Why would variance be non-zero?
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 non-zero 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
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