This is the data I came up with.
You can see that Group 1 shows a mean of around 10 and the other groups show
a mean of around 8. I would like to include the sample size of each group in
some regression modelling to show that the level is indeed roughly of 8, not
I have looked into the suggestions so far (i.e., GLM modelling in Minitab
and heteroskedasticity) but I am trying to find out the level of the groups
using equations such as y=b, whilst including sample sizes as some sort of
weights. Parameter *b* will be estimated by the suggested procedure. I know
that in the ARIMA and structural modelling (i.e., StructTS in R), the level
is automatically modelled. However, once again, they do not include
frequency/sampling/case weights (thank you Anthony and Allan for the correct
terminology!) in their procedures. This could be a simple problem, maybe I
am missing something here... Thank you all for any further
suggestions/pointers and thank you very much for all the pointers suggested
Concerning my other problem, if we toss an unbiased coin, we know that the
theoretical outcome should be 50/50 if we toss the coin infinitely, e.g.,
say 10,000 times. However we know that if we toss it 20 times, we may get a
ratio of 45/55. Is there a way to obtain a prediction band for sample
size=20? This is just to satisfy my curiosity...
Thank you again everyone for any pointers.