Statistical Data Mining Using SAS Applications
Seiten
2010
|
2nd edition
Crc Press Inc (Verlag)
978-1-4398-1075-0 (ISBN)
Crc Press Inc (Verlag)
978-1-4398-1075-0 (ISBN)
Compatible with SAS version 9, SAS Enterprise Guide, and SAS Learning Edition, this resource describes statistical data mining concepts and methods and includes 13 user-friendly SAS macro applications for performing complete data mining tasks. Each chapter emphasizes step-by-step instructions for using SAS macros and interpreting the results.
Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friendly data mining SAS tools. Integrating the statistical and graphical analysis tools available in SAS systems, the book provides complete statistical data mining solutions without writing SAS program codes or using the point-and-click approach. Each chapter emphasizes step-by-step instructions for using SAS macros and interpreting the results. Compiled data mining SAS macro files are available for download on the author’s website. By following the step-by-step instructions and downloading the SAS macros, analysts can perform complete data mining analysis fast and effectively.
New to the Second Edition—General Features
Access to SAS macros directly from desktop
Compatible with SAS version 9, SAS Enterprise Guide, and SAS Learning Edition
Reorganization of all help files to an appendix
Ability to create publication quality graphics
Macro-call error check
New Features in These SAS-Specific Macro Applications
Converting PC data files to SAS data (EXLSAS2 macro)
Randomly splitting data (RANSPLIT2)
Frequency analysis (FREQ2)
Univariate analysis (UNIVAR2)
PCA and factor analysis (FACTOR2)
Multiple linear regressions (REGDIAG2)
Logistic regression (LOGIST2)
CHAID analysis (CHAID2)
Requiring no experience with SAS programming, this resource supplies instructions and tools for quickly performing exploratory statistical methods, regression analysis, logistic regression multivariate methods, and classification analysis. It presents an accessible, SAS macro-oriented approach while offering comprehensive data mining solutions.
Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friendly data mining SAS tools. Integrating the statistical and graphical analysis tools available in SAS systems, the book provides complete statistical data mining solutions without writing SAS program codes or using the point-and-click approach. Each chapter emphasizes step-by-step instructions for using SAS macros and interpreting the results. Compiled data mining SAS macro files are available for download on the author’s website. By following the step-by-step instructions and downloading the SAS macros, analysts can perform complete data mining analysis fast and effectively.
New to the Second Edition—General Features
Access to SAS macros directly from desktop
Compatible with SAS version 9, SAS Enterprise Guide, and SAS Learning Edition
Reorganization of all help files to an appendix
Ability to create publication quality graphics
Macro-call error check
New Features in These SAS-Specific Macro Applications
Converting PC data files to SAS data (EXLSAS2 macro)
Randomly splitting data (RANSPLIT2)
Frequency analysis (FREQ2)
Univariate analysis (UNIVAR2)
PCA and factor analysis (FACTOR2)
Multiple linear regressions (REGDIAG2)
Logistic regression (LOGIST2)
CHAID analysis (CHAID2)
Requiring no experience with SAS programming, this resource supplies instructions and tools for quickly performing exploratory statistical methods, regression analysis, logistic regression multivariate methods, and classification analysis. It presents an accessible, SAS macro-oriented approach while offering comprehensive data mining solutions.
George Fernandez is a professor of applied statistical methods and the director of the Center for Research Design and Analysis at the University of Nevada in Reno.
Data Mining: A Gentle Introduction. Preparing Data for Data Mining. Exploratory Data Analysis. Unsupervised Learning Methods. Supervised Learning Methods: Prediction. Supervised Learning Methods: Classification. Advanced Analytics and Other SAS Data Mining Resources. Appendices. Index.
| Erscheint lt. Verlag | 29.6.2010 |
|---|---|
| Reihe/Serie | Chapman & Hall/CRC Data Mining and Knowledge Discovery Series |
| Zusatzinfo | 164 Tables, black and white; 151 Illustrations, black and white |
| Verlagsort | Bosa Roca |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 793 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| ISBN-10 | 1-4398-1075-3 / 1439810753 |
| ISBN-13 | 978-1-4398-1075-0 / 9781439810750 |
| Zustand | Neuware |
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