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SASInstitute A00-240 Exam Syllabus Topics:

Section	Weight	Objectives
Logistic Regression	25%	- Build models using PROC LOGISTIC - Select and optimize input variables - Score new datasets with LOGISTIC and PLM - Interpret odds ratios and model coefficients
Measure and Evaluate Model Performance	25%	- Validate models with training/validation data - Use confusion matrices and classification metrics - Apply honest assessment principles - Create and interpret ROC, lift, and gains charts - Determine optimal decision cut-off values
Prepare Inputs for Predictive Modeling	20%	- Manipulate data using DATA step - Transform categorical variables - Identify data preparation challenges - Screen variables with CORR procedure and empirical logit plots
Analysis of Variance (ANOVA)	10%	- Perform post-hoc tests - Assess ANOVA assumptions - Use PROC GLM for ANOVA - Analyze factor interactions
Linear Regression	20%	- Fit multiple linear regression models - Interpret REG, GLM, and PLM procedure output - Conduct residual and diagnostic analysis - Perform model selection with GLMSELECT

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q75-Q80):

NEW QUESTION # 75
A linear model has the following characteristics:
A dependent variable (y)

Three continuous predictor variables (x1-x3)

One categorical predictor variable (c1 with 3 levels)

Which SAS program fits this model?

A. Option C
B. Option D
C. Option B
D. Option A

Answer: B

NEW QUESTION # 76
Refer to the exhibit:

Based upon the comparative ROC plot for two competing models, which is the champion model and why?

A. Candidate 2, because it shows less over fit than Candidate 1
B. Candidate 1, because the area outside the curve is greater
C. Candidate 1, because it is closer to the diagonal reference curve
D. Candidate 2, because the area under the curve is greater

Answer: D

NEW QUESTION # 77
Refer to the REG procedure output:

The Intercept estimate is interpreted as:

A. The predicted value of the response when all predictors are at their means.
B. The predicted value of the response when all predictors = 0.
C. The predicted value of the response when all the predictors are at their current values.
D. The predicted value of the response when all predictors are at their minimum values.

Answer: B

NEW QUESTION # 78
Given the following output from the LOGISTIC procedure:

Which variables, among those that are statistically significant at an alpha of 0.05, have the greatest and least relative importance on the fitted model?

A. Greatest: MBALeast: CASH
B. Greatest: DOWN_AMTLeast: CASH
C. Greatest: MBALeast: DOWN_AMT
D. Greatest: DOWN_AMTLeast: HOME

Answer: B

NEW QUESTION # 79
The SAS data set RESULT contains the following variables:
* Region (GrpA or GrpB)
* Sales (dollars per year)
Which SAS programs can be used to find the p-value for comparing GrpA sales with GrpB sales? (Choose two.)

Answer: A,D

NEW QUESTION # 80
......

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