WIREs Computational Statistics / All Issues / Vol 3 Issue 1 (January 2011)
Robert N. Rodriguez
Author Spotlight on Robert N. Rodriguez>
Abstract SAS® software is a comprehensive set of integrated tools and solutions for accessing, managing, and analyzing data. SAS, which was formed as a company in 1976, is a leading developer of statistical software, which is widely used in academic, business, and government organizations. Since the 1980s, SAS has expanded its analytical software to include forecasting and econometrics, data mining, text mining, and operations research. SAS now builds on these components to provide software for business analytics and solutions for industry‐specific problems such as customer intelligence, fraud prevention, and risk management. This article describes the evolution of SAS as a company and overviews new directions in its analytical software. An example program illustrates key elements of SAS programming that are useful for statistical analysis. WIREs Comp Stat 2011 3 1–11 DOI: 10.1002/wics.131 This article is categorized under: Software for Computational Statistics > Software/Statistical Software
SAS/IML Studio session.
Parameter estimate distributions.
Coefficient progression for adaptive lasso.
Plots for assessing Markov chain convergence.
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Davenport, TH, Harris, JG, Morison, R. Analytics at Work. Boston: Harvard Business School Press; 2010.
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Stokes, M, Rodriguez, RN, Cohen, R. The Next Generation: SAS/STAT® 9.22. In: Proceedings of the SAS Global Forum 2010 Conference. Cary, NC: SAS Institute Inc. Available at http://support.sas.com/resources/papers/proceedings10/264‐2010.pdf; 2010.
Wicklin, R. Rediscovering SAS/IML® Software: modern data analysis for the practicing statistician. In: Proceedings of the SAS Global Forum 2010 Conference. Cary, NC: SAS Institute Inc. Available at http://support.sas.com/resources/papers/proceedings10/329‐2010.pdf; 2010.
Wicklin, R. Statistical Programming with SAS/IML Software. Cary, NC: SAS Institute Inc., 2010.
Wicklin, R. SAS Stat Studio: A Programming Environment for High‐End Data Analysts. In: Proceedings of the SAS Global Forum 2008 Conference. Cary, NC: SAS Institute Inc. Available at http://www2.sas.com/proceedings/forum2008/362‐2008.pdf; 2008.
Rodriguez, RN. Getting Started with ODS Statistical Graphics in SAS® 9.2—Revised 2009. Available at http://support.sas.com/rnd/app/papers/intodsgraph.pdf.
Heath, D. Effective Graphics Made Simple Using SAS/GRAPH® SG Procedures. In: Proceedings of the SAS Global Forum 2008 Conference. Cary, NC: SAS Institute Inc. Available at http://www2.sas.com/proceedings/forum2008/255‐2008.pdf; 2008.
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Burlew, MM, Michele, M. SAS Macro Programming Made Easy. 2nd ed. Cary, NC: SAS Institute Inc; 2006.
Carpenter, A. Carpenter`s Complete Guide to the SAS Macro Language. 2nd ed. Cary, NC: SAS Institute Inc.; 2004.
Cody, R. Learning SAS by Example: A Programmer`s Guide. Cary, NC: SAS Institute Inc.; 2007.
Delwiche, L, Slaughter, S. The Little SAS Book: A Primer. 4th ed. Cary, NC: SAS Institute Inc.; 2008.
Slaughter, S, Delwiche, L. The Little SAS Book for Enterprise Guide 4.2.Cary. NC: SAS Institute Inc.; 2010.
The following books provide introductions to SAS programming and basic uses of SAS software. Complete documentation for SAS software products is available at http://support.sas.com/documentation/index.html.
Burlew MM, Michele M. SAS Macro Programming Made Easy. 2nd ed. Cary, NC: SAS Institute Inc; 2006.
Carpenter A. Carpenter's Complete Guide to the SAS Macro Language. 2nd ed. Cary, NC: SAS Institute Inc.; 2004.
Cody R. Learning SAS by Example: A Programmer's Guide. Cary, NC: SAS Institute Inc.; 2007.
Delwiche L, Slaughter S. The Little SAS Book: A Primer. 4th ed. Cary, NC: SAS Institute Inc.; 2008.
Slaughter S, Delwiche L. The Little SAS Book for Enterprise Guide 4.2. Cary, NC: SAS Institute Inc.; 2010.
JMP statistical discovery software
Software for Computational Statistics > Software/Statistical Software
Rodriguez Robert N.. SAS. WIREs Comp Stat 2011, 3: 1-11. doi: 10.1002/wics.131