So I have 1000 variables (different lakes), each with 12 observations (each lake was tested once a year for 12 years). Some of the lakes are really small, so we think they have way too much variation. My task is to determine exactly what is too much variation, trying to figure out which lakes we should eliminate. I was thinking about running var.test between each lake to determine what lakes are significantly different from eachother, but I don't know if that will give me the results that I want. In addition to that, I have 1000 lakes, so I can't perform the test THAT many times.
Ideas?
revised description: we're observing the changing of the lakes over a 12 year span. each year, we observed the lakes 3 separate times. then we averaged those three to get one data point each year for each lake. problem is, we have A LOT of lakes, so we feel like including the significantly smaller ones, which freeze, melt, evaporate, etc. much quicker, will effect our study. we used remote sensory to gather the data so it grabbed EVERY lake of every size. what i need to figure out is what lakes should we use in our study, which lakes are large enough to be worth our time. And I'm not sure how to go about that.
var.test
! Why should the lakes have equal variances is not clear to me and to perform almost a half a million tests is definitely not advisable. $\endgroup$