Estimating variance with limited data?
- From: Dan Bolser <dmb@xxxxxxxxxxxxxxxxxx>
- Date: Sun, 10 Jul 2005 18:26:17 +0100
Hello,
I am a real beginner in stats, so sorry for the potentially naïev
question (and badterminology)!
I have a series of 'experiments' each with a few observations within the
range of discreet values...
experiment A, results 1, 2, 1, 4, 3, 1, 4
experiment B, results 5, 2, 4, 4, 3, 6, 4, 5, 6, 7
experiment C, results 1, 9, 3, 4
Each 'experiment' has a ranking, and when I plot the mean value for each
set of results for each experiment, I think I can see a clear trend.
What I think I want to do is to estimate the variance of the results in
each experiment, so I can see what trends 'fit' the data. I think if I
give each point (mean) some error bars, I can see if my trend is supported
or not.
I used bootstrapping to estimate the variance of the mean value for each
experiment. However, I have a problem, some experiments have results that
only take one value. How do I estimate the variance in these cases?
I want to do that to match my intuition that
experiment X, results 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
has less variance than
experiment Y, results 1, 1, 1, 1, 1
How should I present the data, given that I want to show an average value
with a variance?
I think perhaps I can do something tricky like add the mean value for the
whole results set to each experiment and recalculate the estimated
variance, but can I do that?
If it helps I can send my real data.
Thanks for any clues for how to advance my analysis,
All the best,
Dan.
.
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