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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What does adding an interaction effect in linear regression modeling allow you to capture?

A) The presence of outliers in the data
B) The effect of missing data on the model
C) The multicollinearity among predictors
D) The joint impact of two or more predictors on the response variable

2. When investigating leaf nodes in a decision tree, what does it reveal about the data?

A) The feature values associated with each leaf node
B) The decision rules leading to each leaf node
C) The class labels assigned to each leaf node
D) The statistical significance of each leaf node

3. When exporting score code, what information is typically included in the code?

A) The model parameters and coefficients
B) The entire training dataset
C) Instructions for preprocessing new data
D) The distribution of the response variable

4. Which statement is true for the Informative Missingness property in SAS Visual Statistics?

A) Missing values are imputed and indicator variables are created for missing predictors.
B) Missing values are flagged on diagnostic plots.
C) A table of missingness patterns for the predictor variables is displayed in the model output.
D) The user is prompted to fill in a value to impute for missing predictor variables.

5. When specifying Cluster Roles for Cluster Analysis in SAS Visual Statistics, which condition is correct?

A) At least two variables are required.
B) Category items are not allowed.
C) Interaction items are allowed.
D) A target variable is required.

Solutions: