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Data Analysis Using SAS Enterprise Guide

Lawrence S. Meyers, Glenn Gamst, and A. J. Guarino
Cambridge University Press
Publication Date: 
Number of Pages: 
[Reviewed by
Ita Cirovic Donev
, on

Data Analysis Using SAS Enterprise Guide is a book for novice users of SAS EG. The book focuses on explaining the possibilities of SAS EG, with point and click enabling novice users to get acquainted with the tool in a very short period of time.

Overall the book does not provide a step forward from what one can obtain from a simple help file. The only difference is that it is printed in a book format. Nevertheless, all the options of SAS EG are explained in great detail with plenty of visual guidance, which should make for an extremely easy read.

The book can be of good use to undergradutes and graduate students for whom this is the first encounter with SAS EG, and as such it should serve its purpose.

Ita Cirovic Donev holds a Masters degree in statistics from Rice University. Her main research areas are in mathematical finance; more precisely, statistical methods for credit and market risk. Apart from the academic work she does statistical consulting work for financial institutions in the area of risk management.

Part I. Introducing SAS Enterprise Guide: 1. SAS Enterprise Guide projects; 2. Placing data into SAS Enterprise Guide projects; Part II. Performing and Viewing Output: 3. Performing statistical analyses in SAS Enterprise Guide; 4. Managing and viewing output; Part III. Manipulating Data: 5. Sorting data and selecting cases; 6. Recoding existing variables; 7. Computing new variables; Part IV. Describing Data: 8. Descriptive statistics; 9. Graphing data; 10. Standardizing variables based on the sample data; 11. Standardizing variables based on existing norms; Part V. Score Distribution Issues: 12. Detecting outliers; 13. Assessing normality; 14. Nonlinearly transforming variables in order to meet underlying assumptions; Part VI. Correlation and Prediction: 15. Bivariate correlation: Pearson product moment and Spearman rho correlations; 16. Simple linear regression; 17. Multiple linear regression; 18. Simple logistic regression; 19. Multiple logistic regression; Part VII. Comparing Means t Tests: 20. Independent groups t test; 21. Correlated samples t test; 22. Single sample t test; Part VIII. Comparing means ANOVA: 23. One-way between subjects analysis of variance; 24. Two-way between subjects design; 25. One-way within subjects analysis of variance; 26. Two-way mixed ANOVA design; Part IX. Nonparametric Procedures: 27. One-way chi square; 28. Two-way chi square; 29. Nonparametric between subjects one-way ANOVA; Part X. Advanced ANOVA Techniques: 30. One-way between subjects analysis of covariance; 31. One-way between subjects multivariate analysis of variance; Part XI. Analysis of Structure: 32. Factor analysis; 33. Canonical correlation analysis.