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QUESTION NO: 1
In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?
A. Training: 0% Validation: 100% Testing: 0%
B. Training: 50% Validation: 50% Testing: 0%
C. Training: 50% Validation: 0% Testing: 50%
D. Training: 100% Validation: 0% Testing: 0%
Answer: B

QUESTION NO: 2
Refer to the confusion matrix:
Calculate the accuracy and error rate (0 - negative outcome, 1 - positive outcome)
A. Accuracy = 83/150, Error Rate = 67/150
B. Accuracy = 58/102, Error Rate = 23/48
C. Accuracy = 25/150, Error Rate = 44/150
D. Accuracy = 83/102, Error Rate = 67/102
Answer: B

QUESTION NO: 3
A predictive model uses a data set that has several variables with missing values.
What two problems can arise with this model? (Choose two.)
A. New cases with missing values on input variables cannot be scored without extra data processing.
B. Complete case analysis means that fewer observations will be used in the model building process.
C. The model will likely be overfit.
D. There will be a high rate of collinearity among input variables.
Answer: A,B

QUESTION NO: 4
Which statistic, calculated from a validation sample, can help decide which model to use for prediction of a binary target variable?
A. Chi Square
B. Adjusted R Square
C. Mallow's Cp
D. Average Squared Error
Answer: D

QUESTION NO: 5
Refer to the exhibit.
These graphs were created using the GLM procedure with the plots(only)=diagnostics option.
Which plot do you use to identify influential observations?
A. Residual by Quantile
B. Fit - Mean and Residual Plot
C. Cook's D by Observation
D. Residual by Predicted
Answer: C

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Updated: May 28, 2022