SPSS for Windows Step by Step : A Simple Guide and Reference, 11.0 Update

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  • Edition: 4th
  • Format: Paperback
  • Copyright: 2003-01-01
  • Publisher: Allyn & Bacon
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SPSS for Windows Step by Step provided students with a comprehensive and straightforward guide and reference for using SPSS data analysis. Designed for courses in Research Methods and Statistics across all disciplines, this resource offers a comprehensive coverage of all major SPSS procedures for versions 11.0 and earlier. The clarity in this book is established by the use of more than 200 screenshots, clear writing, and over 500 step-by-step boxes that enable the reader to accomplish a procedure in SPSS one step at a time. Any student, even novices, can use this text as a tool to independently and efficiently learn SPSS data analysis. In addition, data sets that accompany the text, as well as an instructor's manual (available for download) can be located on the Companion Website. Book jacket.

Table of Contents

1. An Overview of SPSS for Windows Step by Step.

2. SPSS Windows Processes: Mouse and Keyboard Processing, Frequently-Used Dialog Boxes, Editing Output, Printing Results.

3. Creating and Editing a Data File.

4. Managing Data: Listing Cases, Replacing Missing Values, Computing New Variables, Recoding Variables, Selecting Cases, Sorting Cases, Merging Files.

5. Graphs: Creating and Editing Graphs and Charts.

6. Frequencies: Frequencies, Bar Charts, Histograms, Percentiles.

7. Descriptive Statistics: Measures of Central Tendency, Variability, Deviation from Normality, Size, and Stability.

8. Crosstabulation and Chi-Square (x 2) Analysis.

9. The Means Procedure.

10. Bivariate Correlation: Bivariate Correlations, Partial Correlations, and the Correlation Matrix.

11. The T-Test Procedure: Independent-Samples, Paired-Samples, and One-Sample Tests.

12. The One-Way ANOVA Procedure: One-Way Analysis of Variance.

13. General Linear Models: Two-Way Analysis of Variance. of Variance.

14. General Linear Models: Three-Way Analysis of Variance and the Influence of Covariates.

15. Simple Linear Regression.

16. Multiple Regression Analysis.

17. Nonparametric Procedures.

18. Reliability Analysis: Coefficient Alpha and split-half Reliability.

19. Multidimensional Scaling.

20. Factor Analysis.

21. Cluster Analysis.

22. Discriminant Analysis

23. General Linear Models: Manova and Manova: Multivariate Analysis of Variance and Covariance.

24. General Linear Models: Repeated-Measures MANCOVA Multivariate Analysis of Variance with Repeated Measures and Within-Subjects Factors.

25. Logistic Regression.

26. Hierarchical Loglinear Models.

27. General Loglinear Models.

28. Residuals: Analyzing Left-Over Variance.




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