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The SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling credential, also known as the A00-240 exam, is a certification program offered by the SAS Institute. SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential certification is designed for professionals who use SAS software for data analysis, regression modeling, and predictive modeling. The program assesses the candidate's proficiency in SAS programming, statistical analysis, and data management.
Reference: https://www.sas.com/en_us/certification/credentials/advanced-analytics/statistical-business-analyst.html
To prepare for the SASInstitute A00-240 exam, candidates can take advantage of a range of resources provided by SAS, including training courses, practice exams, and study materials. The SAS website also provides a comprehensive list of exam objectives, which candidates can use to focus their study efforts.
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SASInstitute A00-240 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Analysis of Variance (ANOVA) | 10% | - Analyze factor interactions
- Assess ANOVA assumptions
- Use PROC GLM for ANOVA
- Perform post-hoc tests
|
| Prepare Inputs for Predictive Modeling | 20% | - Manipulate data using DATA step
- Transform categorical variables
- Identify data preparation challenges
- Screen variables with CORR procedure and empirical logit plots
|
| Measure and Evaluate Model Performance | 25% | - Determine optimal decision cut-off values
- Create and interpret ROC, lift, and gains charts
- Use confusion matrices and classification metrics
- Apply honest assessment principles
- Validate models with training/validation data
|
| Logistic Regression | 25% | - Select and optimize input variables
- Build models using PROC LOGISTIC
- Interpret odds ratios and model coefficients
- Score new datasets with LOGISTIC and PLM
|
| Linear Regression | 20% | - Perform model selection with GLMSELECT
- Fit multiple linear regression models
- Conduct residual and diagnostic analysis
- Interpret REG, GLM, and PLM procedure output
|