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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. When performing linear regression modeling, what is the primary goal of assessing multicollinearity among predictors?

A) To identify influential outliers
B) To calculate the coefficient of determination (R-squared)
C) To ensure that predictor variables are not highly correlated
D) To detect non-linear relationships

2. In SAS Visual Analytics, what can you use to exclude selections and filter data in a visualization?

A) Exclude option in filter dialogs
B) Filter containers
C) Filtering using the toolbar options
D) Interactive filters in the visualization

3. Refer to the exhibit:

Based on the Validation Data in the Model Comparison output which conclusions are valid? (Choose two.)

A) Decision Tree model would be selected at lift=20
B) Logistic Regression model would be selected at lift=20
C) Decision Tree model would be selected at lift=5
D) Logistic Regression model would be selected at lift=5

4. 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) Parallel Coordinates Visible Roles setting is 5.
B) Cluster Matrix Visible Roles setting is 5.
C) There are observations with missing values.
D) Variable Standardization has been chosen.

5. What is the purpose of applying a prediction cut-off in model assessment?

A) To divide the dataset into training and testing sets
B) To identify influential data points in the dataset
C) To calculate the p-values of predictor variables
D) To determine the optimal threshold for classifying outcomes

Solutions: