deletions | additions       diff --git a/Burst_Weights_Theory.tex b/Burst_Weights_Theory.tex  index 7a67d2f..041a9fc 100644  --- a/Burst_Weights_Theory.tex  +++ b/Burst_Weights_Theory.tex 
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and acceptor counts from a binomial distribution ($E_p = 0.2$).   By repeatedly fitting the population parameter $E_p$ using a   size-weighted and unweighted average, we verified that the former has systematically  lower variance of the latter as predicted by the theory. theory  (in the current example the unweighted estimator has $38%$ higher variance).  Note that this result holds for any arbitrary distribution of burst sizes. The full simulation   including exponential and gamma-distributed burst sizes is reported in  the accompanying Jupyter notebook (\href{http://nbviewer.jupyter.org/github/tritemio/fretbursts_paper/blob/master/notebooks/Figures%20-%20Burst%20Weights.ipynb}{link}).