SASInstitute A00-226 real exam prep : SAS Text Analytics, Time Series, Experimentation, and Optimization

  • Exam Code: A00-226
  • Exam Name: SAS Text Analytics, Time Series, Experimentation, and Optimization
  • Updated: Aug 26, 2026
  • Q&As: 0 Questions and Answers

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SASInstitute A00-226 Exam Syllabus Topics:

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

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