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Full Description
This new edition of one of the most widely read textbooks in its field introduces the reader to data analysis with the most powerful and versatile statistical package on the market: IBM SPSS Statistics 19.
Each new release of SPSS Statistics features new options and other improvements. There remains a core of fundamental operating principles and techniques which have continued to apply to all releases issued in recent years and have been proved to be worth communicating in a small volume.
This practical and informal book combines simplicity and clarity of presentation with a comprehensive treatment of the use of IBM SPSS Statistics 19 for the description, exploration and confirmation of data. As in earlier editions, coverage has been extended to address the issues raised by readers since the previous edition. In this edition, there is an introduction to the Analysis of Covariance (ANCOVA).
Each statistical technique is presented in a realistic research context and is fully illustrated with annotated screen shots of SPSS dialog boxes and output. The first chapter sets the scene with a survey of typical research situations, key terms and clear signposts to the location of each technique in the book. It also offers guidance on the choice of statistical techniques, and advice (based on the American Psychological Association's guidelines) on how to report the results of a statistical analysis. The next chapters introduce the reader to the use of SPSS, beginning with the entry, description and exploration of data. There is also a full description of the capabilities of the versatile Chart Builder. Each of the remaining chapters concentrates on one particular kind of research situation and the statistical techniques that are appropriate.
In summary, IBM SPSS Statistics 19 Made Simple
Gets you started with SPSS.
Shows you how to describe and explore a data set with the help of SPSS's extensive
Contents
1. Introduction. 2. Getting Started with SPSS Statistics 19. 3. Editing Data Sets. 4. Describing and Exploring Your Data. 5. More On Graphs and Charts. 6. Comparing Averages: Two-sample and One-sample Tests. 7. The One-way ANOVA. 8. Between Subjects Factorial Experiments. 9. Within Subjects Experiments. 10. Mixed Factorial Experiments. 11. Measuring Statistical Association. 12. Regression. 13. The Analysis of Covariance (ANCOVA). 14. Analyses of Multiway Frequency Tables. 15. Predicting Category Membership: Logistic Regression. 16. The Search for Latent Variables: Factor Analysis.
