\subsection{Results on the Data}
\label{ssec:results}

\subsubsection{Subsample Likelihood Curves}
\label{sssec:resultsSub}

The likelihood fit is first performed on each subsample separately.
For a series of top masses between \gevcc{110} and \gevcc{250}, the
mass parameter is fixed, while the likelihood is maximized with
respect to the remaining parameters ($n_s$ and $n_b$)
using MINUIT. The resulting
negative log-likelihood curves as a function of top mass are shown in
\fig{f:lnlsubs}.

\begin{cfigure}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC1}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC2}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC3}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC4}
\includegraphics{plots/likelihoods_prd}
\caption[Subsample fits likelihood curves.]
{The negative log-likelihood curves as a function of top mass are shown for
the independent fit to each subsample in the data. Upper left:
\twotag events; upper right: \onetagt events; lower left: \onetagl events;
lower right: \zerotag events.}
\label{f:lnlsubs}
\end{cfigure}

\subsubsection{Results of Combined Likelihood}
\label{sssec:resultsCombined}

Finally, the likelihood is maximized with respect to all parameters
using all four subsamples. The result, after scaling the
$\Delta(\ln L)=+1/2$ errors as described in section~\ref{ssec:methodCheck},
is \gevcc{\measAStat{176.7}{6.0}{5.4}}. The combined likelihood
as a function of top mass is shown in \fig{f:lnlcomb}.
For each value of the top mass in the curve,
the likelihood is maximized with respect to all other parameters.

\begin{cfigure}
\includegraphics{plots/finalfitC-1}
\caption[Combined fit likelihood curve.]
{The negative log-likelihood curve as a function of top mass for
the combined fit. For each top mass along the $x$ axis, the
likelihood is maximized with respect to all other free parameters.}
\label{f:lnlcomb}
\end{cfigure}

The input constraints and fit results for the combined fit are
given in \tab{t:fitResults}. \Fig{f:fitConsistency} shows the
consistency of the reconstructed mass distribution in each
subsample with the combined fit results.

\begin{table}
\caption[Combined fit results.]
{The input constraints and fitted values (with errors from $\Delta(\ln L)=+1/2$)
are given for all free parameters in the combined likelihood fit.}
\label{t:fitResults}
\begin{ruledtabular}
\begin{tabular}{llcccc}
\multicolumn{2}{l}{Category} & \twotag & \onetagt & \onetagl & \zerotag \\
\hline
\mtop & constraint & \multicolumn{4}{c}{None} \\
 & raw fit & \multicolumn{4}{c}{\gevcc{\measAStat{176.7}{5.7}{5.1}}} \\
 & scaled fit & \multicolumn{4}{c}{$\mathbf{\gevcc{\measAStat{176.7}{6.0}{5.4}}}$} \\
\hline
$n_s$ & constraint & None & None & None & None \\
 & fit & \measErr{1.8}{1.4} & \measErr{15.4}{4.3} &
  \measErr{0.0}{3.0} & \measErr{18.2}{8.2} \\
\hline
$n_b$ & constraint & \measErr{0.18}{0.02} & \measErr{2.7}{0.6} &
	\measErr{3.9}{0.7} & \measErr{24.5}{7.1} \\
 & fit & \measErr{0.18}{0.04} & \measErr{2.7}{0.6} &
	\measErr{3.7}{0.7} & \measErr{22.3}{6.3} \\
\end{tabular}
\end{ruledtabular}
\end{table}

\begin{cfigure}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC1}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC2}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC3}
%\includegraphics[width=.45\columnwidth]{plots/finalfitC4}
\includegraphics{plots/finalfitC_prd}
\caption[Subsample fits consistency checks.]
{The reconstructed mass distribution for each subsample is
shown overlaid with the expected distribution using the
top mass, signal normalization, and background normalization
from the combined fit.}
\label{f:fitConsistency}
\end{cfigure}


