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SASInstitute A00-240 Exam Syllabus Topics:

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

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q93-Q98):

NEW QUESTION # 93
An analyst compares the mean salaries of men and women working at a company.
The SAS data set SALARY contains variables:
-Gender (M or F) -Pay (dollars per year)
Which SAS programs can be used to find the p-value for comparing men's salaries with women's salaries? (Choose two.)

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

Answer: A,B

NEW QUESTION # 94
A linear model has the following characteristics:
* A dependent variable (y)
* One continuous variable (x1)
* One categorical (1 with 3 levels) predictor variable and an interaction term (1 by x1) How many parameters, including the intercept, will be estimated for this model?

Answer:

Explanation:
Enter your numeric answer in the space below.
7

NEW QUESTION # 95
Screening for non-linearity in binary logistic regression can be achieved by visualizing:

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

Answer: D

Explanation:
Explanation/Reference:

NEW QUESTION # 96
Which SAS program will divide the original data set into 60% training and 40% validation data sets, stratified by county?

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

Answer: A

NEW QUESTION # 97
Refer to the exhibit.

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

A. All groups are significantly different from each other.
B. No groups are significantly different from each other.
C. Only XL and 2XL are not significantly different from each other.
D. 2XL is significantly different from all other groups.

Answer: C

NEW QUESTION # 98
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