I would like to compare two populations which have different means. I want to find a way to compare their variances, to have an idea of which of the two populations have values that disperse further from the mean.
The issues is that I think I should need a variance standardized/normalized on the mean value of each distribution.
The next step would be to get a function in R that it is able to do that.
You don't need to standardise/normalise because variance is calculated as distance from the mean so is already normalised around the sample mean.
To demonstrate this run the following code
x<-runif(10000,min=100,max=101) y<-runif(10000,min=1,max=2) mean(x) mean(y) var(x) var(y)
You'll see while the mean is different the variance of the two samples is identical (allowing for some difference due to pseudo-random number generation and sample size)