Wooldridge Source: Collected by Scott Resnick, a former MSU undergraduate, from various newspaper sources. Data loads lazily.
data('pntsprd')A data.frame with 553 observations on 12 variables:
favscr: favored team's score
undscr: underdog's score
spread: las vegas spread
favhome: =1 if favored team at home
neutral: =1 if neutral site
fav25: =1 if favored team in top 25
und25: =1 if underdog in top 25
fregion: favorite's region of country
uregion: underdog's region of country
scrdiff: favscr - undscr
sprdcvr: =1 if spread covered
favwin: =1 if favored team wins
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
The data are for the 1994-1995 men’s college basketball seasons. The spread is for the day before the game was played. One might collect more recent data and determine whether the spread has become a less accurate predictor of the actual outcome in more recent years. In other words, in the simple regression of the actual score differential on the spread, is the variance larger in more recent years. (We should fully expect the slope coefficient not to be statistically different from one.)
Used in Text: pages 300, 624, 697
str(pntsprd)
#> 'data.frame': 553 obs. of 12 variables:
#> $ favscr : int 72 82 87 69 77 91 95 90 79 103 ...
#> $ undscr : int 61 74 57 70 79 65 88 67 80 68 ...
#> $ spread : num 7 7 17 9 2.5 9 10 18 7.5 8 ...
#> $ favhome: int 0 1 1 1 0 0 1 1 0 0 ...
#> $ neutral: int 0 0 0 0 0 1 0 0 0 0 ...
#> $ fav25 : int 1 0 0 0 0 1 0 1 0 0 ...
#> $ und25 : int 0 0 0 0 0 0 0 0 0 0 ...
#> $ fregion: int 3 3 3 3 2 3 3 4 3 2 ...
#> $ uregion: int 4 1 3 3 3 4 3 4 3 2 ...
#> $ scrdiff: int 11 8 30 -1 -2 26 7 23 -1 35 ...
#> $ sprdcvr: int 1 1 1 0 0 1 0 1 0 1 ...
#> $ favwin : int 1 1 1 0 0 1 1 1 0 1 ...
#> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"