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Updated: Sep 10, 2026

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How much A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam cost

A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam cost is $180.

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

SASInstitute A00-240 Exam Overview:

Certification Vendor:SAS Institute
Exam Name:SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
Exam Number:A00-240
Real Exam Qty:60 scored questions (+ up to 5 unscored questions)
Related Certifications:SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling
Exam Format:Short Answer, Multiple Choice
Exam Duration:110 minutes
Passing Score:68%
Available Languages:English
Certificate Validity Period:No expiration specified by SAS
Exam Price:USD 180
Sample Questions:SASInstitute A00-240 Sample Questions
Exam Way:Pearson VUE testing centers and SAS-authorized online exam delivery where available.
Pre Condition:No formal prerequisite exam is required. Candidates should have experience using SAS/STAT software for statistical analysis, regression modeling and predictive analytics.
Official Syllabus URL:https://www.sas.com/en_gb/certification/credentials/advanced-analytics/statistical-business-analyst.html

What is the duration, language, and format of A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

  • Length of Examination: 120 minutes
  • Passing score: 68% (Must achieve score of 68 percent correct to pass)
  • Language: Czech, simplified Chinese, traditional Chinese, Dutch, English (UK), English (US), French, German, Indonesian, Italian, Japanese, Korean, Polish, Portuguese, Portuguese (Brazil), Russian, Slovak, Spanish, Spanish (Latin America), Thai, Turkish, and Vietnamese
  • Number of Questions: 60 multiple-choice and short-answer questions(In addition to the 60 scored items, there may be up to five unscored items)
  • Format: Multiple choices, multiple answers , short answers

How to book A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exams

The registration for the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam follows the steps given below.

  • Step 1 : Visit to website Pearson VUE
  • Step 2 : Navigate To Certifications
  • Step 3 : Search for the exam name A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling
  • Step 4 : Book the exam.

SASInstitute A00-240 Exam Syllabus Topics:

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

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