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SASInstitute A00-240 Exam Syllabus Topics:

SectionObjectives
Logistic Regression- Binary logistic regression
- Model fit and diagnostics
Model Diagnostics and Validation- Influence and leverage
- Goodness-of-fit measures
ANOVA and General Linear Models- One-way and multi-way ANOVA
- GLM procedures in SAS
Simple Linear Regression- Residual analysis
- Model assumptions and interpretation
- Estimation and inference
Multiple Regression- Model building and selection
- Multicollinearity diagnostics
- Interaction effects

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q66-Q71):

NEW QUESTION # 66
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 AIC statistic, which model is the champion model?

Answer: A


NEW QUESTION # 67
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?

Answer: D


NEW QUESTION # 68
Refer to the exhibit.

Based on the control plot, which conclusion is justified regarding the means of the response?

Answer: B


NEW QUESTION # 69
One common approach for predicting rare events in the LOGISTIC procedure is to build a model that
disproportionately over-re presents those cases with an event occurring (e.g. a 50-50 event/non-event
split).
What problem does this present?

Answer: D


NEW QUESTION # 70
There are missing values in the input variables for a regression application.
Which SAS procedure provides a viable solution?

Answer: C


NEW QUESTION # 71
......

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