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





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