Quantitative Data Analysis with SPSS 14, 15 and 16 : A Guide for Social Scientists

by Bryman, Alan; Cramer, Duncan

• ISBN13: 9780415440899
• ISBN10: 0415440890
• Edition: 1st
• Format: Paperback
• Copyright: 2008-12-01
• Publisher: Routledge

Summary

This edition has been completely updated to accommodate the needs of users of SPSS Releases 14, 15 and 16, whilst still being applicable to those using SPSS Releases 10-13. Alan Bryman and Duncan Cramer provide a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS. No previous familiarity with computing or statistics is required to benefit from this step-by-step guide to statistical techniques, which includes: Non-parametric tests Correlation Simple and multiple regression Analysis of variance and covariance Factor analysis The authors discuss key issues facing the newcomer to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Each chapter contains worked examples to illustrate the points raised and ends with a comprehensive range of exercises which allow the reader to test their understanding of the topic. For the first time, the book includes a helpful glossary of key terms. The datasets used in Quantitative Data Analysis with SPSS 14, 15 & 16are available online at: http://www.psypress.com/brymancramer ; in addition a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available here free of charge to lecturers who adopt the book.

Table of Contents

List of figures	p. ix
List of tables	p. xiii
List of boxes (screenshots)	p. xix
Preface	p. xxiii
Data analysis and the research process	p. 1
Analysing data with computers: first steps with SPSS 14, 15 and 16	p. 19
Analysing data with computers: further steps with SPSS 14, 15 and 16	p. 47
Concepts and their measurement	p. 65
Summarizing data	p. 85
Sampling and statistical significance	p. 119
Bivariate analysis: exploring differences between scores on two variables	p. 141
Bivariate analysis: exploring relationships between two variables	p. 197
Multivariate analysis: exploring differences among three or more variables	p. 245
Multivariate analysis: exploring relationships among three or more variables	p. 281
Aggregating variables: exploratory factor analysis	p. 321
Answers to exercises	p. 339
Appendix	p. 351
Glossary	p. 353
References	p. 369
Index	p. 373
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