SAS/STAT review
A broad SAS toolkit for organizations that need advanced statistical procedures.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
SAS/STAT is statistical analysis software for researchers, analysts and organizations that need a broad set of formal procedures. Its scope spans analysis of variance, linear models, regression, Bayesian inference, categorical data, survival analysis, missing-data methods and predictive modeling. The product is aimed at organizations of different sizes, from small teams to enterprise groups, that need established methods for analyzing both small datasets and large-scale statistical models.
The procedure depth is its central strength. Regression coverage includes least-squares and quantile regression, while Bayesian work includes MCMC procedures. Survival analysis supports proportional hazards and accelerated failure time models, and missing-data workflows include multiple imputation. Predictive modeling adds trees and model selection, while built-in statistical charts and graphs can be customized. This combination suits analysts who need several analytical approaches within one SAS environment rather than a single-purpose testing tool.
SAS/STAT pricing is handled through a sales contact, so organizations should expect a vendor-led purchasing process. SAS describes the software as running across major computing platforms, supporting use in varied computing environments. The breadth is valuable for research programs with varied methods, but may be more than a team needs for occasional or narrowly defined analyses. Organizations seeking deep SAS procedures should consider SAS/STAT; teams prioritizing open-source distribution or a tightly focused, lightweight workflow may prefer another statistical analysis product.
SAS/STAT pros and cons
- Where it wins
- Covers ANOVA, regression, Bayesian, survival and missing-data methods
- Includes predictive modeling, categorical analysis and customizable charts
- Supports statistical work across small datasets and large-scale modeling
- Where it doesn't
- Pricing requires a sales conversation instead of a posted rate
- Broad procedure coverage may exceed the needs of simple analyses
- Proprietary licensing does not support open-source distribution models
SAS/STAT fact sheet, pricing and score →
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