如何模拟50个随机样本并计算每个样本的均值和方差

Question

When I simulate 50 random samples of a normal distribution and try to calculate the mean and the variance of each simulation I got this error: "There were 50 or more warnings (use warnings() to see the first 50)".

n=100
mean=100
sd=25 

sample=NULL
meansample=NULL
sdsample=NULL

for (i in 1:50)
  {

  sample[i]=rnorm(n,mean,sd)
  meansample[i]=mean(sample[i])
  sdsample[i]=sd(sample[i])

  }

sample
meansample
sdsample`

I want to ask how do I calculate correctly the mean and the standard deviation and why I get this error "There were 50 or more warnings (use warnings() to see the first 50)" when I execute my code.

Answer 1

I personally would do that is way.

x <- replicate(50, rnorm(100, 100, 25), simplify = FALSE)
sapply(x, mean)
sapply(x, sd)

The issue with your current code is sample is going to contain 50 separate sets of data, so you'd probably want that to be a list are refer to it as sample[[i]].

n=100
mean=100
sd=25 

sample=list()
meansample=NULL
sdsample=NULL

for (i in 1:50)
{

  sample[[i]]=rnorm(n,mean,sd)
  meansample[i]=mean(sample[[i]])
  sdsample[i]=sd(sample[[i]])

}

sample
meansample
sdsample