Question: PLEASE START THIS QUESTION ONLY IN EXCEL The file ClassificationData.xlsx contains the following information about the top 25 MBA pro- grams: percentage of applicants accepted,

PLEASE START THIS QUESTION ONLY IN EXCEL

The file ClassificationData.xlsx contains the following information about the top 25 MBA pro- grams: percentage of applicants accepted, percentage of accepted applicants who enroll, mean GMAT score of enrollees, mean undergraduate GPA of enrollees, annual cost of school (for state schools, this is the cost for out-of-state students), percentage of students who are minori- ties, percentage of students who are non-U.S. residents, and mean starting salary of graduates (in thousands of dollars). Use these data to divide the top 25 schools into 4 clusters, using for example the K-Means clustering algorithm, and interpret your clusters. The method is ex- plained in our textbook: Section 8.8 in the Fourth and Fifth Edition or Section 14.3 in the Sixth Edition. More precisely, use Evolutionary Solver to find 4 schools to be used as cluster centers and to assign all other schools to one of these cluster centers. Each school is then assigned to the nearest cluster center, where nearest is defined in terms of the eight attributes. The objective is to minimize the sum of the distances from each school to its cluster center.

Hint: Your model will have four decision variables (changing cells) corresponding to the in- dexes of the four schools chosen as cluster centers. In addition, please note that you need to first standardize the value of each attribute by subtract- ing the attribute's mean and dividing the difference by the attribute's standard deviation.

School % accepted % accepted who enroll Mean GMAT Mean GPA Total Cost % minority % non-US Mean Starting Salary
Wharton 15 71 662 3.42 32400 16 30 102
Michigan 28 44 645 3.3 29800 15 26 86
Northwestern 14 69 660 3.3 32600 9 24 99
Harvard 13 88 680 3.5 30100 19 27 114
Virginia 19 49 660 3.1 31200 20 12 93
Columbia 14 70 660 3.3 32200 12 24 93
Stanford 7 81 690 3.6 34500 25 25 111
Chicago 23 57 685 3.4 34200 5 23 90
MIT 14 12 650 3.5 36700 15 37 101
Dartmouth 14 49 669 3.39 32700 9 16 104
Duke 17 50 646 3.33 30100 12 19 84
UCLA 17 55 651 3.5 27100 10 20 91
Berkeley 13 51 652 3.42 29100 11 35 91
NYU 20 11 646 3.3 32700 8 35 79
Indiana 45 20 630 3.2 21000 8 16 68
Washington U 43 40 606 3.2 28000 6 39 62
Carnegie-Mellon 31 65 638 3.2 27200 2 38 86
Cornell 25 38 634 3.3 29600 11 28 55
UNC 19 55 630 3.3 17500 16 19 80
Texas 18 12 631 3.3 19100 14 17 69
Rochester 36 34 630 3.22 28200 9 46 68
Yale 23 54 676 3.38 32000 15 31 88
SMU 62 48 601 3 26300 5 22 63
Vanderbilt 42 47 615 3.2 29700 7 23 63
Thunderbird 75 64 572 3.41 23800 10 33 57

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