- Exam Code: A00-485
- Exam Name: Modeling Using SAS Visual Statistics
- Updated: Jul 31, 2026
- Q & A: 190 Questions and Answers
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| Section | Weight | Objectives |
|---|---|---|
| SAS Visual Statistics Cross-functional Tasks | 22% | - Use interactive group-by functionality - Filter data used for a model - Perform model validation - Prepare data using SAS Visual Analytics |
| Building and Assessing Regression-type Models | 41% | - Assess model fit and diagnostics - Explain concepts of linear models - Perform nonparametric logistic regression modeling - Perform generalized linear regression modeling - Perform linear regression modeling - Perform generalized additive modeling |
| Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
| Building and Assessing Segmentation Models | 28% | - Analyze and interpret cluster results - Perform unsupervised segmentation using cluster analysis - Perform supervised segmentation using decision trees - Assess and interpret decision tree performance |
1. What does adding an interaction effect in linear regression modeling allow you to capture?
A) The effect of missing data on the model
B) The multicollinearity among predictors
C) The joint impact of two or more predictors on the response variable
D) The presence of outliers in the data
2. When reviewing Measure Details in SAS Visual Analytics, what information can you find related to measures?
A) Measure name and label
B) Measure format and informat
C) Measure calculation method
D) Measure data type
3. When performing decision tree analysis in SAS Visual Statistics, how does the property setting for
"include missing" modify the usage of missing values within categorical discrete predictors?
A) assigns its own level
B) assigns the smallest available machine value
C) imputes the median of the predictor's known values
D) imputes the mean of the predictor's known values
4. When specifying Cluster Roles for Cluster Analysis in SAS Visual Statistics, which condition is correct?
A) Category items are not allowed.
B) At least two variables are required.
C) Interaction items are allowed.
D) A target variable is required.
5. Refer to the exhibits:
Exhibit 1:
Exhibit 2:
An analyst has created a cluster model based on the settings in Exhibit 1 and chose to derive a cluster ID variable.
Why are there 5 cluster IDs in Exhibit 2 based on these settings?
A) There are observations with missing values.
B) Parallel Coordinates Visible Roles setting is 5.
C) Cluster Matrix Visible Roles setting is 5.
D) Variable Standardization has been chosen.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A,B,D | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A |
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