Statistical Business Analyst A00-240 Exam Dumps Updated

1. Refer to the ROC curve:

As you move along the curve, what changes?

2. 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?

3. 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?

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

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

6. Refer to the lift chart:

At a depth of 0.1, Lift = 3.14.

What does this mean?

7. Refer to the lift chart:

What does the reference line at lift = 1 corresponds to?

8. Suppose training data are oversampled in the event group to make the number of events and non­events 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.

What does this program calculate?

9. 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?

10. 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?

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

12. Refer to the exhibit:

Based upon the comparative ROC plot for two competing models, which is the champion model and why?

13. 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?

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

What values are not affected by this oversampling?

15. 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?

16. 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 training data set?

17. Refer to the confusion matrix: Calculate the sensitivity. (0 – negative outcome, 1 – positive outcome)

Click the calculator button to display a calculator if needed.

18. The total modeling data has been split into training, validation, and test data.

What is the best data to use for model assessment?

19. What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing after partitioning the data?

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?

21. This question will ask you to provide a missing option.

Complete the following syntax to test the homogeneity of variance assumption in the GLM procedure:

means Region / <insert option here> =levene ;

22. Refer to the exhibit.

Based on the control plot, which conclusion is justified regarding the means of the response?

23. 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:

What percentage of customers’ intent to purchase is explained by market segment?

Click the calculator button to display a calculator if needed.

24. Refer to the exhibit:

The box plot was used to analyze daily sales data following three different ad campaigns.

The business analyst concludes that one of the assumptions of ANOVA was violated.

Which assumption has been violated and why?

25. 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?

26. 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.)

27. Given the following GLM procedure output:

Which statement is correct at an alpha level of 0.05?

28. There are missing values in the input variables for a regression application.

Which SAS procedure provides a viable solution?

29. Screening for non-linearity in binary logistic regression can be achieved by visualizing:

30. Given the following SAS data set TEST:

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

31. 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:

What is the most likely reason that the model fails to converge?

32. 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.)

33. Including redundant input variables in a regression model can:

34. 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?

35. Refer to the following exhibit:

What is a correct interpretation of this graph?