Exhibit 10.1
The following questions are based on the problem description and the output below.
A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores, verbal and quantitative. Students are classified as either successful or not-successful in their graduate studies. The officer has data on 20 current students, ten of whom are doing very well (Group 1) and ten who are not (Group 2) .
-Refer to Exhibit 10.1. Suppose that for a given observation, the difference between Mahalanobis distances between group 1 and 2 (G1-G2) is big and negative. This means that
A) The observation is likely to be classified correctly to group 2
B) The observation is likely to be classified correctly to group 1
C) The observation is likely to be classified incorrectly to group 2
D) The observation is likely to be classified incorrectly to group 1
Correct Answer:
Verified
Q71: A _ provides a visual summary of
Q72: Which of the following is not true
Q73: The k-nearest neighbor classification technique
A) identifies the
Q74: A _ algorithm is used during the
Q75: Affinity analysis is a data mining technique
Q77: To create the training and validation data
Q78: A way to detecting and avoiding overfitting
Q79: Suppose that all observations in partition j
Q80: In using neural networks, an analyst must
Q81: The objective function in k-means clustering attempts
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