By George Fernandez
Statistical info Mining utilizing SAS functions, moment Edition describes statistical info mining ideas and demonstrates the beneficial properties of straight forward facts mining SAS instruments. Integrating the statistical and graphical research instruments to be had in SAS structures, the booklet offers entire statistical information mining strategies with no writing SAS application codes or utilizing the point-and-click method. each one bankruptcy emphasizes step by step directions for utilizing SAS macros and examining the consequences. Compiled information mining SAS macro documents can be found for obtain at the author’s site. via following the step by step directions and downloading the SAS macros, analysts can practice entire info mining research quickly and effectively.
New to the second one Edition—General Features
- Access to SAS macros at once from computing device
- Compatible with SAS model nine, SAS company advisor, and SAS studying variation
- Reorganization of all support documents to an appendix
- Ability to create ebook caliber graphics
- Macro-call mistakes check
New positive factors in those SAS-Specific Macro Applications
- Converting laptop facts records to SAS facts (EXLSAS2 macro)
- Randomly splitting info (RANSPLIT2)
- Frequency research (FREQ2)
- Univariate research (UNIVAR2)
- PCA and issue research (FACTOR2)
- Multiple linear regressions (REGDIAG2)
- Logistic regression (LOGIST2)
- CHAID research (CHAID2)
Requiring no event with SAS programming, this source offers directions and instruments for fast appearing exploratory statistical tools, regression research, logistic regression multivariate tools, and category research. It provides an available, SAS macro-oriented technique whereas supplying finished information mining solutions.
Read Online or Download Statistical Data Mining Using SAS Applications, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) PDF
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Extra resources for Statistical Data Mining Using SAS Applications, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)