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gy6.r
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########################
#6.gyak
########################
###########
#konfidencia intervallum
###########
a <- 5
sig <- 2
n <- 20
xdat=rnorm(n,a,sig)
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
hist(xdat)
abline(v=left,col=2,lty=2)
abline(v=right,col=2,lty=2)
a <- 5
sig <- 2
n <- 2000
xdat=rnorm(n,a,sig)
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
hist(xdat)
abline(v=left,col=2,lty=2)
abline(v=right,col=2,lty=2)
#ellenorizzuk a lefedesi vszget
talal=0
m=1000
for (i in 1:m){
a <- 5
sig <- 2
n <- 20
xdat=rnorm(n,a,sig)
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
if (left<a && a<right) talal=talal+1
}
talal
talal=0
m=1000
for (i in 1:m) {
a <- 5
sig <- 2
n <- 2000
xdat=rnorm(n,a,sig)
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
if (left<a && a<right) talal=talal+1
}
talal
#mi van, ha nem normalis az elo
talal=0
alul=0
m=1000
for (i in 1:m) {
a <- 5
sig <- 2
n <- 20
xdat=rexp(n,1/a)
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
if (left<a && a<right) talal=talal+1
if (a<left) alul=alul+1
}
talal
alul
###
#pontos
###
talal=0
alul=0
felul=0
m=1000
for (i in 1:m) {
a <- 5
#sig <- 2
n <- 20
xdat=rexp(n,a)
#error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- qgamma(0.025,n)/sum(xdat)
right <- qgamma(0.975,n)/sum(xdat)
if (left<a && a<right) talal=talal+1
if (a<left) alul=alul+1
if (a>right) felul=felul+1
}
talal
alul
felul
talal=0
m=1000
elt=matrix(0,m,2)
for (i in 1:m) {
a <- 5
sig <- 2
n <- 2000
xdat=rexp(n,1/a)
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
if (left<a && a<right) talal=talal+1
right2 <- 1/(qgamma(0.025,n)/sum(xdat))
left2 <- 1/(qgamma(0.975,n)/sum(xdat))
elt[i,1]=left-left2
elt[i,2]=right-right2
}
talal
#n=20-ra van elteres
#vajon melyik a jobb? A rovidebb a jobb
#sajat adataink
########
#konf.int
#######
dat<-read.table("diak_18a.csv",sep=";",header=T)
n=dim(dat)[1]
xdat=dat[,1]
##testmagasság
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
left
right
error
sd(xdat)
##súly
xdat=dat[,2]
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
left
right
error
##cipõméret
xdat=dat[,3]
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
left
right
error
##tanulási idõ
xdat=dat[,5]
typeof(xdat)
xdat
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
left
right
error
##utazási idõ
#gamma would be better instead of normal distribution
xdat=dat[,6]
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
left
right
error
##valszám jegy
xdat=dat[,7]
error <- qt(0.975,n-1)*sd(xdat)/sqrt(n)
left <- mean(xdat)-error
right <- mean(xdat)+error
left
right
error