deletions | additions       diff --git a/background.tex b/background.tex  index 76ddad7..7795936 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 by  the ratio of $e \mu$ events to $\mu \mu$ events present in the $t \overline{t}$ sample. Although this ratio will be different for each sample, the tendency for the algorithms to mismeasure does not depend on the process so this number is taken to be representative of all of the 2-to-1 samples. A summary of the scale factors is in section \ref{sect:results}. 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. 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.