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SASInstitute A00-485 Exam Syllabus Topics:

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

Question 1

What is meant by "informative missingness" in the context of linear regression?

A. Missing data that leads to multicollinearity among predictors
B. Missing data that provides valuable information about the outcome
C. Missing data that is unrelated to the outcome variable
D. Missing data that is randomly distributed across observations

Question 2

What does the interactive group-by feature in SAS Visual Analytics allow you to do?

A. Create subgroups within the group-by variable
B. Apply group-by modeling to multiple measures simultaneously
C. Interactively explore different levels of the group-by variable
D. Dynamically change the group-by variable during analysis

Question 3

What are the roles that can be assigned in a generalized linear model (GLM)?

A. Predictor
B. Offset
C. Intercept
D. Target

Question 4

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

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

Question 5

You want to build a model that predicts whether a customer will default on a loan assuming an underlying binomial distribution.
Which model within SAS Visual Statistics would you use?

A. generalized linear model using the binomial distribution and the log link function
B. logistic regression model using the Logit link function
C. logistic regression model using the Probit link function
D. logistic regression model using the Tobit link function

Solutions: