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SASInstitute A00-273 Exam Syllabus Topics:

SectionWeightObjectives
Building and Assessing Regression-Type Models41%- Generalized Linear Models
  • 1. Evaluate predictive performance
  • 2. Select distributions and link functions
  • 3. Interpret model results
- Linear Regression
  • 1. Assess model fit
  • 2. Interpret parameter estimates
  • 3. Build linear regression models
- Advanced Regression Techniques
  • 1. Use interaction effects
  • 2. Perform generalized additive modeling
  • 3. Perform nonparametric logistic regression
SAS Visual Statistics Cross-Functional Tasks18%- Data Filtering and Group-By Analysis
  • 1. Apply filters to models and visualizations
  • 2. Interpret group-by model results
  • 3. Use interactive group-by modeling
  • 4. Review measure details
- Data Preparation
  • 1. Combine category levels
  • 2. Replace invalid data with missing values
  • 3. Create dummy variables
  • 4. Transform variables
  • 5. Impute variables
  • 6. Create aggregated measures
  • 7. Manage explorations and visualizations
Building and Assessing Segmentation Models32%- Cluster Analysis
  • 1. Modify cluster properties
  • 2. Create and use cluster identifiers
  • 3. Assign analysis roles
  • 4. Configure k-means clustering
  • 5. Perform unsupervised segmentation
- Logistic Regression Modeling
  • 1. Configure event levels and response variables
  • 2. Select appropriate link functions
  • 3. Build logistic regression models
  • 4. Apply variable selection methods
- Model Assessment
  • 1. Interpret fit statistics
  • 2. Analyze ROC and Lift charts
  • 3. Evaluate misclassification results
  • 4. Review residual and influence diagnostics
Model Comparison and Scoring9%- Model Scoring
  • 1. Export score code
  • 2. Generate score code
  • 3. Apply models to new data
- Model Comparison
  • 1. Compare candidate models
  • 2. Select champion models
  • 3. Interpret comparison statistics

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