Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 22 Oct 2007 08:58:45 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Oct/22/jtv1jfo3sq3jntw1193068444.htm/, Retrieved Mon, 06 May 2024 10:29:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=1504, Retrieved Mon, 06 May 2024 10:29:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [WS2Q9BASISMETAAL] [2007-10-22 15:58:45] [e0964b90cb3acfe235da067e79729c23] [Current]
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Dataseries X:
467037
460070
447988
442867
436087
431328
484015
509673
512927
502831
470984
471067
476049
474605
470439
461251
454724
455626
516847
525192
522975
518585
509239
512238
519164
517009
509933
509127
500857
506971
569323
579714
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1504&T=0

[TABLE]
[ROW][C]Summary of compuational 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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1504&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1504&T=0

As an alternative you can also use a QR Code:  

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

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean543438.5833333336511.8550090087983.4537290190761
Geometric Mean540583.977041319
Harmonic Mean537651.489721945
Quadratic Mean546201.60747391
Winsorized Mean ( 1 / 24 )543495.6256494.4737626094783.6858604509358
Winsorized Mean ( 2 / 24 )543616.6527777786439.5488846424284.4184371477078
Winsorized Mean ( 3 / 24 )543618.6111111116356.3541655263385.5236503433722
Winsorized Mean ( 4 / 24 )543947.3333333336271.4287225969186.7341968463117
Winsorized Mean ( 5 / 24 )543985.7361111116254.7914103703786.9710435441842
Winsorized Mean ( 6 / 24 )543776.5694444446086.5582266251289.3405680513728
Winsorized Mean ( 7 / 24 )543843.1666666676056.7428077281989.7913588096794
Winsorized Mean ( 8 / 24 )544397.9444444445921.8249754829791.9307724727283
Winsorized Mean ( 9 / 24 )544753.0694444445833.375135139593.3855712729534
Winsorized Mean ( 10 / 24 )542936.8194444445537.9571634264498.039187271091
Winsorized Mean ( 11 / 24 )542691.7638888895500.4571971907298.6630282599165
Winsorized Mean ( 12 / 24 )543273.0972222225392.3615153756100.748641513213
Winsorized Mean ( 13 / 24 )543310.4722222225315.49043308318102.212670507448
Winsorized Mean ( 14 / 24 )544735.5555555565028.76963304713108.323823779034
Winsorized Mean ( 15 / 24 )548218.8888888894462.46028890225122.851264413996
Winsorized Mean ( 16 / 24 )548092.4444444444317.54249325921126.945466153525
Winsorized Mean ( 17 / 24 )548882.7083333334149.64931364417132.272070926233
Winsorized Mean ( 18 / 24 )549248.4583333334049.49364127887135.633861165880
Winsorized Mean ( 19 / 24 )548815.1527777783981.28079048093137.848893775584
Winsorized Mean ( 20 / 24 )548047.6527777783844.18693293346142.565297249884
Winsorized Mean ( 21 / 24 )546773.3611111113657.54349416383149.491964205914
Winsorized Mean ( 22 / 24 )547451.6944444443555.13433236242153.989031992684
Winsorized Mean ( 23 / 24 )547121.7083333333454.66168504998158.372008090111
Winsorized Mean ( 24 / 24 )547166.0416666673117.33919399316175.523421615783
Trimmed Mean ( 1 / 24 )543819.5142857146384.6784642469785.1757088992037
Trimmed Mean ( 2 / 24 )544162.4558823536253.1982234453987.0214626880212
Trimmed Mean ( 3 / 24 )544460.1666666676130.2520546020588.8152985908523
Trimmed Mean ( 4 / 24 )544775.756019.2946852135890.5049143611865
Trimmed Mean ( 5 / 24 )545016.2580645165915.143244041892.1391478749902
Trimmed Mean ( 6 / 24 )545263.5833333335792.4554566849294.1334098139778
Trimmed Mean ( 7 / 24 )545571.241379315688.4375543399595.9088038090654
Trimmed Mean ( 8 / 24 )545888.6428571435566.3859302337598.0687738326148
Trimmed Mean ( 9 / 24 )546137.0925925935447.48219944365100.254956803415
Trimmed Mean ( 10 / 24 )546350.0192307695318.6884733493102.722696012071
Trimmed Mean ( 11 / 24 )546841.525219.63023221111104.766333183021
Trimmed Mean ( 12 / 24 )547407.3958333335097.8371586956107.380322044928
Trimmed Mean ( 13 / 24 )547946.6521739134964.19846503039110.379682849880
Trimmed Mean ( 14 / 24 )548530.2272727274805.46420131611114.147188344988
Trimmed Mean ( 15 / 24 )548994.8809523814666.25528187601117.652131696418
Trimmed Mean ( 16 / 24 )5490884613.56655211228119.015948680442
Trimmed Mean ( 17 / 24 )549205.8947368424566.48673357254120.268803301040
Trimmed Mean ( 18 / 24 )549243.9166666674530.7732085442121.225206247555
Trimmed Mean ( 19 / 24 )549243.3823529414492.51402151822122.257466470261
Trimmed Mean ( 20 / 24 )549294.093754441.75885960208123.665897026929
Trimmed Mean ( 21 / 24 )549443.6666666674389.96954832822125.158878807236
Trimmed Mean ( 22 / 24 )549770.6428571434346.28129293152126.492190864694
Trimmed Mean ( 23 / 24 )550062.5384615384291.93206958601128.161986150586
Trimmed Mean ( 24 / 24 )550446.1254215.82771039578130.566560782989
Median556303
Midrange530106
Midmean - Weighted Average at Xnp548101.405405405
Midmean - Weighted Average at X(n+1)p549243.916666667
Midmean - Empirical Distribution Function548101.405405405
Midmean - Empirical Distribution Function - Averaging549243.916666667
Midmean - Empirical Distribution Function - Interpolation549243.916666667
Midmean - Closest Observation548101.405405405
Midmean - True Basic - Statistics Graphics Toolkit549243.916666667
Midmean - MS Excel (old versions)549205.894736842
Number of observations72

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 543438.583333333 & 6511.85500900879 & 83.4537290190761 \tabularnewline
Geometric Mean & 540583.977041319 &  &  \tabularnewline
Harmonic Mean & 537651.489721945 &  &  \tabularnewline
Quadratic Mean & 546201.60747391 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 543495.625 & 6494.47376260947 & 83.6858604509358 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 543616.652777778 & 6439.54888464242 & 84.4184371477078 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 543618.611111111 & 6356.35416552633 & 85.5236503433722 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 543947.333333333 & 6271.42872259691 & 86.7341968463117 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 543985.736111111 & 6254.79141037037 & 86.9710435441842 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 543776.569444444 & 6086.55822662512 & 89.3405680513728 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 543843.166666667 & 6056.74280772819 & 89.7913588096794 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 544397.944444444 & 5921.82497548297 & 91.9307724727283 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 544753.069444444 & 5833.3751351395 & 93.3855712729534 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 542936.819444444 & 5537.95716342644 & 98.039187271091 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 542691.763888889 & 5500.45719719072 & 98.6630282599165 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 543273.097222222 & 5392.3615153756 & 100.748641513213 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 543310.472222222 & 5315.49043308318 & 102.212670507448 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 544735.555555556 & 5028.76963304713 & 108.323823779034 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 548218.888888889 & 4462.46028890225 & 122.851264413996 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 548092.444444444 & 4317.54249325921 & 126.945466153525 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 548882.708333333 & 4149.64931364417 & 132.272070926233 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 549248.458333333 & 4049.49364127887 & 135.633861165880 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 548815.152777778 & 3981.28079048093 & 137.848893775584 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 548047.652777778 & 3844.18693293346 & 142.565297249884 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 546773.361111111 & 3657.54349416383 & 149.491964205914 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 547451.694444444 & 3555.13433236242 & 153.989031992684 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 547121.708333333 & 3454.66168504998 & 158.372008090111 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 547166.041666667 & 3117.33919399316 & 175.523421615783 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 543819.514285714 & 6384.67846424697 & 85.1757088992037 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 544162.455882353 & 6253.19822344539 & 87.0214626880212 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 544460.166666667 & 6130.25205460205 & 88.8152985908523 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 544775.75 & 6019.29468521358 & 90.5049143611865 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 545016.258064516 & 5915.1432440418 & 92.1391478749902 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 545263.583333333 & 5792.45545668492 & 94.1334098139778 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 545571.24137931 & 5688.43755433995 & 95.9088038090654 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 545888.642857143 & 5566.38593023375 & 98.0687738326148 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 546137.092592593 & 5447.48219944365 & 100.254956803415 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 546350.019230769 & 5318.6884733493 & 102.722696012071 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 546841.52 & 5219.63023221111 & 104.766333183021 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 547407.395833333 & 5097.8371586956 & 107.380322044928 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 547946.652173913 & 4964.19846503039 & 110.379682849880 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 548530.227272727 & 4805.46420131611 & 114.147188344988 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 548994.880952381 & 4666.25528187601 & 117.652131696418 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 549088 & 4613.56655211228 & 119.015948680442 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 549205.894736842 & 4566.48673357254 & 120.268803301040 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 549243.916666667 & 4530.7732085442 & 121.225206247555 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 549243.382352941 & 4492.51402151822 & 122.257466470261 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 549294.09375 & 4441.75885960208 & 123.665897026929 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 549443.666666667 & 4389.96954832822 & 125.158878807236 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 549770.642857143 & 4346.28129293152 & 126.492190864694 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 550062.538461538 & 4291.93206958601 & 128.161986150586 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 550446.125 & 4215.82771039578 & 130.566560782989 \tabularnewline
Median & 556303 &  &  \tabularnewline
Midrange & 530106 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 548101.405405405 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 549243.916666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 548101.405405405 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 549243.916666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 549243.916666667 &  &  \tabularnewline
Midmean - Closest Observation & 548101.405405405 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 549243.916666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 549205.894736842 &  &  \tabularnewline
Number of observations & 72 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=1504&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]543438.583333333[/C][C]6511.85500900879[/C][C]83.4537290190761[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]540583.977041319[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]537651.489721945[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]546201.60747391[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]543495.625[/C][C]6494.47376260947[/C][C]83.6858604509358[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]543616.652777778[/C][C]6439.54888464242[/C][C]84.4184371477078[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]543618.611111111[/C][C]6356.35416552633[/C][C]85.5236503433722[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]543947.333333333[/C][C]6271.42872259691[/C][C]86.7341968463117[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]543985.736111111[/C][C]6254.79141037037[/C][C]86.9710435441842[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]543776.569444444[/C][C]6086.55822662512[/C][C]89.3405680513728[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]543843.166666667[/C][C]6056.74280772819[/C][C]89.7913588096794[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]544397.944444444[/C][C]5921.82497548297[/C][C]91.9307724727283[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]544753.069444444[/C][C]5833.3751351395[/C][C]93.3855712729534[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]542936.819444444[/C][C]5537.95716342644[/C][C]98.039187271091[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]542691.763888889[/C][C]5500.45719719072[/C][C]98.6630282599165[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]543273.097222222[/C][C]5392.3615153756[/C][C]100.748641513213[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]543310.472222222[/C][C]5315.49043308318[/C][C]102.212670507448[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]544735.555555556[/C][C]5028.76963304713[/C][C]108.323823779034[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]548218.888888889[/C][C]4462.46028890225[/C][C]122.851264413996[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]548092.444444444[/C][C]4317.54249325921[/C][C]126.945466153525[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]548882.708333333[/C][C]4149.64931364417[/C][C]132.272070926233[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]549248.458333333[/C][C]4049.49364127887[/C][C]135.633861165880[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]548815.152777778[/C][C]3981.28079048093[/C][C]137.848893775584[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]548047.652777778[/C][C]3844.18693293346[/C][C]142.565297249884[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]546773.361111111[/C][C]3657.54349416383[/C][C]149.491964205914[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]547451.694444444[/C][C]3555.13433236242[/C][C]153.989031992684[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]547121.708333333[/C][C]3454.66168504998[/C][C]158.372008090111[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]547166.041666667[/C][C]3117.33919399316[/C][C]175.523421615783[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]543819.514285714[/C][C]6384.67846424697[/C][C]85.1757088992037[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]544162.455882353[/C][C]6253.19822344539[/C][C]87.0214626880212[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]544460.166666667[/C][C]6130.25205460205[/C][C]88.8152985908523[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]544775.75[/C][C]6019.29468521358[/C][C]90.5049143611865[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]545016.258064516[/C][C]5915.1432440418[/C][C]92.1391478749902[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]545263.583333333[/C][C]5792.45545668492[/C][C]94.1334098139778[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]545571.24137931[/C][C]5688.43755433995[/C][C]95.9088038090654[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]545888.642857143[/C][C]5566.38593023375[/C][C]98.0687738326148[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]546137.092592593[/C][C]5447.48219944365[/C][C]100.254956803415[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]546350.019230769[/C][C]5318.6884733493[/C][C]102.722696012071[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]546841.52[/C][C]5219.63023221111[/C][C]104.766333183021[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]547407.395833333[/C][C]5097.8371586956[/C][C]107.380322044928[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]547946.652173913[/C][C]4964.19846503039[/C][C]110.379682849880[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]548530.227272727[/C][C]4805.46420131611[/C][C]114.147188344988[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]548994.880952381[/C][C]4666.25528187601[/C][C]117.652131696418[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]549088[/C][C]4613.56655211228[/C][C]119.015948680442[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]549205.894736842[/C][C]4566.48673357254[/C][C]120.268803301040[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]549243.916666667[/C][C]4530.7732085442[/C][C]121.225206247555[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]549243.382352941[/C][C]4492.51402151822[/C][C]122.257466470261[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]549294.09375[/C][C]4441.75885960208[/C][C]123.665897026929[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]549443.666666667[/C][C]4389.96954832822[/C][C]125.158878807236[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]549770.642857143[/C][C]4346.28129293152[/C][C]126.492190864694[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]550062.538461538[/C][C]4291.93206958601[/C][C]128.161986150586[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]550446.125[/C][C]4215.82771039578[/C][C]130.566560782989[/C][/ROW]
[ROW][C]Median[/C][C]556303[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]530106[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]548101.405405405[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]549243.916666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]548101.405405405[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]549243.916666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]549243.916666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]548101.405405405[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]549243.916666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]549205.894736842[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]72[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=1504&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=1504&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean543438.5833333336511.8550090087983.4537290190761
Geometric Mean540583.977041319
Harmonic Mean537651.489721945
Quadratic Mean546201.60747391
Winsorized Mean ( 1 / 24 )543495.6256494.4737626094783.6858604509358
Winsorized Mean ( 2 / 24 )543616.6527777786439.5488846424284.4184371477078
Winsorized Mean ( 3 / 24 )543618.6111111116356.3541655263385.5236503433722
Winsorized Mean ( 4 / 24 )543947.3333333336271.4287225969186.7341968463117
Winsorized Mean ( 5 / 24 )543985.7361111116254.7914103703786.9710435441842
Winsorized Mean ( 6 / 24 )543776.5694444446086.5582266251289.3405680513728
Winsorized Mean ( 7 / 24 )543843.1666666676056.7428077281989.7913588096794
Winsorized Mean ( 8 / 24 )544397.9444444445921.8249754829791.9307724727283
Winsorized Mean ( 9 / 24 )544753.0694444445833.375135139593.3855712729534
Winsorized Mean ( 10 / 24 )542936.8194444445537.9571634264498.039187271091
Winsorized Mean ( 11 / 24 )542691.7638888895500.4571971907298.6630282599165
Winsorized Mean ( 12 / 24 )543273.0972222225392.3615153756100.748641513213
Winsorized Mean ( 13 / 24 )543310.4722222225315.49043308318102.212670507448
Winsorized Mean ( 14 / 24 )544735.5555555565028.76963304713108.323823779034
Winsorized Mean ( 15 / 24 )548218.8888888894462.46028890225122.851264413996
Winsorized Mean ( 16 / 24 )548092.4444444444317.54249325921126.945466153525
Winsorized Mean ( 17 / 24 )548882.7083333334149.64931364417132.272070926233
Winsorized Mean ( 18 / 24 )549248.4583333334049.49364127887135.633861165880
Winsorized Mean ( 19 / 24 )548815.1527777783981.28079048093137.848893775584
Winsorized Mean ( 20 / 24 )548047.6527777783844.18693293346142.565297249884
Winsorized Mean ( 21 / 24 )546773.3611111113657.54349416383149.491964205914
Winsorized Mean ( 22 / 24 )547451.6944444443555.13433236242153.989031992684
Winsorized Mean ( 23 / 24 )547121.7083333333454.66168504998158.372008090111
Winsorized Mean ( 24 / 24 )547166.0416666673117.33919399316175.523421615783
Trimmed Mean ( 1 / 24 )543819.5142857146384.6784642469785.1757088992037
Trimmed Mean ( 2 / 24 )544162.4558823536253.1982234453987.0214626880212
Trimmed Mean ( 3 / 24 )544460.1666666676130.2520546020588.8152985908523
Trimmed Mean ( 4 / 24 )544775.756019.2946852135890.5049143611865
Trimmed Mean ( 5 / 24 )545016.2580645165915.143244041892.1391478749902
Trimmed Mean ( 6 / 24 )545263.5833333335792.4554566849294.1334098139778
Trimmed Mean ( 7 / 24 )545571.241379315688.4375543399595.9088038090654
Trimmed Mean ( 8 / 24 )545888.6428571435566.3859302337598.0687738326148
Trimmed Mean ( 9 / 24 )546137.0925925935447.48219944365100.254956803415
Trimmed Mean ( 10 / 24 )546350.0192307695318.6884733493102.722696012071
Trimmed Mean ( 11 / 24 )546841.525219.63023221111104.766333183021
Trimmed Mean ( 12 / 24 )547407.3958333335097.8371586956107.380322044928
Trimmed Mean ( 13 / 24 )547946.6521739134964.19846503039110.379682849880
Trimmed Mean ( 14 / 24 )548530.2272727274805.46420131611114.147188344988
Trimmed Mean ( 15 / 24 )548994.8809523814666.25528187601117.652131696418
Trimmed Mean ( 16 / 24 )5490884613.56655211228119.015948680442
Trimmed Mean ( 17 / 24 )549205.8947368424566.48673357254120.268803301040
Trimmed Mean ( 18 / 24 )549243.9166666674530.7732085442121.225206247555
Trimmed Mean ( 19 / 24 )549243.3823529414492.51402151822122.257466470261
Trimmed Mean ( 20 / 24 )549294.093754441.75885960208123.665897026929
Trimmed Mean ( 21 / 24 )549443.6666666674389.96954832822125.158878807236
Trimmed Mean ( 22 / 24 )549770.6428571434346.28129293152126.492190864694
Trimmed Mean ( 23 / 24 )550062.5384615384291.93206958601128.161986150586
Trimmed Mean ( 24 / 24 )550446.1254215.82771039578130.566560782989
Median556303
Midrange530106
Midmean - Weighted Average at Xnp548101.405405405
Midmean - Weighted Average at X(n+1)p549243.916666667
Midmean - Empirical Distribution Function548101.405405405
Midmean - Empirical Distribution Function - Averaging549243.916666667
Midmean - Empirical Distribution Function - Interpolation549243.916666667
Midmean - Closest Observation548101.405405405
Midmean - True Basic - Statistics Graphics Toolkit549243.916666667
Midmean - MS Excel (old versions)549205.894736842
Number of observations72



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')