Download SAS Statistical Business Analysis SAS9: Regression and Model.A00-240.ExamLabs.2019-12-17.39q.vcex

Vendor:	SASInstitute
Exam Code:	A00-240
Exam Name:	SAS Statistical Business Analysis SAS9: Regression and Model
Date:	Dec 17, 2019
File Size:	2 MB

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Demo Questions

Refer to the ROC curve:

As you move along the curve, what changes?

The priors in the population
The true negative rate in the population
The proportion of events in the training data
The probability cutoff for scoring

Correct answer: D

When mean imputation is performed on data after the data is partitioned for honest assessment, what is the most appropriate method for handling the mean imputation?

The sample means from the validation data set are applied to the training and test data sets.
The sample means from the training data set are applied to the validation and test data sets.
The sample means from the test data set are applied to the training and validation data sets.
The sample means from each partition of the data are applied to their own partition.

Correct answer: B

An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.

Which statement and option combination will generate these statistics?

Score data=valid1 out=roc;
Score data=valid1 outroc=roc;
mode1 resp(event= '1') = gender region/outroc=roc;
mode1 resp(event"1") = gender region/ out=roc;

Correct answer: B

In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)

Simple random sampling without replacement
Simple random sampling with replacement
Stratified random sampling without replacement
Sequential random sampling with replacement

Correct answer: AC

Which SAS program will divide the original data set into 60% training and 40% validation data sets, stratified by county?

Option A
Option B
Option C
Option D

Correct answer: C

Refer to the exhibit:

The plots represent two models, A and B, being fit to the same two data sets, training and validation.

Model A is 90.5% accurate at distinguishing blue from red on the training data and 75.5% accurate at doing the same on validation data. Model B is 83% accurate at distinguishing blue from red on the training data and 78.3% accurate at doing the same on the validation data.

Which of the two models should be selected and why?

Model A. It is more complex with a higher accuracy than model B on training data.
Model A. It performs better on the boundary for the training data.
Model B. It is more complex with a higher accuracy than model A on validation data.
Model B. It is simpler with a higher accuracy than model A on validation data.

Correct answer: D

In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

Training: 50% Validation: 0% Testing: 50%
Training: 100% Validation: 0% Testing: 0%
Training: 0% Validation: 100% Testing: 0%
Training: 50% Validation: 50% Testing: 0%

Correct answer: D

A marketing campaign will send brochures describing an expensive product to a set of customers. The cost for mailing and production per customer is $50. The company makes $500 revenue for each sale.

What is the profit matrix for a typical person in the population?

Option A
Option B
Option C
Option D

Correct answer: C

A confusion matrix is created for data that were oversampled due to a rare target.

What values are not affected by this oversampling?

Sensitivity and PV+
Specificity and PV-
PV+ and PV-
Sensitivity and Specificity

Correct answer: D

This question will ask you to provide missing code segments.

A logistic regression model was fit on a data set where 40% of the outcomes were events (TARGET=1) and 60% were non-events (TARGET=0). The analyst knows that the population where the model will be deployed has 5% events and 95% non-events. The analyst also knows that the company's profit margin for correctly targeted events is nine times higher than the company's loss for incorrectly targeted non-event.

Given the following SAS program: