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SASInstitute A00-240 Exam Syllabus Topics:

Section	Weight	Objectives
Linear Regression	20%	- Interpret Regression Results 1. Interpret REG, PLM and GLM output 2. Evaluate parameter estimates - Build Regression Models 1. Fit multiple linear regression models 2. Use REG and GLM procedures - Model Selection and Diagnostics 1. Assess model validity 2. Perform model selection using REG or GLMSELECT 3. Conduct residual and diagnostic analysis
Prepare Inputs for Predictive Model Performance	20%	- Data Preparation 1. Use loops, arrays, functions and conditional statements 2. Identify challenges in preparing model input data 3. Manipulate data using DATA step programming - Variable Engineering and Screening 1. Identify nonlinear associations using CORR procedure 2. Improve predictive power of categorical variables 3. Use empirical logit plots for nonlinearity detection 4. Screen variables for irrelevance
Logistic Regression	25%	- Develop Logistic Models 1. Perform logistic regression using the LOGISTIC procedure 2. Optimize model performance through input selection - Interpret and Deploy Models 1. Interpret LOGISTIC procedure output 2. Score new data sets using LOGISTIC and PLM procedures
ANOVA	10%	- ANOVA Analysis 1. Perform post hoc tests 2. Detect and analyze factor interactions 3. Evaluate treatment effects 4. Analyze differences between population means using GLM and TTEST procedures - ANOVA Concepts and Assumptions 1. Identify appropriate ANOVA methods 2. Verify ANOVA assumptions
Measure Model Performance	25%	- Model Assessment 1. Apply principles of honest assessment 2. Assess classifier performance using confusion matrices - Performance Visualization 1. Create and interpret gains charts 2. Create and interpret lift charts 3. Create and interpret ROC charts - Validation and Selection 1. Perform model validation using training and validation data 2. Compare and select predictive models - Decision Optimization 1. Establish effective decision cutoff values 2. Evaluate scoring strategies

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q92-Q97):

NEW QUESTION # 92
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. OUTSTAT=estimates
B. OUTP=estimates
C. OUTPUT=estimates
D. OUTCORR=estimates

Answer: B

NEW QUESTION # 93
Which of the following describes a concordant pair of observations in the LOGISTIC procedure?

A. An observation with the event has a higher predicted probability than the observation without the event
B. An observation with the event has a lower predicted probability than the observation without the event.
C. An observation with the event has an equal probability as another observation with the event.
D. An observation with the event has an equal predicted probability as the observation without the event.

Answer: A

Explanation:
Explanation

NEW QUESTION # 94
Refer to the following odds ratio table:

What is a correct interpretation of the estimate?

A. The odds of the event are 1.142 greater for each one dollar increase in salary.
B. The odds of the event are 1.142 greater for each one thousand dollar increase in salary.
C. The probability of the event is 1.142 greater for each one thousand dollar increase in salary.
D. The probability of the event is 1.142 greater for each one dollar increase in salary.

Answer: B

NEW QUESTION # 95
Given the following GLM procedure output:

Which statement is correct at an alpha level of 0.05?

A. Gender should be removed because it is non-significant.
B. School*Gender should be removed because it is non-significant.
C. Gender should not be removed due to its involvement in the significant interaction.
D. School should be removed because it is significant.

Answer: C

NEW QUESTION # 96
An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.
Which statement and option combination will generate these statistics?

A. mode1resp(event= '1') = gender region/outroc=roc;
B. Scoredata=valid1 outroc=roc;
C. Scoredata=valid1 out=roc;
D. mode1resp(event"1") = gender region/ out=roc;

Answer: B

NEW QUESTION # 97
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