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#School #Svys
Score
1
Columbia Southern University  
94
23.4 23.4
2
Brown University  
212
23.3 23.3
3
Colgate University  
174
23.1 23.1
4
University of California Irvine  
161
23.0 23.0
5
Dartmouth College  
102
22.6 22.6
6
The University of West Florida  
87
22.4 22.4
7
Emory University  
101
22.4 22.4
8
College of the Holy Cross  
88
22.3 22.3
9
Yale University  
118
22.3 22.3
10
Rice University  
95
22.2 22.2
11
Knox College  
105
22.2 22.2
12
University of Notre Dame  
106
22.0 22.0
13
Marist College  
255
22.0 22.0
14
University of Chicago  
143
22.0 22.0
15
University of Pennsylvania  
157
21.9 21.9
16
Duke University  
94
21.9 21.9
17
Tufts University  
95
21.9 21.9
18
Mount Holyoke College  
105
21.8 21.8
19
Washington University in St Louis  
122
21.8 21.8
20
Milwaukee School of Engineering  
91
21.7 21.7
21
Cornell University  
225
21.7 21.7
22
Bucknell University  
90
21.7 21.7
23
Massachusetts Institute of Technology  
153
21.6 21.6
24
Wake Forest University  
100
21.6 21.6
25
University of Virginia   
153
21.6 21.6
26
Villanova University  
162
21.5 21.5
27
Saint Joseph's University  
105
21.3 21.3
28
Johns Hopkins University  
192
21.2 21.2
29
College of William and Mary  
191
21.2 21.2
30
University of Rochester  
154
21.2 21.2
31
University of Missouri Columbia  
85
21.2 21.2
32
American University  
129
21.2 21.2
33
Texas A & M University College Station  
235
21.1 21.1
34
Northwestern University  
160
21.1 21.1
35
Brandeis University  
102
21.1 21.1
36
Syracuse University  
187
21.0 21.0
37
Purdue University   
157
21.0 21.0
38
Stanford University  
91
21.0 21.0
39
University of Oregon  
108
21.0 21.0
40
The University of Alabama  
99
21.0 21.0
41
Christopher Newport University  
176
21.0 21.0
42
James Madison University  
224
20.8 20.8
43
University of Pittsburgh Pittsburgh Campus  
163
20.7 20.7
44
Ohio Wesleyan University  
162
20.7 20.7
45
Lehigh University  
135
20.7 20.7
46
Michigan State University  
222
20.7 20.7
47
University of California Santa Barbara  
121
20.7 20.7
48
Texas Tech University  
135
20.6 20.6
49
Indiana University Bloomington  
149
20.6 20.6
50
Tulane University of Louisiana  
136
20.6 20.6

 

About
The Ranking of Top 50 universities is made up as follows:
50% - Educational Quality
25% = Academic Success is based upon 'understanding'
12% - Creativity Encouragement
5% - Work is Useful
4% = Faculty Accessibility
4% - University Funding Use

Filtering
    Student Surveys are filtered of duplicate and “invalid” surveys prior to ranking.  Invalid surveys are those that are not self-consistent, reflecting a corrupting effect on the data, either accidental or with intent.  We have found that certain inclined students survey their “competing” schools, giving artificially bad (or good of their own school) reviews.  While we do not wish to point any fingers, we have been able to link up several groupings of falsified data with admissions staff at some universities. 
    5,000 valid surveys were analyzed statistically, and a gaussian matrix was created to model the survey patterns within and between surveys. 
We can now identify those surveys that: vary too little, vary too much, have fields that do not covary properly, or are inconsistent.  (i.e.  rating the university as an A for friendliness, but then complaining either about the people or the social life).  In addition, a rule-base system was created to identify duplicates and model trends of surveys from the same machine. 
This allows us to be able to identify if a person is falsifying many surveys.  FFT analysis is employed to determine the “data content” of each survey as well, providing more information for modeling. 
    The resulting filter, correlation matrix, and survey model is applied uniformly to all surveys.  Out of 7,500 undergraduate student surveys, 483 surveys were rendered invalid.  Inspection of the invalid surveys revealed a failure rate of 5%.  (24 of the 483 surveys were actually “good",2.5).

How is rank computed?

    The generic quick answer is that it is the average of student opinion ratings minus “variability of score”.  The “variability of score” is larger for low numbers of surveys, meaning that that school's ranking position is less trustably high or low.  Strict statistical variance is not instructive here because 'variance' is computed within a group of surveys — with only 1 survey, there is no variance.

The 'Variability' function decreases exponentially with the size of the sample set, applied equally to all institutions, making it an acceptably fair accounting form.  After 5 surveys, the variability of score drops to less than .3; after 10 surveys, it is less than .1.  After 20 surveys, there no significant variability in position.  Essentially, each school's score converges to a position as the number of surveys increases.

More specifically, Rank is computed by multiplying the importance of each variable selected by that variable and adding together.  The average of all matching surveys for a particular school is then taken.  From this, a 'variability' is computed — this is based upon the number of surveys.  If there is only 1 survey, and it ranks a school at a 10, then 1 more survey could come in, ranking a '0', which would give the school average a 5 (10/(1+1) = 5).  This is the lowest that the school 'could' be — given 1 more survey.  So this 'variability' is subtracted from the overall score, reducing it.  In this manner, schools that have more surveys have a more believable average than school with only 1 survey. 

Actual Equation:
score = average(importances[]*preferences[]) - (10*(sum(importances[])))/(#svys + 1)

 

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