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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationMon, 14 Dec 2015 12:18:08 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/14/t1450095504zcgc71b0ccc9ahi.htm/, Retrieved Thu, 16 May 2024 08:34:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286279, Retrieved Thu, 16 May 2024 08:34:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2015-12-14 12:18:08] [5b06bf1f33fbfa9d6fb3148fdcb0ae6c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 119.992 74.997 0.00007 21.033 0.414783 -4.813031 0.266482 0.284654
1 122.4 113.819 0.00008 19.085 0.458359 -4.075192 0.33559 0.368674
1 116.682 111.555 0.00009 20.651 0.429895 -4.443179 0.311173 0.332634
1 116.676 111.366 0.00009 20.644 0.434969 -4.117501 0.334147 0.368975
1 116.014 110.655 0.00011 19.649 0.417356 -3.747787 0.234513 0.410335
1 120.552 113.787 0.00008 21.378 0.415564 -4.242867 0.299111 0.357775
1 120.267 114.82 0.00003 24.886 0.59604 -5.634322 0.257682 0.211756
1 107.332 104.315 0.00003 26.892 0.63742 -6.167603 0.183721 0.163755
1 95.73 91.754 0.00006 21.812 0.615551 -5.498678 0.327769 0.231571
1 95.056 91.226 0.00006 21.862 0.547037 -5.011879 0.325996 0.271362
1 88.333 84.072 0.00006 21.118 0.611137 -5.24977 0.391002 0.24974
1 91.904 86.292 0.00006 21.414 0.58339 -4.960234 0.363566 0.275931
1 136.926 131.276 0.00002 25.703 0.4606 -6.547148 0.152813 0.138512
1 139.173 76.556 0.00003 24.889 0.430166 -5.660217 0.254989 0.199889
1 152.845 75.836 0.00002 24.922 0.474791 -6.105098 0.203653 0.1701
1 142.167 83.159 0.00003 25.175 0.565924 -5.340115 0.210185 0.234589
1 144.188 82.764 0.00004 22.333 0.56738 -5.44004 0.239764 0.218164
1 168.778 75.603 0.00004 20.376 0.631099 -2.93107 0.434326 0.430788
1 153.046 68.623 0.00005 17.28 0.665318 -3.949079 0.35787 0.377429
1 156.405 142.822 0.00005 17.153 0.649554 -4.554466 0.340176 0.322111
1 153.848 65.782 0.00005 17.536 0.660125 -4.095442 0.262564 0.365391
1 153.88 78.128 0.00003 19.493 0.629017 -5.18696 0.237622 0.259765
1 167.93 79.068 0.00003 22.468 0.61906 -4.330956 0.262384 0.285695
1 173.917 86.18 0.00003 20.422 0.537264 -5.248776 0.210279 0.253556
1 163.656 76.779 0.00005 23.831 0.397937 -5.557447 0.22089 0.215961
1 104.4 77.968 0.00006 22.066 0.522746 -5.571843 0.236853 0.219514
1 171.041 75.501 0.00003 25.908 0.418622 -6.18359 0.226278 0.147403
1 146.845 81.737 0.00003 25.119 0.358773 -6.27169 0.196102 0.162999
1 155.358 80.055 0.00002 25.97 0.470478 -7.120925 0.279789 0.108514
1 162.568 77.63 0.00003 25.678 0.427785 -6.635729 0.209866 0.135242
0 197.076 192.055 0.00001 26.775 0.422229 -7.3483 0.177551 0.085569
0 199.228 192.091 0.00001 30.94 0.432439 -7.682587 0.173319 0.068501
0 198.383 193.104 0.00001 30.775 0.465946 -7.067931 0.175181 0.09632
0 202.266 197.079 0.000009 32.684 0.368535 -7.695734 0.17854 0.056141
0 203.184 196.16 0.000009 33.047 0.340068 -7.964984 0.163519 0.044539
0 201.464 195.708 0.00001 31.732 0.344252 -7.777685 0.170183 0.05761
1 177.876 168.013 0.00002 23.216 0.360148 -6.149653 0.218037 0.165827
1 176.17 163.564 0.00002 24.951 0.341435 -6.006414 0.196371 0.173218
1 180.198 175.456 0.00002 26.738 0.403884 -6.452058 0.212294 0.141929
1 187.733 173.015 0.00002 26.31 0.396793 -6.006647 0.266892 0.160691
1 186.163 177.584 0.00002 26.822 0.32648 -6.647379 0.201095 0.130554
1 184.055 166.977 0.00001 26.453 0.306443 -7.044105 0.063412 0.11573
0 237.226 225.227 0.00001 22.736 0.305062 -7.31055 0.098648 0.095032
0 241.404 232.483 0.00001 23.145 0.457702 -6.793547 0.158266 0.117399
0 243.439 232.435 0.000009 25.368 0.438296 -7.057869 0.091608 0.09147
0 242.852 227.911 0.000009 25.032 0.431285 -6.99582 0.102083 0.102706
0 245.51 231.848 0.00001 24.602 0.467489 -7.156076 0.127642 0.097336
0 252.455 182.786 0.000007 26.805 0.610367 -7.31951 0.200873 0.086398
0 122.188 115.765 0.00004 23.162 0.579597 -6.439398 0.266392 0.133867
0 122.964 114.676 0.00003 24.971 0.538688 -6.482096 0.264967 0.128872
0 124.445 117.495 0.00003 25.135 0.553134 -6.650471 0.254498 0.103561
0 126.344 112.773 0.00004 25.03 0.507504 -6.689151 0.291954 0.105993
0 128.001 122.08 0.00003 24.692 0.459766 -7.072419 0.220434 0.119308
0 129.336 118.604 0.00004 25.429 0.420383 -6.836811 0.269866 0.147491
1 108.807 102.874 0.00007 21.028 0.536009 -4.649573 0.205558 0.3167
1 109.86 104.437 0.00008 20.767 0.558586 -4.333543 0.221727 0.344834
1 110.417 103.37 0.00007 21.422 0.541781 -4.438453 0.238298 0.335041
1 117.274 110.402 0.00006 22.817 0.530529 -4.60826 0.290024 0.314464
1 116.879 108.153 0.00007 22.603 0.540049 -4.476755 0.262633 0.326197
1 114.847 104.68 0.00008 21.66 0.547975 -4.609161 0.221711 0.316395
0 209.144 109.379 0.00001 25.554 0.341788 -7.040508 0.066994 0.101516
0 223.365 98.664 0.00001 26.138 0.447979 -7.293801 0.086372 0.098555
0 222.236 205.495 0.00001 25.856 0.364867 -6.966321 0.095882 0.103224
0 228.832 223.634 0.00001 25.964 0.25657 -7.24562 0.018689 0.093534
0 229.401 221.156 0.000009 26.415 0.27685 -7.496264 0.056844 0.073581
0 228.969 113.201 0.00001 24.547 0.305429 -7.314237 0.006274 0.091546
1 140.341 67.021 0.00006 19.56 0.460139 -5.409423 0.22685 0.226156
1 136.969 66.004 0.00007 19.979 0.498133 -5.324574 0.20566 0.226247
1 143.533 65.809 0.00008 20.338 0.513237 -5.86975 0.151814 0.18558
1 148.09 67.343 0.00005 21.718 0.487407 -6.261141 0.120956 0.141958
1 142.729 65.476 0.00006 20.264 0.489345 -5.720868 0.15883 0.180828
1 136.358 65.75 0.00007 18.57 0.543299 -5.207985 0.224852 0.242981
1 120.08 111.208 0.00003 25.742 0.495954 -5.79182 0.329066 0.18818
1 112.014 107.024 0.00005 24.178 0.509127 -5.389129 0.306636 0.225461
1 110.793 107.316 0.00004 25.438 0.437031 -5.31336 0.201861 0.244512
1 110.707 105.007 0.00005 25.197 0.463514 -5.477592 0.315074 0.228624
1 112.876 106.981 0.00004 23.37 0.489538 -5.775966 0.341169 0.193918
1 110.568 106.821 0.00004 25.82 0.429484 -5.391029 0.250572 0.232744
1 95.385 90.264 0.00006 21.875 0.644954 -5.115212 0.249494 0.260015
1 100.77 85.545 0.0001 19.2 0.594387 -4.913885 0.265699 0.277948
1 96.106 84.51 0.00007 19.055 0.544805 -4.441519 0.155097 0.327978
1 95.605 87.549 0.00007 19.659 0.576084 -5.132032 0.210458 0.260633
1 100.96 95.628 0.00006 20.536 0.55461 -5.022288 0.146948 0.264666
1 98.804 87.804 0.00004 22.244 0.576644 -6.025367 0.078202 0.177275
1 176.858 75.344 0.00004 13.893 0.556494 -5.288912 0.343073 0.242119
1 180.978 155.495 0.00002 16.176 0.583574 -5.657899 0.315903 0.200423
1 178.222 141.047 0.00002 15.924 0.598714 -6.366916 0.335753 0.144614
1 176.281 125.61 0.00003 13.922 0.602874 -5.515071 0.299549 0.220968
1 173.898 74.677 0.00003 14.739 0.599371 -5.783272 0.299793 0.194052
1 179.711 144.878 0.00004 11.866 0.590951 -4.379411 0.375531 0.332086
1 166.605 78.032 0.00004 11.744 0.65341 -4.508984 0.389232 0.301952
1 151.955 147.226 0.00003 19.664 0.501037 -6.411497 0.207156 0.13412
1 148.272 142.299 0.00003 18.78 0.454444 -5.952058 0.08784 0.186489
1 152.125 76.596 0.00003 20.969 0.447456 -6.152551 0.17352 0.160809
1 157.821 68.401 0.00002 22.219 0.50238 -6.251425 0.188056 0.160812
1 157.447 149.605 0.00002 21.693 0.447285 -6.247076 0.180528 0.164916
1 159.116 144.811 0.00002 22.663 0.366329 -6.41744 0.194627 0.151709
1 125.036 116.187 0.0001 15.338 0.629574 -4.020042 0.265315 0.340623
1 125.791 96.206 0.00011 15.433 0.57101 -5.159169 0.202146 0.260375
1 126.512 99.77 0.00015 12.435 0.638545 -3.760348 0.242861 0.378483
1 125.641 116.346 0.00026 8.867 0.671299 -3.700544 0.260481 0.370961
1 128.451 75.632 0.00012 15.06 0.639808 -4.20273 0.310163 0.356881
1 139.224 66.157 0.00022 10.489 0.596362 -3.269487 0.270641 0.444774
1 150.258 75.349 0.00002 26.759 0.296888 -6.878393 0.089267 0.113942
1 154.003 128.621 0.00001 28.409 0.263654 -7.111576 0.14478 0.093193
1 149.689 133.608 0.00002 27.421 0.365488 -6.997403 0.210279 0.112878
1 155.078 144.148 0.00001 29.746 0.334171 -6.981201 0.18455 0.106802
1 151.884 133.751 0.00002 26.833 0.393563 -6.600023 0.249172 0.105306
1 151.989 132.857 0.00001 29.928 0.311369 -6.739151 0.160686 0.11513
1 193.03 80.297 0.00004 21.934 0.497554 -5.845099 0.278679 0.185668
1 200.714 89.686 0.00003 23.239 0.436084 -5.25832 0.256454 0.23252
1 208.519 199.02 0.00003 22.407 0.338097 -6.471427 0.184378 0.13639
1 204.664 189.621 0.00004 21.305 0.498877 -4.876336 0.212054 0.268144
1 210.141 185.258 0.00003 23.671 0.441097 -5.96304 0.250283 0.177807
1 206.327 92.02 0.00002 21.864 0.331508 -6.729713 0.181701 0.115515
1 151.872 69.085 0.00006 23.693 0.407701 -4.673241 0.261549 0.274407
1 158.219 71.948 0.00003 26.356 0.450798 -6.051233 0.27328 0.170106
1 170.756 79.032 0.00003 25.69 0.486738 -4.597834 0.372114 0.28278
1 178.285 82.063 0.00003 25.02 0.470422 -4.913137 0.393056 0.251972
1 217.116 93.978 0.00002 24.581 0.462516 -5.517173 0.389295 0.220657
1 128.94 88.251 0.00005 24.743 0.487756 -6.186128 0.279933 0.152428
1 176.824 83.961 0.00003 27.166 0.400088 -4.711007 0.281618 0.234809
1 138.19 83.34 0.00005 18.305 0.538016 -5.418787 0.160267 0.229892
1 182.018 79.187 0.00005 18.784 0.589956 -5.44514 0.142466 0.215558
1 156.239 79.82 0.00004 19.196 0.618663 -5.944191 0.143359 0.181988
1 145.174 80.637 0.00005 18.857 0.637518 -5.594275 0.12795 0.222716
1 138.145 81.114 0.00004 18.178 0.623209 -5.540351 0.087165 0.214075
1 166.888 79.512 0.00004 18.33 0.585169 -5.825257 0.115697 0.196535
1 119.031 109.216 0.00004 26.842 0.457541 -6.890021 0.152941 0.112856
1 120.078 105.667 0.00002 26.369 0.491345 -5.892061 0.195976 0.183572
1 120.289 100.209 0.00004 23.949 0.46716 -6.135296 0.20363 0.169923
1 120.256 104.773 0.00003 26.017 0.468621 -6.112667 0.217013 0.170633
1 119.056 86.795 0.00003 23.389 0.470972 -5.436135 0.254909 0.232209
1 118.747 109.836 0.00003 25.619 0.482296 -6.448134 0.178713 0.141422
1 106.516 93.105 0.00006 17.06 0.637814 -5.301321 0.320385 0.24308
1 110.453 105.554 0.00004 17.707 0.653427 -5.333619 0.322044 0.228319
1 113.4 107.816 0.00004 19.013 0.6479 -4.378916 0.300067 0.259451
1 113.166 100.673 0.00004 16.747 0.625362 -4.654894 0.304107 0.274387
1 112.239 104.095 0.00004 17.366 0.640945 -5.634576 0.306014 0.209191
1 116.15 109.815 0.00003 18.801 0.624811 -5.866357 0.23307 0.184985
1 170.368 79.543 0.00003 18.54 0.677131 -4.796845 0.397749 0.277227
1 208.083 91.802 0.00004 15.648 0.606344 -5.410336 0.288917 0.231723
1 198.458 148.691 0.00002 18.702 0.606273 -5.585259 0.310746 0.209863
1 202.805 86.232 0.00002 18.687 0.536102 -5.898673 0.213353 0.189032
1 202.544 164.168 0.00001 20.68 0.49748 -6.132663 0.220617 0.159777
1 223.361 87.638 0.00002 20.366 0.566849 -5.456811 0.345238 0.232861
1 169.774 151.451 0.00009 12.359 0.56161 -3.297668 0.414758 0.457533
1 183.52 161.34 0.00008 14.367 0.478024 -4.276605 0.355736 0.336085
1 188.62 165.982 0.00009 12.298 0.55287 -3.377325 0.335357 0.418646
1 202.632 177.258 0.00008 14.989 0.427627 -4.892495 0.262281 0.270173
1 186.695 149.442 0.0001 12.529 0.507826 -4.484303 0.340256 0.301487
1 192.818 168.793 0.00016 8.441 0.625866 -2.434031 0.450493 0.527367
1 198.116 174.478 0.00014 9.449 0.584164 -2.839756 0.356224 0.454721
1 121.345 98.25 0.00006 21.52 0.566867 -4.865194 0.246404 0.168581
1 119.1 88.833 0.00006 21.824 0.65168 -4.239028 0.175691 0.247455
1 117.87 95.654 0.00005 22.431 0.6283 -3.583722 0.207914 0.206256
1 122.336 94.794 0.00006 22.953 0.611679 -5.4351 0.230532 0.220546
1 117.963 100.757 0.00015 19.075 0.630547 -3.444478 0.303214 0.261305
1 126.144 97.543 0.00008 21.534 0.635015 -5.070096 0.280091 0.249703
1 127.93 112.173 0.00005 19.651 0.654945 -5.498456 0.234196 0.216638
1 114.238 77.022 0.00005 20.437 0.653139 -5.185987 0.259229 0.244948
1 115.322 107.802 0.00005 19.388 0.577802 -5.283009 0.226528 0.238281
1 114.554 91.121 0.00006 18.954 0.685151 -5.529833 0.24275 0.22052
1 112.15 97.527 0.00005 21.219 0.557045 -5.617124 0.184896 0.212386
1 102.273 85.902 0.00009 18.447 0.671378 -2.929379 0.396746 0.367233
0 236.2 102.137 0.00001 24.078 0.469928 -6.816086 0.17227 0.119652
0 237.323 229.256 0.00001 24.679 0.384868 -7.018057 0.176316 0.091604
0 260.105 237.303 0.00001 21.083 0.440988 -7.517934 0.160414 0.075587
0 197.569 90.794 0.00004 19.269 0.372222 -5.736781 0.164529 0.202879
0 240.301 219.783 0.00002 21.02 0.371837 -7.169701 0.073298 0.100881
0 244.99 239.17 0.00002 21.528 0.522812 -7.3045 0.171088 0.09622
0 112.547 105.715 0.00003 26.436 0.413295 -6.323531 0.218885 0.160376
0 110.739 100.139 0.00003 26.55 0.36909 -6.085567 0.192375 0.174152
0 113.715 96.913 0.00003 26.547 0.380253 -5.943501 0.19215 0.179677
0 117.004 99.923 0.00003 25.445 0.387482 -6.012559 0.229298 0.163118
0 115.38 108.634 0.00003 26.005 0.405991 -5.966779 0.197938 0.184067
0 116.388 108.97 0.00003 26.143 0.361232 -6.016891 0.109256 0.174429
1 151.737 129.859 0.00002 24.151 0.39661 -6.486822 0.197919 0.132703
1 148.79 138.99 0.00002 24.412 0.402591 -6.311987 0.182459 0.160306
1 148.143 135.041 0.00003 23.683 0.398499 -5.711205 0.240875 0.19273
1 150.44 144.736 0.00003 23.133 0.352396 -6.261446 0.183218 0.144105
1 148.462 141.998 0.00003 22.866 0.408598 -5.704053 0.216204 0.19771
1 149.818 144.786 0.00002 23.008 0.329577 -6.27717 0.109397 0.156368
0 117.226 106.656 0.00004 23.079 0.603515 -5.61907 0.191576 0.215724
0 116.848 99.503 0.00005 22.085 0.663842 -5.198864 0.206768 0.252404
0 116.286 96.983 0.00003 24.199 0.598515 -5.592584 0.133917 0.214346
0 116.556 86.228 0.00004 23.958 0.566424 -6.431119 0.15331 0.120605
0 116.342 94.246 0.00002 25.023 0.528485 -6.359018 0.116636 0.138868
0 114.563 86.647 0.00003 24.775 0.555303 -6.710219 0.149694 0.121777
0 201.774 78.228 0.00003 19.368 0.508479 -6.934474 0.15989 0.112838
0 174.188 94.261 0.00003 19.517 0.448439 -6.538586 0.121952 0.13305
0 209.516 89.488 0.00003 19.147 0.431674 -6.195325 0.129303 0.168895
0 174.688 74.287 0.00008 17.883 0.407567 -6.787197 0.158453 0.131728
0 198.764 74.904 0.00004 19.02 0.451221 -6.744577 0.207454 0.123306
0 214.289 77.973 0.00003 21.209 0.462803 -5.724056 0.190667 0.148569

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286279&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286279&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286279&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






ANOVA Model
spread1 ~ status
means-6.7591.426

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
spread1  ~  status \tabularnewline
means & -6.759 & 1.426 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286279&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]spread1  ~  status[/C][/ROW]
[ROW][C]means[/C][C]-6.759[/C][C]1.426[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286279&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286279&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Model
spread1 ~ status
means-6.7591.426






ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
status173.56473.56490.4240
Residuals193157.0150.814 

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
status & 1 & 73.564 & 73.564 & 90.424 & 0 \tabularnewline
Residuals & 193 & 157.015 & 0.814 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286279&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]status[/C][C]1[/C][C]73.564[/C][C]73.564[/C][C]90.424[/C][C]0[/C][/ROW]
[ROW][C]Residuals[/C][C]193[/C][C]157.015[/C][C]0.814[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286279&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286279&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
status173.56473.56490.4240
Residuals193157.0150.814






Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-01.4261.131.7220

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
1-0 & 1.426 & 1.13 & 1.722 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286279&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]1-0[/C][C]1.426[/C][C]1.13[/C][C]1.722[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286279&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286279&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
1-01.4261.131.7220






Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group16.470.012
193 

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 6.47 & 0.012 \tabularnewline
  & 193 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286279&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]1[/C][C]6.47[/C][C]0.012[/C][/ROW]
[ROW][C] [/C][C]193[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286279&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286279&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group16.470.012
193


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 7 ; par2 = 1 ; par3 = TRUE ;
R code (references can be found in the software module):
par3 <- 'TRUE'
par2 <- '1'
par1 <- '6'
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
'Tukey Plot'
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-leveneTest(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')