| lawsch85 | R Documentation |
Wooldridge Source: Collected by Kelly Barnett, an MSU economics student, for use in a term project. The data come from two sources: The Official Guide to U.S. Law Schools, 1986, Law School Admission Services, and The Gourman Report: A Ranking of Graduate and Professional Programs in American and International Universities, 1995, Washington, D.C. Data loads lazily.
data('lawsch85')
A data.frame with 156 observations on 21 variables:
rank: law school ranking
salary: median starting salary
cost: law school cost
LSAT: median LSAT score
GPA: median college GPA
libvol: no. volumes in lib., 1000s
faculty: no. of faculty
age: age of law sch., years
clsize: size of entering class
north: =1 if law sch in north
south: =1 if law sch in south
east: =1 if law sch in east
west: =1 if law sch in west
lsalary: log(salary)
studfac: student-faculty ratio
top10: =1 if ranked in top 10
r11_25: =1 if ranked 11-25
r26_40: =1 if ranked 26-40
r41_60: =1 if ranked 41-60
llibvol: log(libvol)
lcost: log(cost)
More recent versions of both cited documents are available. One could try a similar analysis for, say, MBA programs or Ph.D. programs in economics. Quality of placements may be a good dependent variable, and measures of business school or graduate program quality could be included among the explanatory variables. Of course, one would want to control for factors describing the incoming class so as to isolate the effect of the program itself.
Used in Text: pages 107, 164-165, 239
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
str(lawsch85)