where it appears in various statistical tests-will not only help students understand how to use statistical tests in SPSS and how to interpret their output, but will also teach them about the concept of variance itself.

Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, pointing out wherever possible how the SPSS procedure and output connects back to the conceptual underpinnings of the test. Each of the steps is accompanied by annotated screen shots from SPSS, and relevant components of output are highlighted in both the text and in the figures.

Sections explain the conceptual machinery underlying the statistical tests. In contrast to merely presenting the equations for computing the statistic, these sections describe the idea behind each test in plain language and help students make the connection between the ideas and SPSS procedures. These include extensive treatment of custom hypothesis testing in ANOVA, MANOVA, ANCOVA, and regression, and an entire chapter on the advanced matrix algebra functions available only through syntax in SPSS.

The book will be appropriate for both advanced undergraduate and graduate level courses in statistics.

 
1. Introduction
 
2. Descriptive Statistics
 
3. Chi-Squared Test
 
4. Linear Correlation
 
5. One- and Two Sample T-Tests
 
6. One-way ANOVA
 
7. Two- and Higher-way ANOVA
 
8. Within-subject ANOVA
 
9. Mixed-model ANOVA
 
10. MANOVA
 
11. Regression
 
12. ANCOVA
 
13. Factor and Components Analysis
 
14. Psychometrics
 
15. Non-parametric Tests
 
16. Matrix Algebra
 
17. Appendix on the General Formulation of Custom Contrasts using Syntax

“The most impressive part of this text is its comprehensiveness. It covers all of the major statistical analyses anyone would need to know about. I found it difficult to read at times because I was not given the figures to see in order to understand better the text. Also headings were not distinct and/or missing which would have made it easier to read. There are not many texts like this available so it would allow instructors some flexibility in choosing a text appropriate for their needs. At this point it is too advanced for my students but I might buy a personal edition as a reference for myself.”

Carmela Battaglia
Keuka College

“I think the tone is excellent and like the way that the author explained the concepts in an efficient way. The main advantage of this book over its competitors is its scope and coverage of both “point and click” and syntax methods for using SPSS. I do prefer this style to the texts I’ve used in the past, but I find it easier to write my own lab guides and post them on the course’s e-learning page.”

John Stogner
University Of Florida

"In my view the text is written in a user friendly language and illustrates concepts that would otherwise be confusing to beginning students and those with limited computer skills. Increasingly there are non-traditional students who are entering the education pipelines who need precise resources to guide them in accomplishing the tasks they need to without going through.”

Justice Mbizo
University Of West Florida

“I think the single most impressive aspect is the bridge between the practical and conceptual/theoretical. The author has done a nice job with this. I also like some of the things he mentions (“tidbits”) that are normally not mentioned in texts like this. I believe these two things distinguish it from other like texts. Adopt: Very likely. As I said earlier, I’ve been looking for something like this. So, it would definitely go further than any other book I know in fulfilling that need.”

J.D. Jasper
University Of Toledo

Clear explanations and nice visuals. This book would possibly serve as a nice supplementary text in a course in which another book with more theoretical information about the methods. I didn't adopt because the book doesn't include the nonparametric methods I am required to teach.

Dr Stefanie A Wind
College Of Education, University Of Alabama
September 23, 2015

Excellent book for my students

Dr Marie Leiner
Psychiatry Dept, Texas Technology University Health Science - El Paso
June 4, 2013

like Salkind better

Dr T Alexander
Social Sciences Div, Texas Wesleyan University
September 27, 2012

Course being retooled - but this book may be a possibility for the future.

Dr Christopher Sedelmaier
Criminal Justice Dept, University of New Haven
March 12, 2012

More detail than I need

Dr Jeanne Thomas
Social Work Dept, Eastern Michigan University
February 17, 2012

Compared to other potential texts, this book is an easy read that is less intimidating, but contains much of the same information. The availability of data files and PowerPoint slides from the author's website facilitated the understanding of complex numerical concepts that can be somewhat challenging.

Dr Clive Kennedy
Psychology , Chicago School of Professional Psychology
November 5, 2011

Elliot T. Berkman

Elliot T. Berkman is Assistant Professor of Psychology and director of the Social and Affective Neuroscience Laboratory at the University of Oregon. He has been teaching statistics to graduate students using SPSS for the past six years. In that time, he has been awarded the UCLA Distinguished Teaching Award and the Arthur J. Woodward Peer Mentoring Award. He has published numerous papers on the social psychological and neural processes involved in goal pursuit. His research on smoking cessation was recognized with the Joseph A. Gengerelli Distinguished Dissertation Award. He received his PhD in 2010 from the University of California, Los... More About Author

Steven Paul Reise

Steve P. Reise is professor, chair of Quantitative Psychology, and co-director of the Advanced Quantitative Methods training program at University of California, Los Angeles. Dr. Reise is an internationally renowned teacher in quantitative methods; in particular, the application of item response theory models to personality, psychopathology, and patient reported outcomes. In recognition of his dedication to teaching, Dr. Reise was named "Professor of the Year" in 1995-96 by the graduate students in the psychology department at UC Riverside, and was awarded the 2008 Psychology Department Distinguished teaching award. Most recently, in... More About Author

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ISBN: 9781412974066
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