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Last Updated: Sep 09, 2026
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The SAS Institute is a leading global software company that provides innovative analytics and business intelligence solutions designed to transform data into actionable insights. One of the most popular products offered by SAS is SAS 9, which provides advanced statistical analysis capabilities. For individuals who want to demonstrate their proficiency in SAS 9, the SAS Institute offers the A00-240 certification exam, also known as the SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential.
The SAS Certified Statistical Business Analyst using SAS 9: Regression and Modeling Credential is a certification program provided by the SAS Institute. It is designed to validate the skills and knowledge of statistical analysts who use SAS software to perform data analysis, model building, and regression analysis. SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential certification exam focuses on essential statistical concepts and SAS programming skills, preparing candidates to work effectively with SAS to analyze data and develop models.
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The SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential certification exam covers important topics such as multiple regression, general linear models, logistic regression, and variable selection techniques. A00-240 exam is structured in such a way that it challenges participants to demonstrate their competence in working with data sets, developing and validating predictive models, and interpreting statistical results. With this certification, you can build a foundation for future SAS certifications, such as the SAS Certified Data Scientist and the SAS Certified Advanced Analytics Professional.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Measure Model Performance | 25% | - Decision Optimization
|
| Topic 2: ANOVA | 10% | - ANOVA Concepts and Assumptions
|
| Topic 3: Prepare Inputs for Predictive Model Performance | 20% | - Data Preparation
|
| Topic 4: Logistic Regression | 25% | - Develop Logistic Models
|
| Topic 5: Linear Regression | 20% | - Build Regression Models
|
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