It appears that you have a fundamental misunderstanding of what p-values do and
do not say (though this misunderstanding is commom). The following article
addresses this issue and could help with a better understanding:
Murdock, D, Tsai, Y, and Adcock, J (2008) _P-Values are Random
Rolf,
I no longer claim to be young, the naïve part is still up for debate,
but I find that restricting the null to only include = to be more confusing
than to have it include the inequality. To have the alternative be and the
null be = implies that we are working on the assumption
Hi,
I have the precision values of a system on two different data sets.
The snippets of these results are as shown:
sample1: (total 194 samples)
0.600238
0.800119
0.600238
0.200030
0.600238
...
...
sample2: (total 188 samples)
0.8001
0.2000
0.8001
0.
Robert,
We unfortunately do not have enough information to help you interpret the
results, and this is not really an R question at all, but general statistical
advice. You will probably have much better understanding and confidence in
your results by consulting a local statistical consultant
Hi,
I was just going to send this when I saw Erik's post. He's right -- we
can't say anything about your data, but we can say something about
using a t-test.
I'm not a real statistician, so this answer isn't very rigorous, but
might be helpful.
On Sep 16, 2009, at 2:55 PM, Robert Hall
I am loathe to expound basic statistics here ... but, at the considerable
risk of pedantry, I must note that Steve's reply below contains fundamental
errors, which I feel should not be left on this list unremarked: t-tests do
**not** test for differences in **sample** means; they test for
On 17/09/2009, at 8:06 AM, Bert Gunter wrote:
snip
Furthermore, the null can be other than equality -- e.g. that the
mean of
the first population is less than the second.
snip
QUIBBLE: Some elementary texts will indeed state the null hypothesis as
``mu_1 = mu_2'' when
Hi,
I have the precision values of a system on two different data sets.
The snippets of these results are as shown:
sample1: (total 194 samples)
0.600238
0.800119
0.600238
0.200030
0.600238
...
...
sample2: (total 188 samples)
0.8001
0.2000
0.8001
0.
Hi Bert,
On Sep 16, 2009, at 4:06 PM, Bert Gunter wrote:
snip
Finally, statistically different is a meaningless phrase.
I'm not sure if you're quoting that to point out something in
particular you're taking exception to, but I never said that. I did
mention statistical significance with
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