Hi
t.test assumes that your data within each group has a normal
distribution. This is not the case in your example.
I would recommend you a non parametric test like wilcox.test if
you want to compare the mean of two samples that are not normal
distributed.
see ?wilcox.test
Be careful. Your
From: Christoph Buser
Hi
t.test assumes that your data within each group has a normal
distribution. This is not the case in your example.
Eh? What happen to the CLT?
Andy
I would recommend you a non parametric test like wilcox.test if
you want to compare the mean of two samples that
Dear Andy
Since the power of the t-test decreases when there are
discrepancies in the data to the normal distribution and there
is only a small loss of power if the data is normal distributed,
the only reason to use the t.test is his simplicity and the
easier interpretation.
Generally I'd prefer
Hi R Users
I have a code which I am running for my thesis work. Just want to make sure that
its ok. Its a t test I am conducting between two gamma distributions with
different shape parameters.
the code looks like:
sink(a1.txt);
for (i in 1:1000)
{
x-rgamma(40, 2.5, 10) # n = 40, shape = 2.5,
