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SAS/STAT® Software

State-of-the-art statistical analysis software for making new discoveries.

From traditional analysis of variance and linear regression to Bayesian inference and high-performance modeling tools for massive data, SAS/STAT meets both specialized and enterprisewide statistical needs. You get proven techniques that produce accurate results, now and in the future.


Apply the latest statistical techniques to any size of data.

With an accelerated release schedule, SAS/STAT keeps pace with new methods from the rapidly expanding field of statistics. The software includes exact techniques for small data sets, high-performance statistical modeling tools for large data tasks and modern methods for analyzing data with missing values.

Take advantage of our technical support and web user communities.

Have a question and need answers quickly? Our technical support is staffed by highly experienced statisticians who provide a level of service and knowledge rarely found with other software vendors. You can also use our web user communities to ask questions and share experiences.

Rely on validated algorithms.

SAS has nearly four decades of experience developing advanced statistical analysis software and an established reputation for delivering superior, reliable results. You can produce code that is easily documented and verified to meet corporate and governmental compliance requirements.

Simplify with a single environment.

The software is integrated, enabling you to access and manage data, build and deploy statistical models, and readily understand your results using hundreds of built-in graphs. Metadata is stored in a centralized repository, so it’s easy to incorporate SAS/STAT models with other SAS solutions.



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  • Analysis of variance
  • Bayesian analysis
  • Categorical data analysis
  • Causal inference
  • Cluster analysis
  • Descriptive statistics
  • Discriminant analysis
  • Distribution analysis
  • Exact inference
  • Finite mixture models
  • Group sequential design and analysis
  • High performance
  • Longitudinal data analysis
  • Market research
  • Missing data analysis
  • Mixed models
  • Model selection
  • Multivariate analysis
  • Nonparametric analysis
  • Nonparametric regression
  • Post processing
  • Power and sample size
  • Predictive modeling
  • Psychometric analysis
  • Quantile regression
  • Regression
  • Robust regression
  • Spatial analysis
  • Standardization
  • Statistical graphics
  • Structural equations
  • Survey sampling and analysis
  • Survival analysis
  • And more!
New Zealand Ministry of Health
SAS is the only tool that is able to deal with the amount of number crunching that we require. Some of the data sets we use are very large with more than 1 million rows of data per month. Sometimes we need to go back 10 years, so we're looking at working with over 100 million rows of data. SAS is the best tool to enable this.
Couple looking at monitor

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