#	School	#Svys	Score
1	Brown University	209	23.3 23.3
2	Columbia Southern University	88	23.2 23.2
3	Colgate University	168	23.0 23.0
4	University of California Irvine	158	23.0 23.0
5	Dartmouth College	101	22.6 22.6
6	The University of West Florida	83	22.5 22.5
7	Emory University	99	22.4 22.4
8	College of the Holy Cross	85	22.3 22.3
9	Yale University	111	22.2 22.2
10	Rice University	93	22.2 22.2
11	Knox College	101	22.2 22.2
12	Marist College	249	22.0 22.0
13	University of Chicago	140	21.9 21.9
14	University of Notre Dame	101	21.9 21.9
15	University of Pennsylvania	155	21.9 21.9
16	Duke University	93	21.9 21.9
17	Tufts University	94	21.9 21.9
18	Mount Holyoke College	99	21.8 21.8
19	Cornell University	217	21.7 21.7
20	Milwaukee School of Engineering	91	21.7 21.7
21	Washington University in St Louis	111	21.7 21.7
22	Bucknell University	88	21.7 21.7
23	Wake Forest University	99	21.6 21.6
24	University of Virginia	149	21.6 21.6
25	Massachusetts Institute of Technology	150	21.6 21.6
26	Villanova University	161	21.5 21.5
27	University of Missouri Columbia	80	21.5 21.5
28	Saint Joseph's University	97	21.4 21.4
29	Johns Hopkins University	190	21.3 21.3
30	College of William and Mary	186	21.3 21.3
31	American University	125	21.2 21.2
32	University of Rochester	147	21.2 21.2
33	The University of Alabama	94	21.1 21.1
34	Syracuse University	180	21.1 21.1
35	Brandeis University	99	21.1 21.1
36	Purdue University	154	21.1 21.1
37	Northwestern University	154	21.0 21.0
38	Texas A & M University College Station	229	21.0 21.0
39	University of Oregon	104	21.0 21.0
40	Stanford University	89	21.0 21.0
41	Lehigh University	126	21.0 21.0
42	Christopher Newport University	171	20.9 20.9
43	Michigan State University	216	20.9 20.9
44	University of Pittsburgh Pittsburgh Campus	153	20.9 20.9
45	University of Wisconsin Madison	181	20.8 20.8
46	James Madison University	213	20.7 20.7
47	Indiana University Bloomington	140	20.7 20.7
48	Ohio Wesleyan University	159	20.7 20.7
49	Texas Tech University	130	20.7 20.7
50	University of California Santa Barbara	117	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)