Description 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.

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( ~ week1, data=fumbles)
# 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 July 28, 2017, 1:02 a.m.

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