Features easy-to-follow insight and clear guidelines to perform
data analysis using IBM SPSS®
Performing Data Analysis Using IBM SPSS® uniquely
addresses the presented statistical procedures with an example
problem, detailed analysis, and the related data sets. Data entry
procedures, variable naming, and step-by-step instructions for all
analyses are provided in addition to IBM SPSS point-and-click
methods, including details on how to view and manipulate
output.
Designed as a user’s guide for students and other
interested readers to perform statistical data analysis with IBM
SPSS, this book addresses the needs, level of sophistication, and
interest in introductory statistical methodology on the part of
readers in social and behavioral science, business, health-related,
and education programs. Each chapter of Performing Data Analysis
Using IBM SPSS covers a particular statistical procedure and
offers the following: an example problem or analysis goal, together
with a data set; IBM SPSS analysis with step-by-step analysis setup
and accompanying screen shots; and IBM SPSS output with screen
shots and narrative on how to read or interpret the results of the
analysis.
The book provides in-depth chapter coverage of:
* IBM SPSS statistical output
* Descriptive statistics procedures
* Score distribution assumption evaluations
* Bivariate correlation
* Regressing (predicting) quantitative and categorical
variables
* Survival analysis
* t Test
* ANOVA and ANCOVA
* Multivariate group differences
* Multidimensional scaling
* Cluster analysis
* Nonparametric procedures for frequency data
Performing Data Analysis Using IBM SPSS is an excellent
text for upper-undergraduate and graduate-level students in courses
on social, behavioral, and health sciences as well as secondary
education, research design, and statistics. Also an excellent
reference, the book is ideal for professionals and researchers in
the social, behavioral, and health sciences; applied statisticians;
and practitioners working in industry.
A propos de l’auteur
LAWRENCE S. MEYERS, Ph D, is Professor in the Depart-ment
of Psychology at California State University, Sacramento. The
author of numerous books, Dr. Meyers is a member of the Association
for Psychological Science and the Society for Industrial and
Organiza-tional Psychology.
GLENN C. GAMST, Ph D, is Chair and Professor in the
Department of Psychology at the University of La Verne. His
research interests include univariate and multivariate statistics
as well as multicultural community mental health outcome
research.
A. J. Guarino, Ph D, is Professor of Biostatistics at
Massachusetts General Hospital, Institute of Health Professions,
where he serves as the methodologist for capstones and
dissertations as well as teaching advanced Biostatistics courses.
Dr. Guarino is also the statistician on numerous National
Institutes of Health grants and coauthor of several statistical
textbooks.
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