An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process. What is the purpose of the training data set?

A. To provide an unbiased measure of assessment for the final model.

B. To compare models and select and fine-tune the final model.

C. To reduce total sample size to make computations more efficient.

D. To build the predictive models.

An analyst investigates Region (A, B, or C) as an input variable in a logistic regression model.

The analyst discovers that the probability of purchasing a certain item when Region = A is 1.

What problem does this illustrate?

A. Collinearity

B. Influential observations

C. Quasi-complete separation

D. Problems that arise due to missing values

A linear model has the following characteristics:

1.

A dependent variable (y)

2.

Three continuous predictor variables (x1-x3)

3.

One categorical predictor variable (c1 with 3 levels)

Which SAS program fits this model?

A. Option A

B. Option B

C. Option C

D. Option D

One common approach for predicting rare events in the LOGISTIC procedure is to build a model that disproportionately over-re presents those cases with an event occurring (e.g. a 50-50 event/non-event split). What problem does this present?

A. All parameter estimates are biased.

B. Only the intercept estimate is biased.

C. Only the non-intercept parameter estimates are biased.

D. Sensitivity estimates are biased.

A researcher has several variables that could be possible predictors for the final model. There is interest in checking all 2-way interactions for possible entry to the model. The researcher has decided to use forward selection within PROC LOGISTIC. Fill in the missing code option that will ensure that all 2-way interactions will be considered for entry.

A. start = 5

B. include = 4

C. include = 5

D. start = 4