#НОРМАЛЬНОЕ
N_median<-vector(length = 1000)
N_mad<-vector(length = 1000)
N_s<- vector(length = 1000)
N_mean <- vector(length = 1000)
N_iqr<-vector(length = 1000)
N_sigma_a <- 0
N_sigma_b <- 0
N_tuky <- 0
N_UQ <-0
N_LQ <-0
N_k <- 0
N_m <- 0
N_z<-0


for(i in 1:1000)
{
  n<-rnorm(100, mean = 0, sd =1)
  n<-sort(n)

  N_mean[i]<-mean(n)
  N_s[i]<-sd(n, FALSE)
  N_median[i]<-median(n)
  N_mad[i]<-mad(n, median(n), 1.46, FALSE, FALSE, FALSE)
  N_iqr<-IQR(n)
  N_UQ <- n[75]
  N_LQ <- n[25]

  for (j in 1:100){
  if( (abs(n[j] - N_mean[i]) / (N_s[i]))>3) {N_k<-N_k+1}
  if ( (abs (n[j] - N_median[i]) / (N_mad[i]))>3) {N_m<-N_m+1}
  if ((n[j] > (N_UQ + 3/2*(N_iqr)))| (n[j] < (N_LQ - 3/2*(N_iqr)))) {N_z<-N_z+1}
  }
}
boxplot(n, horizontal = TRUE)
N_sigma_a <- N_k/1000
N_sigma_b <- N_m/1000
N_tuky <- N_z/1000