Data analysis using SAS Enterprise guide / Lawrence S. Meyers, Glenn Gamst, A.J. Guarino.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- text
- computer
- online resource
- 0511603681
- 9780511603686
- 9780511604461
- 0511604467
- 9780511651670
- 0511651678
- 9780511804786
- 0511804784
- 0511602901
- 9780511602900
- SAS (Computer file)
- Enterprise guide
- Enterprise guide
- SAS (Computer file)
- Social sciences -- Statistical methods -- Data processing
- Mathematical statistics -- Data processing
- Sciences sociales -- Méthodes statistiques -- Informatique
- Statistique mathématique -- Informatique
- BUSINESS & ECONOMICS -- Economics -- General
- BUSINESS & ECONOMICS -- Reference
- Mathematical statistics -- Data processing
- Social sciences -- Statistical methods -- Data processing
- Electronic books
- 330.0285/555 22
- HA32 .M499 2009eb
Item type | Home library | Collection | Call number | Materials specified | Status | Date due | Barcode | |
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OPJGU Sonepat- Campus | E-Books EBSCO | Available |
Includes bibliographical references and indexes.
Title from title screen.
This book presents the basic procedures for using SAS Enterprise Guide to analyse statistical data.
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.
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