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| Section | Weight | Objectives |
|---|---|---|
| Model Assessment and Selection | 20% | - Model comparison - ROC and Lift curves - Model fit statistics |
| Building Predictive Models | 40% | - Neural networks - Regression models - Gradient boosting - Decision trees |
| Data Preparation and Exploration | 20% | - Importing data - Data exploration using SAS Visual Statistics - Data quality |
| Scoring and Deployment | 20% | - Model deployment - Model scoring |
1. Refer to the exhibit:
A cluster has been created with four variables selected on the roles tab.
Select the set of Parallel Coordinates Properties that would display the image in the exhibit.
A)
B)
C)
D) 
2. Which statement is correct about using a multinomial response variable (with 3 or more levels) in the logistic regression task in SAS Visual Statistics?
A) The resulting model is an ordinal logistic regression model with the lowest level of the response as the reference.
B) You cannot assign a response variable with 3 or more levels to the logistic regression visualization.
C) The resulting model is a binary logistic regression model with a selected level as the event.
D) The resulting model is a multinomial logistic regression model with a generalized logit link.
3. You want to fit a Poisson regression and use the log link function to predict skin cancer from weather, pollution, and demographic variables. Each row in the data is a geographic region.
The response, Melanoma, is stored as the number of melanoma skin cancer cases in each region.
Because some regions have many people and some have few, your data also includes a variable with the region population.
What is the best way to include population in this model?
A) Add the log of Population as an effect.
B) Add Population as an effect.
C) Add Population as an offset.
D) Add the log of Population as an offset.
4. When assigning roles in a GLM, what does the "offset" variable typically represent?
A) A variable used to adjust the intercept
B) A predictor variable
C) The target variable
D) A variable with a known constant coefficient
5. What information can you interpret from a Cluster Matrix?
A) The cluster centroids
B) The number of data points in each cluster
C) The order of cluster creation
D) The proximity or similarity between clusters
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: A,D | Question # 5 Answer: A,D |
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