Each number in the list belowresides in a quantile. When put in order,
there are 10 numbers, so the first is in the 0.1 quantile, the second
in the 0.2 etc.
Lets say we have 10 examples of systolic blood pressure from 30 year olds:
104,95,106,105,110,150,101,98,85,104
This is a random sample.
What I want to do is in R, calculate the corresponding quantiles from a
normal distribution with the same mean and variance as the sample.
So, using the same mean and variance as the above random sample, create
a normal distribution. From this normal distribution, I want to
calculate 10 corresponding quantiles.
Then, I want to plot a qqplot of both data sets to see the distribution.
One idea was this:
qnorm(c(0.25,0.5,0.75),mean=mean(x),sd=sd(x))
Output:
[1] 3.76997 5.50000 7.23003
...But this does not give me 10 corresponding quantiles?
Another idea was this:
> > > x=c(104,95,106,105,110,150,101,98,85,104)
> > > n=length(x)
> > > p=(1:n-0.5)/n
> > > z=qnorm(p, mean(x), sd(x),)[order(order(x))]
But this seems to generate 10 new numbers. And not give corresponding quantiles
from a normal distribution.
Any ideas?
Thanks.
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