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- A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
Free A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling Exam Questions and Answers
Last updated: March 29, 2025
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1175-A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
#Question
In regression analysis, what does the term "white noise" mean concerning residuals?
A.
Residuals are uncorrelated with zero mean
B.
Residuals show a pattern or trend
C.
Residuals are consistently positive
D.
Residuals are highly volatile
Correct Answer:
A
White noise implies that the residuals are uncorrelated and follow a normal distribution with a mean of zero.
#Question
What does the term "cross-validation" imply in model evaluation?
A.
Testing the model on a different dataset
B.
Evaluating model accuracy through multiple batches
C.
Randomly selecting subsets for training
D.
Fitting the model on the same dataset multiple times
Correct Answer:
A
Cross-validation involves assessing the model's performance using an independent dataset.
#Question
Which SAS procedure is typically used for conducting regression analysis?
A.
PROC MEANS
B.
PROC GLM
C.
PROC REG
D.
PROC SURVEY
Correct Answer:
C
PROC REG is specifically designed for performing linear regression analyses in SAS.
#Question
In statistical terminology, what is "power"?
A.
The amount of data used
B.
The probability of making a Type I error
C.
The ability of a test to reject a true null hypothesis
D.
The significance level of a test
Correct Answer:
C
Power refers to the likelihood that a statistical test will correctly reject a false null hypothesis.
#Question
Which technique helps to deal with multicollinearity in regression models?
A.
Any of the above
B.
Ridge regression
C.
Transformation of variables
D.
Removing predictors
Correct Answer:
A
Multicollinearity can be addressed through various methods, including removal or regularization techniques like ridge regression.
#Question
What is a benefit of using the AIC (Akaike Information Criterion) for model comparison?
A.
It does not need evaluation against other models
B.
It only accepts linear models
C.
It penalizes for the number of parameters
D.
All of the above
Correct Answer:
C
AIC penalizes the number of parameters in the model, balancing model fit and complexity for better comparison.
#Question
When should you consider conducting a Mann-Whitney U test?
A.
When data follows a normal distribution
B.
When variables are categorical
C.
For paired sample comparisons
D.
When comparing two independent groups with non-normally distributed data
Correct Answer:
D
The Mann-Whitney U test is appropriate for comparing two independent groups when the data do not follow a normal distribution.
1175-A00-240: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
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