SASInstitute A00-240 Valid Test : SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential

  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Updated: Jul 14, 2026
  • Q&As: 100 Questions and Answers

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Who should take the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Individuals should pursue the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam if they want to demonstrate their expertise and ability to access and manage data to perform queries and analyses from A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification

  • Anyone writing & interested in Statistical Business Analysis
  • Stastical Analyst, or
  • Business Analyst

Reference: https://www.sas.com/en_us/certification/credentials/advanced-analytics/statistical-business-analyst.html

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Introduction to A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

According to SAS, SAS® Certified Statistical Business Analyst for SAS®9 this credentials signifies the upper echelon of SAS programmers who demonstrate a high level of proficiency in SAS® programming expertise.

A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Statistical Business Analyst in the Company.

A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling exam covers the basic and advanced concepts of variance analysis, linear and logistic regression, preparing inputs for predictive models and measuring model performance.

After passing this exam, candidates get a certificate from SAS that helps them to demonstrate their proficiency in A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling to their clients and employers.

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SASInstitute A00-240 Exam Syllabus Topics:

SectionObjectives
Topic 1: Logistic Regression- Binary logistic regression
- Model fit and diagnostics
Topic 2: Model Diagnostics and Validation- Influence and leverage
- Goodness-of-fit measures
Topic 3: Simple Linear Regression- Model assumptions and interpretation
- Residual analysis
- Estimation and inference
Topic 4: ANOVA and General Linear Models- GLM procedures in SAS
- One-way and multi-way ANOVA
Topic 5: Multiple Regression- Interaction effects
- Multicollinearity diagnostics
- Model building and selection

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