&StatCorr Name1 = 'CMS Boson rapidity' Name2 = 'CMS Boson rapidity' NIdColumns1 = 2 NIdColumns2 = 2 IdColumns1 = 'y1','y2' IdColumns2 = 'y1','y2' NCorr = 279 ! 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 = 'Full covariance matrix' &End 0.0 0.1 0.0 0.1 0.0002405 0.0 0.1 0.1 0.2 -0.00004611 0.0 0.1 0.2 0.3 0.000001313 0.0 0.1 0.3 0.4 -0.0000008622 0.1 0.2 0.0 0.1 -0.00004611 0.1 0.2 0.1 0.2 0.0002733 0.1 0.2 0.2 0.3 -0.00004847 0.1 0.2 0.3 0.4 0.000002420 0.1 0.2 0.4 0.5 -0.0000009014 0.2 0.3 0.0 0.1 0.000001313 0.2 0.3 0.1 0.2 -0.00004847 0.2 0.3 0.2 0.3 0.0002884 0.2 0.3 0.3 0.4 -0.00005090 0.2 0.3 0.4 0.5 0.000002631 0.2 0.3 0.5 0.6 -0.0000008851 0.3 0.4 0.0 0.1 -0.0000008622 0.3 0.4 0.1 0.2 0.000002420 0.3 0.4 0.2 0.3 -0.00005090 0.3 0.4 0.3 0.4 0.0003026 0.3 0.4 0.4 0.5 -0.00005286 0.3 0.4 0.5 0.6 0.000002722 0.3 0.4 0.6 0.7 -0.0000009373 0.4 0.5 0.1 0.2 -0.0000009014 0.4 0.5 0.2 0.3 0.000002631 0.4 0.5 0.3 0.4 -0.00005286 0.4 0.5 0.4 0.5 0.0002975 0.4 0.5 0.5 0.6 -0.00005377 0.4 0.5 0.6 0.7 0.000002872 0.4 0.5 0.7 0.8 -0.0000009191 0.5 0.6 0.2 0.3 -0.0000008851 0.5 0.6 0.3 0.4 0.000002722 0.5 0.6 0.4 0.5 -0.00005377 0.5 0.6 0.5 0.6 0.0003054 0.5 0.6 0.6 0.7 -0.00005619 0.5 0.6 0.7 0.8 0.000003176 0.5 0.6 0.8 0.9 -0.0000009296 0.6 0.7 0.3 0.4 -0.0000009373 0.6 0.7 0.4 0.5 0.000002872 0.6 0.7 0.5 0.6 -0.00005619 0.6 0.7 0.6 0.7 0.0003172 0.6 0.7 0.7 0.8 -0.00005740 0.6 0.7 0.8 0.9 0.000003234 0.6 0.7 0.9 1.0 -0.0000009837 0.7 0.8 0.4 0.5 -0.0000009191 0.7 0.8 0.5 0.6 0.000003176 0.7 0.8 0.6 0.7 -0.00005740 0.7 0.8 0.7 0.8 0.0003117 0.7 0.8 0.8 0.9 -0.00005881 0.7 0.8 0.9 1.0 0.000003491 0.7 0.8 1.0 1.1 -0.0000008944 0.8 0.9 0.5 0.6 -0.0000009296 0.8 0.9 0.6 0.7 0.000003234 0.8 0.9 0.7 0.8 -0.00005881 0.8 0.9 0.8 0.9 0.0003286 0.8 0.9 0.9 1.0 -0.00006089 0.8 0.9 1.0 1.1 0.000003514 0.8 0.9 1.1 1.2 -0.0000009687 0.9 1.0 0.6 0.7 -0.0000009837 0.9 1.0 0.7 0.8 0.000003491 0.9 1.0 0.8 0.9 -0.00006089 0.9 1.0 0.9 1.0 0.0003203 0.9 1.0 1.0 1.1 -0.00006101 0.9 1.0 1.1 1.2 0.000003573 0.9 1.0 1.2 1.3 -0.0000009256 1.0 1.1 0.7 0.8 -0.0000008944 1.0 1.1 0.8 0.9 0.000003514 1.0 1.1 0.9 1.0 -0.00006101 1.0 1.1 1.0 1.1 0.0003233 1.0 1.1 1.1 1.2 -0.00006439 1.0 1.1 1.2 1.3 0.000004023 1.0 1.1 1.3 1.4 -0.0000008598 1.1 1.2 0.8 0.9 -0.0000009687 1.1 1.2 0.9 1.0 0.000003573 1.1 1.2 1.0 1.1 -0.00006439 1.1 1.2 1.1 1.2 0.0003534 1.1 1.2 1.2 1.3 -0.00007089 1.1 1.2 1.3 1.4 0.000004452 1.1 1.2 1.4 1.5 -0.0000008270 1.2 1.3 0.9 1.0 -0.0000009256 1.2 1.3 1.0 1.1 0.000004023 1.2 1.3 1.1 1.2 -0.00007089 1.2 1.3 1.2 1.3 0.0003688 1.2 1.3 1.3 1.4 -0.00007475 1.2 1.3 1.4 1.5 0.000004940 1.2 1.3 1.5 1.6 -0.0000008685 1.3 1.4 1.0 1.1 -0.0000008598 1.3 1.4 1.1 1.2 0.000004452 1.3 1.4 1.2 1.3 -0.00007475 1.3 1.4 1.3 1.4 0.0003756 1.3 1.4 1.4 1.5 -0.00007856 1.3 1.4 1.5 1.6 0.000005532 1.3 1.4 1.6 1.7 -0.0000007671 1.4 1.5 1.1 1.2 -0.0000008270 1.4 1.5 1.2 1.3 0.000004940 1.4 1.5 1.3 1.4 -0.00007856 1.4 1.5 1.4 1.5 0.0003754 1.4 1.5 1.5 1.6 -0.00008684 1.4 1.5 1.6 1.7 0.000006978 1.4 1.5 1.7 1.8 -0.0000008450 1.5 1.6 1.2 1.3 -0.0000008685 1.5 1.6 1.3 1.4 0.000005532 1.5 1.6 1.4 1.5 -0.00008684 1.5 1.6 1.5 1.6 0.0004163 1.5 1.6 1.6 1.7 -0.0001024 1.5 1.6 1.7 1.8 0.000009331 1.5 1.6 1.8 1.9 -0.000001011 1.6 1.7 1.3 1.4 -0.0000007671 1.6 1.7 1.4 1.5 0.000006978 1.6 1.7 1.5 1.6 -0.0001024 1.6 1.7 1.6 1.7 0.0004670 1.6 1.7 1.7 1.8 -0.0001253 1.6 1.7 1.8 1.9 0.00001352 1.6 1.7 1.9 2.0 -0.000001477 1.7 1.8 1.4 1.5 -0.0000008450 1.7 1.8 1.5 1.6 0.000009331 1.7 1.8 1.6 1.7 -0.0001253 1.7 1.8 1.7 1.8 0.0005560 1.7 1.8 1.8 1.9 -0.0001482 1.7 1.8 1.9 2.0 0.00001803 1.7 1.8 2.0 2.1 -0.000002173 1.8 1.9 1.5 1.6 -0.000001011 1.8 1.9 1.6 1.7 0.00001352 1.8 1.9 1.7 1.8 -0.0001482 1.8 1.9 1.8 1.9 0.0005856 1.8 1.9 1.9 2.0 -0.0001770 1.8 1.9 2.0 2.1 0.00002449 1.8 1.9 2.1 2.2 -0.000003159 1.9 2.0 1.6 1.7 -0.000001477 1.9 2.0 1.7 1.8 0.00001803 1.9 2.0 1.8 1.9 -0.0001770 1.9 2.0 1.9 2.0 0.0006931 1.9 2.0 2.0 2.1 -0.0002009 1.9 2.0 2.1 2.2 0.00003155 1.9 2.0 2.2 2.3 -0.000004979 2.0 2.1 1.7 1.8 -0.000002173 2.0 2.1 1.8 1.9 0.00002449 2.0 2.1 1.9 2.0 -0.0002009 2.0 2.1 2.0 2.1 0.0007073 2.0 2.1 2.1 2.2 -0.0002304 2.0 2.1 2.2 2.3 0.00004278 2.0 2.1 2.3 2.4 -0.000008130 2.0 2.1 2.4 2.5 0.000001062 2.1 2.2 1.8 1.9 -0.000003159 2.1 2.2 1.9 2.0 0.00003155 2.1 2.2 2.0 2.1 -0.0002304 2.1 2.2 2.1 2.2 0.0008138 2.1 2.2 2.2 2.3 -0.0002821 2.1 2.2 2.3 2.4 0.00006122 2.1 2.2 2.4 2.5 -0.00001345 2.1 2.2 2.5 2.6 0.000002478 2.2 2.3 1.9 2.0 -0.000004979 2.2 2.3 2.0 2.1 0.00004278 2.2 2.3 2.1 2.2 -0.0002821 2.2 2.3 2.2 2.3 0.0009704 2.2 2.3 2.3 2.4 -0.0003637 2.2 2.3 2.4 2.5 0.00008714 2.2 2.3 2.5 2.6 -0.00002126 2.2 2.3 2.6 2.7 0.000004288 2.3 2.4 2.0 2.1 -0.000008130 2.3 2.4 2.1 2.2 0.00006122 2.3 2.4 2.2 2.3 -0.0003637 2.3 2.4 2.3 2.4 0.001232 2.3 2.4 2.4 2.5 -0.0004508 2.3 2.4 2.5 2.6 0.0001164 2.3 2.4 2.6 2.7 -0.00002772 2.3 2.4 2.7 2.8 0.000006034 2.3 2.4 2.8 2.9 -0.000001520 2.4 2.5 2.0 2.1 0.000001062 2.4 2.5 2.1 2.2 -0.00001345 2.4 2.5 2.2 2.3 0.00008714 2.4 2.5 2.3 2.4 -0.0004508 2.4 2.5 2.4 2.5 0.001427 2.4 2.5 2.5 2.6 -0.0005291 2.4 2.5 2.6 2.7 0.0001323 2.4 2.5 2.7 2.8 -0.00003288 2.4 2.5 2.8 2.9 0.000008279 2.4 2.5 2.9 3.0 -0.000002383 2.5 2.6 2.1 2.2 0.000002478 2.5 2.6 2.2 2.3 -0.00002126 2.5 2.6 2.3 2.4 0.0001164 2.5 2.6 2.4 2.5 -0.0005291 2.5 2.6 2.5 2.6 0.001572 2.5 2.6 2.6 2.7 -0.0005217 2.5 2.6 2.7 2.8 0.0001368 2.5 2.6 2.8 2.9 -0.00003822 2.5 2.6 2.9 3.0 0.00001133 2.5 2.6 3.0 3.1 -0.000004286 2.5 2.6 3.1 3.2 0.000001710 2.6 2.7 2.2 2.3 0.000004288 2.6 2.7 2.3 2.4 -0.00002772 2.6 2.7 2.4 2.5 0.0001323 2.6 2.7 2.5 2.6 -0.0005217 2.6 2.7 2.6 2.7 0.001350 2.6 2.7 2.7 2.8 -0.0004850 2.6 2.7 2.8 2.9 0.0001436 2.6 2.7 2.9 3.0 -0.00004646 2.6 2.7 3.0 3.1 0.00001745 2.6 2.7 3.1 3.2 -0.000006962 2.6 2.7 3.2 3.3 0.000002450 2.7 2.8 2.3 2.4 0.000006034 2.7 2.8 2.4 2.5 -0.00003288 2.7 2.8 2.5 2.6 0.0001368 2.7 2.8 2.6 2.7 -0.0004850 2.7 2.8 2.7 2.8 0.001213 2.7 2.8 2.8 2.9 -0.0004762 2.7 2.8 2.9 3.0 0.0001620 2.7 2.8 3.0 3.1 -0.00006539 2.7 2.8 3.1 3.2 0.00002603 2.7 2.8 3.2 3.3 -0.000009104 2.7 2.8 3.3 3.4 0.000003682 2.7 2.8 3.4 3.5 -0.000001491 2.8 2.9 2.3 2.4 -0.000001520 2.8 2.9 2.4 2.5 0.000008279 2.8 2.9 2.5 2.6 -0.00003822 2.8 2.9 2.6 2.7 0.0001436 2.8 2.9 2.7 2.8 -0.0004762 2.8 2.9 2.8 2.9 0.001151 2.8 2.9 2.9 3.0 -0.0005065 2.8 2.9 3.0 3.1 0.0002146 2.8 2.9 3.1 3.2 -0.00009107 2.8 2.9 3.2 3.3 0.00003188 2.8 2.9 3.3 3.4 -0.00001284 2.8 2.9 3.4 3.5 0.000005205 2.9 3.0 2.4 2.5 -0.000002383 2.9 3.0 2.5 2.6 0.00001133 2.9 3.0 2.6 2.7 -0.00004646 2.9 3.0 2.7 2.8 0.0001620 2.9 3.0 2.8 2.9 -0.0005065 2.9 3.0 2.9 3.0 0.001207 2.9 3.0 3.0 3.1 -0.0006519 2.9 3.0 3.1 3.2 0.0002856 2.9 3.0 3.2 3.3 -0.0001046 2.9 3.0 3.3 3.4 0.00004244 2.9 3.0 3.4 3.5 -0.00001727 3.0 3.1 2.5 2.6 -0.000004286 3.0 3.1 2.6 2.7 0.00001745 3.0 3.1 2.7 2.8 -0.00006539 3.0 3.1 2.8 2.9 0.0002146 3.0 3.1 2.9 3.0 -0.0006519 3.0 3.1 3.0 3.1 0.001602 3.0 3.1 3.1 3.2 -0.0008345 3.0 3.1 3.2 3.3 0.0003138 3.0 3.1 3.3 3.4 -0.0001331 3.0 3.1 3.4 3.5 0.00005450 3.1 3.2 2.5 2.6 0.000001710 3.1 3.2 2.6 2.7 -0.000006962 3.1 3.2 2.7 2.8 0.00002603 3.1 3.2 2.8 2.9 -0.00009107 3.1 3.2 2.9 3.0 0.0002856 3.1 3.2 3.0 3.1 -0.0008345 3.1 3.2 3.1 3.2 0.002015 3.1 3.2 3.2 3.3 -0.0008683 3.1 3.2 3.3 3.4 0.0003876 3.1 3.2 3.4 3.5 -0.0001672 3.2 3.3 2.6 2.7 0.000002450 3.2 3.3 2.7 2.8 -0.000009104 3.2 3.3 2.8 2.9 0.00003188 3.2 3.3 2.9 3.0 -0.0001046 3.2 3.3 3.0 3.1 0.0003138 3.2 3.3 3.1 3.2 -0.0008683 3.2 3.3 3.2 3.3 0.001838 3.2 3.3 3.3 3.4 -0.001053 3.2 3.3 3.4 3.5 0.0004747 3.3 3.4 2.7 2.8 0.000003682 3.3 3.4 2.8 2.9 -0.00001284 3.3 3.4 2.9 3.0 0.00004244 3.3 3.4 3.0 3.1 -0.0001331 3.3 3.4 3.1 3.2 0.0003876 3.3 3.4 3.2 3.3 -0.001053 3.3 3.4 3.3 3.4 0.002553 3.3 3.4 3.4 3.5 -0.001326 3.4 3.5 2.7 2.8 -0.000001491 3.4 3.5 2.8 2.9 0.000005205 3.4 3.5 2.9 3.0 -0.00001727 3.4 3.5 3.0 3.1 0.00005450 3.4 3.5 3.1 3.2 -0.0001672 3.4 3.5 3.2 3.3 0.0004747 3.4 3.5 3.3 3.4 -0.001326 3.4 3.5 3.4 3.5 0.003848