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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. After a logistic regression has been created in SAS Visual Statistics, you discover that not all observations were used to create the model.
How would you run the model on all of the data?

A) Include the correct offset term.
B) Include the correct interaction term.
C) Select Informative Missingness on the properties tab.
D) Select Use Variable Selection on the properties tab.

2. How are split points determined in a decision tree?

A) By maximizing information gain or Gini impurity reduction
B) Randomly assigned
C) Based on the order of appearance in the dataset
D) By minimizing the number of leaf nodes

3. What is the primary purpose of concordance statistics in model comparison?

A) To measure the balance between sensitivity and specificity
B) To evaluate the relationship between two predictor variables
C) To calculate the p-values of predictor variables
D) To assess the multicollinearity among predictors

4. You would like to build a cluster analysis using several variables related to demographics. You noticed that the variable Inferred HH Education is a nominal variable with values of "High School Grad",
"College Grad", etc.
Which action allows you to incorporate this variable in the cluster analysis without returning a warning?

A)

B)

C)

D)

5. What properties can be assigned when comparing models in SAS Visual Statistics?

A) The variables to include in the model comparison
B) The learning rate for gradient boosting models
C) The number of observations in the dataset
D) The color scheme for visualization

Solutions:

Question # 1 Answer: C

Question # 2 Answer: A

Question # 3 Answer: A

Question # 4 Answer: A

Question # 5 Answer: A