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SASInstitute A00-240 Exam Syllabus Topics:

SectionObjectives
Topic 1: Multiple Regression- Multicollinearity diagnostics
- Model building and selection
- Interaction effects
Topic 2: Logistic Regression- Model fit and diagnostics
- Binary logistic regression
Topic 3: Simple Linear Regression- Residual analysis
- Estimation and inference
- Model assumptions and interpretation
Topic 4: Model Diagnostics and Validation- Goodness-of-fit measures
- Influence and leverage
Topic 5: ANOVA and General Linear Models- One-way and multi-way ANOVA
- GLM procedures in SAS

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q81-Q86):

NEW QUESTION # 81
In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

Answer: B


NEW QUESTION # 82
An analyst knows that the categorical predictor, zip_code, is an important predictor of a binary target.
However, zip_code has too many levels to be a feasible predictor in a model. The analyst uses PROC CLUSTER to implement Greenacre's method to reduce the number of categorical levels.
What is the correct application of Greenacre's method in this situation?

Answer: C

Explanation:
Explanation/Reference: https://support.sas.com/resources/papers/proceedings/proceedings/sugi31/079-31.pdf


NEW QUESTION # 83
Screening for non-linearity in binary logistic regression can be achieved by visualizing:

Answer: C


NEW QUESTION # 84
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: D


NEW QUESTION # 85
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?

Answer: A


NEW QUESTION # 86
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