A00-240題庫分享，Sasinstitute A00-240證照指南 & SAS Certified Statistical Business Analyst Using SAS 9: Regression And Modeling Credential - Royalholidayclubbed

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因為這個考古題的命中率非常高，只要你認真記住考古題裏面出現的問題和答案，那麼你就可以通過A00-240題庫分享考試。你已經報名參加SASInstitute的A00-240題庫分享認證考試了嗎？“馬上就要到考試的時間了，但是我還是沒有信心通過考試，應該怎麼辦呢？有捷徑可以讓我順利通過考試嗎？看參考書的時間也不夠了。

A00-240 PDF DEMO:

QUESTION NO: 1
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: 2
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: 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

by RHC.

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