Reading taal2.log Killing partial data Storing raw data in spss-taal.txt Normalizing Subject 1 ... Sum 849.000 in 183.000, Adjust: add -4.639 Variance is 0.93004 Standard Deviation is 0.96438, Adjust: multiply by 1.03693 Normalizing Subject 2 ... Sum 816.000 in 180.000, Adjust: add -4.533 Variance is 1.17111 Standard Deviation is 1.08218, Adjust: multiply by 0.92406 Normalizing Subject 3 ... Sum 759.000 in 183.000, Adjust: add -4.148 Variance is 1.18588 Standard Deviation is 1.08898, Adjust: multiply by 0.91829 Normalizing Subject 4 ... Sum 717.000 in 183.000, Adjust: add -3.918 Variance is 0.81842 Standard Deviation is 0.90466, Adjust: multiply by 1.10538 Normalizing Subject 5 ... Sum 635.000 in 183.000, Adjust: add -3.470 Variance is 0.82833 Standard Deviation is 0.91013, Adjust: multiply by 1.09875 Normalizing Subject 6 ... Sum 813.000 in 183.000, Adjust: add -4.443 Variance is 1.04452 Standard Deviation is 1.02202, Adjust: multiply by 0.97846 Normalizing Subject 7 ... Sum 555.000 in 183.000, Adjust: add -3.033 Variance is 1.51805 Standard Deviation is 1.23209, Adjust: multiply by 0.81163 Normalizing Subject 8 ... Sum 649.000 in 183.000, Adjust: add -3.546 Variance is 1.61396 Standard Deviation is 1.27042, Adjust: multiply by 0.78714 Normalizing Subject 9 ... Sum 873.000 in 183.000, Adjust: add -4.770 Variance is 0.54842 Standard Deviation is 0.74055, Adjust: multiply by 1.35034 Normalizing Subject 10 ... Sum 889.000 in 183.000, Adjust: add -4.858 Variance is 0.40604 Standard Deviation is 0.63722, Adjust: multiply by 1.56933 Normalizing Subject 11 ... Sum 721.000 in 183.000, Adjust: add -3.940 Variance is 1.83792 Standard Deviation is 1.35570, Adjust: multiply by 0.73763 Normalizing Subject 12 ... Sum 679.000 in 180.000, Adjust: add -3.772 Variance is 1.62034 Standard Deviation is 1.27293, Adjust: multiply by 0.78559 Normalizing Subject 13 ... Sum 833.000 in 183.000, Adjust: add -4.552 Variance is 0.71725 Standard Deviation is 0.84691, Adjust: multiply by 1.18077 Normalizing Subject 14 ... Sum 815.000 in 183.000, Adjust: add -4.454 Variance is 1.12216 Standard Deviation is 1.05932, Adjust: multiply by 0.94400 Normalizing Subject 15 ... Sum 317.000 in 99.000, Adjust: add -3.202 Variance is 2.48444 Standard Deviation is 1.57621, Adjust: multiply by 0.63443 Normalizing Subject 16 ... Sum 656.000 in 183.000, Adjust: add -3.585 Variance is 1.41222 Standard Deviation is 1.18837, Adjust: multiply by 0.84149 Normalizing Subject 17 ... Sum 662.000 in 180.000, Adjust: add -3.678 Variance is 0.26284 Standard Deviation is 0.51268, Adjust: multiply by 1.95054 Normalizing Subject 18 ... Sum 856.000 in 183.000, Adjust: add -4.678 Variance is 0.76491 Standard Deviation is 0.87459, Adjust: multiply by 1.14339 Normalizing Subject 19 ... Sum 768.000 in 183.000, Adjust: add -4.197 Variance is 1.40392 Standard Deviation is 1.18487, Adjust: multiply by 0.84397 Normalizing Subject 20 ... Sum 611.000 in 183.000, Adjust: add -3.339 Variance is 1.98358 Standard Deviation is 1.40840, Adjust: multiply by 0.71003 Normalizing Subject 21 ... Sum 689.000 in 180.000, Adjust: add -3.828 Variance is 0.62034 Standard Deviation is 0.78762, Adjust: multiply by 1.26965 Normalizing Subject 22 ... Sum 911.000 in 183.000, Adjust: add -4.978 Variance is 0.08695 Standard Deviation is 0.29488, Adjust: multiply by 3.39122 Normalizing Subject 23 ... Sum 733.000 in 183.000, Adjust: add -4.005 Variance is 0.98904 Standard Deviation is 0.99451, Adjust: multiply by 1.00552 Calculating mean and standard deviation per sentence and part sent.part 1.1: mean 0.43102 std dev: 0.57176 (00023 samples) sent.part 1.2: mean -0.98315 std dev: 1.09109 (00023 samples) sent.part 1.3: mean -0.00293 std dev: 0.73356 (00023 samples) sent.part 2.1: mean -0.37654 std dev: 0.95626 (00023 samples) sent.part 2.2: mean 0.00071 std dev: 0.82431 (00023 samples) sent.part 2.3: mean 0.21528 std dev: 0.59214 (00023 samples) sent.part 3.1: mean 0.38050 std dev: 0.83405 (00023 samples) sent.part 3.2: mean -0.14926 std dev: 1.09264 (00023 samples) sent.part 3.3: mean -0.27672 std dev: 0.73837 (00023 samples) sent.part 4.1: mean 0.01421 std dev: 0.93986 (00023 samples) sent.part 4.2: mean -0.76124 std dev: 1.24119 (00023 samples) sent.part 4.3: mean 0.48103 std dev: 0.51654 (00023 samples) sent.part 5.1: mean 0.10150 std dev: 0.84358 (00023 samples) sent.part 5.2: mean -0.73938 std dev: 0.94198 (00023 samples) sent.part 5.3: mean -0.14771 std dev: 0.93967 (00023 samples) sent.part 6.1: mean 0.63647 std dev: 0.36128 (00023 samples) sent.part 6.2: mean 0.06501 std dev: 0.91564 (00023 samples) sent.part 6.3: mean -0.17633 std dev: 0.82919 (00023 samples) sent.part 7.1: mean -0.65804 std dev: 1.44705 (00023 samples) sent.part 7.2: mean -0.63334 std dev: 1.36820 (00023 samples) sent.part 7.3: mean -0.03119 std dev: 1.40216 (00023 samples) sent.part 8.1: mean 0.15471 std dev: 0.82379 (00023 samples) sent.part 8.2: mean 0.15055 std dev: 0.79431 (00023 samples) sent.part 8.3: mean -0.09800 std dev: 0.82168 (00023 samples) sent.part 9.1: mean 0.09608 std dev: 0.87848 (00023 samples) sent.part 9.2: mean -0.41319 std dev: 1.60489 (00023 samples) sent.part 9.3: mean 0.17625 std dev: 0.57287 (00023 samples) sent.part 10.1: mean -0.14356 std dev: 0.78759 (00023 samples) sent.part 10.2: mean 0.24113 std dev: 0.69487 (00023 samples) sent.part 10.3: mean -0.14614 std dev: 0.83479 (00023 samples) sent.part 11.1: mean 0.37302 std dev: 0.71700 (00023 samples) sent.part 11.2: mean -0.02028 std dev: 0.72450 (00023 samples) sent.part 11.3: mean 0.46601 std dev: 0.65862 (00023 samples) sent.part 12.1: mean 0.23736 std dev: 0.62152 (00023 samples) sent.part 12.2: mean 0.14236 std dev: 0.73798 (00023 samples) sent.part 12.3: mean 0.25022 std dev: 0.67695 (00023 samples) sent.part 13.1: mean -0.59314 std dev: 1.30725 (00023 samples) sent.part 13.2: mean -0.56727 std dev: 1.41361 (00023 samples) sent.part 13.3: mean -1.34917 std dev: 1.20755 (00023 samples) sent.part 14.1: mean 0.42764 std dev: 0.72938 (00023 samples) sent.part 14.2: mean 0.05880 std dev: 0.70998 (00023 samples) sent.part 14.3: mean -1.40817 std dev: 2.76281 (00023 samples) sent.part 15.1: mean 0.30215 std dev: 1.09345 (00023 samples) sent.part 15.2: mean -0.55559 std dev: 0.91305 (00023 samples) sent.part 15.3: mean -0.73804 std dev: 1.12431 (00023 samples) sent.part 16.1: mean 0.29200 std dev: 0.81052 (00023 samples) sent.part 16.2: mean 0.13597 std dev: 0.81112 (00023 samples) sent.part 16.3: mean 0.08563 std dev: 0.75435 (00023 samples) sent.part 17.1: mean 0.07186 std dev: 0.68494 (00023 samples) sent.part 17.2: mean 0.44441 std dev: 0.31337 (00023 samples) sent.part 17.3: mean -0.20391 std dev: 0.76516 (00023 samples) sent.part 18.1: mean -0.05405 std dev: 0.83815 (00023 samples) sent.part 18.2: mean 0.11508 std dev: 0.65823 (00023 samples) sent.part 18.3: mean 0.09517 std dev: 0.71426 (00023 samples) sent.part 19.1: mean 0.25078 std dev: 0.74329 (00023 samples) sent.part 19.2: mean -1.09914 std dev: 1.01764 (00023 samples) sent.part 19.3: mean 0.03133 std dev: 0.74471 (00023 samples) sent.part 20.1: mean 0.34247 std dev: 0.66797 (00023 samples) sent.part 20.2: mean -0.60524 std dev: 0.75975 (00023 samples) sent.part 20.3: mean -0.19381 std dev: 0.94352 (00023 samples) sent.part 21.1: mean -1.69014 std dev: 1.60281 (00023 samples) sent.part 21.2: mean -0.13501 std dev: 1.36606 (00023 samples) sent.part 21.3: mean 0.39016 std dev: 0.49211 (00023 samples) sent.part 22.1: mean -0.47684 std dev: 0.92109 (00023 samples) sent.part 22.2: mean -0.66747 std dev: 0.92232 (00023 samples) sent.part 22.3: mean -0.27528 std dev: 0.77902 (00023 samples) sent.part 23.1: mean 0.50107 std dev: 0.37899 (00023 samples) sent.part 23.2: mean 0.12331 std dev: 0.80845 (00023 samples) sent.part 23.3: mean 0.34159 std dev: 0.79550 (00023 samples) sent.part 24.1: mean -0.06214 std dev: 0.80490 (00023 samples) sent.part 24.2: mean 0.31631 std dev: 0.96959 (00023 samples) sent.part 24.3: mean 0.01771 std dev: 0.80043 (00023 samples) sent.part 25.1: mean 0.21412 std dev: 0.82228 (00022 samples) sent.part 25.2: mean 0.35983 std dev: 0.55597 (00022 samples) sent.part 25.3: mean 0.09353 std dev: 0.79924 (00022 samples) sent.part 26.1: mean -1.44658 std dev: 1.26666 (00023 samples) sent.part 26.2: mean -0.81009 std dev: 1.21288 (00023 samples) sent.part 26.3: mean -1.20530 std dev: 1.11512 (00023 samples) sent.part 27.1: mean 0.17703 std dev: 0.58360 (00023 samples) sent.part 27.2: mean -0.82818 std dev: 1.01860 (00023 samples) sent.part 27.3: mean 0.13550 std dev: 0.65593 (00023 samples) sent.part 28.1: mean 0.14847 std dev: 0.57268 (00023 samples) sent.part 28.2: mean 0.30769 std dev: 0.58088 (00023 samples) sent.part 28.3: mean 0.39573 std dev: 0.52338 (00023 samples) sent.part 29.1: mean 0.50318 std dev: 0.85346 (00023 samples) sent.part 29.2: mean 0.23969 std dev: 1.00925 (00023 samples) sent.part 29.3: mean -0.79395 std dev: 0.93274 (00023 samples) sent.part 30.1: mean -0.83745 std dev: 1.64391 (00023 samples) sent.part 30.2: mean -0.66277 std dev: 1.38250 (00023 samples) sent.part 30.3: mean -1.13958 std dev: 1.33191 (00023 samples) sent.part 31.1: mean 0.09021 std dev: 0.69689 (00023 samples) sent.part 31.2: mean -0.74625 std dev: 1.04191 (00023 samples) sent.part 31.3: mean 0.26789 std dev: 0.66467 (00023 samples) sent.part 32.1: mean 0.20440 std dev: 0.61744 (00023 samples) sent.part 32.2: mean 0.10969 std dev: 1.11056 (00023 samples) sent.part 32.3: mean 0.62502 std dev: 0.36413 (00023 samples) sent.part 33.1: mean 0.23172 std dev: 0.71147 (00023 samples) sent.part 33.2: mean 0.16747 std dev: 0.67969 (00023 samples) sent.part 33.3: mean 0.13913 std dev: 0.78074 (00023 samples) sent.part 34.1: mean 0.13479 std dev: 0.67317 (00022 samples) sent.part 34.2: mean -0.17799 std dev: 0.82880 (00022 samples) sent.part 34.3: mean 0.40706 std dev: 0.31832 (00022 samples) sent.part 35.1: mean 0.61012 std dev: 0.37886 (00022 samples) sent.part 35.2: mean -0.54327 std dev: 1.08227 (00022 samples) sent.part 35.3: mean 0.33512 std dev: 0.47489 (00022 samples) sent.part 36.1: mean -0.10516 std dev: 0.77607 (00022 samples) sent.part 36.2: mean 0.16257 std dev: 1.20466 (00022 samples) sent.part 36.3: mean 0.22740 std dev: 0.66492 (00022 samples) sent.part 37.1: mean 0.37734 std dev: 0.71661 (00022 samples) sent.part 37.2: mean 0.61459 std dev: 0.54923 (00022 samples) sent.part 37.3: mean 0.63131 std dev: 0.44955 (00022 samples) sent.part 38.1: mean 0.26927 std dev: 0.57050 (00022 samples) sent.part 38.2: mean -0.59023 std dev: 1.25938 (00022 samples) sent.part 38.3: mean -1.01900 std dev: 1.11922 (00022 samples) sent.part 39.1: mean -0.72576 std dev: 1.03405 (00022 samples) sent.part 39.2: mean 0.60154 std dev: 0.48213 (00022 samples) sent.part 39.3: mean 0.38116 std dev: 0.50527 (00022 samples) sent.part 40.1: mean 0.51366 std dev: 0.60283 (00022 samples) sent.part 40.2: mean 0.39797 std dev: 0.55139 (00022 samples) sent.part 40.3: mean 0.39417 std dev: 0.65602 (00022 samples) sent.part 41.1: mean -0.44469 std dev: 0.88101 (00022 samples) sent.part 41.2: mean 0.42210 std dev: 0.67196 (00022 samples) sent.part 41.3: mean -0.17453 std dev: 0.76516 (00022 samples) sent.part 42.1: mean 0.14922 std dev: 0.83051 (00022 samples) sent.part 42.2: mean -0.24988 std dev: 1.07849 (00022 samples) sent.part 42.3: mean 0.27354 std dev: 0.68972 (00022 samples) sent.part 43.1: mean 0.20126 std dev: 0.84049 (00022 samples) sent.part 43.2: mean 0.39321 std dev: 0.59724 (00022 samples) sent.part 43.3: mean 0.54829 std dev: 0.36736 (00022 samples) sent.part 44.1: mean 0.03380 std dev: 0.74386 (00022 samples) sent.part 44.2: mean 0.59273 std dev: 0.53422 (00022 samples) sent.part 44.3: mean 0.55786 std dev: 0.78920 (00022 samples) sent.part 45.1: mean -0.48522 std dev: 1.06925 (00022 samples) sent.part 45.2: mean -0.11997 std dev: 1.05162 (00022 samples) sent.part 45.3: mean 0.08778 std dev: 1.00702 (00022 samples) sent.part 46.1: mean 0.20072 std dev: 0.89784 (00022 samples) sent.part 46.2: mean 0.45215 std dev: 0.74440 (00022 samples) sent.part 46.3: mean 0.21664 std dev: 0.93192 (00022 samples) sent.part 47.1: mean 0.64666 std dev: 0.48498 (00022 samples) sent.part 47.2: mean 0.12481 std dev: 0.56096 (00022 samples) sent.part 47.3: mean 0.28587 std dev: 0.55404 (00022 samples) sent.part 48.1: mean 0.21719 std dev: 0.50898 (00022 samples) sent.part 48.2: mean 0.47727 std dev: 0.43502 (00022 samples) sent.part 48.3: mean -0.30865 std dev: 0.87246 (00022 samples) sent.part 49.1: mean -0.45369 std dev: 1.59505 (00022 samples) sent.part 49.2: mean 0.35877 std dev: 0.51028 (00022 samples) sent.part 49.3: mean 0.62236 std dev: 0.36188 (00022 samples) sent.part 50.1: mean 0.47345 std dev: 0.54115 (00022 samples) sent.part 50.2: mean -0.01896 std dev: 0.90912 (00022 samples) sent.part 50.3: mean 0.22831 std dev: 0.64696 (00022 samples) sent.part 51.1: mean 0.41508 std dev: 0.65728 (00022 samples) sent.part 51.2: mean 0.14856 std dev: 0.63191 (00022 samples) sent.part 51.3: mean 0.15268 std dev: 0.72565 (00022 samples) sent.part 52.1: mean 0.19294 std dev: 1.07269 (00022 samples) sent.part 52.2: mean 0.22434 std dev: 0.61767 (00022 samples) sent.part 52.3: mean 0.48093 std dev: 0.52897 (00022 samples) sent.part 53.1: mean 0.28880 std dev: 0.83649 (00022 samples) sent.part 53.2: mean 0.51899 std dev: 0.55019 (00022 samples) sent.part 53.3: mean 0.40950 std dev: 0.63485 (00022 samples) sent.part 54.1: mean 0.41232 std dev: 0.66502 (00022 samples) sent.part 54.2: mean -0.39990 std dev: 0.88021 (00022 samples) sent.part 54.3: mean -0.26952 std dev: 1.06959 (00022 samples) sent.part 55.1: mean 0.09747 std dev: 0.90191 (00022 samples) sent.part 55.2: mean 0.19637 std dev: 0.96967 (00022 samples) sent.part 55.3: mean -0.18034 std dev: 1.13617 (00022 samples) sent.part 56.1: mean -0.07241 std dev: 0.75222 (00022 samples) sent.part 56.2: mean 0.30680 std dev: 0.60865 (00022 samples) sent.part 56.3: mean 0.65760 std dev: 0.43725 (00022 samples) sent.part 57.1: mean 0.33534 std dev: 0.49648 (00021 samples) sent.part 57.2: mean 0.47289 std dev: 0.42536 (00021 samples) sent.part 57.3: mean -0.68567 std dev: 1.19981 (00021 samples) sent.part 58.1: mean -0.34490 std dev: 0.85882 (00022 samples) sent.part 58.2: mean 0.14254 std dev: 0.78612 (00022 samples) sent.part 58.3: mean -0.24786 std dev: 0.96853 (00022 samples) sent.part 59.1: mean 0.55249 std dev: 0.38198 (00021 samples) sent.part 59.2: mean 0.44416 std dev: 0.47230 (00021 samples) sent.part 59.3: mean 0.48245 std dev: 0.55072 (00021 samples) sent.part 60.1: mean -0.37050 std dev: 1.02640 (00022 samples) sent.part 60.2: mean -0.19592 std dev: 0.97337 (00022 samples) sent.part 60.3: mean 0.00004 std dev: 0.92428 (00022 samples) sent.part 61.1: mean 0.17591 std dev: 0.65963 (00021 samples) sent.part 61.2: mean -0.56224 std dev: 1.19743 (00021 samples) sent.part 61.3: mean 0.16790 std dev: 0.83089 (00021 samples) sent: 001 F: 5.10671 mean: -0.18502 in: 023 MSB: 24.14268 MSW: 47.27638 sent: 002 F: 0.92326 mean: -0.05352 in: 023 MSB: 4.12924 MSW: 44.72471 sent: 003 F: 0.99786 mean: -0.01516 in: 023 MSB: 5.58781 MSW: 55.99777 sent: 004 F: 2.92672 mean: -0.08867 in: 023 MSB: 18.11229 MSW: 61.88607 sent: 005 F: 1.50322 mean: -0.26187 in: 023 MSB: 8.58110 MSW: 57.08470 sent: 006 F: 2.10377 mean: 0.17505 in: 023 MSB: 8.01506 MSW: 38.09864 sent: 007 F: 0.42489 mean: -0.44086 in: 023 MSB: 5.79703 MSW: 136.43529 sent: 008 F: 0.21103 mean: 0.06909 in: 023 MSB: 0.96334 MSW: 45.64874 sent: 009 F: 0.55613 mean: -0.04695 in: 023 MSB: 4.70137 MSW: 84.53799 sent: 010 F: 0.55182 mean: -0.01619 in: 023 MSB: 2.28454 MSW: 41.40039 sent: 011 F: 0.90491 mean: 0.27292 in: 023 MSB: 3.06527 MSW: 33.87361 sent: 012 F: 0.04997 mean: 0.20998 in: 023 MSB: 0.15965 MSW: 31.95097 sent: 013 F: 0.76382 mean: -0.83653 in: 023 MSB: 9.07442 MSW: 118.80359 sent: 014 F: 2.17560 mean: -0.30724 in: 023 MSB: 43.37960 MSW: 199.39133 sent: 015 F: 1.87344 mean: -0.33049 in: 023 MSB: 14.19078 MSW: 75.74729 sent: 016 F: 0.12291 mean: 0.17120 in: 023 MSB: 0.53256 MSW: 43.32994 sent: 017 F: 1.83654 mean: 0.10412 in: 023 MSB: 4.86959 MSW: 26.51493 sent: 018 F: 0.10383 mean: 0.05207 in: 023 MSB: 0.39306 MSW: 37.85616 sent: 019 F: 4.89797 mean: -0.27234 in: 023 MSB: 24.13785 MSW: 49.28135 sent: 020 F: 2.36030 mean: -0.15219 in: 023 MSB: 10.38856 MSW: 44.01364 sent: 021 F: 5.00425 mean: -0.47833 in: 023 MSB: 53.83446 MSW: 107.57748 sent: 022 F: 0.33362 mean: -0.47319 in: 023 MSB: 1.76939 MSW: 53.03676 sent: 023 F: 0.50298 mean: 0.32199 in: 023 MSB: 1.65436 MSW: 32.89079 sent: 024 F: 0.35710 mean: 0.09062 in: 023 MSB: 1.83047 MSW: 51.25888 sent: 025 F: 0.20802 mean: 0.22249 in: 022 MSB: 0.78235 MSW: 35.72892 sent: 026 F: 0.47815 mean: -1.15399 in: 023 MSB: 4.74976 MSW: 99.33673 sent: 027 F: 3.57748 mean: -0.17188 in: 023 MSB: 14.87981 MSW: 41.59298 sent: 028 F: 0.33442 mean: 0.28396 in: 023 MSB: 0.72250 MSW: 21.60435 sent: 029 F: 3.59240 mean: -0.01703 in: 023 MSB: 21.62286 MSW: 60.19054 sent: 030 F: 0.18220 mean: -0.87993 in: 023 MSB: 2.67679 MSW: 146.91759 sent: 031 F: 2.91388 mean: -0.12938 in: 023 MSB: 13.49111 MSW: 46.29949 sent: 032 F: 0.86130 mean: 0.31304 in: 023 MSB: 3.46113 MSW: 40.18478 sent: 033 F: 0.02853 mean: 0.17944 in: 023 MSB: 0.10354 MSW: 36.28797 sent: 034 F: 1.31180 mean: 0.12128 in: 022 MSB: 3.77118 MSW: 27.31072 sent: 035 F: 4.47652 mean: 0.13399 in: 022 MSB: 15.96842 MSW: 33.88792 sent: 036 F: 0.23661 mean: 0.09494 in: 022 MSB: 1.36746 MSW: 54.90296 sent: 037 F: 0.37688 mean: 0.54108 in: 022 MSB: 0.88785 MSW: 22.38022 sent: 038 F: 2.58428 mean: -0.44666 in: 022 MSB: 18.93639 MSW: 69.61153 sent: 039 F: 6.17384 mean: 0.08565 in: 022 MSB: 22.26106 MSW: 34.25420 sent: 040 F: 0.07984 mean: 0.43527 in: 022 MSB: 0.20296 MSW: 24.15153 sent: 041 F: 2.06131 mean: -0.06571 in: 022 MSB: 8.65533 MSW: 39.88995 sent: 042 F: 0.61018 mean: 0.05763 in: 022 MSB: 3.29041 MSW: 51.22921 sent: 043 F: 0.47926 mean: 0.38092 in: 022 MSB: 1.32972 MSW: 26.35781 sent: 044 F: 1.27454 mean: 0.39479 in: 022 MSB: 4.31391 MSW: 32.15434 sent: 045 F: 0.48994 mean: -0.17247 in: 022 MSB: 3.70251 MSW: 71.79258 sent: 046 F: 0.16899 mean: 0.28984 in: 022 MSB: 0.87218 MSW: 49.03195 sent: 047 F: 1.58340 mean: 0.35245 in: 022 MSB: 3.14187 MSW: 18.85045 sent: 048 F: 2.51819 mean: 0.12861 in: 022 MSB: 7.05330 MSW: 26.60896 sent: 049 F: 2.03608 mean: 0.17581 in: 022 MSB: 13.84146 MSW: 64.58181 sent: 050 F: 0.74891 mean: 0.22760 in: 022 MSB: 2.66721 MSW: 33.83382 sent: 051 F: 0.32628 mean: 0.23877 in: 022 MSB: 1.02601 MSW: 29.87359 sent: 052 F: 0.26174 mean: 0.29941 in: 022 MSB: 1.09829 MSW: 39.86340 sent: 053 F: 0.17923 mean: 0.40576 in: 022 MSB: 0.58335 MSW: 30.92025 sent: 054 F: 1.53113 mean: -0.08570 in: 022 MSB: 8.37179 MSW: 51.94339 sent: 055 F: 0.23804 mean: 0.03783 in: 022 MSB: 1.67834 MSW: 66.98114 sent: 056 F: 2.24626 mean: 0.29733 in: 022 MSB: 5.86503 MSW: 24.80474 sent: 057 F: 3.86240 mean: 0.04085 in: 021 MSB: 16.82564 MSW: 39.20641 sent: 058 F: 0.55146 mean: -0.15007 in: 022 MSB: 2.92908 MSW: 50.45943 sent: 059 F: 0.08080 mean: 0.49303 in: 021 MSB: 0.12674 MSW: 14.11756 sent: 060 F: 0.22867 mean: -0.18879 in: 022 MSB: 1.51201 MSW: 62.81556 sent: 061 F: 1.26364 mean: -0.07281 in: 021 MSB: 7.54618 MSW: 53.74610 Storing the essence of our calculations in measures-taal.txt 001. choice: sent: 033 F: 0.02853 df_1: 2 df_2: 20 002. choice: sent: 012 F: 0.04997 df_1: 2 df_2: 20 003. choice: sent: 040 F: 0.07984 df_1: 2 df_2: 19 004. choice: sent: 059 F: 0.08080 df_1: 2 df_2: 18 005. choice: sent: 018 F: 0.10383 df_1: 2 df_2: 20 006. choice: sent: 016 F: 0.12291 df_1: 2 df_2: 20 007. choice: sent: 046 F: 0.16899 df_1: 2 df_2: 19 008. choice: sent: 053 F: 0.17923 df_1: 2 df_2: 19 009. choice: sent: 030 F: 0.18220 df_1: 2 df_2: 20 010. choice: sent: 025 F: 0.20802 df_1: 2 df_2: 19 011. choice: sent: 008 F: 0.21103 df_1: 2 df_2: 20 012. choice: sent: 060 F: 0.22867 df_1: 2 df_2: 19 013. choice: sent: 036 F: 0.23661 df_1: 2 df_2: 19 014. choice: sent: 055 F: 0.23804 df_1: 2 df_2: 19 015. choice: sent: 052 F: 0.26174 df_1: 2 df_2: 19 016. choice: sent: 051 F: 0.32628 df_1: 2 df_2: 19 017. choice: sent: 022 F: 0.33362 df_1: 2 df_2: 20 018. choice: sent: 028 F: 0.33442 df_1: 2 df_2: 20 019. choice: sent: 024 F: 0.35710 df_1: 2 df_2: 20 020. choice: sent: 037 F: 0.37688 df_1: 2 df_2: 19 021. choice: sent: 007 F: 0.42489 df_1: 2 df_2: 20 022. choice: sent: 026 F: 0.47815 df_1: 2 df_2: 20 023. choice: sent: 043 F: 0.47926 df_1: 2 df_2: 19 024. choice: sent: 045 F: 0.48994 df_1: 2 df_2: 19 025. choice: sent: 023 F: 0.50298 df_1: 2 df_2: 20 026. choice: sent: 058 F: 0.55146 df_1: 2 df_2: 19 027. choice: sent: 010 F: 0.55182 df_1: 2 df_2: 20 028. choice: sent: 009 F: 0.55613 df_1: 2 df_2: 20 029. choice: sent: 042 F: 0.61018 df_1: 2 df_2: 19 030. choice: sent: 050 F: 0.74891 df_1: 2 df_2: 19 031. choice: sent: 013 F: 0.76382 df_1: 2 df_2: 20 032. choice: sent: 032 F: 0.86130 df_1: 2 df_2: 20 033. choice: sent: 011 F: 0.90491 df_1: 2 df_2: 20 034. choice: sent: 002 F: 0.92326 df_1: 2 df_2: 20 035. choice: sent: 003 F: 0.99786 df_1: 2 df_2: 20 036. choice: sent: 061 F: 1.26364 df_1: 2 df_2: 18 037. choice: sent: 044 F: 1.27454 df_1: 2 df_2: 19 038. choice: sent: 034 F: 1.31180 df_1: 2 df_2: 19 039. choice: sent: 005 F: 1.50322 df_1: 2 df_2: 20 040. choice: sent: 054 F: 1.53113 df_1: 2 df_2: 19 041. choice: sent: 047 F: 1.58340 df_1: 2 df_2: 19 042. choice: sent: 017 F: 1.83654 df_1: 2 df_2: 20 043. choice: sent: 015 F: 1.87344 df_1: 2 df_2: 20 044. choice: sent: 049 F: 2.03608 df_1: 2 df_2: 19 045. choice: sent: 041 F: 2.06131 df_1: 2 df_2: 19 046. choice: sent: 006 F: 2.10377 df_1: 2 df_2: 20 047. choice: sent: 014 F: 2.17560 df_1: 2 df_2: 20 048. choice: sent: 056 F: 2.24626 df_1: 2 df_2: 19 049. choice: sent: 020 F: 2.36030 df_1: 2 df_2: 20 050. choice: sent: 048 F: 2.51819 df_1: 2 df_2: 19 051. choice: sent: 038 F: 2.58428 df_1: 2 df_2: 19 052. choice: sent: 031 F: 2.91388 df_1: 2 df_2: 20 053. choice: sent: 004 F: 2.92672 df_1: 2 df_2: 20 054. choice: sent: 027 F: 3.57748 df_1: 2 df_2: 20 055. choice: sent: 029 F: 3.59240 df_1: 2 df_2: 20 056. choice: sent: 057 F: 3.86240 df_1: 2 df_2: 18 057. choice: sent: 035 F: 4.47652 df_1: 2 df_2: 19 058. choice: sent: 019 F: 4.89797 df_1: 2 df_2: 20 059. choice: sent: 021 F: 5.00425 df_1: 2 df_2: 20 060. choice: sent: 001 F: 5.10671 df_1: 2 df_2: 20 061. choice: sent: 039 F: 6.17384 df_1: 2 df_2: 19