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

A00-240 real exams

Exam Code: A00-240

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

Updated: Sep 13, 2026

Q & A: 100 Questions and Answers

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Who should take the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam

Individuals should pursue the A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam if they want to demonstrate their expertise and ability to access and manage data to perform queries and analyses from A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification

  • Business Analyst
  • Stastical Analyst, or
  • Anyone writing & interested in Statistical Business Analysis

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

  • 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
  • Length of Examination: 120 minutes
  • Format: Multiple choices, multiple answers , short answers
  • Passing score: 68% (Must achieve score of 68 percent correct to pass)
  • 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)

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

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A00-240 exam dumps

A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification Path

The A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Certification is one of the highest level of certification mainly focussing to the Advanced statistical analysis.

if you pass your exam and meet all requirements for a credential, you will receive an e-mail from SAS within 72 business hours with instructions providing access to your certificate and logo through the SAS Certification Manager. You will also receive an email from Acclaim with access to your digital badge. For questions regarding access to either of these, please visit SAS Website.

SASInstitute A00-240 Exam Syllabus Topics:

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

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