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SASInstitute A00-240 Exam Syllabus Topics:

Section	Objectives
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
Logistic Regression	- Binary logistic regression - Model fit and diagnostics
Multiple Regression	- Model building and selection - Multicollinearity diagnostics - Interaction effects
Simple Linear Regression	- Model assumptions and interpretation - Residual analysis - Estimation and inference

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q67-Q72):

NEW QUESTION # 67
This question will ask you to provide a missing option. Given the following SAS program:

What option must be added to the program to obtain a data set containing Pearson statistics?

A. OUTPUT=estimates
B. OUTP=estimates
C. OUTCORR=estimates
D. OUTSTAT=estimates

Answer: B

NEW QUESTION # 68
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?

A. Age Weight RunTime RunPulse RestPulse MaxPulse
B. RestPulse
C. RunTime
D. Age Weight RunTime RunPulse MaxPulse

Answer: D

NEW QUESTION # 69
The PROC LOGISTIC options SELECTION=SCOREand BEST=2are used in a MODEL statement to generate a series of predictive models. The models are assigned numbers in order from 1 to 99 reflecting the fact that there are 50 candidate input variables. Results from the collection of derived models are used to generate the following plot of overall average profit by model number. Results are restricted to models with at least 9 inputs and at most 40 inputs.

The maximum value for the training data occurs for model number 46, and the maximum value for the validation data occurs for model number 43.
If you base model selection solely on overall average profit, what is the correct choice?

A. Select model 21
B. Select model 46
C. Select model 43
D. Select model 45

Answer: C

NEW QUESTION # 70
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?

A. It omits the training (and test) data sets from the benefits of the cleansing methods.
B. It violates assumptions of the model.
C. It requires extra computational effort and time.
D. There is no ability to compare the effectiveness of different cleansing methods.

Answer: D

NEW QUESTION # 71
Screening for non-linearity in binary logistic regression can be achieved by visualizing:

A. A trend plot of empirical logit versus a predictor variable.
B. A box plot of the odds ratio values versus a predictor variable.
C. A logistic regression plot of predicted probability values versus a predictor variable.
D. A scatter plot of binary response versus a predictor variable.

Answer: A

NEW QUESTION # 72
......

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