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SAS-STAT Software

by SAS Institute · Since 1976
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Active1+ countriesCloud
Quick facts
VendorSAS Institute
Year launched1976
StatusActive
Location100 SAS Campus Drive, Cary, North Carolina 27513
Countries served1+
Languages8
Integrations
Free tier
Free trial
Contact salesYES

About SAS-STAT Software

SAS/STAT Software is a statistical analysis platform from SAS Institute that provides a comprehensive suite of statistical methods for data analysis. It combines data management, advanced analytics, and reporting capabilities to help users make informed decisions based on reliable insights. Designed for organizations of all sizes, it supports a variety of statistical techniques, ensuring reliable and precise results. Additionally, SAS/STAT integrates with the SAS Viya platform, improving its capabilities for modern analytics environments. Key capabilities: data management advanced analytics reporting statistical methods integration with SAS Viya Best for: data analysts and researchers that need capable statistical tools for conducting complex analyses.

SAS/STAT® Software is a comprehensive and powerful statistical analysis tool trusted by industry leaders worldwide. With nearly five decades of development, it offers an extensive library of over 100 prewritten procedures, providing capabilities for a vast array of statistical analyses, from analysis of variance and regression to more advanced methods such as Bayesian inference, survival analysis, and multivariate analysis. Its robust tools support both small datasets with exact inference and large, complex data requiring high-performance modeling, making it suitable for diverse research and enterprise needs. The user interface emphasizes clarity and ease of understanding by providing hundreds of customizable graphs and charts that help interpret results vividly. Metadata management in a centralized repository simplifies integration with other SAS solutions, enhancing workflows across advanced analytics platforms like SAS Viya and SAS Analytics Pro. The software is compatible across major computing platforms, ensuring scalability and accessibility, whether on-premise or in the cloud, enabling organizations to handle increasing data complexity efficiently. SAS/STAT’s functionality encompasses an array of advanced statistical techniques required across industries—such as healthcare, financial services, and scientific research—making it highly versatile.

Pros & Cons

What users like
  • +Excellent and comprehensive documentation
  • +Effective use of PROC procedures for streamlined statistical analysis
  • +Supports SQL coding and has powerful add-ons for reporting
  • +Log feature aids in debugging code
  • +Syntax is mostly not case-sensitive, easing code readability
  • +Widely respected in research and professional statistics fields
  • +Strong library of supporting books and resources
What users flag
  • Steep learning curve, especially for users familiar with other coding languages
  • Coding can be complex and unintuitive for beginners
  • Software bugs may require restarting the program
  • Data import and reading can be problematic

Features

Key features

Analysis of Variance
Enables detailed comparative studies of multiple groups or factors.
Bayesian Analysis
Facilitates probabilistic modeling for inference on complex data.
Cluster Analysis
Groups data points based on similarities for segmentation tasks.
Power & Sample Size
Assists in designing studies with sufficient statistical power.
Survival Analysis
Analyzes time-to-event data critical in clinical and risk studies.
Regression and Nonlinear Regression
Supports predictive modeling and curve fitting.
High-Performance Computing
Delivers fast, large-scale data processing for enterprise needs.

Additional features

Exact Inference
Provides precise statistical results for small or specialized datasets.
Structural Equations
Models complex relationships between variables.
Predictive Modeling
Creates accurate forecasts based on data patterns.
Quantile Regression
Analyzes different points in the data distribution.
Multivariate Analysis
Examines multiple variables simultaneously for comprehensive insights.
Survey Sampling & Analysis
Handles survey data with complex sampling designs.
Distribution Analysis
Investigates data distribution characteristics.
Missing Data Analysis
Addresses incomplete data to reduce bias.
Model Selection
Identifies best models based on statistical criteria.
Robust Regression
Supports analysis resistant to outliers and data anomalies.

Pricing

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Countries & Languages

1
Countries served
8
Interface languages
10
Billing currencies

Available in

All Countries.

Interface languages

EnglishFrenchGermanItalianSpanishPortugueseJapaneseChinese

Billing currencies

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