#1




Why would variance be nonzero?
In question 6 on the homework, we are asked to compute the variance across all data sets.
If we are sampling uniformly from the interval [1, 1] for the calculation of g_bar, as well as for each data set (g_d), why would the variance be anything but a very small quantity? In the general case, when the data sets are not drawn from a uniform distribution, a nonzero variance makes sense, but if there is sufficient overlap in the data sets, it makes intuitive sense that the variance should be close to zero. I ask this because my simulation results support the above (potentially flawed) theory. Please answer the question in general terms  I don't care about the homework answer  I was merely using that as an example. Thanks for any input. Samir 
#2




Re: Why would variance be nonzero?
Quote:
This argument holds for any probability distribution, uniform or not, that is used to generate the different 's.
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#3




Re: Why would variance be nonzero?
Thank you ... now that you explain it that way, it makes perfect sense. (Not sure what I was thinking...)
Samir 
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