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SASInstitute A00-240 certification exam is designed to validate the skills and knowledge of statistical business analysts who use SAS 9 software for regression and modelling. SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential certification is ideal for professionals who want to demonstrate their expertise in statistical analysis, predictive modelling, and data-driven decision-making. A00-240 exam covers a wide range of topics, including linear regression, logistic regression, model selection, and validation, among others.
The A00-240 exam is an assessment of the individual's proficiency in data analysis, regression analysis, and modeling using SAS software. It is intended for those who have an understanding of basic statistical concepts and have a desire to develop their expertise in the SAS software. By attaining this credential, you prove your competency in using SAS tools to perform statistical analysis and modeling, enabling you to provide insights into data that can help you make informed business decisions.
NEW QUESTION # 52
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?
- A. Option D
- B. Option A
- C. Option B
- D. Option C
Answer: B
NEW QUESTION # 53
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. Use subject matter expertise to combine stores that are similar.
- B. Randomly combine the stores into five groups to keep the stochastic variation among the observations
intact. - C. Cluster by using Greenacre's method to combine stores that are similar.
- D. Eliminate store_id as a predictor in the model because it has too many levels to be feasible.
Answer: A,C
NEW QUESTION # 54
A researcher is planning a logistic regression to model the probability of disease occurrence. The researcher determines the rate of disease occurrence in the population is 1%.
For which of the following would this study be a candidate?
- A. oversampling
- B. multicollinearity
- C. over fitting
- D. simple random sample
Answer: B
NEW QUESTION # 55
The PROC LOGISTIC options SELECTION=SCORE and BEST=2 are used in a MODEL statement to generate a series of predictive models. The models are assigned numbers in order from 1 to 99 reflecting the fact that there are 50 candidate input variables. Results from the collection of derived models are used to generate the following plot of overall average profit by model number. Results are restricted to models with at least 9 inputs and at most 40 inputs.
The maximum value for the training data occurs for model number 46, and the maximum value for the validation data occurs for model number 43.
If you base model selection solely on overall average profit, what is the correct choice?
- A. Select model 43
- B. Select model 46
- C. Select model 45
- D. Select model 21
Answer: A
NEW QUESTION # 56
Refer to the exhibit.
Based on the control plot, which conclusion is justified regarding the means of the response?
- A. No 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. All groups are significantly different from each other.
Answer: C
NEW QUESTION # 57
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?
- A. Large wrist size is significantly different than small wrist size.
- B. Medium wrist size is significantly different than small wrist size.
- C. There is no significant difference due to wrist size.
- D. Large wrist size is significantly different than medium wrist size.
Answer: A
NEW QUESTION # 58
A non-contributing predictor variable (Pr > |t| =0.658) is added to an existing multiple linear regression model.
What will be the result?
- A. A decrease in Mean Square Error
- B. A decrease in R-Square
- C. An increase in R-Square
- D. No change in R-Square
Answer: C
NEW QUESTION # 59
Given the following output from the LOGISTIC procedure:
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: DOWN_AMT
Least: HOME - B. Greatest: DOWN_AMT
Least: CASH - C. Greatest: MBA
Least: DOWN_AMT - D. Greatest: MBA
Least: CASH
Answer: B
NEW QUESTION # 60
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. OUTSTAT=estimates
- B. OUTP=estimates
- C. OUTCORR=estimates
- D. OUTPUT=estimates
Answer: B
NEW QUESTION # 61
Refer to the exhibit:
Which statement is true, based on the plots above?
- A. Approximately ten percent of a randomly selected subset of twenty percent of the customers are expected to have a positive event.
- B. Approximately twice as many customers with the top ten percent of predicted probabilities are expected to have a positive versus negative event.
- C. Approximately ten percent of those customers with the top twenty percent of predicted probabilities are expected to have a positive event.
- D. Approximately twenty percent of the customers with a predicted score of 3 have a positive predicted class.
Answer: B
NEW QUESTION # 62
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. Score data data=MYDIR.NEW_DATA out=scores;
- B. Score data data=MYDIR.NEW_DATA output=scores;
- C. Score data=MYDIR, NEW DATA out=scores;
- D. Score data=HYDIR.NEU_DATA output=scores;
Answer: C
Explanation:
Explanation/Reference:
NEW QUESTION # 63
A linear model has the following characteristics:
A dependent variable (y)
Three continuous predictor variables (x1-x3)
One categorical predictor variable (c1 with 3 levels)
Which SAS program fits this model?
- A. Option D
- B. Option A
- C. Option B
- D. Option C
Answer: A
NEW QUESTION # 64
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. hovtest
- B. var
- C. adjust
- D. test
Answer: A
NEW QUESTION # 65
Spearman statistics in the CORR procedure are useful for screening for irrelevant variables by investigating the association between which function of the input variables?
- A. Weighted sum of chi-square statistics for 2x2 tables
- B. Logit link (log (p/1-p))
- C. Concordant and discordant pairs of ranked observations
- D. Rank-ordered values of the variables
Answer: D
NEW QUESTION # 66
While building a predictive model, median imputations are performed while preparing the training data.
How should the imputations be addressed in the validation data?
- A. The imputed values must be applied directly to the validation data without recalculation.
- B. The imputed values must be recalculated using both the training and the validation data.
- C. The imputed values are irrelevant to the validation data, and are not used.
- D. The imputed values must be recalculated using the validation data.
Answer: D
NEW QUESTION # 67
Which statistic is based on the maximum vertical distance between the primary event EDF and the secondary event EDF?
- A. Brier Score
- B. SBC
- C. Max EDF
- D. KS
Answer: D
Explanation:
Explanation/Reference: https://support.sas.com/documentation/onlinedoc/ets/132/severity.pdf
NEW QUESTION # 68
Refer to the lift chart:
At a depth of 0.1, Lift = 3.14. What does this mean?
- A. Selecting the top 10% of the population scored by the model should result in 3.14 times more events than a random draw of 10%.
- B. Selecting the observations with a response probability of at least 10% should result in 3.14 times greater accuracy than a random draw of 10%.
- C. Selecting the observations with a response probability of at least 10% should result in 3.14 times more events than a random draw of 10%.
- D. Selecting the top 10% of the population scored by the model should result in 3.14 times greater accuracy than a random draw of 10%.
Answer: A
NEW QUESTION # 69
PROC GLMSELECT was used for building a model predicting the natural log of a baseball player's salary from certain performance and longevity statistics. The model used backward elimination using SBC as its selection criterion. The sequence of steps is summarized in the graphic shown below:
At Step 9 number of at bats (nAtBat) was removed from the model.
Why was it removed?
- A. Removing nAtBat had the largest effect on the parameter estimate of nHits.
- B. Removing nAtBat yielded the largest improvement to SBC.
- C. The p-Value for nAtBat was largest.
- D. The p-Value for nAtBat was smallest.
Answer: C
NEW QUESTION # 70
Consider scoring new observations in the SCORE procedure versus the SCORE statement in the LOGISTIC procedure.
Which statement is true?
- A. The SCORE procedure and the SCORE statement in the LOGISTIC procedure produce the same output.
- B. Unlike the SCORE procedure, the SCORE statement in the LOGISTIC procedure produces both predicted probabilities and predicted logits.
- C. The SCORE statement in the LOGISTIC procedure returns only predicted probabilities, whereas the SCORE procedure returns only predicted logits.
- D. The SCORE statement in the LOGISTIC procedure returns only predicted logits, whereas the SCORE procedure returns only predicted probabilities.
Answer: C
NEW QUESTION # 71
Spearman statistics in the CORR procedure are useful for screening for irrelevant variables by
investigating the association between which function of the input variables?
- A. Weighted sum of chi-square statistics for 2x2 tables
- B. Logit link (log (p/1-p))
- C. Concordant and discordant pairs of ranked observations
- D. Rank-ordered values of the variables
Answer: D
NEW QUESTION # 72
Which of the following describes a concordant pair of observations in the LOGISTIC procedure?
- A. An observation with the event has a higher predicted probability than the observation without the event
- B. An observation with the event has an equal predicted probability as the observation without the event.
- C. An observation with the event has a lower predicted probability than the observation without the event.
- D. An observation with the event has an equal probability as another observation with the event.
Answer: A
NEW QUESTION # 73
Which SAS program will divide the original data set into 60% training and 40% validation data sets,
stratified by county?
- A. Option D
- B. Option A
- C. Option C
- D. Option B
Answer: C
NEW QUESTION # 74
Refer to the exhibit:
On the Gains Chart, what is the correct interpretation of the horizontal reference line?
- A. the prior event rate
- B. the proportion of cases that cannot be classified
- C. the probability of a false negative
- D. the probability of a false positive
Answer: C
NEW QUESTION # 75
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 D
- B. Option B
- C. Option A
- D. Option C
Answer: B,C
NEW QUESTION # 76
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