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

A00-240

Exam Code: A00-240

Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential

Updated: Nov 07, 2026

Q & A: 100 Questions and Answers

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

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