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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What is the primary purpose of scoring functionality in SAS Visual Statistics?

A) To assess the distribution of predictor variables
B) To select the best model for a given dataset
C) To generate code for deploying models in production
D) To evaluate model performance on a test dataset

2. Refer to the Parallel Coordinates Plot shown on the Exhibit.

Which two statements about cluster 0 in the Parallel Coordinates Plot are correct? (Choose two.)

A) It contains the most observations.
B) In relation to the other clusters, it consists of people whose house values are lower.
C) In relation to the other clusters, it consists of people who are younger.
D) In relation to the other clusters, it consists of people from the lower income group.

3. What is unsupervised classification in the context of cluster analysis?

A) Assigning predefined labels to data points
B) Creating a scatter plot of data points
C) Grouping similar data points together without predefined labels
D) Using a decision tree for data classification

4. 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) Select View Measure Details within the Actions menu to the right of the dataset name.
B) Create aggregated measures using the Min and Max aggregations.
C) Create a calculated item subtracting the Min aggregation from the Max aggregation.
D) Select a histogram object for each measure.

5. Refer to the exhibits:


An analyst is evaluating which model to use.
What changed from Comparison 1 to Comparison 2 to select a different champion model?

A) Prediction Cutoff reduced from .5 to .19
B) Percentile changed from 5th percentile to 40th percentile
C) Misclassification was used instead of Cumulative Lift
D) Analyst clicked on Model 2 to highlight it

Solutions: