deletions | additions       diff --git a/Burst_Variance_Analysis.tex b/Burst_Variance_Analysis.tex  index 46479a9..bd7dc1a 100644  --- a/Burst_Variance_Analysis.tex  +++ b/Burst_Variance_Analysis.tex 
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\operatorname{Std(\textit{E})} = {\sqrt{\frac{E(1 - E)}{n}}}  \end{equation}  BVA analysis consists of four steps: 1) slicing bursts into sub-bursts containing a constant number of consecutive photons,\textit{n}, photons,~\textit{n},  2) computing FRET efficiencies of each sub-burst, 3) calculating the empirical standard deviation ($s_E$) of sub-burst FRET efficiencies over the whole burst, and 4) comparing $s_E$ to an expected standard deviation based on shot noise limited distribution~\cite{Torella_2011}. If the observed broadening originates from different molecules having distinct FRET efficiencies without dynamics, $s_E$ of each burst is only affected by shot noise and will follow the expected standard deviation curve based on eq.~\ref{eq:binom_std} (Fig.~\ref{fig:bva_static}). However, if the observed broadness is due to millisecond dynamics of single species of biomolecules, $s_E$ of each burst is supposed to be larger than the expected standard deviation and sit above the expected standard deviation curve as shown in figure~\ref{fig:bva_dynamic}.