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Quantitative data analysis with IBM SPSS 17, 18 and 19 : a guide for social scientists / Alan Bryman and Duncan Cramer.

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16. As with previous editions, Alan Bryman and Duncan Cramer continue to offer a comprehensive and user-friendly introduction to t...

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Bibliographic Details
Online Access: Full Text (via Taylor & Francis)
Main Author: Bryman, Alan
Other Authors: Cramer, Duncan, 1948-
Other title:Quantitative data analysis with IBM SPSS 17, 18 & 19.
Format: eBook
Language:English
Published: Hove ; New York : Routledge, 2011.
Subjects:
SPSS for Windows.
Social sciences > Statistical methods > Computer programs.
Table of Contents:
  • Machine generated contents note: 1. Data analysis and the research process
  • 2. Analysing data with computers: first steps with SPSS 17, 18 and 19
  • 3. Analysing data with computers: further steps with SPSS 17, 18 and 19
  • 4. Concepts and their measurement
  • 5. Summarizing data
  • 6. Sampling and statistical significance
  • 7. Bivariate analysis: exploring differences between scores on two variables
  • 8. Bivariate analysis: exploring relationships between two variables
  • 9. Multivariate analysis: exploring differences among three or more variables
  • 10. Multivariate analysis: exploring relationships among three or more variables
  • 11. Aggregating variables: exploratory factor analysis.
  • Quantitative Data Analysis with IBM SPSS17, 18 and 19
  • Figures
  • Tables
  • Boxes
  • 1. Data analysis and the research process
  • 2. Analysing data with computers: first steps with SPSS 17, 18 and 19
  • 3. Analysing data with computers: further steps with SPSS 17, 18 and 19
  • 4. Concepts and their measurement
  • 5. Summarizing data
  • 6. Sampling and statistical significance
  • 7. Bivariate analysis: exploring differences between scores on two variables
  • 8. Bivariate analysis: exploring relationships between two variables.
  • 9. Multivariate analysis: exploring differences among three or more variables
  • 10. Multivariate analysis: exploring relationships among three or more variables
  • 11. Aggregating variables: exploratory factor analysis
  • Answers to exercises
  • Appendix.

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