SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential model question
Q.1Which statement best summarizes the assumptions placed on the errors term in liner regression?
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.
Q.2 A non-contributing predictor variable (Pr > |t| =0.658) is added to an existing multiple linear
regression model.
What will be the result?
A. An increase in R-Square
B. A decrease in R-Square
C. A decrease in Mean Square Error
D. No change in R-Square
Q.3 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. Concordant and discordant pairs of ranked observations
B. Logit link (log(p/1-p))
C. Rank-ordered values of the variables
D. Weighted sum of chi-square statistics for 2×2 tables
Q.4
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.
Q.5 There are missing values in the input variables for a regression application.
Which SAS procedure provides a viable solution?
A. GLM
B. VARCLUS
C. STDIZE
D. CLUSTER
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