Quiz SASInstitute - A00-240 - SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential–Efficient Test Passing Score

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SASInstitute A00-240 Exam Syllabus Topics:

Section	Weight	Objectives
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 ROC charts 2. Create and interpret lift charts 3. Create and interpret gains charts - Decision Optimization 1. Establish effective decision cutoff values 2. Evaluate scoring strategies - Validation and Selection 1. Perform model validation using training and validation data 2. Compare and select predictive models
ANOVA	10%	- ANOVA Analysis 1. Detect and analyze factor interactions 2. Analyze differences between population means using GLM and TTEST procedures 3. Evaluate treatment effects 4. Perform post hoc tests - ANOVA Concepts and Assumptions 1. Verify ANOVA assumptions 2. Identify appropriate ANOVA methods
Linear Regression	20%	- Model Selection and Diagnostics 1. Assess model validity 2. Perform model selection using REG or GLMSELECT 3. Conduct residual and diagnostic analysis - Build Regression Models 1. Fit multiple linear regression models 2. Use REG and GLM procedures - Interpret Regression Results 1. Evaluate parameter estimates 2. Interpret REG, PLM and GLM output
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
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. Improve predictive power of categorical variables 2. Use empirical logit plots for nonlinearity detection 3. Identify nonlinear associations using CORR procedure 4. Screen variables for irrelevance

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q16-Q21):

NEW QUESTION # 16
Refer to the following exhibit:

What is a correct interpretation of this graph?

A. The association between the continuous predictor and the continuous response is quadratic.
B. The association between the binary predictor and the log-odds is quadratic.
C. The association between the continuous predictor and the log-odds is quadratic.
D. The association between the continuous predictor and the binary response is quadratic.

Answer: C

NEW QUESTION # 17
Refer to the exhibit:

The plots represent two models, A and B, being fit to the same two data sets, training and validation.
Model A is 90.5% accurate at distinguishing blue from red on the training data and 75.5% accurate at doing the same on validation data. Model B is 83% accurate at distinguishing blue from red on the training data and
78.3% accurate at doing the same on the validation data.
Which of the two models should be selected and why?

A. Model A. It is more complex with a higher accuracy than model B on training data.
B. Model B. It is more complex with a higher accuracy than model A on validation data.
C. Model A. It performs better on the boundary for the training data.
D. Model B. It is simpler with a higher accuracy than model A on validation data.

Answer: D

NEW QUESTION # 18
A financial services manager wants to assess the probability that certain clients will default on their Home Equity Line of Credit (HELOC). A former employee left the code listed below.

The training data set is named HELOC, while a similar data set of more recent clients is named RECENT_HELOC.
Which SAS data steps will calculate the predicted probability of default on recent clients? (Choose two.)

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

Answer: A,D

NEW QUESTION # 19
Suppose training data are oversampled in the event group to make the number of events and non-events roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than 0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0= No event).
The following SAS program was used.

What does this program calculate?

A. Positive predictive value
B. Depth
C. Sensitivity
D. Specificity

Answer: C

NEW QUESTION # 20
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 C
C. Option D
D. Option A

Answer: A,D

NEW QUESTION # 21
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