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Data analysis using SAS Enterprise guide /
This book presents the basic procedures for using SAS Enterprise Guide to analyse statistical data.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge ; New York :
Cambridge University Press,
2009.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 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.