656
Le logiciel R
9.8- bornes <- res$breaks
plot(bornes,ecdf(taille)(bornes),type="l",main=
paste("Polygone des fr´ equences cumul´ ees",
"de la variable taille",sep="\n"),ylab="Fr´ equences",
col="darkolivegreen",lwd=3)
abline(h=c(0.25,0.5,0.75))
locator(1)$x # Cliquez sur l’intersection recherch´ ee.
9.9- mean(taille)
mean(poids)
mean(age)
9.10- table(the)
sum(c(0:6,9,10) * as.numeric(table(the)))/sum(table(the))
9.11- sum(res$mids * res$counts)/sum(res$counts)
9.12- diff(range(poids))
9.13- boxplot(poids)
9.14- var.pop <- function(x) var(x) * (length(x)-1)/length(x)
sd.pop <- function(x) sqrt(var.pop(x))
sd.pop(taille)
9.15- coeffvar.tab <- function(tabx) {
val <- as.numeric(names(tabx))
freq <- as.numeric(tabx)/sum(tabx)
moy <- sum(val * freq)
var <- sum(val^2 * freq) - moy^2
res <- sqrt(var)/moy
return(res)
}
coeffvar.tab(table(the))
9.16- eta2 <- function(x, gpe) {
moyennes <- tapply(x, gpe, mean)
effectifs <- tapply(x, gpe, length)
varinter <- (sum(effectifs * (moyennes - mean(x))^2))
vartot <- (var(x) * (length(x) - 1))
res <- varinter/vartot
list(var.tot=vartot,var.inter=varinter,
var.intra=vartot-varinter,eta2=res)
}
res <- eta2(the,sexe)