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SAS A00-240 Exam Questions
- Topic 1: Identify the potential challenges when preparing input data for a model/ Detect and analyze interactions between factors
- Topic 2: Model selection and validation using training and validation data/ Perform ANOVA post hoc test to evaluate treatment effect
- Topic 3: Establish effective decision cut-off values for scoring/ Fit a multiple linear regression model using the REG and GLM procedures
- Topic 4: Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection/ Use the REG or GLMSELECT procedure to perform model selection
- Topic 5: Screen variables for irrelevance and non-linear association using the CORR procedure/ Perform logistic regression with the LOGISTIC procedure
- Topic 6: Screen variables for non-linearity using empirical logit plots/ Score new data sets using the LOGISTIC and PLM procedures
- Topic 7: Apply the principles of honest assessment to model performance measurement/ Optimize model performance through input selection
- Topic 8: Analyze differences between population means using the GLM and TTEST procedures/ Assess classifier performance using the confusion matrix
- Topic 9: Assess the validity of a given regression model through the use of diagnostic and residual analysis/ Prepare Inputs for Predictive Model Performance
- Topic 10: Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models/ Improve the predictive power of categorical inputs
Free SAS A00-240 Exam Actual Questions
Note: Premium Questions for A00-240 were last updated On Apr. 13, 2025 (see below)
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?
Given the following SAS data set TEST:
Which SAS program is NOT a correct way to create dummy variables?
This question will ask you to provide a segment of missing code.
The following code is used to create missing value indicator variables for input variables, fred1 to fred7.
Which segment of code would complete the task?
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 dat
a. 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?
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