QUESTION: 37

A predictive model uses a data set that has several variables with missing values. What two problems can arise with this model? (Choose two.)

The model will likely be overfit.
There will be a high rate of collinearity among input variables.
Complete case analysis means that fewer observations will be used in the model building process.
New cases with missing values on input variables cannot be scored without extra data processing.

Answer(s): C,D

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QUESTION: 38

Spearman statistics in the CORR procedure are useful for screening for irrelevant variables by investigating the association between which function of the input variables?

Concordant and discordant pairs of ranked observations
Logit link (log (p/1-p))
Rank-ordered values of the variables
Weighted sum of chi-square statistics for 2x2 tables

Answer(s): C

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QUESTION: 39

A non-contributing predictor variable (Pr > |t| =0.658) is added to an existing multiple linear regression model. What will be the result?

An increase in R-Square
A decrease in R-Square
A decrease in Mean Square Error
No change in R-Square

Answer(s): A

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QUESTION: 40

The standard form of a linear regression model is:

Which statement best summarizes the assumptions placed on the errors?

The errors are correlated, normally distributed with constant mean and zero variance.
The errors are correlated, normally distributed with zero mean and constant variance.
The errors are independent, normally distributed with constant mean and zero variance.
The errors are independent, normally distributed with zero mean and constant variance.

Answer(s): D

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