deletions | additions       diff --git a/background.tex b/background.tex  index d576951..54c61fa 100644  --- a/background.tex  +++ b/background.tex 
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\end{split}  \end{equation}  Of these 8 backgrounds, the processes with a * after them exhibit a 2-to-1 ratio of $e \mu$ to $\mu \mu$ events as the final state. Using this, the number of $\mu \mu$ events present in the data that come from these background processes can be estimated from the total number of $e \mu$ events present in data. However, due to experimental variations, we do not expect $\frac{N_{e \mu}}{N_{\mu \mu}} = 2$. For this reason, the actual number used is computed in the $tt$ dominated control region using the ratio of $e \mu$ events to $\mu \mu$ events in data, subtracting off the events from non 2:1 backgrounds. A summary of the scale factors is in section \ref{sect:results}. This ratio was found to be $R_{2:1} = 2.01 \pm 0.033$  For those processes which do not exhibit the 2-to-1 ratio, the expected number of events is computed based on estimates produced by the Monte Carlo samples discussed in section \ref{sect:eventSelection}. Since the Monte Carlo simulations cannot be assumed to be perfect, the estimates for the non 2-to-1 processes were scaled by a factor such that $\frac{N_{MC}}{N_{data}} = 1$ in the $dy$ sample. Where N correspondes to the number of events in the $dy$ dominated control region. Similar to the scale factor implemented for the 2-to-1 samples, while this factor has a different value depending on the sample chosen, $dy$ contributes very significantly to the overall number of events that do not have the 2-to-1 ratio and this scale factor is taken to be representative of the group as a whole.