StudentsReview ™ :: Top PreLaw and Legal School Ranking

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Best PreLaw and Legal Programs

Careers in PreLaw and Legal: PreLaw and Legal Salary, Satisfaction, Unemployment, PreLaw and Legal Salary Trend
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From Surveys Matching: PreLaw and Legal

Colgate University
A- 8.5
University of West Florida
A- 8.2
Texas Tech University  
B+ 7.7
Cornell University
B+ 7.6
St John's University New York
B+ 7.6
Sacred Heart University
B 7.3
Drake University  
B 7.3
University of Iowa
B 7.1
Auburn University
B 7.1
University of California - Santa Barbara
B 6.9
Chapman University
B 6.9
Green Mountain College
B 6.9
Liberty University
B 6.7
University of Texas - Austin
B- 6.3
Stevenson University
B- 6.2
Bard College Simon's Rock  
B- 6.2
College of William and Mary  
B- 6.0
Frostburg State University
B- 6.0
Michigan State University
B- 6.0
University of California - Irvine
B- 6.0
Oral Roberts University
B- 5.9
Mount Holyoke College
B- 5.9
Villanova University
B- 5.8
Pensacola Christian College
B- 5.8
State University of New York Binghamton
B- 5.8
Johns Hopkins University
C+ 5.6
University of Tampa
C+ 5.5
Evangel University
C+ 5.4
University of Central Florida
C+ 5.3
University of Massachusetts - Amherst
C+ 5.3
Hampton University
C+ 5.3
University of Michigan - Ann Arbor
C+ 5.2
Barry University
C+ 5.2
University of California - Davis
C+ 5.1
Southern Methodist University
C 5.0
Washington College
C 4.9
University of Colorado - Boulder
C 4.7
California State University - Chico
C 4.5
American University
C 4.3
Quincy College
C- 4.1
Bob Jones University
C- 4.0
Widener University
C- 3.9
Fordham University
C- 3.9
Howard University
C- 3.9
Stephens College
C- 3.7
Southern Illinois University - Carbondale
D+ 3.2
George Mason University
D+ 2.8
George Washington University
D 2.6
University of Maryland - College Park
D 2.6
Nova Southeastern University
D 2.5


About this College Ranking

Removing bad surveys
    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 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. 


PreLaw and Legal Major unemployment rate

_PreLaw and LegalAll Majors
Minimum Wage%6%4
All Others%86%88
More: Unemployment for all Majors *** not counting stay at home parents *** not counting those currently in grad school

Are things going well in PreLaw and Legal?

Going Well%74
Not Going Well%26
More: All Majors Satisfaction ??? This is a social "life satisfaction" question. Overall, would people who graduated with a degree in PreLaw and Legal say that their life is going well? It could be interpreted in terms of stress, salary, long hours, future prospects, etc. *** not counting those currently in grad school

Graduates who stayed in PreLaw and Legal

Still in Field%66
Got out%34
More: All Majors Still in field ??? A high "got out" percentage can be interpreted a couple of ways -- for instance, perhaps the major is a great stepping stone to becoming a totally different career -- like a doctor. Or perhaps the jobs one gets with the major just aren't that great. *** not counting those currently in grad school

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