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)
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
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
#> 'data.frame': 156 obs. of 21 variables: #> $ rank : int 128 104 34 49 95 98 124 157 145 91 ... #> $ salary : num 31400 33098 32870 35000 33606 ... #> $ cost : int 8340 6980 16370 17566 8350 8350 6020 5986 4785 7680 ... #> $ LSAT : int 155 160 155 157 162 161 155 152 155 160 ... #> $ GPA : num 3.15 3.5 3.25 3.2 3.38 ... #> $ libvol : int 216 256 424 329 332 311 220 230 230 157 ... #> $ faculty: int 45 44 78 136 56 40 40 45 101 44 ... #> $ age : int 12 113 134 89 70 29 61 60 70 128 ... #> $ clsize : int 210 190 270 277 150 156 151 149 322 70 ... #> $ north : int 1 0 0 0 0 0 0 0 0 0 ... #> $ south : int 0 1 0 0 0 0 1 1 0 1 ... #> $ east : int 0 0 1 1 0 0 0 0 1 0 ... #> $ west : int 0 0 0 0 1 1 0 0 0 0 ... #> $ lsalary: num 10.4 10.4 10.4 10.5 10.4 ... #> $ studfac: num 4.67 4.32 3.46 2.04 2.68 ... #> $ top10 : int 0 0 0 0 0 0 0 0 0 0 ... #> $ r11_25 : int 0 0 0 0 0 0 0 0 0 0 ... #> $ r26_40 : int 0 0 1 0 0 0 0 0 0 0 ... #> $ r41_60 : int 0 0 0 1 0 0 0 0 0 0 ... #> $ llibvol: num 5.38 5.55 6.05 5.8 5.81 ... #> $ lcost : num 9.03 8.85 9.7 9.77 9.03 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"