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Last Updated: Aug 01, 2026
No. of Questions: 190 Questions & Answers with Testing Engine
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| Section | Weight | Objectives |
|---|---|---|
| Building and Assessing Segmentation Models | 28% | - Perform supervised segmentation using decision trees - Assess and interpret decision tree performance - Analyze and interpret cluster results - Perform unsupervised segmentation using cluster analysis |
| SAS Visual Statistics Cross-functional Tasks | 22% | - Perform model validation - Filter data used for a model - Use interactive group-by functionality - Prepare data using SAS Visual Analytics |
| Model Comparison and Scoring | 9% | - Apply models to score new data - Compare multiple models using fit statistics |
| Building and Assessing Regression-type Models | 41% | - Assess model fit and diagnostics - Perform generalized additive modeling - Explain concepts of linear models - Perform linear regression modeling - Perform generalized linear regression modeling - Perform nonparametric logistic regression modeling |
1. What is one advantage of using SAS Studio to score new data with exported score code?
A) It automatically optimizes the scoring process.
B) It requires no additional software installation.
C) It allows for direct integration with Hadoop clusters.
D) It provides advanced visualization capabilities.
2. When assigning variable roles for a decision tree, which role typically represents the target variable you want to predict?
A) Predictor
B) Input
C) Splitter
D) Output
3. You would like to see the minimum and maximum values for all of your measures so that you can filter variables as needed.
Which is the most efficient way to do that?
A) Create a calculated item subtracting the Min aggregation from the Max aggregation.
B) Select a histogram object for each measure.
C) Select View Measure Details within the Actions menu to the right of the dataset name.
D) Create aggregated measures using the Min and Max aggregations.
4. What are the roles that can be assigned in a generalized linear model (GLM)?
A) Predictor
B) Offset
C) Target
D) Intercept
5. Refer to the exhibit:
An economist is predicting demand using a linear regression model.
If all of the effect variables equal 1, what is the predicted demand?
A) 352.405432
B) 352.415433
C) 352.454433
D) 362.415133
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: A,B,C | Question # 5 Answer: B |
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