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SASInstitute Statistical Business Analyst A00-240 Practice Questions
QUESTION 1
A non-contributing predictor variable (Pr > |t| =0.658) is added to an existing multiple linear regression model.
What will be the result?
A. An increase in R-Square
B. A decrease in R-Square
C. A decrease in Mean Square Error
D. No change in R-Square
Correct Answer: A
QUESTION 2
There are missing values in the input variables for a regression application.
Which SAS procedure provides a viable solution?
A. GLM
B. VARCLUS
C. STDI2E
D. CLUSTER
Correct Answer: C
QUESTION 3
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?
A. The sample means from the validation data set are applied to the training and test data sets.
B. The sample means from the training data set are applied to the validation and test data sets.
C. The sample means from the test data set are applied to the training and validation data sets.
D. The sample means from each partition of the data are applied to their own partition.
Correct Answer: B
QUESTION 4
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A non-contributing predictor variable (Pr > |t| = 0.658) is removed from an existing multiple linear regression model.
What will be the result?
A. An increase in R-Square
B. A decrease in R-Square
C. A decrease in Mean Square Error
D. No change in R-Square
Correct Answer: B
QUESTION 5
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?
A. Score data=valid1 out=roc;
B. Score data=valid1 outroc=roc;
C. mode1 resp(event= \\’1\\’) = gender region/outroc=roc;
D. mode1 resp(event”1″) = gender region/ out=roc;
Correct Answer: B
QUESTION 6
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:
What X and Y values should be added to the program to correctly score the data?
A. X=40, Y=10
B. X=.05, Y=10
C. X=.05, Y=.40
D. X=.10, Y=05
Correct Answer: B
QUESTION 7
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)
A. Simple random sampling without replacement
B. Simple random sampling with replacement
C. Stratified random sampling without replacement
D. Sequential random sampling with replacement
Correct Answer: AC
QUESTION 8
Refer to the following exhibit:
What is a correct interpretation of this graph?
A. The association between the continuous predictor and the binary response is quadratic.
B. The association between the continuous predictor and the log-odds is quadratic.
C. The association between the continuous predictor and the continuous response is quadratic.
D. The association between the binary predictor and the log-odds is quadratic.
Correct Answer: B
QUESTION 9
Refer to the exhibit:
SAS output from the RSQUARE selection method, within the REG procedure, is shown. The top two models in each
subset are given. Based on the exhibit, which statement is true?
A. The AIC champion model is more parsimonious than the SBC champion.
B. The SBC champion model is more parsimonious than the AIC champion.
C. The R-Square champion model is the most parsimonious.
D. Adjusted R-Square and R-Square agree on the champion model.
Correct Answer: B
QUESTION 10
Which SAS program will divide the original data set into 60% training and 40% validation data sets, stratified by county?
A. Option A
B. Option B
C. Option C
D. Option D
Correct Answer: C
QUESTION 11
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?
A. Model A. It is more complex with a higher accuracy than model B on training data.
B. Model A. It performs better on the boundary for the training data.
C. Model B. It is more complex with a higher accuracy than model A on validation data.
D. Model B. It is simpler with a higher accuracy than model A on validation data.
Correct Answer: D
QUESTION 12
The Model SS in a multiple linear regression model is equal to:
A. the total SS- MSE
B. the sum of Type I SS of all model terms
C. the sum of Type II SS of all model terms
D. the sum of SSE and MSE
Correct Answer: B
Reference: http://core.ecu.edu/psyc/wuenschk/SAS/SS1234.pdf
QUESTION 13
One common approach for predicting rare events in the LOGISTIC procedure is to build a model that disproportionately
over-re presents those cases with an event occurring (e.g. a 50-50 event/non-event split). What problem does this
present?
A. All parameter estimates are biased.
B. Only the intercept estimate is biased.
C. Only the non-intercept parameter estimates are biased.
D. Sensitivity estimates are biased.
Correct Answer: B
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