Q34. If you only consider observations for which TARGET=0, what percentage of such observations has BanruptcyInd=1?
Response:

Q35. Perform these tasks in SAS Enterprise Miner:
– Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
– Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:

Q36. You are building a model to identify fraud. Your model will produce predictions that can be interpreted as the probability of fraud. You will pass on the top 100 scoring cases to management for investigation. Assume that you have sufficient data to hold out a validation and test data set for model evaluation.
Which selection would represent a reasonable ordering of fit statistics (best to worst) for this situation?
Select one:
Response:

Q37. An analyst is performing a market basket analysis (affinity analysis) on the purchase of Shaving Cream and Seltzer Water. The purchase data from a set of 250 customers is shown below:

What is the confidence of the rule “Shaving Cream implies Seltzer Water”? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

Q38. How many hidden layers are generally needed in an MLP-based neural network to capture a discontinuous relationship between inputs and target?
Response:

Q39. The selected model, based on the misclassification rate for the validation data, has how many input variables?
Response:

Q40. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

* Run the Decision Tree node.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:

Q41. For the variable TLCnt24, apply a Max Normal transformation. What transformation was selected by SAS Enterprise Miner?
Response:

Q42. Refer to the exhibit:

When the Explore button is selected in the graphic, what information will be displayed?
Select one:
Response:

Q43. Which of the following solves problems for you when you impute missing values?
Response:

Q44. Which model was picked as the best model by SAS Enterprise Miner?
Response:

Q45. Refer to the exhibit:

What would be the decision threshold (probability cutoff) generated for this decision matrix. You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

Q46. Which method of input selection for regression analysis evaluates the statistical significance of the total model to see if it improves on the baseline as the variables are added and once no further improvement is made then variable selection ends?
Select one:
Response:

Q47. For an ordinal variable with L levels, the number of possible splits in a decision tree is which of the following?
Response:

Q48. In segment 2, what percentage of GiftAvgCard36 values are between 6.6638 and 11.998?
Select one:
Response:

Q49. Multicollinearity in regression refers to which of the following?
Response:

Q50. Which of the following is not true about results produced by the Regression node?
Response:

Q51. -> Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
– Allow for 1 substitute rule in case the variable for the primary splitting rule is missing.
– Disable pruning for the decision tree.
-> Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
– Configure the Neural Network model to use Average Error for Model Selection Criterion.
-> Run the process flow.
What is the number of input variables being used by the Neural Network Model?
Enter your numeric answer in the space below:
Response:

Q52. Refer to the graphs shown below. The graphs are from a study of response rate to a marketing campaign.

How much more likely are the top 20% of targeted respondents to purchase the product than a randomly selected sample?
Select one:
Response:

Q53. Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
The percentage of observations correctly predicted in the validation data by the Ensemble model is in which of the following ranges?
Response:

Q54. Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:

Q55. Refer to the following profit matrix and confusion matrix for a campaign soliciting product purchases. The predicted variable is a binary outcome.

Based on the above tables, what is the average profit? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response: