NEW QUESTION 1
Spearman statistics in the CORR procedure are useful for screening for irrelevant variables by investigating the association between which function of the input variables?

• A. Concordant and discordant pairs of ranked observations
• B. Logit link (log(p/1-p))
• C. Rank-ordered values of the variables
• D. Weighted sum of chi-square statistics for 2x2 tables

Answer: C

NEW QUESTION 2
An analyst investigates Region (A, B, or C) as an input variable in a logistic regression model.
The analyst discovers that the probability of purchasing a certain item when Region = A is 1.
What problem does this illustrate?

• A. Collinearity
• B. Influential observations
• C. Quasi-complete separation
• D. Problems that arise due to missing values

Answer: C

NEW QUESTION 3
Refer to the following odds ratio table:

What is a correct interpretation of the estimate?

• A. The odds of the event are 1.142 greater for each one dollar increase in salary.
• B. The odds of the event are 1.142 greater for each one thousand dollar increase in salary.
• C. The probability of the event is 1.142 greater for each one dollar increase in salary.
• D. The probability of the event is 1.142 greater for each one thousand dollar increase in salary.

Answer: B

NEW QUESTION 4
An analyst compares the mean salaries of men and women working at a company.
The SAS data set SALARY contains variables:
✑ Gender (M or F)
✑ Pay (dollars per year)
Which SAS programs can be used to find the p-value for comparing men's salaries with women's salaries? (Choose two.)

• A. Option A
• B. Option B
• C. Option C
• D. Option D

Answer: AB

NEW QUESTION 5
A marketing manager attempts to determine those customers most likely to purchase additional products as the result of a nation-wide marketing campaign.
The manager possesses a historical dataset (CAMPAIGN) of a similar campaign from last year.
It has the following characteristics:
✑ Target variable Respond (0,1)
✑ Continuous predictor Income
✑ Categorical predictor Homeowner(Y,N)
Which SAS program performs this analysis?

• A. Option A
• B. Option B
• C. Option C
• D. Option D

Answer: A

NEW QUESTION 6
Consider scoring new observations in the SCORE procedure versus the SCORE statement in the LOGISTIC procedure.
Which statement is true?

• A. The SCORE statement in the LOGISTIC procedure returns only predicted probabilities, whereas the SCORE procedure returns only predicted logits.
• B. The SCORE statement in the LOGISTIC procedure returns only predicted logits, whereas the SCORE procedure returns only predicted probabilities.
• C. Unlike the SCORE procedure, the SCORE statement in the LOGISTIC procedure produces both predicted probabilities and predicted logits.
• D. The SCORE procedure and the SCORE statement in the LOGISTIC procedure produce the same output.

Answer: A

NEW QUESTION 7
An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process.
What is the purpose of the test data set?

• A. To provide a unbiased measure of assessment for the final model.
• B. To compare models and select and fine-tune the final model.
• C. To reduce total sample size to make computations more efficient.
• D. To build the predictive models.

Answer: A

NEW QUESTION 8
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?

• A. Option A
• B. Option B
• C. Option C
• D. Option D

Answer: C

NEW QUESTION 9
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.

Answer: B

NEW QUESTION 10
Refer to the lift chart:

At a depth of 0.1, Lift = 3.14. What does this mean?

• A. Selecting the top 10% of the population scored by the model should result in 3.14 times more events than a random draw of 10%.
• B. Selecting the observations with a response probability of at least 10% should result in3.14 times more events than a random draw of 10%.
• C. Selecting the top 10% of the population scored by the model should result in 3.14 timesgreater accuracy than a random draw of 10%.
• D. Selecting the observations with a response probability of atleast 10% should result in 3.14times greater accuracy than a random draw of 10%.

Answer: A

NEW QUESTION 11
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

Answer: B

NEW QUESTION 12
Screening for non-linearity in binary logistic regression can be achieved by visualizing:

• A. A scatter plot of binary response versus a predictor variable.
• B. A trend plot of empirical logit versus a predictor variable.
• C. A logistic regression plot of predicted probability values versus a predictor variable.
• D. A box plot of the odds ratio values versus a predictor variable.

Answer: B

NEW QUESTION 13
Which statistic, calculated from a validation sample, can help decide which model to use for prediction of a binary target variable?

• A. Adjusted R Square
• B. Mallow's Cp
• C. Chi Square
• D. Average Squared Error

Answer: D

NEW QUESTION 14
Refer to the confusion matrix:

Calculate the sensitivity. (0 - negative outcome, 1 - positive outcome) Click the calculator button to display a calculator if needed.

• A. 25/48
• B. 58/102
• C. 25/B9
• D. 58/81

Answer: A

NEW QUESTION 15
Including redundant input variables in a regression model can:

• A. Stabilize parameter estimates and increase the risk of overfitting.
• B. Destabilize parameter estimates and increase the risk of overfitting.
• C. Stabilize parameter estimates and decrease the risk of overfitting.
• D. Destabilize parameter estimates and decrease the risk of overfitting.

Answer: B

NEW QUESTION 16
Which of the following describes a concordant pair of observations in the LOGISTIC procedure?

• A. An observation with the event has an equal probability as another observation with the event.
• B. An observation with the event has a lower predicted probability than the observation without the event.
• C. An observation with the event has an equal predicted probability as the observation without the event.
• D. An observation with the event has a higher predicted probability than the observation without the event

Answer: D

NEW QUESTION 17
Refer to the REG procedure output:

Click on the calculator button to display a calculator if needed.

• A. 0.4115
• B. 0.6994
• C. 0.5884
• D. 0.1372

Answer: A

NEW QUESTION 18
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
• B. It is more complex with a higher accuracy than model B on training data.
• C. Model
• D. It performs better on the boundary for the training data.
• E. Model
• F. It is more complex with a higher accuracy than model A on validation data.
• G. Model
• H. It is simpler with a higher accuracy than model A on validation data.

Answer: D

NEW QUESTION 19
The following LOGISTIC procedure output analyzes the relationship between a binary response and an ordinal predictor variable, wrist_size Using reference cell coding, the analyst selects Large (L) as the reference level.

What is the estimated logit for a person with large wrist size? Click the calculator button to display a calculator if needed. A. 0.0819

• A. 0.5663
• B. -3.7727
• C. -1.0415

Answer: D

NEW QUESTION 20
A company has branch offices in eight regions. Customers within each region are classified as either "High Value" or "Medium Value" and are coded using the variable name VALUE. In the last year, the total amount of purchases per customer is used as the response variable.
Suppose there is a significant interaction between REGION and VALUE. What can you conclude?

• A. More high value customers are found in some regions than others.
• B. The difference between average purchases for medium and high value customers depends on the region.
• C. Regions with higher average purchases have more high value customers.
• D. Regions with higher average purchases have more medium value customers.

Answer: B

NEW QUESTION 21
Refer to the exhibit.

Given alpha=0.02, which conclusion is justified regarding percentage of body fat, comparing small (S), medium (M), and large (L) wrist sizes?

• A. Medium wrist size is significantly different than small wrist size.
• B. Large wrist size is significantly different than medium wrist size.
• C. Large wrist size is significantly different than small wrist size.
• D. There is no significant difference due to wrist size.

Answer: C

NEW QUESTION 22
Refer to the REG procedure output:

An analyst has selected this model as a champion because it shows better model fit than a competing model with more predictors.
Which statistic justifies this rationale?

• A. R-Square
• B. Coeff Var
• C. Adj R-Sq
• D. Error DF

Answer: C

NEW QUESTION 23
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

Answer: C

NEW QUESTION 24
Given the following SAS data set TEST:

Which SAS program is NOT a correct way to create dummy variables?

• A. Option A
• B. Option B
• C. Option C
• D. Option D

Answer: D

NEW QUESTION 25
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. The model will likely be overfit.
• B. There will be a high rate of collinearity among input variables.
• C. Complete case analysis means that fewer observations will be used in the model building process.
• D. New cases with missing values on input variables cannot be scored without extra data processing.

Answer: CD

NEW QUESTION 26
......