SASInstitute 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: Aug 12, 2026     Q & A: 100 Questions and Answers

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Topics of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Dumps will include the following topics:

1. ANOVA - 10%

  • Perform ANOVA post hoc test to evaluate treatment effect
  • Analyze differences between population means using the GLM and TTEST procedures
  • Detect and analyze interactions between factors
  • Verify the assumptions of ANOVA

2. Linear Regression - 20%

  • Assess the validity of a given regression model through the use of diagnostic and residual analysis
  • Fit a multiple linear regression model using the REG and GLM procedures
  • Use the REG or GLMSELECT procedure to perform model selection
  • Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models

3. Logistic Regression - 25%

  • Score new data sets using the LOGISTIC and PLM procedures
  • Interpret the output of the LOGISTIC procedure
  • Perform logistic regression with the LOGISTIC procedure
  • Optimize model performance through input selection

4. Prepare Inputs for Predictive Model Performance - 20%

  • Screen variables for irrelevance and non-linear association using the CORR procedure
  • Screen variables for non-linearity using empirical logit plots
  • Use the DATA step to manipulate data with loops, arrays, conditional statements and functions
  • Improve the predictive power of categorical inputs
  • Identify the potential challenges when preparing input data for a model

5. Measure Model Performance - 25%

  • Establish effective decision cut-off values for scoring
  • Apply the principles of honest assessment to model performance measurement
  • Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection
  • Assess classifier performance using the confusion matrix
  • Model selection and validation using training and validation data

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
Analysis of Variance (ANOVA)10%- Analyze factor interactions
- Perform post-hoc tests
- Use PROC GLM for ANOVA
- Assess ANOVA assumptions
Logistic Regression25%- Build models using PROC LOGISTIC
- Select and optimize input variables
- Interpret odds ratios and model coefficients
- Score new datasets with LOGISTIC and PLM
Prepare Inputs for Predictive Modeling20%- Screen variables with CORR procedure and empirical logit plots
- Transform categorical variables
- Manipulate data using DATA step
- Identify data preparation challenges
Measure and Evaluate Model Performance25%- Create and interpret ROC, lift, and gains charts
- Apply honest assessment principles
- Validate models with training/validation data
- Determine optimal decision cut-off values
- Use confusion matrices and classification metrics
Linear Regression20%- Conduct residual and diagnostic analysis
- Fit multiple linear regression models
- Interpret REG, GLM, and PLM procedure output
- Perform model selection with GLMSELECT

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