# SAS-Institute A00-240 ExamSAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential

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NEW QUESTION 1
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.

NEW QUESTION 2
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.

NEW QUESTION 3
Refer to the following 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.

NEW QUESTION 4
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

NEW QUESTION 5
In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

• A. Training: 50% Validation: 0% Testing: 50%
• B. Training: 100% Validation: 0% Testing: 0%
• C. Training: 0% Validation: 100% Testing: 0%
• D. Training: 50% Validation: 50% Testing: 0%

NEW QUESTION 6
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.

NEW QUESTION 7
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)

• A. Simple random sampling without replacement
• B. Simple random sampling with replacement
• C. Stratified random sampling without replacement
• D. Sequential random sampling with replacement

NEW QUESTION 8
Which SAS program will divide the original data set into 60% training and 40% validation
data sets, stratified by county? • A. Option A
• B. Option B
• C. Option C
• D. Option D

NEW QUESTION 9
The standard form of a linear regression model is: Which statement best summarizes the assumptions placed on the errors?

• A. The errors are correlated, normally distributed with constant mean and zero variance.
• B. The errors are correlated, normally distributed with zero mean and constant variance.
• C. The errors are independent, normally distributed with constant mean and zero variance.
• D. The errors are independent, normally distributed with zero mean and constant variance.

NEW QUESTION 10
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

NEW QUESTION 11
Select the equivalent LOGISTIC procedure model statements. (Choose two.)

• A. Mode1 Purchase * Gender Age Region;
• B. Mode1 Purchase * Gender | Age | Region;
• C. Mode1 Purchase * Gender|Age|Region @1;
• D. Mode1 Purchase * Gender|Age|Region @2;

NEW QUESTION 12
Which statistic, calculated from a validation sample, can help decide which model to use for prediction of a binary target variable?

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

NEW QUESTION 13
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.

NEW QUESTION 14
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

NEW QUESTION 15
A financial services manager wants to assess the probability that certain clients will default on their Home Equity Line of Credit (HELOC). A former employee left the code listed below. The training data set is named HELOC, while a similar data set of more recent clients is named RECENT_HELOC. Which SAS data steps will calculate the predicted probability of default on recent clients? (Choose two.) • A. Option A
• B. Option B
• C. Option C
• D. Option D

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.

NEW QUESTION 17
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.

NEW QUESTION 18
Refer to the exhibit: SAS output from the RSOUARE selection method, within the REG procedure, is shown. The top two models in each subset are given.
Based on the AIC statistic, which model is the champion model?

• A. Age Weight RunTime RunPulse MaxPulse
• B. Age Weight RunTime RunPulse RestPulse MaxPulse
• C. RestPulse
• D. RunTime

NEW QUESTION 19
The selection criterion used in the forward selection method in the REG procedure is:

• B. SLE
• C. Mallows' Cp
• D. AIC

NEW QUESTION 20
Refer to the ROC curve: As you move along the curve, what changes?

• A. The priors in the population
• B. The true negative rate in the population
• C. The proportion of events in the training data
• D. The probability cutoff for scoring

NEW QUESTION 21
Refer to the exhibit. Based on the control plot, which conclusion is justified regarding the means of the response?

• A. All groups are significantly different from each other.
• B. 2XL is significantly different from all other groups.
• C. Only XL and 2XL are not significantly different from each other.
• D. No groups are significantly different from each other.

NEW QUESTION 22
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

NEW QUESTION 23
Identify the correct SAS program for fitting a multiple linear regression model with dependent variable (y) and four predictor variables (x1-x4). • A. Option A
• B. Option B
• C. Option C
• D. Option D

NEW QUESTION 24
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.

NEW QUESTION 25
A confusion matrix is created for data that were oversampled due to a rare target. What values are not affected by this oversampling?

• A. Sensitivity and PV+
• B. Specificity and PV-
• C. PV+ and PV-
• D. Sensitivity and Specificity