Loi normale N(0,1)
Variance connue
Variance inconnue
Loi de Student a 2 degres de liberte
Variance connue
impossible
Variance inconnue
Loi de Student a 6 degres de liberte
Variance connue
Variance inconnue
Loi du chi-deux a 10 degres de liberte
Variance connue
Variance inconnue
Loi de Poisson lambda = 5
Variance connue
Variance connue
Code:
obs1=matrix(rnorm(2000,0,1),ncol=20)
xbar=apply(obs1,1,mean)
Bn=for(i in 1:100){xbar+1.96/sqrt(n)}
An=for(i in 1:100){xbar-1.96/sqrt(n)}
e=Xbar[0>An & 0<Bn]
p=length(e)/100
p
Variance inconnue
Code:
ecarttype=apply(obs1,1,sd)
Bn=for(i in 1:100){xbar+1.96*ecarttype/sqrt(n)}
An=for(i in 1:100){xbar- 1.96*ecarttype/sqrt(n)}
e=Xbar[0>An & 0<Bn]
p=length(e)/100
p
Loi de Student a 2 degres de liberte
Variance connue
impossible
Variance inconnue
Code:
obs2=matrix(rt(2000,2),ncol=20)
xbar=apply(obs2,1,mean)
variance=1.5
qt(0.95,2)
Bn=for(i in 1:100){xbar+1.96*sqrt(variance)/sqrt(n)}
An=for(i in 1:100){xbar-1.96*sqrt(variance)/sqrt(n)}
e=Xbar[0>An & 0<Bn]
p=length(e)/100
p
Loi de Student a 6 degres de liberte
Variance connue
Code:
obs3=matrix(rt(2000,6),ncol=20)
xbar=apply(obs3,1,mean)
variance=1.5
Bn=for(i in 1:100){xbar+1.96*sqrt(variance)/sqrt(n)}
An=for(i in 1:100){xbar-1.96*sqrt(variance)/sqrt(n)}
e=Xbar[0>An & 0<Bn]
p=length(e)/100
p
Variance inconnue
Code:
variance=apply(obs3,1,var)
Bn=for(i in 1:100){xbar+1.96*sqrt(variance)/sqrt(n)}
An=for(i in 1:100){xbar-1.96*sqrt(variance)/sqrt(n)}
e=Xbar[0>An & 0<Bn]
p=length(e)/100
p
Loi du chi-deux a 10 degres de liberte
Variance connue
Code:
obs4=matrix(rchisq(2000, 10, ncp=0),ncol=20)
xbar=apply(obs4,1,mean)
variance=20
Bn=for(i in 1:100){xbar+1.96*sqrt(variance)/sqrt(n)}
An=for(i in 1:100){xbar-1.96*sqrt(variance)/sqrt(n)}
e=Xbar[10>An & 10<Bn]
p=length(e)/100
p
Variance inconnue
Code:
obs4=matrix(rchisq(2000, 10, ncp=0),ncol=20)
xbar=apply(obs4,1,mean)
variance=apply(obs4,1,var)
Bn=for(i in 1:100){xbar+1.96*sqrt(variance)/sqrt(n)}
An=for(i in 1:100){xbar-1.96*sqrt(variance)/sqrt(n)}
e=Xbar[10>An & 10<Bn]
p=length(e)/100
p
Loi de Poisson lambda = 5
Variance connue
Code:
obs5=matrix(rpois(2000, 5),ncol=20)
xbar=apply(obs5,1,mean)
variance=5
Bn=for(i in 1:100){xbar+1.96*sqrt(variance)/sqrt(n)}
An=for(i in 1:100){xbar-1.96*sqrt(variance)/sqrt(n)}
e=Xbar[5>An & 5<Bn]
p=length(e)/100
p