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

2. Which SAS tool is suitable for creating complex data manipulation and transformation workflows in a visual interface?

A) SAS Visual Analytics
B) SAS Studio
C) SAS Visual Data Builder
D) SAS Enterprise Guide

3. In logistic regression modeling, how is the probability of an event typically estimated?

A) By applying the link function to the linear predictor
B) By fitting a linear regression model to the data
C) By calculating the mean of the predictor variables
D) By assigning roles to variables

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

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

5. What information is conveyed by a Summary bar in model assessment?

A) The summary statistics of the response variable
B) The distribution of residuals in the model
C) The performance metrics of the model, such as AUC and KS Statistic
D) The standard deviation of the predictor variables

Solutions: