On the PERFORMANCE of JACKKNIFE VARIANCE Amstat

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hi in this video we're going to discuss jackknife estimation which is an important tool in the toolkit of lattice QCD grande assumes that by this point in your calculation you have an ensemble of configurations and you've managed to compute some sort of quantity on these configurations how do you know with what precision you've managed to calculate this quantity jackknife method is an easy way to estimate the uncertainty of a value that's been computed on a data set other alternatives to the jackknife method include the bootstrap and the resampling techniques sure won't discuss in detail here but I'll try to contrast jackknife to them and describe why we want to use jackknife the notion behind jackknife estimation is that we want to create new data sets from the data that we already have after all if we could create more data we would have already done that but we're going to use our new data sets in order to compute many values whatever it was that we were trying to compute in our or