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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Building and Assessing Regression-type Models | 41% | - Perform linear regression modeling - Explain concepts of linear models - Perform nonparametric logistic regression modeling - Perform generalized additive modeling - Assess model fit and diagnostics - Perform generalized linear regression modeling |
| Building and Assessing Segmentation Models | 28% | - Perform supervised segmentation using decision trees - Perform unsupervised segmentation using cluster analysis - Analyze and interpret cluster results - Assess and interpret decision tree performance |
| Model Comparison and Scoring | 9% | - Apply models to score new data - Compare multiple models using fit statistics |
| SAS Visual Statistics Cross-functional Tasks | 22% | - Prepare data using SAS Visual Analytics - Filter data used for a model - Perform model validation - Use interactive group-by functionality |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
When interpreting an Influence plot, what does it typically show?
- A. The relationship between the response variable and the intercept term
- B. The effect of each predictor variable on the response
- C. The interaction between two predictor variables
- D. The distribution of residuals in the model
Correct Answer: B 🗳️
In linear regression, what does a high p-value for a predictor variable suggest?
- A. The predictor is a categorical variable.
- B. The predictor is highly significant for the model.
- C. The predictor has a strong linear relationship with the response.
- D. The predictor is not relevant for the model.
Correct Answer: D 🗳️
How is the KS Statistic typically used when interpreting an ROC chart?
- A. To evaluate the overall performance of a classification model
- B. To measure the area under the ROC curve
- C. To assess the balance between sensitivity and specificity
- D. To identify the optimal prediction cut-off threshold
Correct Answer: C 🗳️
Why are decision trees a useful technique for segmentation?
- A. Trees split data into smaller cells which are decreasingly "pure".
- B. Trees treat each split cell dependently based on earlier split decisions.
- C. Trees split the response into heterogeneous groups, while minimizing the difference in the response of the groups.
- D. Trees split the response into homogeneous groups, while maximizing the difference in the response of the groups.
Correct Answer: D 🗳️
When examining the summary table for group-by processing, what information can you find?
- A. The standard deviation of the target variable for each group
- B. The mean value of the target variable for each group
- C. The distribution of the group-by variable
- D. The number of observations in each group
Correct Answer: A,B,D 🗳️
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