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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. In the context of linear regression, what does the term "linearity" refer to?

A) The use of polynomial functions for modeling
B) The requirement for variables to be categorical
C) The use of a straight line to model relationships
D) The absence of any relationship between variables

2. Interactions can be created and added to a linear regression model.
Which statement is true about interactions?

A) An interaction can be created for a squared category variable.
B) Each interaction is limited to 3 effects or fewer.
C) The maximum number of interactions allowed in a model is 3.
D) Measures and categories can be combined to create an interaction.

3. Why are decision trees a useful technique for segmentation?

A) Trees split the response into homogeneous groups, while maximizing the difference in the response of the groups.
B) Trees split the response into heterogeneous groups, while minimizing the difference in the response of the groups.
C) Trees split data into smaller cells which are decreasingly "pure".
D) Trees treat each split cell dependently based on earlier split decisions.

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

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

5. In SAS Visual Analytics, what can you use to choose the best fitting group-by model?

A) Visualization of model residuals
B) Fit statistics such as AIC and BIC
C) Group-by variable with the highest p-value
D) Variable Importance

Solutions: