Confidance_level = function(data,alpha) {
    mean_B=mean(data$ele)
    sd_B=sd(data$ele)
    Confidance=qnorm(1-alpha/2)*sd_B/sqrt(length(data[,1]))
    return(c(mean_B,+Confidance,-Confidance))
}
alpha=0.05
#source("read_data2.R")
source("read_data1.R")
n=seq(from=250,to=4000,by=250)
n=c(n,seq(from=5000,to=10000,by=1000))
#eps=seq(from=1,to=15,by=1)
algo_aux=c("quick","bubble","insertion","merge")
medias=c()
confidace_level1=c()
confidace_level2=c()
for (i in n) {
    teste=Confidance_level(t1[which((t1$algo==aux[2])&(t1$n==i)),],alpha)
    medias=c(medias,teste[1])
    confidace_level1=c(confidace_level1,teste[2])
    confidace_level2=c(confidace_level2,teste[3])

}
mediasN=medias/n
confidace_level1N=confidace_level1/n
confidace_level2N=confidace_level2/n
#p=plot(n,medias,type="b")
#arrows(n,medias,n,medias+confidace_level1,length=0.05, angle = 90)
#arrows(n,medias,n,medias+confidace_level2,length=0.05, angle = 90)


p=plot(n,mediasN,type="b",ylim=c(0.65, 0.75))
arrows(n,mediasN,n,mediasN+confidace_level1N,length=0.05, angle = 90)
arrows(n,mediasN,n,mediasN+confidace_level2N,length=0.05, angle = 90)

#plot(1)
#arrows(1,1,1,2)

#mean_B=mean(bubble_aux$ele)
#sd_B=sd(bubble_aux$ele)
#Confidance=qnorm(1-alpha/2)*sd_B/sqrt(length(bubble_aux[,1]))