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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 20 Apr 2008 06:46:03 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Apr/20/t1208695599kea8jhrelf8t6iw.htm/, Retrieved Sun, 12 May 2024 20:52:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=10335, Retrieved Sun, 12 May 2024 20:52:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [centrummaten cham...] [2008-04-20 12:46:03] [56744542a24c8707256dac9921ca917a] [Current]
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Dataseries X:
2815
2672
2755
2721
2946
3036
2282
2212
2922
4301
5764
7312
2541
2475
3031
3266
3776
3230
3028
1759
3595
4474
6838
8357
3113
3006
4047
3523
3937
3986
3260
1573
3528
5211
7614
9254
5375
3088
3718
4514
4520
4539
3663
1643
4739
5428
8314
10651
3633
4292
4154
4121
4647
4753
3965
1723
5048
6922
9858
11331
4016
4276
4968
4677
3523
1821
5222
6872
10803
13916
2639
2899
3370
3740
2927
3986
4217
1738
5221
6424
9842
13076




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 7 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=10335&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=10335&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10335&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 time7 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean4694.78048780488288.91679770567916.2495933953535
Geometric Mean4143.63440911547
Harmonic Mean3711.87474211097
Quadratic Mean5366.77463886739
Winsorized Mean ( 1 / 27 )4685.39024390244284.92213010162916.4444588499714
Winsorized Mean ( 2 / 27 )4644.78048780488270.39770135828917.1775886572731
Winsorized Mean ( 3 / 27 )4626.01219512195264.59007313832317.4836952129476
Winsorized Mean ( 4 / 27 )4619.62195121951262.33121651943617.6098826991001
Winsorized Mean ( 5 / 27 )4575.04878048780248.59892910605318.4033326166746
Winsorized Mean ( 6 / 27 )4602.48780487805244.60632804433418.8158983525719
Winsorized Mean ( 7 / 27 )4558.26829268293230.93543592143219.7382799850333
Winsorized Mean ( 8 / 27 )4489.58536585366207.56233192806721.6300584222073
Winsorized Mean ( 9 / 27 )4492.10975609756205.61965894623621.8466939353894
Winsorized Mean ( 10 / 27 )4418.69512195122185.29317629930323.8470472048777
Winsorized Mean ( 11 / 27 )4382.60975609756176.29389841886824.8596791800737
Winsorized Mean ( 12 / 27 )4332.70731707317164.00280225406526.4184956447338
Winsorized Mean ( 13 / 27 )4330.17073170732161.81069847009226.7607196103147
Winsorized Mean ( 14 / 27 )4334.60975609756159.46706614222927.1818492743292
Winsorized Mean ( 15 / 27 )4274.24390243902143.28322747766229.8307343970555
Winsorized Mean ( 16 / 27 )4149.95121951220120.00768933313534.5807109742122
Winsorized Mean ( 17 / 27 )4081.32926829268108.74370479154737.531637128938
Winsorized Mean ( 18 / 27 )4073.86585365854106.43013629669738.2773713856926
Winsorized Mean ( 19 / 27 )4052.3170731707399.361999522586140.7833688194811
Winsorized Mean ( 20 / 27 )4057.4390243902498.632005645518741.1371440521304
Winsorized Mean ( 21 / 27 )4055.6463414634198.160441415793641.3165047239781
Winsorized Mean ( 22 / 27 )4013.2560975609891.75995714533343.7364643839646
Winsorized Mean ( 23 / 27 )4005.4024390243986.74913361529346.1722471694897
Winsorized Mean ( 24 / 27 )3949.7926829268377.428287066175451.0122699673192
Winsorized Mean ( 25 / 27 )3981.1951219512272.205020755414255.1373724472297
Winsorized Mean ( 26 / 27 )3971.0487804878068.458720976214558.0064705250266
Winsorized Mean ( 27 / 27 )3963.1463414634166.953430498000159.1925807533013
Trimmed Mean ( 1 / 27 )4618.5375269.54769483771517.1343980618371
Trimmed Mean ( 2 / 27 )4548.25641025641251.01123979375218.1197320645624
Trimmed Mean ( 3 / 27 )4496.18421052632238.49827518632418.852061747674
Trimmed Mean ( 4 / 27 )4448.22972972973226.31018720337019.6554551286390
Trimmed Mean ( 5 / 27 )4399.43055555556212.47879561552520.7052686966290
Trimmed Mean ( 6 / 27 )4358.28571428571200.53236408286221.7335776906556
Trimmed Mean ( 7 / 27 )4309.20588235294187.04088133370623.0388450462054
Trimmed Mean ( 8 / 27 )4265174.54496551990524.4349642929897
Trimmed Mean ( 9 / 27 )4229.03125165.67228655426425.5264856781876
Trimmed Mean ( 10 / 27 )4190.37096774194155.14996282468427.0085206045261
Trimmed Mean ( 11 / 27 )4159.16666666667147.34183738271528.2280086942542
Trimmed Mean ( 12 / 27 )4130.44827586207139.84282329930429.5363621701323
Trimmed Mean ( 13 / 27 )4105.76785714286133.43461113499630.7698866300066
Trimmed Mean ( 14 / 27 )4079.55555555556125.84453118200432.41742423956
Trimmed Mean ( 15 / 27 )4050.82692307692116.6300623070734.7322709338154
Trimmed Mean ( 16 / 27 )4026.4108.95707823707136.9540012007231
Trimmed Mean ( 17 / 27 )4013.20833333333104.92783723536538.2473177668882
Trimmed Mean ( 18 / 27 )4006.06521739130102.27932012763839.1678905607897
Trimmed Mean ( 19 / 27 )3999.0454545454599.295893019577940.2740267793047
Trimmed Mean ( 20 / 27 )3993.5714285714396.907730237877941.2100398881335
Trimmed Mean ( 21 / 27 )3987.02593.818103383280442.4973950252605
Trimmed Mean ( 22 / 27 )3979.9736842105389.716151780182944.3618412653501
Trimmed Mean ( 23 / 27 )3976.5277777777885.8416915589446.3239680574962
Trimmed Mean ( 24 / 27 )3973.581.823428976129848.5618856325268
Trimmed Mean ( 25 / 27 )3976.0312578.824446178023850.441600833074
Trimmed Mean ( 26 / 27 )3975.4666666666775.998286933708252.3099510142168
Trimmed Mean ( 27 / 27 )3975.9642857142972.928581469043654.5186017007884
Median3986
Midrange7744.5
Midmean - Weighted Average at Xnp3963.63414634146
Midmean - Weighted Average at X(n+1)p3993.57142857143
Midmean - Empirical Distribution Function3993.57142857143
Midmean - Empirical Distribution Function - Averaging3993.57142857143
Midmean - Empirical Distribution Function - Interpolation3987.025
Midmean - Closest Observation3993.57142857143
Midmean - True Basic - Statistics Graphics Toolkit3993.57142857143
Midmean - MS Excel (old versions)3993.57142857143
Number of observations82

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4694.78048780488 & 288.916797705679 & 16.2495933953535 \tabularnewline
Geometric Mean & 4143.63440911547 &  &  \tabularnewline
Harmonic Mean & 3711.87474211097 &  &  \tabularnewline
Quadratic Mean & 5366.77463886739 &  &  \tabularnewline
Winsorized Mean ( 1 / 27 ) & 4685.39024390244 & 284.922130101629 & 16.4444588499714 \tabularnewline
Winsorized Mean ( 2 / 27 ) & 4644.78048780488 & 270.397701358289 & 17.1775886572731 \tabularnewline
Winsorized Mean ( 3 / 27 ) & 4626.01219512195 & 264.590073138323 & 17.4836952129476 \tabularnewline
Winsorized Mean ( 4 / 27 ) & 4619.62195121951 & 262.331216519436 & 17.6098826991001 \tabularnewline
Winsorized Mean ( 5 / 27 ) & 4575.04878048780 & 248.598929106053 & 18.4033326166746 \tabularnewline
Winsorized Mean ( 6 / 27 ) & 4602.48780487805 & 244.606328044334 & 18.8158983525719 \tabularnewline
Winsorized Mean ( 7 / 27 ) & 4558.26829268293 & 230.935435921432 & 19.7382799850333 \tabularnewline
Winsorized Mean ( 8 / 27 ) & 4489.58536585366 & 207.562331928067 & 21.6300584222073 \tabularnewline
Winsorized Mean ( 9 / 27 ) & 4492.10975609756 & 205.619658946236 & 21.8466939353894 \tabularnewline
Winsorized Mean ( 10 / 27 ) & 4418.69512195122 & 185.293176299303 & 23.8470472048777 \tabularnewline
Winsorized Mean ( 11 / 27 ) & 4382.60975609756 & 176.293898418868 & 24.8596791800737 \tabularnewline
Winsorized Mean ( 12 / 27 ) & 4332.70731707317 & 164.002802254065 & 26.4184956447338 \tabularnewline
Winsorized Mean ( 13 / 27 ) & 4330.17073170732 & 161.810698470092 & 26.7607196103147 \tabularnewline
Winsorized Mean ( 14 / 27 ) & 4334.60975609756 & 159.467066142229 & 27.1818492743292 \tabularnewline
Winsorized Mean ( 15 / 27 ) & 4274.24390243902 & 143.283227477662 & 29.8307343970555 \tabularnewline
Winsorized Mean ( 16 / 27 ) & 4149.95121951220 & 120.007689333135 & 34.5807109742122 \tabularnewline
Winsorized Mean ( 17 / 27 ) & 4081.32926829268 & 108.743704791547 & 37.531637128938 \tabularnewline
Winsorized Mean ( 18 / 27 ) & 4073.86585365854 & 106.430136296697 & 38.2773713856926 \tabularnewline
Winsorized Mean ( 19 / 27 ) & 4052.31707317073 & 99.3619995225861 & 40.7833688194811 \tabularnewline
Winsorized Mean ( 20 / 27 ) & 4057.43902439024 & 98.6320056455187 & 41.1371440521304 \tabularnewline
Winsorized Mean ( 21 / 27 ) & 4055.64634146341 & 98.1604414157936 & 41.3165047239781 \tabularnewline
Winsorized Mean ( 22 / 27 ) & 4013.25609756098 & 91.759957145333 & 43.7364643839646 \tabularnewline
Winsorized Mean ( 23 / 27 ) & 4005.40243902439 & 86.749133615293 & 46.1722471694897 \tabularnewline
Winsorized Mean ( 24 / 27 ) & 3949.79268292683 & 77.4282870661754 & 51.0122699673192 \tabularnewline
Winsorized Mean ( 25 / 27 ) & 3981.19512195122 & 72.2050207554142 & 55.1373724472297 \tabularnewline
Winsorized Mean ( 26 / 27 ) & 3971.04878048780 & 68.4587209762145 & 58.0064705250266 \tabularnewline
Winsorized Mean ( 27 / 27 ) & 3963.14634146341 & 66.9534304980001 & 59.1925807533013 \tabularnewline
Trimmed Mean ( 1 / 27 ) & 4618.5375 & 269.547694837715 & 17.1343980618371 \tabularnewline
Trimmed Mean ( 2 / 27 ) & 4548.25641025641 & 251.011239793752 & 18.1197320645624 \tabularnewline
Trimmed Mean ( 3 / 27 ) & 4496.18421052632 & 238.498275186324 & 18.852061747674 \tabularnewline
Trimmed Mean ( 4 / 27 ) & 4448.22972972973 & 226.310187203370 & 19.6554551286390 \tabularnewline
Trimmed Mean ( 5 / 27 ) & 4399.43055555556 & 212.478795615525 & 20.7052686966290 \tabularnewline
Trimmed Mean ( 6 / 27 ) & 4358.28571428571 & 200.532364082862 & 21.7335776906556 \tabularnewline
Trimmed Mean ( 7 / 27 ) & 4309.20588235294 & 187.040881333706 & 23.0388450462054 \tabularnewline
Trimmed Mean ( 8 / 27 ) & 4265 & 174.544965519905 & 24.4349642929897 \tabularnewline
Trimmed Mean ( 9 / 27 ) & 4229.03125 & 165.672286554264 & 25.5264856781876 \tabularnewline
Trimmed Mean ( 10 / 27 ) & 4190.37096774194 & 155.149962824684 & 27.0085206045261 \tabularnewline
Trimmed Mean ( 11 / 27 ) & 4159.16666666667 & 147.341837382715 & 28.2280086942542 \tabularnewline
Trimmed Mean ( 12 / 27 ) & 4130.44827586207 & 139.842823299304 & 29.5363621701323 \tabularnewline
Trimmed Mean ( 13 / 27 ) & 4105.76785714286 & 133.434611134996 & 30.7698866300066 \tabularnewline
Trimmed Mean ( 14 / 27 ) & 4079.55555555556 & 125.844531182004 & 32.41742423956 \tabularnewline
Trimmed Mean ( 15 / 27 ) & 4050.82692307692 & 116.63006230707 & 34.7322709338154 \tabularnewline
Trimmed Mean ( 16 / 27 ) & 4026.4 & 108.957078237071 & 36.9540012007231 \tabularnewline
Trimmed Mean ( 17 / 27 ) & 4013.20833333333 & 104.927837235365 & 38.2473177668882 \tabularnewline
Trimmed Mean ( 18 / 27 ) & 4006.06521739130 & 102.279320127638 & 39.1678905607897 \tabularnewline
Trimmed Mean ( 19 / 27 ) & 3999.04545454545 & 99.2958930195779 & 40.2740267793047 \tabularnewline
Trimmed Mean ( 20 / 27 ) & 3993.57142857143 & 96.9077302378779 & 41.2100398881335 \tabularnewline
Trimmed Mean ( 21 / 27 ) & 3987.025 & 93.8181033832804 & 42.4973950252605 \tabularnewline
Trimmed Mean ( 22 / 27 ) & 3979.97368421053 & 89.7161517801829 & 44.3618412653501 \tabularnewline
Trimmed Mean ( 23 / 27 ) & 3976.52777777778 & 85.84169155894 & 46.3239680574962 \tabularnewline
Trimmed Mean ( 24 / 27 ) & 3973.5 & 81.8234289761298 & 48.5618856325268 \tabularnewline
Trimmed Mean ( 25 / 27 ) & 3976.03125 & 78.8244461780238 & 50.441600833074 \tabularnewline
Trimmed Mean ( 26 / 27 ) & 3975.46666666667 & 75.9982869337082 & 52.3099510142168 \tabularnewline
Trimmed Mean ( 27 / 27 ) & 3975.96428571429 & 72.9285814690436 & 54.5186017007884 \tabularnewline
Median & 3986 &  &  \tabularnewline
Midrange & 7744.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 3963.63414634146 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 3993.57142857143 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 3993.57142857143 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 3993.57142857143 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 3987.025 &  &  \tabularnewline
Midmean - Closest Observation & 3993.57142857143 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 3993.57142857143 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 3993.57142857143 &  &  \tabularnewline
Number of observations & 82 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=10335&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]4694.78048780488[/C][C]288.916797705679[/C][C]16.2495933953535[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4143.63440911547[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3711.87474211097[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5366.77463886739[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 27 )[/C][C]4685.39024390244[/C][C]284.922130101629[/C][C]16.4444588499714[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 27 )[/C][C]4644.78048780488[/C][C]270.397701358289[/C][C]17.1775886572731[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 27 )[/C][C]4626.01219512195[/C][C]264.590073138323[/C][C]17.4836952129476[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 27 )[/C][C]4619.62195121951[/C][C]262.331216519436[/C][C]17.6098826991001[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 27 )[/C][C]4575.04878048780[/C][C]248.598929106053[/C][C]18.4033326166746[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 27 )[/C][C]4602.48780487805[/C][C]244.606328044334[/C][C]18.8158983525719[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 27 )[/C][C]4558.26829268293[/C][C]230.935435921432[/C][C]19.7382799850333[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 27 )[/C][C]4489.58536585366[/C][C]207.562331928067[/C][C]21.6300584222073[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 27 )[/C][C]4492.10975609756[/C][C]205.619658946236[/C][C]21.8466939353894[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 27 )[/C][C]4418.69512195122[/C][C]185.293176299303[/C][C]23.8470472048777[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 27 )[/C][C]4382.60975609756[/C][C]176.293898418868[/C][C]24.8596791800737[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 27 )[/C][C]4332.70731707317[/C][C]164.002802254065[/C][C]26.4184956447338[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 27 )[/C][C]4330.17073170732[/C][C]161.810698470092[/C][C]26.7607196103147[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 27 )[/C][C]4334.60975609756[/C][C]159.467066142229[/C][C]27.1818492743292[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 27 )[/C][C]4274.24390243902[/C][C]143.283227477662[/C][C]29.8307343970555[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 27 )[/C][C]4149.95121951220[/C][C]120.007689333135[/C][C]34.5807109742122[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 27 )[/C][C]4081.32926829268[/C][C]108.743704791547[/C][C]37.531637128938[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 27 )[/C][C]4073.86585365854[/C][C]106.430136296697[/C][C]38.2773713856926[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 27 )[/C][C]4052.31707317073[/C][C]99.3619995225861[/C][C]40.7833688194811[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 27 )[/C][C]4057.43902439024[/C][C]98.6320056455187[/C][C]41.1371440521304[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 27 )[/C][C]4055.64634146341[/C][C]98.1604414157936[/C][C]41.3165047239781[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 27 )[/C][C]4013.25609756098[/C][C]91.759957145333[/C][C]43.7364643839646[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 27 )[/C][C]4005.40243902439[/C][C]86.749133615293[/C][C]46.1722471694897[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 27 )[/C][C]3949.79268292683[/C][C]77.4282870661754[/C][C]51.0122699673192[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 27 )[/C][C]3981.19512195122[/C][C]72.2050207554142[/C][C]55.1373724472297[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 27 )[/C][C]3971.04878048780[/C][C]68.4587209762145[/C][C]58.0064705250266[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 27 )[/C][C]3963.14634146341[/C][C]66.9534304980001[/C][C]59.1925807533013[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 27 )[/C][C]4618.5375[/C][C]269.547694837715[/C][C]17.1343980618371[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 27 )[/C][C]4548.25641025641[/C][C]251.011239793752[/C][C]18.1197320645624[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 27 )[/C][C]4496.18421052632[/C][C]238.498275186324[/C][C]18.852061747674[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 27 )[/C][C]4448.22972972973[/C][C]226.310187203370[/C][C]19.6554551286390[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 27 )[/C][C]4399.43055555556[/C][C]212.478795615525[/C][C]20.7052686966290[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 27 )[/C][C]4358.28571428571[/C][C]200.532364082862[/C][C]21.7335776906556[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 27 )[/C][C]4309.20588235294[/C][C]187.040881333706[/C][C]23.0388450462054[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 27 )[/C][C]4265[/C][C]174.544965519905[/C][C]24.4349642929897[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 27 )[/C][C]4229.03125[/C][C]165.672286554264[/C][C]25.5264856781876[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 27 )[/C][C]4190.37096774194[/C][C]155.149962824684[/C][C]27.0085206045261[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 27 )[/C][C]4159.16666666667[/C][C]147.341837382715[/C][C]28.2280086942542[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 27 )[/C][C]4130.44827586207[/C][C]139.842823299304[/C][C]29.5363621701323[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 27 )[/C][C]4105.76785714286[/C][C]133.434611134996[/C][C]30.7698866300066[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 27 )[/C][C]4079.55555555556[/C][C]125.844531182004[/C][C]32.41742423956[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 27 )[/C][C]4050.82692307692[/C][C]116.63006230707[/C][C]34.7322709338154[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 27 )[/C][C]4026.4[/C][C]108.957078237071[/C][C]36.9540012007231[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 27 )[/C][C]4013.20833333333[/C][C]104.927837235365[/C][C]38.2473177668882[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 27 )[/C][C]4006.06521739130[/C][C]102.279320127638[/C][C]39.1678905607897[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 27 )[/C][C]3999.04545454545[/C][C]99.2958930195779[/C][C]40.2740267793047[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 27 )[/C][C]3993.57142857143[/C][C]96.9077302378779[/C][C]41.2100398881335[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 27 )[/C][C]3987.025[/C][C]93.8181033832804[/C][C]42.4973950252605[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 27 )[/C][C]3979.97368421053[/C][C]89.7161517801829[/C][C]44.3618412653501[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 27 )[/C][C]3976.52777777778[/C][C]85.84169155894[/C][C]46.3239680574962[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 27 )[/C][C]3973.5[/C][C]81.8234289761298[/C][C]48.5618856325268[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 27 )[/C][C]3976.03125[/C][C]78.8244461780238[/C][C]50.441600833074[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 27 )[/C][C]3975.46666666667[/C][C]75.9982869337082[/C][C]52.3099510142168[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 27 )[/C][C]3975.96428571429[/C][C]72.9285814690436[/C][C]54.5186017007884[/C][/ROW]
[ROW][C]Median[/C][C]3986[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]7744.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]3963.63414634146[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]3993.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]3993.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]3993.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]3987.025[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]3993.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]3993.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]3993.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]82[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=10335&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10335&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 Mean4694.78048780488288.91679770567916.2495933953535
Geometric Mean4143.63440911547
Harmonic Mean3711.87474211097
Quadratic Mean5366.77463886739
Winsorized Mean ( 1 / 27 )4685.39024390244284.92213010162916.4444588499714
Winsorized Mean ( 2 / 27 )4644.78048780488270.39770135828917.1775886572731
Winsorized Mean ( 3 / 27 )4626.01219512195264.59007313832317.4836952129476
Winsorized Mean ( 4 / 27 )4619.62195121951262.33121651943617.6098826991001
Winsorized Mean ( 5 / 27 )4575.04878048780248.59892910605318.4033326166746
Winsorized Mean ( 6 / 27 )4602.48780487805244.60632804433418.8158983525719
Winsorized Mean ( 7 / 27 )4558.26829268293230.93543592143219.7382799850333
Winsorized Mean ( 8 / 27 )4489.58536585366207.56233192806721.6300584222073
Winsorized Mean ( 9 / 27 )4492.10975609756205.61965894623621.8466939353894
Winsorized Mean ( 10 / 27 )4418.69512195122185.29317629930323.8470472048777
Winsorized Mean ( 11 / 27 )4382.60975609756176.29389841886824.8596791800737
Winsorized Mean ( 12 / 27 )4332.70731707317164.00280225406526.4184956447338
Winsorized Mean ( 13 / 27 )4330.17073170732161.81069847009226.7607196103147
Winsorized Mean ( 14 / 27 )4334.60975609756159.46706614222927.1818492743292
Winsorized Mean ( 15 / 27 )4274.24390243902143.28322747766229.8307343970555
Winsorized Mean ( 16 / 27 )4149.95121951220120.00768933313534.5807109742122
Winsorized Mean ( 17 / 27 )4081.32926829268108.74370479154737.531637128938
Winsorized Mean ( 18 / 27 )4073.86585365854106.43013629669738.2773713856926
Winsorized Mean ( 19 / 27 )4052.3170731707399.361999522586140.7833688194811
Winsorized Mean ( 20 / 27 )4057.4390243902498.632005645518741.1371440521304
Winsorized Mean ( 21 / 27 )4055.6463414634198.160441415793641.3165047239781
Winsorized Mean ( 22 / 27 )4013.2560975609891.75995714533343.7364643839646
Winsorized Mean ( 23 / 27 )4005.4024390243986.74913361529346.1722471694897
Winsorized Mean ( 24 / 27 )3949.7926829268377.428287066175451.0122699673192
Winsorized Mean ( 25 / 27 )3981.1951219512272.205020755414255.1373724472297
Winsorized Mean ( 26 / 27 )3971.0487804878068.458720976214558.0064705250266
Winsorized Mean ( 27 / 27 )3963.1463414634166.953430498000159.1925807533013
Trimmed Mean ( 1 / 27 )4618.5375269.54769483771517.1343980618371
Trimmed Mean ( 2 / 27 )4548.25641025641251.01123979375218.1197320645624
Trimmed Mean ( 3 / 27 )4496.18421052632238.49827518632418.852061747674
Trimmed Mean ( 4 / 27 )4448.22972972973226.31018720337019.6554551286390
Trimmed Mean ( 5 / 27 )4399.43055555556212.47879561552520.7052686966290
Trimmed Mean ( 6 / 27 )4358.28571428571200.53236408286221.7335776906556
Trimmed Mean ( 7 / 27 )4309.20588235294187.04088133370623.0388450462054
Trimmed Mean ( 8 / 27 )4265174.54496551990524.4349642929897
Trimmed Mean ( 9 / 27 )4229.03125165.67228655426425.5264856781876
Trimmed Mean ( 10 / 27 )4190.37096774194155.14996282468427.0085206045261
Trimmed Mean ( 11 / 27 )4159.16666666667147.34183738271528.2280086942542
Trimmed Mean ( 12 / 27 )4130.44827586207139.84282329930429.5363621701323
Trimmed Mean ( 13 / 27 )4105.76785714286133.43461113499630.7698866300066
Trimmed Mean ( 14 / 27 )4079.55555555556125.84453118200432.41742423956
Trimmed Mean ( 15 / 27 )4050.82692307692116.6300623070734.7322709338154
Trimmed Mean ( 16 / 27 )4026.4108.95707823707136.9540012007231
Trimmed Mean ( 17 / 27 )4013.20833333333104.92783723536538.2473177668882
Trimmed Mean ( 18 / 27 )4006.06521739130102.27932012763839.1678905607897
Trimmed Mean ( 19 / 27 )3999.0454545454599.295893019577940.2740267793047
Trimmed Mean ( 20 / 27 )3993.5714285714396.907730237877941.2100398881335
Trimmed Mean ( 21 / 27 )3987.02593.818103383280442.4973950252605
Trimmed Mean ( 22 / 27 )3979.9736842105389.716151780182944.3618412653501
Trimmed Mean ( 23 / 27 )3976.5277777777885.8416915589446.3239680574962
Trimmed Mean ( 24 / 27 )3973.581.823428976129848.5618856325268
Trimmed Mean ( 25 / 27 )3976.0312578.824446178023850.441600833074
Trimmed Mean ( 26 / 27 )3975.4666666666775.998286933708252.3099510142168
Trimmed Mean ( 27 / 27 )3975.9642857142972.928581469043654.5186017007884
Median3986
Midrange7744.5
Midmean - Weighted Average at Xnp3963.63414634146
Midmean - Weighted Average at X(n+1)p3993.57142857143
Midmean - Empirical Distribution Function3993.57142857143
Midmean - Empirical Distribution Function - Averaging3993.57142857143
Midmean - Empirical Distribution Function - Interpolation3987.025
Midmean - Closest Observation3993.57142857143
Midmean - True Basic - Statistics Graphics Toolkit3993.57142857143
Midmean - MS Excel (old versions)3993.57142857143
Number of observations82



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')