SASInstitute A00-226 Exam : SAS Text Analytics, Time Series, Experimentation, and Optimization

  • Exam Code: A00-226
  • Exam Name: SAS Text Analytics, Time Series, Experimentation, and Optimization
  • Updated: Sep 01, 2026
  • Q & A: 0 Questions and Answers

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SASInstitute A00-226 Exam Syllabus Topics:

SectionWeightObjectives
Text Analytics30%- Text Processing and Modeling
  • 1. Topic modeling and clustering
    • 2. Tokenization, parsing, and feature extraction
      - Text Mining Data Preparation
      • 1. Import and merge text and structured datasets
        • 2. Create and prepare text data sources for analysis
          - Text Analytics Applications
          • 1. Text Rule Builder and SVD-based reduction
            • 2. Predictive modeling with text features
              Experimentation and Incremental Response Models20%- Business Experimentation
              • 1. Nuisance variable control and blocking
                • 2. Marketing campaign response modeling
                  - Experimental Design
                  • 1. Factorial vs OFAT designs
                    • 2. Design of Experiments (DOE) principles
                      - Incremental Response Modeling
                      • 1. Treatment vs control group analysis
                        • 2. Net Information Value (NIV) and WOE concepts
                          Time Series30%- Time Series Modeling
                          • 1. Unobserved components models
                            • 2. Exponential smoothing models
                              • 3. ARIMA and ARIMAX models
                                - Time Series Fundamentals
                                • 1. Stationarity and transformations
                                  • 2. Components: trend, seasonality, noise, cycle
                                    - Forecasting and Evaluation
                                    • 1. Holdout sample evaluation
                                      • 2. Forecast accuracy metrics and validation
                                        Optimization20%- Linear Programming
                                        • 1. OPTMODEL procedure usage
                                          • 2. Formulating optimization problems
                                            - Advanced Optimization Techniques
                                            • 1. Constraints, decision variables, and parameter modeling
                                              • 2. Data Envelopment Analysis (DEA)

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