Wooldridge Source: These data were collected by Daniel Martin, a former MSU undergraduate, for a final project. They come from the FBI Uniform Crime Reports and are for the year 1992. Data loads lazily.

data('campus')

Format

A data.frame with 97 observations on 7 variables:

  • enroll: total enrollment

  • priv: =1 if private college

  • police: employed officers

  • crime: total campus crimes

  • lcrime: log(crime)

  • lenroll: log(enroll)

  • lpolice: log(police)

Source

https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041

Notes

Colleges and universities are now required to provide much better, more detailed crime data. A very rich data set can now be obtained, even a panel data set for colleges across different years. Statistics on male/female ratios, fraction of men/women in fraternities or sororities, policy variables – such as a “safe house” for women on campus, as was started at MSU in 1994 – could be added as explanatory variables. The crime rate in the host town would be a good control.

Used in Text: pages 131-132

Examples

str(campus)
#> 'data.frame': 97 obs. of 7 variables: #> $ enroll : num 21836 6485 2123 8240 19793 ... #> $ priv : int 0 0 0 0 0 1 0 0 1 0 ... #> $ police : int 24 13 3 17 30 9 20 44 7 18 ... #> $ crime : int 446 1 1 121 470 25 67 1327 43 484 ... #> $ lcrime : num 6.1 0 0 4.8 6.15 ... #> $ lenroll: num 9.99 8.78 7.66 9.02 9.89 ... #> $ lpolice: num 3.18 2.56 1.1 2.83 3.4 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"