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Please help!
2 messages · jimbib webber, David Winsemius
jimbib webber <alfieim21 at hotmail.co.uk> wrote in news:BLU108-W44A9C8E34EC3B26B0D73C1F2730 at phx.gbl:
Each number in the below list resides 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
What I want to do is in R, calculate the corresponding quantiles from 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 person told me to do 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 person told me to do 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.
Try: qqnorm(x); qqline(x, col = 2) ....as suggested in the examples in the help message from ?qqplot. If you want the quantiles, invoking str(qqnorm(x)) suggests that the "x- values" can be recovered by: qqnorm(x)$x ....and therefore the quantiles from: pnorm(qqnorm(x)$x)
David Winsemius