Quantitative Data Analysis with SPSS 12 and 13: A Guide for Social ScientistsPaperback Quantitative Data Analysis with SPSS
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Additional formats available
- Hardback $133.87
- Publisher: ROUTLEDGE
- Format: Paperback | 368 pages
- Dimensions: 174mm x 242mm x 22mm | 739g
- Publication date: 11 February 2005
- Publication City/Country: London
- ISBN 10: 0415340802
- ISBN 13: 9780415340809
- Edition statement: New.
- Sales rank: 1,118,105
This new edition has been completely updated to accommodate the needs of users of SPSS Release 12 and 13 for Windows, whilst still being applicable to those using SPSS Release 11 and 10. 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 techniques including: Non-parametric tests Correlation Simple and multiple regression Multivarate 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. This new edition of this hugely successful textbook will guide the reader through the basics of quantitative data analysis and become an essential reference tool for both students and researchers in the social sciences. The datasets used in Quantitative Data Analysis for SPSS Release 12 and 13 are available online at www.psypress.com/brymancramer/ .
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Table of contents
Data Analysis and the Research Process. Analyzing Data with Computers: First Steps with SPSS 12. Analyzing Data with Computers: Further Steps with SPSS 12. Concepts and their Measurement. Summarizing Data. Sampling and Statistical Significance. Bivariate Analysis: Exploring Differences between Scores on Two Variables. Bivariate Analysis: Exploring Relationships. Multivariate Analysis: Exploring Differences Among Three or More Variables. Multivariate Analysis: Exploring Relationships Among Three or More Variables. Aggregating Variables: Exploratory Factor Analysis. Answers to Exercises.