QUESTION: 33

Including redundant input variables in a regression model can:

Stabilize parameter estimates and increase the risk of overfitting.
Destabilize parameter estimates and increase the risk of overfitting.
Stabilize parameter estimates and decrease the risk of overfitting.
Destabilize parameter estimates and decrease the risk of overfitting.

Answer(s): B

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?

Collinearity
Influential observations
Quasi-complete separation
Problems that arise due to missing values

Answer(s): C

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QUESTION: 35

Refer to the following exhibit:

What is a correct interpretation of this graph?

The association between the continuous predictor and the binary response is quadratic.
The association between the continuous predictor and the log-odds is quadratic.
The association between the continuous predictor and the continuous response is quadratic.
The association between the binary predictor and the log-odds is quadratic.

Answer(s): B

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QUESTION: 36

This question will ask you to provide a missing option. Given the following SAS program:

What option must be added to the program to obtain a data set containing Pearson statistics?

OUTPUT=estimates
OUTP=estimates
OUTSTAT=estimates
OUTCORR=estimates

Answer(s): B

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