Download A00-240 Exam Dumps 2021

are updated and are verified by experts. Once you have completely prepared with our you will be ready for the real A00-240 exam without a problem. We have . PASSED First attempt! Here What I Did.

Free demo questions for SAS Institute A00-240 Exam Dumps Below:

NEW QUESTION 1
Refer to the exhibit:
A00-240 dumps exhibit
An analyst examined logistic regression models for predicting whether a customer would make a purchase. The ROC curve displayed summarizes the models. Using the selected model and the analyst's decision rule, 25% of the customers who did not make a purchase are incorrectly classified as purchasers.
What can be concluded from the graph?

  • A. About 25% of the customers who did make a purchase are correctly classified as making a purchase.
  • B. About 50% of the customers who did make a purchase are correctly classified as making a purchase.
  • C. About 85% of the customers who did make a purchase are correctly classified as making a purchase.
  • D. About 95% of the customers who did make a purchase are correctly classified as making a purchase.

Answer: C

NEW QUESTION 2
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 3
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?
A00-240 dumps exhibit

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

Answer: C

NEW QUESTION 4
Which SAS program will detect collinearity in a multiple regression application?
A00-240 dumps exhibit

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

Answer: B

NEW QUESTION 5
Customers were surveyed to assess their intent to purchase a product. An analyst divided the customers into groups defined by the company's pre-assigned market segments and tested for difference in the customers' average intent to purchase. The following is the output from the GLM procedure:
A00-240 dumps exhibit
What percentage of customers' intent to purchase is explained by market segment? Click the calculator button to display a calculator if needed.

  • A. <0.01%
  • B. 35%
  • C. 65%
  • D. 76%

Answer: D

NEW QUESTION 6
Refer to the following odds ratio table:
A00-240 dumps exhibit
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 7
Identify the correct SAS program for fitting a multiple linear regression model with dependent variable (y) and four predictor variables (x1-x4).
A00-240 dumps exhibit

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

Answer: B

NEW QUESTION 8
Refer to the following exhibit:
A00-240 dumps 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.

Answer: B

NEW QUESTION 9
Suppose training data are oversampled in the event group to make the number of events and non-events roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than 0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0= No event).
The following SAS program was used.
A00-240 dumps exhibit
What does this program calculate?

  • A. Depth
  • B. Sensitivity
  • C. Specificity
  • D. Positive predictive value

Answer: B

NEW QUESTION 10
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?
A00-240 dumps exhibit

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

Answer: A

NEW QUESTION 11
Assume a $10 cost for soliciting a non-responder and a $200 profit for soliciting a responder. The logistic regression model gives a probability score named P_R on a SAS data set called VALID. The VALID data set contains the responder variable Pinch, a 1/0 variable coded as 1 for responder. Customers will be solicited when their probability score is more than 0.05.
Which SAS program computes the profit for each customer in the data set VALID?
A00-240 dumps exhibit

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

Answer: A

NEW QUESTION 12
An analyst fits a logistic regression model to predict whether or not a client will default on a loan. One of the predictors in the model is agent, and each agent serves 15-20 clients each. The model fails to converge. The analyst prints the summarized data, showing the number of defaulted loans per agent. See the partial output below:
A00-240 dumps exhibit
What is the most likely reason that the model fails to converge?

  • A. There is quasi-complete separation in the data.
  • B. There is collinearity among the predictors.
  • C. There are missing values in the data.
  • D. There are too many observations in the data.

Answer: A

NEW QUESTION 13
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 14
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:
A00-240 dumps exhibit
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 15
Refer to the exhibit.
A00-240 dumps 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 16
An analyst knows that the categorical predictor, storeId, is an important predictor of the target.
However, store_Id has too many levels to be a feasible predictor in the model. The analyst
wants to combine stores and treat them as members of the same class level. What are the two most effective ways to address the problem? (Choose two.)

  • A. Eliminate store_id as a predictor in the model because it has too many levels to be feasible.
  • B. Cluster by using Greenacre's method to combine stores that are similar.
  • C. Use subject matter expertise to combine stores that are similar.
  • D. Randomly combine the stores into five groups to keep the stochastic variation among the observations intact.

Answer: BC

NEW QUESTION 17
Given the following output from the LOGISTIC procedure:
A00-240 dumps exhibit
Which variables, among those that are statistically significant at an alpha of 0.05, have the greatest and least relative importance on the fitted model?

  • A. Greatest: MBA Least: DOWN_AMT
  • B. Greatest: MBA Least: CASH
  • C. Greatest: DOWN_AMT Least: CASH
  • D. Greatest: DOWN_AMT Least: HOME

Answer: C

NEW QUESTION 18
Given the following LOGISTIC procedure:
A00-240 dumps exhibit
What is the difference between the datasets OUTFILEJ and OUTFILE_2?

  • A. OUTFILE_1 contains the final parameter estimates while OUTFILE_2 contains the newly scored probabilities.
  • B. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored probabilities
  • C. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored logits.
  • D. OUTFILEJ contains the final parameter estimates and Wald Chi-Square values while OUTFILE_2 contains the newly scored probabilities.

Answer: A

P.S. Easily pass A00-240 Exam with 65 Q&As Certshared Dumps & pdf Version, Welcome to Download the Newest Certshared A00-240 Dumps: https://www.certshared.com/exam/A00-240/ (65 New Questions)