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This book presents the basic procedures for using SAS Enterprise Guide to analyse statistical data.
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This book presents the basic procedures for using SAS Enterprise Guide to analyse statistical data.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 398
- Erscheinungstermin: 17. August 2009
- Englisch
- Abmessung: 239mm x 178mm x 28mm
- Gewicht: 726g
- ISBN-13: 9780521112680
- ISBN-10: 0521112680
- Artikelnr.: 26551568
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Cambridge University Press
- Seitenzahl: 398
- Erscheinungstermin: 17. August 2009
- Englisch
- Abmessung: 239mm x 178mm x 28mm
- Gewicht: 726g
- ISBN-13: 9780521112680
- ISBN-10: 0521112680
- Artikelnr.: 26551568
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
Lawrence S. Meyers is Professor of Psychology at Sacramento State University. He teaches undergraduate and graduate courses in research design, data analysis, data interpretation, testing and measurement, and history and systems of psychology. He was coauthor of a textbook on research methods in the 1970s, has recently coauthored books on multivariate research design and analysis of variance, and has more than three dozen publications; some of his relatively recent work has been in areas such as measurement and testing and positive psychology. He received his doctorate from Adelphi University and worked on a National Science Foundation Postdoctoral Fellowship at the University of Texas, Austin, and Purdue University.
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.
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.
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.
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.