&StatCorr Name1 = 'H1 normalised trijets with unfolding' Name2 = 'H1 normalised trijets with unfolding' NIdColumns1 = 2 NIdColumns2 = 2 IdColumns1 = 'q2min','etmin' IdColumns2 = 'q2min','etmin' NCorr = 120 ! Matrix Type: ! 'Statistical correlations': Given are correlation factors that need to be applied to statistical errors ! needs 'stat' column in data files ! 'Systematic correlations' : Given are correlation factors that need to be applied to systematic errors ! needs 'uncor' column in data files ! 'Systematic covariance matrix': Given is a systematic covariance matrix ! ! 'Full covariance matrix': Given is a full covariance matrix including stat and syst parts MatrixType = 'Statistical correlations' &End 150. 7. 150. 11. -0.374672342797 150. 7. 150. 18. 0.0911407484668 150. 7. 200. 7. 0.0103918250186 150. 7. 200. 11. 0.0181607332321 150. 7. 200. 18. -0.00424229615895 150. 7. 270. 7. 0.144838323514 150. 7. 270. 11. -0.0386601071467 150. 7. 270. 18. 0.0105445408209 150. 7. 400. 7. 0.122473002142 150. 7. 400. 11. -0.0302674602666 150. 7. 400. 18. 0.0056925854097 150. 7. 700. 7. 0.121329623893 150. 7. 700. 11. -0.0319493536091 150. 7. 700. 18. 0.00574516300426 150. 7. 5000. 11. -0.00824736635766 150. 11. 150. 18. -0.266043114462 150. 11. 200. 7. 0.0141394536666 150. 11. 200. 11. -0.0816746308 150. 11. 200. 18. 0.024682880617 150. 11. 270. 7. -0.0343073237826 150. 11. 270. 11. 0.0695108700525 150. 11. 270. 18. -0.0180284954723 150. 11. 400. 7. -0.0269065179292 150. 11. 400. 11. 0.0556813132277 150. 11. 400. 18. -0.00956605018856 150. 11. 700. 7. -0.0260206161832 150. 11. 700. 11. 0.0640954542081 150. 11. 700. 18. -0.0115897630522 150. 11. 5000. 11. 0.021845578868 150. 18. 200. 7. -0.00188595905515 150. 18. 200. 11. 0.0214873666157 150. 18. 200. 18. -0.109137622334 150. 18. 270. 7. 0.00874468738866 150. 18. 270. 11. -0.0173530628492 150. 18. 270. 18. 0.0505489091018 150. 18. 400. 7. 0.00569086495988 150. 18. 400. 11. -0.0101638854642 150. 18. 400. 18. 0.0271175998967 150. 18. 700. 7. 0.00486014210847 150. 18. 700. 11. -0.00966977849321 150. 18. 700. 18. 0.0273803978656 150. 18. 5000. 11. -0.00409066737694 200. 7. 200. 11. -0.352854955012 200. 7. 200. 18. 0.0756901993239 200. 7. 270. 7. 0.0223008797057 200. 7. 270. 11. 0.00890088362156 200. 7. 270. 18. -0.0032869737834 200. 7. 400. 7. 0.107575249249 200. 7. 400. 11. -0.0265789369114 200. 7. 400. 18. 0.00542035813245 200. 7. 700. 7. 0.0975497038934 200. 7. 700. 11. -0.0240502879773 200. 7. 700. 18. 0.00505177481229 200. 7. 5000. 11. -0.00564691729007 200. 11. 200. 18. -0.245136823661 200. 11. 270. 7. 0.00732917444288 200. 11. 270. 11. -0.0531726417803 200. 11. 270. 18. 0.019941930102 200. 11. 400. 7. -0.0250251974585 200. 11. 400. 11. 0.05993221349 200. 11. 400. 18. -0.0119090810402 200. 11. 700. 7. -0.0216326286113 200. 11. 700. 11. 0.0592872225723 200. 11. 700. 18. -0.0119622154059 200. 11. 5000. 11. 0.0198233648247 200. 18. 270. 7. -0.00328680413565 200. 18. 270. 11. 0.0205675810245 200. 18. 270. 18. -0.0831427950345 200. 18. 400. 7. 0.00505901641866 200. 18. 400. 11. -0.0111333627293 200. 18. 400. 18. 0.0351221399819 200. 18. 700. 7. 0.0039616969414 200. 18. 700. 11. -0.00799408228192 200. 18. 700. 18. 0.0309808436593 200. 18. 5000. 11. -0.00362771871322 270. 7. 270. 11. -0.374351609495 270. 7. 270. 18. 0.099791774526 270. 7. 400. 7. 0.0284919615645 270. 7. 400. 11. 0.00651230294459 270. 7. 400. 18. -0.00258086629366 270. 7. 700. 7. 0.0995143678348 270. 7. 700. 11. -0.0259285229625 270. 7. 700. 18. 0.006096770945 270. 7. 5000. 11. -0.00599018512079 270. 11. 270. 18. -0.293626097287 270. 11. 400. 7. 0.000718489606176 270. 11. 400. 11. -0.0208385148884 270. 11. 400. 18. 0.0116688838325 270. 11. 700. 7. -0.0233126450084 270. 11. 700. 11. 0.0679427122842 270. 11. 700. 18. -0.0133510931642 270. 11. 5000. 11. 0.0215212895925 270. 18. 400. 7. -0.000478457810293 270. 18. 400. 11. 0.00907561026905 270. 18. 400. 18. -0.0477034355061 270. 18. 700. 7. 0.00428804886399 270. 18. 700. 11. -0.011513094392 270. 18. 700. 18. 0.0349787915906 270. 18. 5000. 11. -0.00464306254845 400. 7. 400. 11. -0.357279147837 400. 7. 400. 18. 0.0842589277842 400. 7. 700. 7. 0.0480188628585 400. 7. 700. 11. -0.00471751737469 400. 7. 700. 18. 0.00132753097065 400. 7. 5000. 11. -0.0055917154408 400. 11. 400. 18. -0.272243358973 400. 11. 700. 7. -0.00704991537968 400. 11. 700. 11. 0.0288838263761 400. 11. 700. 18. -0.00258087120041 400. 11. 5000. 11. 0.0236399403461 400. 18. 700. 7. 0.00248943640488 400. 18. 700. 11. -0.00299016664803 400. 18. 700. 18. 0.0148760748874 400. 18. 5000. 11. -0.00460141015472 700. 7. 700. 11. -0.363079822075 700. 7. 700. 18. 0.0874190887263 700. 7. 5000. 11. -0.00169169158939 700. 11. 700. 18. -0.289573210345 700. 11. 5000. 11. 0.0186604735002 700. 18. 5000. 11. -0.00429436416522