Reference no: EM132161727

1. Mountain Insurance is assigning their most complicated workers compensation claims to seasoned claims adjusters as soon as they are reported. The company has a data science team that uses the classification tree technique to develop a predictive model. Holdout data is used to test their model's predictive accuracy, 25% of the complex claims were assigned to experienced adjusters. When claims were randomly assigned, only 17% of the complex claims were assigned to experienced adjusters. What is the lift provided by the predictive model?

A. 0.25.

B. 0.40.

C. 0.68.

D. 0.75

2. Which one of the following types of data is used to test a predictive model?

A. Holdout data.

B. Lift data.

C. Node data.

D. Leaf data.

3. A branch of a classification tree , leading to a classification of a target variable ends at a..

A. Leaf node.

B. Root node.

C. Classification tree.

D. Regression leaf.

4. Predicting claims that would result into long term disability claims is a challenge for all insurers. One company’s data science team uses a classification tree technique to develop a predictive model based on the specific attributes of past long term disability claims. Restricted or light duty work was also found be one of the most informative attribute. What part of the classification tree should be used?

A. Root node.

B. Leaf node.

C. Second branch.

D. Trunk node.

5. Which kinds of workers compensation claims are the most difficult for insurers to identify when initially reported?  

A. Medical payment claims.

B. Major claims.

C. Potentially complex claims.

D. Potentially minor claims.