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

SASInstitute A00-226 test insides dumps
  • Exam Code: A00-226
  • Exam Name: SAS Text Analytics, Time Series, Experimentation, and Optimization
  • Updated: Aug 04, 2026
  • Q & A: 0 Questions and Answers

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SASInstitute A00-226 Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: 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
          Topic 2: Experimentation and Incremental Response Models20%- Experimental Design
          • 1. Design of Experiments (DOE) principles
            • 2. Factorial vs OFAT designs
              - Incremental Response Modeling
              • 1. Net Information Value (NIV) and WOE concepts
                • 2. Treatment vs control group analysis
                  - Business Experimentation
                  • 1. Marketing campaign response modeling
                    • 2. Nuisance variable control and blocking
                      Topic 3: Text Analytics30%- 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
                              - Text Processing and Modeling
                              • 1. Tokenization, parsing, and feature extraction
                                • 2. Topic modeling and clustering
                                  Topic 4: Time Series30%- Time Series Fundamentals
                                  • 1. Stationarity and transformations
                                    • 2. Components: trend, seasonality, noise, cycle
                                      - Time Series Modeling
                                      • 1. Unobserved components models
                                        • 2. ARIMA and ARIMAX models
                                          • 3. Exponential smoothing models
                                            - Forecasting and Evaluation
                                            • 1. Forecast accuracy metrics and validation
                                              • 2. Holdout sample evaluation

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