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| Section | Weight | Objectives |
|---|---|---|
| Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
| SAS Visual Statistics Cross-functional Tasks | 22% | - Perform model validation - Prepare data using SAS Visual Analytics - Use interactive group-by functionality - Filter data used for a model |
| Building and Assessing Segmentation Models | 28% | - Assess and interpret decision tree performance - Perform unsupervised segmentation using cluster analysis - Analyze and interpret cluster results - Perform supervised segmentation using decision trees |
| Building and Assessing Regression-type Models | 41% | - Perform generalized linear regression modeling - Perform nonparametric logistic regression modeling - Assess model fit and diagnostics - Perform generalized additive modeling - Explain concepts of linear models - Perform linear regression modeling |
In group-by modeling, when is the p-value for the group-by variable considered significant?
Correct Answer: C,D 🗳️
In model assessment, why might you need to assess residuals and other model diagnostics to choose an appropriate distribution and link function?
Correct Answer: A 🗳️
What is the purpose of setting Parallel Coordinate properties for a cluster in SAS Visual Statistics?
Correct Answer: D 🗳️
When filtering data for a model in SAS Visual Analytics, what can you do to exclude selections and filter data?
Correct Answer: A,B,C,D 🗳️
Which of the following are common distributions used in generalized linear models?
Correct Answer: A,B,C 🗳️
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