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NEW QUESTION 1
Refer to the lift chart:
What does the reference line at lift = 1 corresponds to?
- A. The predicted lift for the best 50% of validation data cases
- B. The predicted lift if the entire population is scored as event cases
- C. The predicted lift if none of the population are scored as event cases
- D. The predicted lift if 50% of the population are randomly scored as event cases
Answer: B
NEW QUESTION 2
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?
- A. Option A
- B. Option B
- C. Option C
- D. Option D
Answer: A
NEW QUESTION 3
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 4
The question will ask you to provide a missing statement. Given the following SAS program:
Which SAS statement will complete the program to correctly score the data set NEW_DATA?
- A. Scoredata data=MYDIR.NEW_DATA out=scores;
- B. Scoredata data=MYDIR.NEW_DATA output=scores;
- C. Scoredata=HYDIR.NEU_DATA output=scores;
- D. Scoredata=MYDIR,NEW DATA out=scores;
Answer: D
NEW QUESTION 5
What is the default method in the LOGISTIC procedure to handle observations with missing data?
- A. Missing values are imputed.
- B. Parameters are estimated accounting for the missing values.
- C. Parameter estimates are made on all available data.
- D. Only cases with variables that are fully populated are used.
Answer: D
NEW QUESTION 6
Given the following LOGISTIC procedure:
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
NEW QUESTION 7
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 8
This question will ask you to provide a missing option. Given the following SAS program:
What option must be added to the program to obtain a data set containing Pearson statistics?
- A. OUTPUT=estimates
- B. OUTP=estimates
- C. OUTSTAT=estimates
- D. OUTCORR=estimates
Answer: B
NEW QUESTION 9
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 10
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.
- A. <0.01%
- B. 35%
- C. 65%
- D. 76%
Answer: D
NEW QUESTION 11
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;
- A. test
- B. adjust
- C. var
- D. hovtest
Answer: D
NEW QUESTION 12
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 13
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 14
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 15
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 16
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?
- A. It violates assumptions of the model.
- B. It requires extra computational effort and time.
- C. It omits the training (and test) data sets from the benefits of the cleansing methods.
- D. There is no ability to compare the effectiveness of different cleansing methods.
Answer: D
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