Conceptual Guide to Statistics Using SPSS

ISBN-10: 1412974062
ISBN-13: 9781412974066
Edition: 2012
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Description: 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  More...

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Book details

List price: $57.00
Copyright year: 2012
Publisher: SAGE Publications, Incorporated
Publication date: 4/12/2011
Binding: Paperback
Pages: 312
Size: 7.50" wide x 9.50" long x 0.75" tall
Weight: 1.430
Language: English

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.

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 Angeles.

Introduction
Descriptive Statistics
Chi-Squared Test
Linear Correlation
One- and Two Sample T-Tests
One-way ANOVA
Two- and Higher-way ANOVA
Within-subject ANOVA
Mixed-model ANOVA
MANOVA
Regression
ANCOVA
Factor and Components Analysis
Psychometrics
Non-parametric Tests
Matrix Algebra
Appendix on the General Formulation of Custom Contrasts using Syntax

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