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

"SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential", also known as A00-240 exam, is a SASInstitute Certification. With the complete collection of questions and answers, PrepAwayPDF has assembled to take you through 100 Q&As to your A00-240 Exam preparation. In the A00-240 exam resources, you will cover every field and category in SAS Institute Systems Certification Certification helping to ready you for your successful SASInstitute Certification.

  • Exam Code: A00-240
  • Exam Name: SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Certification Provider: SASInstitute
  • Corresponding Certification: SAS Institute Systems Certification
  • Updated: Sep 08, 2026
  • No. of Questions: 100 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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The benefits of obtaining A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling Exam Certification

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  • A00-240: Statistical Business Analysis improves reasoning power and promotes analytical thinking and research ability of appearing professional.
  • As there's a worldwide requirement for SAS experts, you've got the selection to use for employment in many alternative locations round the world.
  • Learning SAS won't cause you to abandon the previous data formats acknowledged by you like Oracle and DB2.
  • You'll simply connect with the worldwide network of SAS consultants and users to exchange knowledge and concepts.
  • A00-240: Statistical Business Analysis Using SAS®9:Regression and Modeling certified professionals will be confident and stand different from others as their skills are more trained than non-certified professionals.
  • Freshers will get spectacular pay package and dealing professionals will get guaranteed profession advancement through the SAS accreditation courses.

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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.

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

SASInstitute A00-240 Exam Syllabus Topics:

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

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