A00-240 Exam Dumps - SAS Institute Statistical Business Analyst Questions and Answers

The predicted lift for the best 50% of validation data cases

The predicted lift if the entire population is scored as event cases

The predicted lift if none of the population are scored as event cases

The predicted lift if 50% of the population are randomly scored as event cases

Only studentized residuals greater than negative two

Only studentized residuals less than negative two and greater than two

Only studentized residuals greater than two

Only studentized residuals less than two and greater than negative two

Training: 40% Validation: 30% Testing: 30%

K-fold cross validation

Cross validation using 4th quartile observations

Use the AIC goodness of fit statistic

The imputed values are irrelevant to the validation data, and are not used.

The imputed values must be applied directly to the validation data without recalculation.

The imputed values must be recalculated using the validation data.

The imputed values must be recalculated using both the training and the validation data.

It violates assumptions of the model.

It requires extra computational effort and time.

It omits the training (and test) data sets from the benefits of the cleansing methods.

There is no ability to compare the effectiveness of different cleansing methods.

RSQ

MSE

R-squared

AIC

Score data data=MYDIR.NEW_DATA out=scores;

Score data data=MYDIR.NEW_DATA output=scores;

Score data=HYDIR.NEU_DATA output=scores;

Score data=MYDIR, NEW DATA out=scores;

Option A

Option B

Option C

Option D

A scatter plot of binary response versus a predictor variable.

A trend plot of empirical logit versus a predictor variable.

A logistic regression plot of predicted probability values versus a predictor variable.

A box plot of the odds ratio values versus a predictor variable.

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