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SASInstitute A00-480 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Statistical Foundations of Machine Learning | 18-24% | - Model performance metrics - Bias-variance trade-off - Cross-validation techniques - Overfitting and model complexity |
| Topic 2: Statistics and Machine Learning | 9-12% | - Relationship between statistical methods and machine learning |
| Topic 3: Fundamental Statistical Concepts | 17-21% | - Descriptive statistics and distributions - Probability concepts - Data types and measurement scales - Hypothesis testing and confidence intervals |
| Topic 4: Explanatory Modeling Using Linear Regression | 18-24% | - Simple and multiple linear regression - Model assumptions and diagnostics - Goodness of fit measures - Interpretation of coefficients and output |
| Topic 5: Predictive Modeling Using Logistic Regression | 25-31% | - Binary logistic regression model - Interpretation of odds ratios - Classification metrics and model evaluation - Model building and variable selection |
