How to Use This Document
The examples given in this document are for using SAS under a Unix environment. We assume you are familiar with basic Unix commands and at least one of the editors available in Unix. We also assume you have basic statistical knowledge. This document is not intended to substitute for the vendor-supplied SAS documents. The term SAS refers to the software command language, and the basic command structure is the same across all platforms for SAS products.
This document is intended to introduce researchers to using SAS software from the Unix environment. At present there are several variations of the Unix system. University Information Technology Services (UITS) at Indiana University, Bloomington, offers such Unix-based operating systems as Solaris, and AIX. This document assumes you know the basics of UNIX computing. To learn more about Unix, see Getting Started with UNIX. You may also enroll in an UITS STEPS or PROSTEPS class by contacting the UITS IT Training & Education, which offers a Unix for Beginners class.
UITS supports SAS software on several timesharing Unix-like environments: AIX by IBM (the Research SP system computers; node aries05), and SunOS (Steel and Nations cluster). Graduate students and staff need a faculty sponsor for accounts on the research-only computers (SP system). Undergraduates are only eligible for accounts on Steel and the Nations cluster. If you want to set up an account on any of the timesharing comp uters, use the appropriate account generation system:
For more information related to the SAS System at IU, please visit our SAS Page.
What is SAS?
SAS is a software system for data analysis and management. In addition to data management facilities and general purpose statistical procedures (Base SAS), and SAS/STAT for statistical analyses. SAS includes the SAS/ETS procedures for econometric and time series analysis, the SAS/GRAPH procedures for color graphics, SAS/IML facilities for matrix manipulation.
The data management capabilities of SAS include:
- Reading data in almost any format.
- Reading, writing, combining multiple files.
- Convenient transformation of data and creation of new variables; elaborate looping and conditional transformation capabilities.
- Storing and using output from statistical procedures in the same run.
- Producing specially-formatted output for reports; printing mailing labels.
- Sorting data; subsetting data; analyzing multiple subsets of cases.
- Storing data and data documentation in SAS libraries.
The statistical capabilities of SAS include the following:
- Univariate descriptive statistics; univariate and multivariate frequency distributions; bar charts, star charts, pie charts, scatter plots, time plots.
- Standardization and ranking of observations; construction of scales.
- Linear probability models, loglinear contingency table models, logistic regression, repeated measurement analysis, probit models.
- Correlations, other measures of association for quantitative variables.
- Multiple regression, regression with linear constraints, stepwise regression; quadratic response-surface regression models; nonlinear regression; extensive regression diagnostics.
- T-tests, analysis of variance and covariance, analysis of nested designs, multivariate analysis of variance and covariance (including repeated measures); variance components models; ANOVA with ranks.
- Factor analysis with principle components analysis, canonical correlation analysis; cluster analysis. Life tables; fully parametric regression models for survival data.
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