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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What are decision tree properties that can be defined during model construction?

A) The learning rate for gradient boosting
B) The maximum depth of the tree
C) The number of neighbors in a k-nearest neighbors model
D) The minimum number of data points in a leaf node

2. What can be interpreted from the Summary Table for model comparison, including statistics and variable importance?

A) The distribution of predictor variables
B) The correlation matrix of predictor variables
C) Model performance metrics and their relative importance
D) The number of iterations performed by each model

3. 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)

4. When modeling binary outcomes in a generalized linear model, which distribution and link function combination is commonly used?

A) Poisson distribution with a log link function
B) Normal distribution with an identity link function
C) Exponential distribution with a square root link function
D) Binomial distribution with a logit link function

5. What is the purpose of setting Parallel Coordinate properties for a cluster in SAS Visual Statistics?

A) To determine the cluster's centroid
B) To assign labels to the cluster's variables
C) To create a scatter plot of data points
D) To visualize the distribution of data within the cluster

Solutions: