SASInstitute : A00-240 Questions & Answers

Last Updated: Aug 18, 2026

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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.

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

Preparation Guide for A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Introduction

SAS (previously “Statistical Analysis System”) may be a package suite designed by SAS Institute for advanced analytics, variable analyses, business intelligence, knowledge management, and prognosticative analytics.

A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling exam is administered by SAS and Pearson VUE. has created a track for IT professionals to certify as business analyst on SAS. This certification program provides SAS professionals a way to demonstrate their skills. The assessment is based on a rigorous exam using industry standard methodology to determine whether a candidate meets SAS's proficiency standards.

SAS® Certified Statistical Business Analyst for SAS®9 this credential is for professionals who use SAS/STAT® software to conduct and interpret complex statistical data analysis.

In this guide, we will cover the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam, A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certified professional's salary and all aspects of the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification.

The SAS international Certification Program currently issues versioned accreditation that don't lapse.The version is indicated in the credential name.

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

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SASInstitute A00-240 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Measure Model Performance25%- Validation and Selection
  • 1. Compare and select predictive models
  • 2. Perform model validation using training and validation data
- Performance Visualization
  • 1. Create and interpret gains charts
  • 2. Create and interpret ROC charts
  • 3. Create and interpret lift charts
- Decision Optimization
  • 1. Establish effective decision cutoff values
  • 2. Evaluate scoring strategies
- Model Assessment
  • 1. Assess classifier performance using confusion matrices
  • 2. Apply principles of honest assessment
Topic 2: Prepare Inputs for Predictive Model Performance20%- Data Preparation
  • 1. Use loops, arrays, functions and conditional statements
  • 2. Manipulate data using DATA step programming
  • 3. Identify challenges in preparing model input data
- Variable Engineering and Screening
  • 1. Screen variables for irrelevance
  • 2. Improve predictive power of categorical variables
  • 3. Identify nonlinear associations using CORR procedure
  • 4. Use empirical logit plots for nonlinearity detection
Topic 3: Logistic Regression25%- Interpret and Deploy Models
  • 1. Score new data sets using LOGISTIC and PLM procedures
  • 2. Interpret LOGISTIC procedure output
- Develop Logistic Models
  • 1. Optimize model performance through input selection
  • 2. Perform logistic regression using the LOGISTIC procedure
Topic 4: ANOVA10%- ANOVA Concepts and Assumptions
  • 1. Verify ANOVA assumptions
  • 2. Identify appropriate ANOVA methods
- ANOVA Analysis
  • 1. Detect and analyze factor interactions
  • 2. Evaluate treatment effects
  • 3. Analyze differences between population means using GLM and TTEST procedures
  • 4. Perform post hoc tests
Topic 5: Linear Regression20%- Interpret Regression Results
  • 1. Interpret REG, PLM and GLM output
  • 2. Evaluate parameter estimates
- Model Selection and Diagnostics
  • 1. Conduct residual and diagnostic analysis
  • 2. Perform model selection using REG or GLMSELECT
  • 3. Assess model validity
- Build Regression Models
  • 1. Fit multiple linear regression models
  • 2. Use REG and GLM procedures

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