On Sep 2, 2010, at 2:01 PM, Greg Snow wrote:
<snipped much good material>
The real tricky bit about hypothesis testing is that we compute a
single p-value, a single observation from a distribution, and based
on that try to decide if the process that produced that observation
is a uniform distribution or something else (that may be close to a
uniform or very different).
My friendly addition would be to point the OP in the direction of
using qqplot() for the examination of distributional properties rather
than doing any sort of hypothesis testing. There is a learning curve
for using that tool, but it will pay off in the end.
--
David.
Hope this helps,
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
project.org] On Behalf Of Kay Cecil Cichini
Sent: Thursday, September 02, 2010 6:40 AM
To: ted.hard...@manchester.ac.uk
Cc: r-help@r-project.org
Subject: Re: [R] general question on binomial test / sign test
thanks a lot for the elaborations.
your explanations clearly brought to me that either
binom.test(1,1,0.5,"two-sided") or binom.test(0,1,0.5) giving a
p-value of 1 simply indicate i have abolutely no ensurance to reject
H0.
considering binom.test(0,1,0.5,alternative="greater") and
binom.test(1,1,0.5,alternative="less") where i get a p-value of 1 and
0.5,respectively - am i right in stating that for the first estimate
0/1 i have no ensurance at all for rejection of H0 and for the second
estimate = 1/1 i have same chance for beeing wrong in either
rejecting
or keeping H0.
many thanks,
kay
David Winsemius, MD
West Hartford, CT
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