\begin{frame}[allowframebreaks] \frametitle{overload_reg_asym_manual_main_det crex_pitt} \begin{figure} \centering \includegraphics[page=1,width=0.9\textwidth]{images/partAvgAllEvMonLagr_mini_overload_det_asyms_det_weighted_overload_reg_asym_manual_main_det_crex_pitt_wise_IncludeBMOD_NULL_both_main_det_corrections.pdf} \caption{Main detector weighted average overload_reg_asym_manual_main_det ( ppb) vs. crex_pitt.} \label{fig:overload_reg_asym_manual_main_det_crex_pitt_p0} \end{figure} \begin{figure} \centering \includegraphics[page=2,width=0.9\textwidth]{images/partAvgAllEvMonLagr_mini_overload_det_asyms_det_weighted_overload_reg_asym_manual_main_det_crex_pitt_wise_IncludeBMOD_NULL_both_main_det_corrections.pdf} \caption{Main detector weighted average overload_reg_asym_manual_main_det ( ppb) vs. crex_pitt pull.} \label{fig:overload_reg_asym_manual_main_det_crex_pitt_pull} \end{figure} \begin{table} \caption{overload_reg_asym_manual_main_det vs. crex_pitt, main-det weighted} \begin{tabular}{cccc} \cline{1-4} \multicolumn{1}{|c|}{Averaging} & \multicolumn{1}{c|}{Value} & \multicolumn{1}{c|}{Error} & \multicolumn{1}{c|}{Weight into avg} \\ \hline \multicolumn{1}{|c|}{crex_pitt 1} & \multicolumn{1}{c|}{253.146} & \multicolumn{1}{c|}{437.73} & \multicolumn{1}{c|}{4.44748\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 2} & \multicolumn{1}{c|}{182.712} & \multicolumn{1}{c|}{474.428} & \multicolumn{1}{c|}{4.16725\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 3} & \multicolumn{1}{c|}{389.933} & \multicolumn{1}{c|}{454.965} & \multicolumn{1}{c|}{4.29636\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 4} & \multicolumn{1}{c|}{-358.51} & \multicolumn{1}{c|}{421.886} & \multicolumn{1}{c|}{5.07571\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 5} & \multicolumn{1}{c|}{-226.146} & \multicolumn{1}{c|}{488.224} & \multicolumn{1}{c|}{4.01544\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 6} & \multicolumn{1}{c|}{-14.2291} & \multicolumn{1}{c|}{489.745} & \multicolumn{1}{c|}{4.14121\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 7} & \multicolumn{1}{c|}{-4.53922} & \multicolumn{1}{c|}{432.766} & \multicolumn{1}{c|}{4.17129\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 8} & \multicolumn{1}{c|}{57.1056} & \multicolumn{1}{c|}{455.521} & \multicolumn{1}{c|}{4.15961\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 9} & \multicolumn{1}{c|}{298.882} & \multicolumn{1}{c|}{473.855} & \multicolumn{1}{c|}{4.00095\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 10} & \multicolumn{1}{c|}{610.069} & \multicolumn{1}{c|}{461.772} & \multicolumn{1}{c|}{4.04315\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 11} & \multicolumn{1}{c|}{43.0675} & \multicolumn{1}{c|}{418.405} & \multicolumn{1}{c|}{5.2268\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 12} & \multicolumn{1}{c|}{-791.791} & \multicolumn{1}{c|}{463.188} & \multicolumn{1}{c|}{3.97494\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 13} & \multicolumn{1}{c|}{-775.982} & \multicolumn{1}{c|}{469.615} & \multicolumn{1}{c|}{3.82912\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 14} & \multicolumn{1}{c|}{-403.324} & \multicolumn{1}{c|}{484.601} & \multicolumn{1}{c|}{4.05571\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 15} & \multicolumn{1}{c|}{-574.324} & \multicolumn{1}{c|}{485.894} & \multicolumn{1}{c|}{3.44318\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 16} & \multicolumn{1}{c|}{508.709} & \multicolumn{1}{c|}{460.298} & \multicolumn{1}{c|}{4.06967\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 17} & \multicolumn{1}{c|}{320.656} & \multicolumn{1}{c|}{467.712} & \multicolumn{1}{c|}{4.10447\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 18} & \multicolumn{1}{c|}{292.858} & \multicolumn{1}{c|}{473.032} & \multicolumn{1}{c|}{4.06021\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 19} & \multicolumn{1}{c|}{214.722} & \multicolumn{1}{c|}{445.008} & \multicolumn{1}{c|}{4.35099\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 20} & \multicolumn{1}{c|}{-565.581} & \multicolumn{1}{c|}{429.113} & \multicolumn{1}{c|}{4.53436\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 21} & \multicolumn{1}{c|}{159.103} & \multicolumn{1}{c|}{455.538} & \multicolumn{1}{c|}{4.12718\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 22} & \multicolumn{1}{c|}{0.406207} & \multicolumn{1}{c|}{445.538} & \multicolumn{1}{c|}{4.37284\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 23} & \multicolumn{1}{c|}{284.957} & \multicolumn{1}{c|}{435.702} & \multicolumn{1}{c|}{4.45634\%} \\ \hline \multicolumn{1}{|c|}{crex_pitt 24} & \multicolumn{1}{c|}{770.579} & \multicolumn{1}{c|}{543.394} & \multicolumn{1}{c|}{2.87575\%} \\ \hline \multicolumn{1}{|c|}{Main det weighted average} & \multicolumn{1}{c|}{22.3952\pm 93.8184} & \multicolumn{1}{c|}{Chi2/NDOF = 18.1926/23} & \multicolumn{1}{c|}{Probability = 0.746959} \\ \hline \end{tabular} \end{table} \end{frame} Plain Overload Regression Apv maindet weighted average, 22.3952 +- 93.8184 Plain Overload Regression Apv maindet weighted mean, self pull = 0.00414407 +- 0.880859 Plain Overload Regression Apv crex_pitt, time, Value, Value Error Plain Overload Regression Apv crex_pitt,1,253.146,437.73 Plain Overload Regression Apv crex_pitt,2,182.712,474.428 Plain Overload Regression Apv crex_pitt,3,389.933,454.965 Plain Overload Regression Apv crex_pitt,4,-358.51,421.886 Plain Overload Regression Apv crex_pitt,5,-226.146,488.224 Plain Overload Regression Apv crex_pitt,6,-14.2291,489.745 Plain Overload Regression Apv crex_pitt,7,-4.53922,432.766 Plain Overload Regression Apv crex_pitt,8,57.1056,455.521 Plain Overload Regression Apv crex_pitt,9,298.882,473.855 Plain Overload Regression Apv crex_pitt,10,610.069,461.772 Plain Overload Regression Apv crex_pitt,11,43.0675,418.405 Plain Overload Regression Apv crex_pitt,12,-791.791,463.188 Plain Overload Regression Apv crex_pitt,13,-775.982,469.615 Plain Overload Regression Apv crex_pitt,14,-403.324,484.601 Plain Overload Regression Apv crex_pitt,15,-574.324,485.894 Plain Overload Regression Apv crex_pitt,16,508.709,460.298 Plain Overload Regression Apv crex_pitt,17,320.656,467.712 Plain Overload Regression Apv crex_pitt,18,292.858,473.032 Plain Overload Regression Apv crex_pitt,19,214.722,445.008 Plain Overload Regression Apv crex_pitt,20,-565.581,429.113 Plain Overload Regression Apv crex_pitt,21,159.103,455.538 Plain Overload Regression Apv crex_pitt,22,0.406207,445.538 Plain Overload Regression Apv crex_pitt,23,284.957,435.702 Plain Overload Regression Apv crex_pitt,24,770.579,543.394 Plain Overload Regression Apv total average, 20.997 +- 93.687 Plain Overload Regression Apv pull plot stats = 0.00718586 +- 0.880834 Plain Overload Regression Apv crex_pitt, time, Value, Avg Weight Plain Overload Regression Apv crex_pitt,1,253.146,0.0444748 Plain Overload Regression Apv crex_pitt,2,182.712,0.0416725 Plain Overload Regression Apv crex_pitt,3,389.933,0.0429636 Plain Overload Regression Apv crex_pitt,4,-358.51,0.0507571 Plain Overload Regression Apv crex_pitt,5,-226.146,0.0401544 Plain Overload Regression Apv crex_pitt,6,-14.2291,0.0414121 Plain Overload Regression Apv crex_pitt,7,-4.53922,0.0417129 Plain Overload Regression Apv crex_pitt,8,57.1056,0.0415961 Plain Overload Regression Apv crex_pitt,9,298.882,0.0400095 Plain Overload Regression Apv crex_pitt,10,610.069,0.0404315 Plain Overload Regression Apv crex_pitt,11,43.0675,0.052268 Plain Overload Regression Apv crex_pitt,12,-791.791,0.0397494 Plain Overload Regression Apv crex_pitt,13,-775.982,0.0382912 Plain Overload Regression Apv crex_pitt,14,-403.324,0.0405571 Plain Overload Regression Apv crex_pitt,15,-574.324,0.0344318 Plain Overload Regression Apv crex_pitt,16,508.709,0.0406967 Plain Overload Regression Apv crex_pitt,17,320.656,0.0410447 Plain Overload Regression Apv crex_pitt,18,292.858,0.0406021 Plain Overload Regression Apv crex_pitt,19,214.722,0.0435099 Plain Overload Regression Apv crex_pitt,20,-565.581,0.0453436 Plain Overload Regression Apv crex_pitt,21,159.103,0.0412718 Plain Overload Regression Apv crex_pitt,22,0.406207,0.0437284 Plain Overload Regression Apv crex_pitt,23,284.957,0.0445634 Plain Overload Regression Apv crex_pitt,24,770.579,0.0287575 Plain Overload Regression Apv maindet weighted average, 22.3952 +- 93.8184 Plain Overload Regression Apv maindet weighted pull (not meaningful) = 0.00563269 +- 0.870629 Plain Overload Regression Apv crex_pitt, time, Value, Equally weighted Weight Plain Overload Regression Apv crex_pitt,1,253.146,0.0416667 Plain Overload Regression Apv crex_pitt,2,182.712,0.0416667 Plain Overload Regression Apv crex_pitt,3,389.933,0.0416667 Plain Overload Regression Apv crex_pitt,4,-358.51,0.0416667 Plain Overload Regression Apv crex_pitt,5,-226.146,0.0416667 Plain Overload Regression Apv crex_pitt,6,-14.2291,0.0416667 Plain Overload Regression Apv crex_pitt,7,-4.53922,0.0416667 Plain Overload Regression Apv crex_pitt,8,57.1056,0.0416667 Plain Overload Regression Apv crex_pitt,9,298.882,0.0416667 Plain Overload Regression Apv crex_pitt,10,610.069,0.0416667 Plain Overload Regression Apv crex_pitt,11,43.0675,0.0416667 Plain Overload Regression Apv crex_pitt,12,-791.791,0.0416667 Plain Overload Regression Apv crex_pitt,13,-775.982,0.0416667 Plain Overload Regression Apv crex_pitt,14,-403.324,0.0416667 Plain Overload Regression Apv crex_pitt,15,-574.324,0.0416667 Plain Overload Regression Apv crex_pitt,16,508.709,0.0416667 Plain Overload Regression Apv crex_pitt,17,320.656,0.0416667 Plain Overload Regression Apv crex_pitt,18,292.858,0.0416667 Plain Overload Regression Apv crex_pitt,19,214.722,0.0416667 Plain Overload Regression Apv crex_pitt,20,-565.581,0.0416667 Plain Overload Regression Apv crex_pitt,21,159.103,0.0416667 Plain Overload Regression Apv crex_pitt,22,0.406207,0.0416667 Plain Overload Regression Apv crex_pitt,23,284.957,0.0416667 Plain Overload Regression Apv crex_pitt,24,770.579,0.0416667 Plain Overload Regression Apv tg_equal_weighted = 28.02 +- 94.292 Plain Overload Regression Apv th_pull_equal_weighted = 3.52574e-09 +- 0.896117