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

A00-240
  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Updated: Aug 28, 2026
  • Q & A: 100 Questions and Answers

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About SASInstitute A00-240Latest exam Dumps

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The average salary of a A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certified Expert in

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  • United State - 70,247 USD
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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%

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

2. Linear Regression - 20%

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

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 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
  • Screen variables for irrelevance and non-linear association using the CORR procedure
  • Identify the potential challenges when preparing input data for a model

5. Measure Model Performance - 25%

  • Establish effective decision cut-off values for scoring
  • 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
  • Apply the principles of honest assessment to model performance measurement

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

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