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QUESTION NO: 1 Refer to the exhibit: Based upon the comparative ROC plot for two competing models, which is the champion model and why? A. Candidate 2, because the area under the curve is greater B. Candidate 2, because it shows less over fit than Candidate 1 C. Candidate 1, because it is closer to the diagonal reference curve D. Candidate 1, because the area outside the curve is greater Answer: A
QUESTION NO: 2 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
QUESTION NO: 3 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: 4 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: 5 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
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Updated: May 28, 2022
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QUESTION NO: 1 Refer to the exhibit: Based upon the comparative ROC plot for two competing models, which is the champion model and why? A. Candidate 2, because the area under the curve is greater B. Candidate 2, because it shows less over fit than Candidate 1 C. Candidate 1, because it is closer to the diagonal reference curve D. Candidate 1, because the area outside the curve is greater Answer: A
QUESTION NO: 2 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
QUESTION NO: 3 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: 4 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: 5 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
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QUESTION NO: 1 Refer to the exhibit: Based upon the comparative ROC plot for two competing models, which is the champion model and why? A. Candidate 2, because the area under the curve is greater B. Candidate 2, because it shows less over fit than Candidate 1 C. Candidate 1, because it is closer to the diagonal reference curve D. Candidate 1, because the area outside the curve is greater Answer: A
QUESTION NO: 2 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
QUESTION NO: 3 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: 4 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: 5 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
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