Description Usage Format Details Source Examples

This data frame gives the number of fumbles by each NCAA FBS team for the first three weeks in November, 2010.

1 |

A data frame with 120 observations on the following 7 variables.

`team`

NCAA football team

`rank`

rank based on fumbles per game through games on November 26, 2010

`W`

number of wins through games on November 26, 2010

`L`

number of losses through games on November 26, 2010

`week1`

number of fumbles on November 6, 2010

`week2`

number of fumbles on November 13, 2010

`week3`

number of fumbles on November 20, 2010

The fumble counts listed here are total fumbles, not fumbles lost. Some of these fumbles were recovered by the team that fumbled.

http://www.teamrankings.com/college-football/stat/fumbles-per-game

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
data(fumbles)
m <- max(fumbles$week1)
table(factor(fumbles$week1,levels=0:m))
favstats(fumbles$week1)
# compare with Poisson distribution
signif( cbind(
fumbles=0:m,
observedCount=table(factor(fumbles$week1,levels=0:m)),
modelCount= 120* dpois(0:m,mean(fumbles$week1)),
observedPct=table(factor(fumbles$week1,levels=0:m))/120,
modelPct= dpois(0:m,mean(fumbles$week1))
) ,3)
showFumbles <- function(x,lambda=mean(x),...) {
mx <- max(x)
result <- histogram(~x,type="density", xlim=c(-.5,(mx+2.5)),
xlab='number of fumbles',
panel=function(x,y,...){
panel.histogram(x,alpha=0.8,breaks=seq(-0.5,(mx+2.5),by=1,...))
panel.points(0:(mx+2),dpois(0:(mx+2),lambda),pch=19,alpha=0.8)
}
)
print(result)
return(result)
}
showFumbles(fumbles$week1)
showFumbles(fumbles$week2)
showFumbles(fumbles$week3)
``` |

fastR documentation built on May 31, 2017, 4:12 a.m.

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