Other SAS Modules
SAS (Statistical Analysis System) is a software suite that provides a wide range of modules for different purposes.
Here are some additional SAS modules beyond the core components:
- SAS/STAT: This module offers a comprehensive set of statistical procedures for data analysis, including regression analysis, analysis of variance, multivariate analysis, survival analysis, and more.
- SAS/GRAPH: This module provides tools for creating and customizing high-quality graphs and charts, allowing users to visualize their data effectively.
- SAS/ETS: This module focuses on econometric and time series analysis, offering various techniques for forecasting, modeling, and analyzing economic and financial data.
- SAS/OR: This module is designed for operations research, optimization, and simulation tasks. It includes solvers for linear programming, nonlinear programming, network optimization, and discrete event simulation.
- SAS/IML: This module provides an interactive matrix language that allows users to perform matrix computations, statistical analysis, and customized modeling.
- SAS/Enterprise Miner: This module is a data mining and predictive modeling tool that enables users to discover patterns, build predictive models, and make informed business decisions.
- SAS/Text Miner: This module focuses on text mining and text analytics, allowing users to extract valuable insights and patterns from unstructured text data.
- SAS/Forecast Studio: This module offers an interactive interface for creating and managing forecasting models. It includes automated model selection, validation, and performance monitoring capabilities.
- SAS/ACCESS: This module provides connectivity to various external data sources such as databases (e.g., Oracle, SQL Server) and file formats (e.g., Excel, CSV), allowing users to import, export, and manipulate data from different systems.
- SAS/ETS Enterprise Miner Integration Node: This module integrates SAS/ETS procedures into SAS Enterprise Miner, enabling users to incorporate advanced econometric and time series analysis techniques into their predictive modeling workflows.
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