Exam Details

  • Exam Code
    :A00-240
  • Exam Name
    :SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential
  • Certification
    :Statistical Business Analyst
  • Vendor
    :SASInstitute
  • Total Questions
    :99 Q&As
  • Last Updated
    :May 16, 2024

SASInstitute Statistical Business Analyst A00-240 Questions & Answers

  • Question 21:

    Refer to the exhibit.

    Output from a multiple linear regression analysis is shown.

    What is the most appropriate statement concerning collinearity between the input variables?

    A. Collinearity is a problem since all variance inflation values are less than 10.

    B. Collinearity is not a problem since all variance inflation values are less than 10.

    C. Collinearity is not a problem since all Pr>|t| values are less than 0.05.

    D. Collinearity is a problem since all Pr>|t| values are less than 0.05.

  • Question 22:

    The Model SS in a multiple linear regression model is equal to:

    A. the total SS- MSE

    B. the sum of Type I SS of all model terms

    C. the sum of Type II SS of all model terms

    D. the sum of SSE and MSE

  • Question 23:

    Which characteristic of Studentized residuals indicate potential outliers?

    A. Only studentized residuals greater than negative two

    B. Only studentized residuals less than negative two and greater than two

    C. Only studentized residuals greater than two

    D. Only studentized residuals less than two and greater than negative two

  • Question 24:

    Refer to the exhibit:

    SAS output from the RSQUARE selection method, within the REG procedure, is shown. The top two models in each subset are given. Based on the exhibit, which statement is true?

    A. The AIC champion model is more parsimonious than the SBC champion.

    B. The SBC champion model is more parsimonious than the AIC champion.

    C. The R-Square champion model is the most parsimonious.

    D. Adjusted R-Square and R-Square agree on the champion model.

  • Question 25:

    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. The p-Value for nAtBat was largest.

    C. Removing nAtBat yielded the largest improvement to SBC.

    D. The p-Value for nAtBat was smallest.

  • Question 26:

    The SAS data set RESULT contains the following variables:

    1.

    Region (GrpA or GrpB)

    2.

    Sales (dollars per year)

    Which SAS programs can be used to find the p-value for comparing GrpA sales with GrpB sales? (Choose two.)

    A. Option A

    B. Option B

    C. Option C

    D. Option D

  • Question 27:

    Refer to the exhibit.

    These graphs were created using the GLM procedure with the plots(only)=diagnostics option.

    Which plot do you use to identify influential observations?

    A. Cook's D by Observation

    B. Residual by Quantile

    C. Residual by Predicted

    D. Fit - Mean and Residual Plot

  • Question 28:

    Within PROC GLM, the interaction between the two categorical predictors, Income and Gender, was shown to be significant. An item store was saved from the GLM analysis.

    Which statement from PROC PLM would test the significance of Gender within each level of Income and adjust for multiple tests?

    A. sliceby Gender / adjust=tukey;

    B. slice Income*Gender / sliceby=Gender adjust=tukey;

    C. slice Income*Gender / sliceby=Income adjust=tukey;

    D. sliceby Income / adjust=tukey;

  • Question 29:

    Refer to the exhibit.

    Which conclusion is justified concerning Sales, comparing stores A, B, and C?

    A. Store B is significantly different from store A.

    B. Store C is significantly different from Store A.

    C. Store B is significantly different from store C.

    D. There is no significant difference between stores.

  • Question 30:

    What is the default method in the LOGISTIC procedure to handle observations with missing data?

    A. Missing values are imputed.

    B. Parameters are estimated accounting for the missing values.

    C. Parameter estimates are made on all available data.

    D. Only cases with variables that are fully populated are used.

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