Построение регрессионной модели системы двух случайных величин
Номера, которые необходимо выбрать, для выполнения лабораторной работы №4 определяются с помощью двух последних цифр шифра студента +15 значений. Например, если две последние цифры шифра студента 22, то выбираем с 22 по 36 строку.
Значения Х выбираются всеми студентами со 2-го столбца (вес железобетонных перекрытий), значения У выбираем по первой букве фамилии.
Номер п/п | Вес железобетонных перекрытий кг/м кв | Длина плиты перекрытия, м А-Л | Время установки плиты перекрытия, час. М-Т | Стоимость строительно-монтажных работ, млн р. У-Я |
516,148 | 30,31 | 4,1 | 33,2 | |
512,475 | 30,4 | 4,185 | 32,8 | |
443,568 | 31,1 | 4,098 | 26,6 | |
510,058 | 30,35 | 4,19 | 32,6 | |
488,541 | 30,7 | 4,156 | 30,7 | |
541,694 | 30,1 | 4,225 | 35,5 | |
449,666 | 31,1 | 4,108 | 27,2 | |
472,208 | 30,9 | 3,95 | 29,2 | |
553,791 | 29,85 | 4,2 | 36,5 | |
507,401 | 30,45 | 4,18 | 32,4 | |
480,709 | 30,79 | 4,145 | ||
404,602 | 31,7 | 4,05 | 23,1 | |
468,393 | 31,1 | 4,13 | 28,9 | |
487,242 | 30,65 | 4,154 | 30,6 | |
400,322 | 31,8 | 4,04 | 22,7 | |
462,801 | 30,95 | 4,122 | 28,4 | |
429,344 | 31,35 | 4,274 | 25,3 | |
503,57 | 30,46 | 4,175 | ||
578,028 | 29,56 | 4,274 | 38,7 | |
475,214 | 3,97 | 29,5 | ||
611,563 | 29,2 | 4,32 | 41,7 | |
478,877 | 30,75 | 4,143 | 29,8 | |
514,042 | 30,33 | 4,189 | ||
585,644 | 29,47 | 4,285 | 39,4 | |
524,349 | 31,5 | 4,2 | 33,9 | |
500,753 | 30,5 | 4,17 | 31,8 | |
532,163 | 30,11 | 4,21 | 34,6 | |
529,632 | 30,2 | 4,3 | 34,4 | |
404,673 | 31,65 | 4,05 | 23,1 | |
405,141 | 31,64 | 4,05 | 23,2 | |
479,527 | 30,75 | 4,146 | 29,9 | |
473,668 | 30,9 | 4,137 | 29,3 | |
468,759 | 30,87 | 4,13 | 28,9 | |
439,92 | 31,22 | 4,09 | 26,3 | |
542,804 | 30,2 | 4,22 | 35,6 | |
507,974 | 30,4 | 4,181 | 32,4 | |
493,446 | 30,65 | 4,162 | 31,1 | |
520,758 | 30,3 | 4,2 | 33,6 | |
555,651 | 30,5 | 4,244 | 36,7 | |
354,368 | 32,25 | 3,987 | 18,6 | |
487,813 | 30,8 | 4,156 | 30,6 | |
559,046 | 4,25 | |||
519,484 | 30,27 | 4,2 | 33,5 | |
421,672 | 31,6 | 4,07 | 24,7 | |
479,017 | 30,75 | 4,143 | 29,8 | |
558,401 | 29,8 | 4,248 | ||
490,911 | 30,61 | 4,156 | 30,9 | |
467,798 | 30,95 | 4,128 | 28,8 | |
534,327 | 4,214 | 34,8 | ||
486,433 | 30,66 | 4,15 | 30,5 | |
513,547 | 30,34 | 4,19 | 32,9 | |
522,285 | 30,23 | 4,2 | 33,7 | |
533,934 | 29,5 | 4,22 | 34,8 | |
493,953 | 30,6 | 4,162 | 31,2 | |
436,678 | 31,7 | 4,09 | ||
455,322 | 31,05 | 4,01 | 27,7 | |
513,041 | 30,34 | 4,19 | 32,9 | |
506,337 | 30,42 | 4,18 | 32,3 | |
571,162 | 29,65 | 4,265 | 38,1 | |
473,051 | 30,82 | 4,136 | 29,3 | |
502,705 | 30,47 | 4,174 | 31,9 | |
522,44 | 31,2 | 4,2 | 33,7 | |
553,71 | 29,86 | 4,24 | 36,5 | |
30,1 | 4,238 | 36,3 | ||
523,344 | 30,22 | 4,2 | 33,8 | |
491,266 | 30,6 | 4,16 | 30,9 | |
532,988 | 30,1 | 4,2 | 34,7 | |
545,561 | 29,95 | 4,231 | 35,8 | |
519,683 | 30,26 | 4,19 | 33,5 | |
592,408 | 30,1 | 4,294 | ||
447,626 | 31,2 | 4,1 | ||
484,998 | 30,68 | 4,15 | 30,3 | |
603,083 | 29,7 | 4,31 | ||
530,224 | 30,14 | 4,21 | 34,4 | |
518,926 | 30,27 | 4,19 | 33,4 | |
471,808 | 30,84 | 4,137 | 29,2 | |
538,127 | 30,04 | 4,22 | 35,1 | |
504,49 | 30,45 | 4,18 | 32,1 | |
498,215 | 30,52 | 4,168 | 31,5 | |
457,645 | 31,01 | 4,214 | 27,9 | |
471,706 | 4,137 | 29,2 | ||
604,033 | 29,5 | 4,314 | 41,1 | |
435,876 | 31,27 | 4,09 | 25,9 | |
547,073 | 30,1 | 4,233 | 35,9 | |
488,658 | 30,64 | 4,156 | 30,7 | |
483,232 | 30,7 | 4,15 | 30,2 | |
525,513 | 30,2 | 4,21 | ||
437,864 | 31,25 | 4,09 | 26,1 | |
523,714 | 30,2 | 4,2 | 33,8 | |
615,479 | 29,1 | 4,325 | 42,1 | |
388,428 | 31,8 | 4,09 | 21,7 | |
421,66 | 31,44 | 4,07 | 24,6 | |
517,403 | 30,29 | 4,19 | 33,3 | |
575,794 | 30,1 | 4,271 | 38,5 | |
485,776 | 30,67 | 4,156 | 30,4 | |
497,492 | 30,53 | 4,167 | 31,5 | |
446,804 | 31,14 | 4,1 | 26,9 | |
475,051 | 30,8 | 4,138 | 29,5 | |
528,184 | 30,16 | 4,208 | 34,2 | |
545,557 | 30,9 | 4,234 | 35,8 |
ПРИЛОЖЕНИЕ А (справочное) Критические точки распределения Стьюдента
Степени свободы n | Уровень значимости a (односторонняя критическая область) | |||||||
0.2 | 0.1 | 0.05 | 0.025 | 0.01 | 0.005 | 0.001 | 0.0005 | |
1.376 | 3.078 | 6.314 | 12.706 | 31.821 | 63.656 | 318.29 | 636.58 | |
1.061 | 1.886 | 2.920 | 4.303 | 6.965 | 9.925 | 22.328 | 31.600 | |
0.978 | 1.638 | 2.353 | 3.182 | 4.541 | 5.841 | 10.214 | 12.924 | |
0.941 | 1.533 | 2.132 | 2.776 | 3.747 | 4.604 | 7.173 | 8.610 | |
0.920 | 1.476 | 2.015 | 2.571 | 3.365 | 4.032 | 5.894 | 6.869 | |
0.906 | 1.440 | 1.943 | 2.447 | 3.143 | 3.707 | 5.208 | 5.959 | |
0.896 | 1.415 | 1.895 | 2.365 | 2.998 | 3.499 | 4.785 | 5.408 | |
0.889 | 1.397 | 1.860 | 2.306 | 2.896 | 3.355 | 4.501 | 5.041 | |
0.883 | 1.383 | 1.833 | 2.262 | 2.821 | 3.250 | 4.297 | 4.781 | |
0.879 | 1.372 | 1.812 | 2.228 | 2.764 | 3.169 | 4.144 | 4.587 | |
0.876 | 1.363 | 1.796 | 2.201 | 2.718 | 3.106 | 4.025 | 4.437 | |
0.873 | 1.356 | 1.782 | 2.179 | 2.681 | 3.055 | 3.930 | 4.318 | |
0.870 | 1.350 | 1.771 | 2.160 | 2.650 | 3.012 | 3.852 | 4.221 | |
0.868 | 1.345 | 1.761 | 2.145 | 2.624 | 2.977 | 3.787 | 4.140 | |
0.866 | 1.341 | 1.753 | 2.131 | 2.602 | 2.947 | 3.733 | 4.073 | |
0.865 | 1.337 | 1.746 | 2.120 | 2.583 | 2.921 | 3.686 | 4.015 | |
0.863 | 1.333 | 1.740 | 2.110 | 2.567 | 2.898 | 3.646 | 3.965 | |
0.862 | 1.330 | 1.734 | 2.101 | 2.552 | 2.878 | 3.610 | 3.922 | |
0.861 | 1.328 | 1.729 | 2.093 | 2.539 | 2.861 | 3.579 | 3.883 | |
0.860 | 1.325 | 1.725 | 2.086 | 2.528 | 2.845 | 3.552 | 3.850 | |
0.859 | 1.323 | 1.721 | 2.080 | 2.518 | 2.831 | 3.527 | 3.819 | |
0.858 | 1.321 | 1.717 | 2.074 | 2.508 | 2.819 | 3.505 | 3.792 | |
0.858 | 1.319 | 1.714 | 2.069 | 2.500 | 2.807 | 3.485 | 3.768 | |
0.857 | 1.318 | 1.711 | 2.064 | 2.492 | 2.797 | 3.467 | 3.745 | |
0.856 | 1.316 | 1.708 | 2.060 | 2.485 | 2.787 | 3.450 | 3.725 | |
0.856 | 1.315 | 1.706 | 2.056 | 2.479 | 2.779 | 3.435 | 3.707 | |
0.855 | 1.314 | 1.703 | 2.052 | 2.473 | 2.771 | 3.421 | 3.689 | |
0.855 | 1.313 | 1.701 | 2.048 | 2.467 | 2.763 | 3.408 | 3.674 | |
0.854 | 1.311 | 1.699 | 2.045 | 2.462 | 2.756 | 3.396 | 3.660 | |
0.854 | 1.310 | 1.697 | 2.042 | 2.457 | 2.750 | 3.385 | 3.646 | |
0.851 | 1.303 | 1.684 | 2.021 | 2.423 | 2.704 | 3.307 | 3.551 | |
0.849 | 1.299 | 1.676 | 2.009 | 2.403 | 2.678 | 3.261 | 3.496 | |
0.848 | 1.296 | 1.671 | 2.000 | 2.390 | 2.660 | 3.232 | 3.460 | |
0.847 | 1.294 | 1.667 | 1.994 | 2.381 | 2.648 | 3.211 | 3.435 | |
0.846 | 1.292 | 1.664 | 1.990 | 2.374 | 2.639 | 3.195 | 3.416 | |
0.846 | 1.291 | 1.662 | 1.987 | 2.368 | 2.632 | 3.183 | 3.402 | |
0.845 | 1.290 | 1.660 | 1.984 | 2.364 | 2.626 | 3.174 | 3.390 | |
0.844 | 1.287 | 1.655 | 1.976 | 2.351 | 2.609 | 3.145 | 3.357 | |
0.843 | 1.286 | 1.653 | 1.972 | 2.345 | 2.601 | 3.131 | 3.340 | |
0.842 | 1.283 | 1.648 | 1.965 | 2.334 | 2.586 | 3.107 | 3.310 | |
¥ | 0.842 | 1.282 | 1.645 | 1.960 | 2.326 | 2.576 | 3.090 | 3.290 |
Степени свободы | 0.4 | 0.2 | 0.1 | 0.05 | 0.02 | 0.01 | 0.002 | 0.001 |
n | Уровень значимости a (двусторонняя критическая область) |
ПРИЛОЖЕНИЕ Б (справочное) Критические точки распределения Фишера
(число степеней свободы бóльшей дисперсии – n1. меньшей – n2)
Уровень значимости a = 0.05 | ||||||||||||
n2 | n1 | |||||||||||
¥ | ||||||||||||
161.45 | 199.50 | 215.71 | 224.58 | 230.16 | 233.99 | 238.88 | 243.90 | 246.47 | 249.05 | 251.77 | 254.31 | |
18.513 | 19.000 | 19.164 | 19.247 | 19.296 | 19.329 | 19.371 | 19.412 | 19.433 | 19.454 | 19.476 | 19.496 | |
10.128 | 9.552 | 9.277 | 9.117 | 9.013 | 8.941 | 8.845 | 8.745 | 8.692 | 8.638 | 8.581 | 8.526 | |
7.709 | 6.944 | 6.591 | 6.388 | 6.256 | 6.163 | 6.041 | 5.912 | 5.844 | 5.774 | 5.699 | 5.628 | |
6.608 | 5.786 | 5.409 | 5.192 | 5.050 | 4.950 | 4.818 | 4.678 | 4.604 | 4.527 | 4.444 | 4.365 | |
5.987 | 5.143 | 4.757 | 4.534 | 4.387 | 4.284 | 4.147 | 4.000 | 3.922 | 3.841 | 3.754 | 3.669 | |
5.591 | 4.737 | 4.347 | 4.120 | 3.972 | 3.866 | 3.726 | 3.575 | 3.494 | 3.410 | 3.319 | 3.230 | |
5.318 | 4.459 | 4.066 | 3.838 | 3.688 | 3.581 | 3.438 | 3.284 | 3.202 | 3.115 | 3.020 | 2.928 | |
5.117 | 4.256 | 3.863 | 3.633 | 3.482 | 3.374 | 3.230 | 3.073 | 2.989 | 2.900 | 2.803 | 2.707 | |
4.965 | 4.103 | 3.708 | 3.478 | 3.326 | 3.217 | 3.072 | 2.913 | 2.828 | 2.737 | 2.637 | 2.538 | |
4.844 | 3.982 | 3.587 | 3.357 | 3.204 | 3.095 | 2.948 | 2.788 | 2.701 | 2.609 | 2.507 | 2.404 | |
4.747 | 3.885 | 3.490 | 3.259 | 3.106 | 2.996 | 2.849 | 2.687 | 2.599 | 2.505 | 2.401 | 2.296 | |
4.667 | 3.806 | 3.411 | 3.179 | 3.025 | 2.915 | 2.767 | 2.604 | 2.515 | 2.420 | 2.314 | 2.206 | |
4.600 | 3.739 | 3.344 | 3.112 | 2.958 | 2.848 | 2.699 | 2.534 | 2.445 | 2.349 | 2.241 | 2.131 | |
4.543 | 3.682 | 3.287 | 3.056 | 2.901 | 2.790 | 2.641 | 2.475 | 2.385 | 2.288 | 2.178 | 2.066 | |
4.494 | 3.634 | 3.239 | 3.007 | 2.852 | 2.741 | 2.591 | 2.425 | 2.333 | 2.235 | 2.124 | 2.010 | |
4.451 | 3.592 | 3.197 | 2.965 | 2.810 | 2.699 | 2.548 | 2.381 | 2.289 | 2.190 | 2.077 | 1.960 | |
4.414 | 3.555 | 3.160 | 2.928 | 2.773 | 2.661 | 2.510 | 2.342 | 2.250 | 2.150 | 2.035 | 1.917 | |
4.381 | 3.522 | 3.127 | 2.895 | 2.740 | 2.628 | 2.477 | 2.308 | 2.215 | 2.114 | 1.999 | 1.878 | |
4.351 | 3.493 | 3.098 | 2.866 | 2.711 | 2.599 | 2.447 | 2.278 | 2.184 | 2.082 | 1.966 | 1.843 | |
4.325 | 3.467 | 3.072 | 2.840 | 2.685 | 2.573 | 2.420 | 2.250 | 2.156 | 2.054 | 1.936 | 1.812 | |
4.301 | 3.443 | 3.049 | 2.817 | 2.661 | 2.549 | 2.397 | 2.226 | 2.131 | 2.028 | 1.909 | 1.783 | |
4.279 | 3.422 | 3.028 | 2.796 | 2.640 | 2.528 | 2.375 | 2.204 | 2.109 | 2.005 | 1.885 | 1.757 | |
4.260 | 3.403 | 3.009 | 2.776 | 2.621 | 2.508 | 2.355 | 2.183 | 2.088 | 1.984 | 1.863 | 1.733 | |
4.242 | 3.385 | 2.991 | 2.759 | 2.603 | 2.490 | 2.337 | 2.165 | 2.069 | 1.964 | 1.842 | 1.711 | |
4.225 | 3.369 | 2.975 | 2.743 | 2.587 | 2.474 | 2.321 | 2.148 | 2.052 | 1.946 | 1.823 | 1.691 | |
4.210 | 3.354 | 2.960 | 2.728 | 2.572 | 2.459 | 2.305 | 2.132 | 2.036 | 1.930 | 1.806 | 1.672 | |
4.196 | 3.340 | 2.947 | 2.714 | 2.558 | 2.445 | 2.291 | 2.118 | 2.021 | 1.915 | 1.790 | 1.654 | |
4.183 | 3.328 | 2.934 | 2.701 | 2.545 | 2.432 | 2.278 | 2.104 | 2.007 | 1.901 | 1.775 | 1.638 | |
4.171 | 3.316 | 2.922 | 2.690 | 2.534 | 2.421 | 2.266 | 2.092 | 1.995 | 1.887 | 1.761 | 1.622 | |
4.085 | 3.232 | 2.839 | 2.606 | 2.449 | 2.336 | 2.180 | 2.003 | 1.904 | 1.793 | 1.660 | 1.509 | |
4.034 | 3.183 | 2.790 | 2.557 | 2.400 | 2.286 | 2.130 | 1.952 | 1.850 | 1.737 | 1.599 | 1.438 | |
4.001 | 3.150 | 2.758 | 2.525 | 2.368 | 2.254 | 2.097 | 1.917 | 1.815 | 1.700 | 1.559 | 1.389 | |
3.978 | 3.128 | 2.736 | 2.503 | 2.346 | 2.231 | 2.074 | 1.893 | 1.790 | 1.674 | 1.530 | 1.353 | |
3.960 | 3.111 | 2.719 | 2.486 | 2.329 | 2.214 | 2.056 | 1.875 | 1.772 | 1.654 | 1.508 | 1.325 | |
3.947 | 3.098 | 2.706 | 2.473 | 2.316 | 2.201 | 2.043 | 1.861 | 1.757 | 1.639 | 1.491 | 1.302 | |
3.936 | 3.087 | 2.696 | 2.463 | 2.305 | 2.191 | 2.032 | 1.850 | 1.746 | 1.627 | 1.477 | 1.283 | |
3.904 | 3.056 | 2.665 | 2.432 | 2.274 | 2.160 | 2.001 | 1.817 | 1.711 | 1.590 | 1.436 | 1.223 | |
3.888 | 3.041 | 2.650 | 2.417 | 2.259 | 2.144 | 1.985 | 1.801 | 1.694 | 1.572 | 1.415 | 1.189 | |
3.860 | 3.014 | 2.623 | 2.390 | 2.232 | 2.117 | 1.957 | 1.772 | 1.664 | 1.539 | 1.376 | 1.113 | |
¥ | 3.841 | 2.996 | 2.605 | 2.372 | 2.214 | 2.099 | 1.938 | 1.752 | 1.644 | 1.517 | 1.350 | 1.000 |
Продолжение приложения Б
Уровень значимости a = 0.01 | ||||||||||||
n2 | n1 | |||||||||||
¥ | ||||||||||||
4052.2 | 4999.3 | 5403.5 | 5624.3 | 5764.0 | 5859.0 | 5981.0 | 6106.7 | 6170.0 | 6234.3 | 6302.3 | 6365.6 | |
98.502 | 99.000 | 99.164 | 99.251 | 99.302 | 99.331 | 99.375 | 99.419 | 99.437 | 99.455 | 99.477 | 99.499 | |
34.116 | 30.816 | 29.457 | 28.710 | 28.237 | 27.911 | 27.489 | 27.052 | 26.826 | 26.597 | 26.354 | 26.125 | |
21.198 | 18.000 | 16.694 | 15.977 | 15.522 | 15.207 | 14.799 | 14.374 | 14.154 | 13.929 | 13.690 | 13.463 | |
16.258 | 13.274 | 12.060 | 11.392 | 10.967 | 10.672 | 10.289 | 9.888 | 9.680 | 9.466 | 9.238 | 9.020 | |
13.745 | 10.925 | 9.780 | 9.148 | 8.746 | 8.466 | 8.102 | 7.718 | 7.519 | 7.313 | 7.091 | 6.880 | |
12.246 | 9.547 | 8.451 | 7.847 | 7.460 | 7.191 | 6.840 | 6.469 | 6.275 | 6.074 | 5.858 | 5.650 | |
11.259 | 8.649 | 7.591 | 7.006 | 6.632 | 6.371 | 6.029 | 5.667 | 5.477 | 5.279 | 5.065 | 4.859 | |
10.562 | 8.022 | 6.992 | 6.422 | 6.057 | 5.802 | 5.467 | 5.111 | 4.924 | 4.729 | 4.517 | 4.311 | |
10.044 | 7.559 | 6.552 | 5.994 | 5.636 | 5.386 | 5.057 | 4.706 | 4.520 | 4.327 | 4.115 | 3.909 | |
9.646 | 7.206 | 6.217 | 5.668 | 5.316 | 5.069 | 4.744 | 4.397 | 4.213 | 4.021 | 3.810 | 3.602 | |
9.330 | 6.927 | 5.953 | 5.412 | 5.064 | 4.821 | 4.499 | 4.155 | 3.972 | 3.780 | 3.569 | 3.361 | |
9.074 | 6.701 | 5.739 | 5.205 | 4.862 | 4.620 | 4.302 | 3.960 | 3.778 | 3.587 | 3.375 | 3.165 | |
8.862 | 6.515 | 5.564 | 5.035 | 4.695 | 4.456 | 4.140 | 3.800 | 3.619 | 3.427 | 3.215 | 3.004 | |
8.683 | 6.359 | 5.417 | 4.893 | 4.556 | 4.318 | 4.004 | 3.666 | 3.485 | 3.294 | 3.081 | 2.868 | |
8.531 | 6.226 | 5.292 | 4.773 | 4.437 | 4.202 | 3.890 | 3.553 | 3.372 | 3.181 | 2.967 | 2.753 | |
8.400 | 6.112 | 5.185 | 4.669 | 4.336 | 4.101 | 3.791 | 3.455 | 3.275 | 3.083 | 2.869 | 2.653 | |
8.285 | 6.013 | 5.092 | 4.579 | 4.248 | 4.015 | 3.705 | 3.371 | 3.190 | 2.999 | 2.784 | 2.566 | |
8.185 | 5.926 | 5.010 | 4.500 | 4.171 | 3.939 | 3.631 | 3.297 | 3.116 | 2.925 | 2.709 | 2.489 | |
8.096 | 5.849 | 4.938 | 4.431 | 4.103 | 3.871 | 3.564 | 3.231 | 3.051 | 2.859 | 2.643 | 2.421 | |
7.945 | 5.719 | 4.817 | 4.313 | 3.988 | 3.758 | 3.453 | 3.121 | 2.941 | 2.749 | 2.531 | 2.305 | |
7.823 | 5.614 | 4.718 | 4.218 | 3.895 | 3.667 | 3.363 | 3.032 | 2.852 | 2.659 | 2.440 | 2.211 | |
7.636 | 5.453 | 4.568 | 4.074 | 3.754 | 3.528 | 3.226 | 2.896 | 2.716 | 2.522 | 2.300 | 2.064 | |
7.562 | 5.390 | 4.510 | 4.018 | 3.699 | 3.473 | 3.173 | 2.843 | 2.663 | 2.469 | 2.245 | 2.006 | |
7.314 | 5.178 | 4.313 | 3.828 | 3.514 | 3.291 | 2.993 | 2.665 | 2.484 | 2.288 | 2.058 | 1.805 | |
7.171 | 5.057 | 4.199 | 3.720 | 3.408 | 3.186 | 2.890 | 2.563 | 2.382 | 2.183 | 1.949 | 1.683 | |
7.077 | 4.977 | 4.126 | 3.649 | 3.339 | 3.119 | 2.823 | 2.496 | 2.315 | 2.115 | 1.877 | 1.601 | |
7.011 | 4.922 | 4.074 | 3.600 | 3.291 | 3.071 | 2.777 | 2.450 | 2.268 | 2.067 | 1.826 | 1.540 | |
6.963 | 4.881 | 4.036 | 3.563 | 3.255 | 3.036 | 2.742 | 2.415 | 2.233 | 2.032 | 1.788 | 1.494 | |
6.925 | 4.849 | 4.007 | 3.535 | 3.228 | 3.009 | 2.715 | 2.389 | 2.206 | 2.004 | 1.759 | 1.457 | |
6.895 | 4.824 | 3.984 | 3.513 | 3.206 | 2.988 | 2.694 | 2.368 | 2.185 | 1.983 | 1.735 | 1.427 | |
6.807 | 4.749 | 3.915 | 3.447 | 3.142 | 2.924 | 2.632 | 2.305 | 2.122 | 1.918 | 1.665 | 1.331 | |
6.763 | 4.713 | 3.881 | 3.414 | 3.110 | 2.893 | 2.601 | 2.275 | 2.091 | 1.886 | 1.629 | 1.279 | |
6.686 | 4.648 | 3.821 | 3.357 | 3.054 | 2.838 | 2.547 | 2.220 | 2.036 | 1.829 | 1.566 | 1.164 | |
¥ | 6.635 | 4.605 | 3.782 | 3.319 | 3.017 | 2.802 | 2.511 | 2.185 | 2.000 | 1.791 | 1.523 | 1.000 |
Multiple Regression - A.Col_2
Dependent variable: A.Col_2
Independent variables:
A.Col_3
Standard | T | |||
Parameter | Estimate | Error | Statistic | P-Value |
CONSTANT | 3439,34 | 147,937 | 23,2486 | 0,0000 |
A.Col_3 | -96,2044 | 4,85659 | -19,809 | 0,0000 |
Analysis of Variance
Source | Sum of Squares | Df | Mean Square | F-Ratio | P-Value |
Model | 32211,1 | 32211,1 | 392,40 | 0,0000 | |
Residual | 1067,14 | 82,0879 | |||
Total (Corr.) | 33278,2 |
R-squared = 96,7933 percent
R-squared (adjusted for d.f.) = 96,5466 percent
Standard Error of Est. = 9,06024
Mean absolute error = 6,45345
Durbin-Watson statistic = 1,98052 (P=0,5328)
Lag 1 residual autocorrelation = 0,00286229
The StatAdvisor
The output shows the results of fitting a multiple linear regression model to describe the relationship between A.Col_2 and 1 independent variables. The equation of the fitted model is
A.Col_2 = 3439,34 - 96,2044*A.Col_3
Since the P-value in the ANOVA table is less than 0,05, there is a statistically significant relationship between the variables at the 95,0% confidence level.
The R-Squared statistic indicates that the model as fitted explains 96,7933% of the variability in A.Col_2. The adjusted R-squared statistic, which is more suitable for comparing models with different numbers of independent variables, is 96,5466%. The standard error of the estimate shows the standard deviation of the residuals to be 9,06024. This value can be used to construct prediction limits for new observations by selecting the Reports option from the text menu. The mean absolute error (MAE) of 6,45345 is the average value of the residuals. The Durbin-Watson (DW) statistic tests the residuals to determine if there is any significant correlation based on the order in which they occur in your data file. Since the P-value is greater than 0,05, there is no indication of serial autocorrelation in the residuals at the 95,0% confidence level.
In determining whether the model can be simplified, notice that the highest P-value on the independent variables is 0,0000, belonging to A.Col_3. Since the P-value is less than 0,05, that term is statistically significant at the 95,0% confidence level. Consequently, you probably don't want to remove any variables from the model.