1 - Identify the uncontrollable variable from the following inputs of a decision

ID: 338529 • Letter: 1

Question

1 - Identify the uncontrollable variable from the following inputs of a decision model.

Investment returns

Machine capacities

Staffing levels

Intercity distances

2. In the ________ method, the distance between groups is defined as the distance between the closest pair of objects, where only pairs consisting of one object from each group are considered.

Ward's linkage clustering

single linkage clustering

divisive clustering

average group linkage clustering

3. Divisive clustering method is different from agglomerative clustering methods in that divisive clustering methods:

can only have a pair of subjects in each cluster.

separate objects into a particular cluster in one step.

separate n objects successively into finer groupings.

can only have a single subject in each cluster.

4. ________ is the ratio of the number of transactions that include all items in the consequent as well as the antecedent to the number of transactions that include all items in the antecedent.

Lift

Logit

Support for the association rule

Confidence of the association rule.

5. The weights for determining the discriminant functions are determined by:

assessing the number of outliers that are present in each group.

calculating the distance between the two closest observations in each group.

measuring the closeness between predictor values of each set.

maximizing the between-group variance relative to the within-group variance.

6. In classification, which of the following would be considered as a categorical variable of interest for a credit approval decision for a requester?

Age of the requester

Income of the requester

Revolving balance of the requester Reject or accept credit approval

7. Logistic regression is different from discriminant analysis in that logistic regression:

does not predict the weights.

sets observation into predefined classes.

does not depend on assumptions.

depends on assumptions such as normalization of independent variables.

8. Which of the following is true of association rule mining?

It develops analytic models to describe the relationship between metrics that drive business performance.

It identifies attributes that occur frequently together in a given data set.

It seeks to classify a categorical outcome into one of two or more categories.

It is a data reduction technique that reduces large information into smaller heterogeneous groups.

Explanation / Answer