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SASInstitute A00-240 Exam is a computer-based exam that consists of 66 multiple choice and short-answer questions. Candidates have two hours and 30 minutes to complete the exam. A00-240 exam is rigorous and challenging, designed to test a candidate's understanding of various regression and modeling concepts along with SAS programming skills. Therefore, candidates need to have a thorough understanding of the SAS software and statistics to pass the exam.

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SASInstitute A00-240 Certification is a valuable credential for professionals who work in the field of business analytics. By passing A00-240 exam, individuals can demonstrate their proficiency in SAS statistical software and their ability to perform statistical analysis using regression and modeling techniques.

SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q80-Q85):

NEW QUESTION # 80
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. Regions with higher average purchases have more medium value customers.
C. Regions with higher average purchases have more high value customers.
D. The difference between average purchases for medium and high value customers depends on the region.

Answer: D

Explanation:
Explanation/Reference:

NEW QUESTION # 81
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: MBA
Least: CASH
B. Greatest: DOWN_AMT
Least: CASH
C. Greatest: DOWN_AMT
Least: HOME
D. Greatest: MBA
Least: DOWN_AMT

Answer: B

NEW QUESTION # 82
After performing an ANOVA test, an analyst has determined that a significant effect exists due to income. The analyst wants to compare each Income to all others and wants to control for experimentwise error.
Which GLM procedure statement would provide the most appropriate output?

A. lsmeans Income / pdiff=all adjust=tukey;
B. lsmeans Income / pdiff=control adjust=dunnett;
C. lsmeans Income / pdiff=all adjust=t;
D. lsmeans Income / pdiff=control adjust=t;

Answer: B

NEW QUESTION # 83
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 recalculated using the validation data.
B. The imputed values are irrelevant to the validation data, and are not used.
C. The imputed values must be applied directly to the validation data without recalculation.
D. The imputed values must be recalculated using both the training and the validation data.

Answer: A

NEW QUESTION # 84
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. There is no ability to compare the effectiveness of different cleansing methods.
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. It violates assumptions of the model.

Answer: A

NEW QUESTION # 85
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