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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Linear Regression | 20% | - Conduct residual and diagnostic analysis - Perform model selection with GLMSELECT - Fit multiple linear regression models - Interpret REG, GLM, and PLM procedure output |
| Topic 2: Logistic Regression | 25% | - Select and optimize input variables - Build models using PROC LOGISTIC - Score new datasets with LOGISTIC and PLM - Interpret odds ratios and model coefficients |
| Topic 3: Prepare Inputs for Predictive Modeling | 20% | - Transform categorical variables - Manipulate data using DATA step - Screen variables with CORR procedure and empirical logit plots - Identify data preparation challenges |
| Topic 4: Measure and Evaluate Model Performance | 25% | - Validate models with training/validation data - Create and interpret ROC, lift, and gains charts - Apply honest assessment principles - Determine optimal decision cut-off values - Use confusion matrices and classification metrics |
| Topic 5: Analysis of Variance (ANOVA) | 10% | - Perform post-hoc tests - Assess ANOVA assumptions - Analyze factor interactions - Use PROC GLM for ANOVA |
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NEW QUESTION # 77
A researcher is planning a logistic regression to model the probability of disease occurrence. The researcher determines the rate of disease occurrence in the population is 1%.
For which of the following would this study be a candidate?
Answer: B
NEW QUESTION # 78
Refer to the ROC curve:
As you move along the curve, what changes?
Answer: A
NEW QUESTION # 79
This question will ask you to provide a missing option.
A business analyst is investigating the differences in sales figures across 8 sales regions. The analyst is interested in viewing the regression equation parameter estimates for each of the design variables.
Which option completes the program to produce the regression equation parameter estimates?
Answer: A
NEW QUESTION # 80
The total modeling data has been split into training, validation, and test data. What is the best data to use for model assessment?
Answer: B
NEW QUESTION # 81
Identify the correct SAS program for fitting a multiple linear regression model with dependent
variable (y) and four predictor variables (x1-x4).
Answer: B
NEW QUESTION # 82
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