
Quantitative Data Analysis with IBM SPSS 17, 18 & 19
A Guide for Social Scientists
- 408 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Quantitative Data Analysis with IBM SPSS 17, 18 & 19
A Guide for Social Scientists
About this book
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 the widely used IBM SPSS Statistics. The simple, non-technical approach to quantitative data analysis enables the reader to quickly become familiar with SPSS and with the tests available to them.
No previous experience of statistics or computing is required as this book provides a step-by-step guide to statistical techniques, including:
- Non-parametric tests
- Correlation
- Simple and multiple regression
- Analysis of variance and covariance
- Factor analysis.
This book comes equipped with a comprehensive range of exercises for further practice, and it covers key issues such as sampling, statistical inference, conceptualization and measurement and selection of appropriate tests. The authors have also included a helpful glossary of key terms.
The data sets used in Quantitative Data Analysis with IBM SPSS 17, 18 and 19 are available online at http://www.routledgetextbooks.com/textbooks/_author/bryman-9780415579193/; in addition, a set of multiple-choice questions and a chapter-by-chapter PowerPoint lecture course are available free of charge to lecturers who adopt the book.
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Information
Table of contents
- Cover
- Title
- Copyright
- Contents
- List of Figures
- List of Tables
- List of Boxes
- Preface
- 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. key differences between SPSS 19 and recent earlier versions
- Glossary
- References
- Index