1. Identify the dependent variable and independent variables in the Credit

Approval data set.

2. provide a one-paragraph masters-level response describing what you anticipate that

the ctree (conditional inference tree) method will accomplish for the Credit

Approval data? Be specific about the behavior and structure of tree-based

models.

3. Why do we split the dataset into training and test data? Provide a one paragraph,

masters-level response in your own words.

4. interpret the structure of the model including the splitting and leaf nodes in your

discussion. Provide a one-paragraph, masters-level response.

5. Based on the results of your ctree model, which independent variables could

be significant predictors of the dependent variable? Justify why you made

this conclusion by supporting your answer with specific references to the

ctree model itself. Provide a one-paragraph, masters-level response.

6. What differences did you observe between the Apriori association rules

method and the Conditional Inference ctree method? Compar and contrast

at least two characteristics from each method. Provide a one-paragraph,

masters-level response.

7. Do missing values affect the results of the ctree model? Provide a oneparagraph,

masters-level response.

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