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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Which statement is true about Decision Trees in SAS Visual Statistics

A) Decision trees cannot handle continuous dependent variables.
B) Decision trees cannot handle missing values.
C) Decision trees can be used for classification and estimation.
D) Decision trees can be used for outlier detection.

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

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

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

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

4. When interpreting an Influence plot, what does it typically show?

A) The distribution of residuals in the model
B) The effect of each predictor variable on the response
C) The relationship between the response variable and the intercept term
D) The interaction between two predictor variables

5. What is the primary purpose of imputing a variable in SAS Visual Analytics?

A) To create new variables
B) To remove missing values
C) To aggregate data
D) To replace incorrect values

Solutions: