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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 computationSat, 11 Oct 2014 14:01:12 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/11/t141303249814io4qx9iig9g68.htm/, Retrieved Tue, 14 May 2024 20:37:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=240438, Retrieved Tue, 14 May 2024 20:37:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Gemiddelde consum...] [2014-10-11 13:01:12] [6e93958bb59fd6ca90246553243cf8d9] [Current]
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Dataseries X:
389,09
391,76
390,96
391,76
392,8
393,06
393,06
393,26
393,87
394,47
394,57
394,57
394,57
399,57
406,13
407,03
409,46
409,9
409,9
410,14
410,54
410,69
410,79
410,97
410,97
413,8
423,31
423,85
426,6
426,26
426,26
426,32
427,14
427,55
428,29
428,8
428,8
434,87
435,66
440,75
440,99
441,04
441,04
441,88
441,92
442,48
442,81
442,81
442,81
447,19
446,52
448,57
448,71
448,73
449,07
449,03
448,68
450,08
449,96
449,96
449,96
452,56
455,31
456,2
456,75
457,63
457,63
457,65
458,32
459,64
460,16
459,89




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240438&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240438&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240438&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean428.1684722222222.7145352367638157.731779062361
Geometric Mean427.549957466556
Harmonic Mean426.924589752367
Quadratic Mean428.778985510342
Winsorized Mean ( 1 / 24 )428.1906944444442.7087678476027158.07581842918
Winsorized Mean ( 2 / 24 )428.2059722222222.70336609611016158.397330216711
Winsorized Mean ( 3 / 24 )428.1509722222222.69452548192796158.896612815061
Winsorized Mean ( 4 / 24 )428.1715277777782.6778347028163159.894681821647
Winsorized Mean ( 5 / 24 )428.1881944444442.67426957782828160.114073014347
Winsorized Mean ( 6 / 24 )428.1881944444442.67426957782828160.114073014347
Winsorized Mean ( 7 / 24 )428.1220833333332.65755063710761161.096491391519
Winsorized Mean ( 8 / 24 )428.128752.63586596682207162.424324828691
Winsorized Mean ( 9 / 24 )428.09252.60565765768063164.293455334826
Winsorized Mean ( 10 / 24 )427.7244444444442.54879769201856167.814199527818
Winsorized Mean ( 11 / 24 )427.3455555555562.49850237528076171.040684124839
Winsorized Mean ( 12 / 24 )427.3255555555562.49594353914156171.208021677657
Winsorized Mean ( 13 / 24 )428.2283333333332.33427622632423183.452296049668
Winsorized Mean ( 14 / 24 )429.5038888888892.12463100502048202.154580194855
Winsorized Mean ( 15 / 24 )429.5059722222222.07086016938546207.404622761024
Winsorized Mean ( 16 / 24 )430.0370833333331.98901707031525216.205828371887
Winsorized Mean ( 17 / 24 )430.0701388888891.96443432321201218.92823486493
Winsorized Mean ( 18 / 24 )430.0651388888891.96376554534883219.000246698235
Winsorized Mean ( 19 / 24 )430.1205555555561.95356495575179220.172129055228
Winsorized Mean ( 20 / 24 )430.2011111111111.93351662110331222.496722508456
Winsorized Mean ( 21 / 24 )429.8423611111111.87405770263651229.36452837412
Winsorized Mean ( 22 / 24 )429.6681944444441.84312624937685233.119242151596
Winsorized Mean ( 23 / 24 )428.5405555555561.68763654045518253.929412692126
Winsorized Mean ( 24 / 24 )428.5405555555561.68763654045518253.929412692126
Trimmed Mean ( 1 / 24 )428.2697142857142.69642428645129158.828755710902
Trimmed Mean ( 2 / 24 )428.3533823529412.68008813564974159.828095447725
Trimmed Mean ( 3 / 24 )428.4337878787882.6622988100674160.926259012955
Trimmed Mean ( 4 / 24 )428.539843752.64312242534591162.133936604891
Trimmed Mean ( 5 / 24 )428.6467741935482.62410082078032163.349963842503
Trimmed Mean ( 6 / 24 )428.7568333333332.60026728843029164.889523181351
Trimmed Mean ( 7 / 24 )428.8744827586212.56945822264534166.912417169827
Trimmed Mean ( 8 / 24 )429.0126785714292.53418758583485169.290024530721
Trimmed Mean ( 9 / 24 )429.162.49421121553507172.062412889093
Trimmed Mean ( 10 / 24 )429.3242307692312.44980816723902175.248101672012
Trimmed Mean ( 11 / 24 )429.55462.40456421797534178.641350806463
Trimmed Mean ( 12 / 24 )429.8558333333332.35540689730909182.497484330379
Trimmed Mean ( 13 / 24 )430.1858695652172.29069513690712187.797085100574
Trimmed Mean ( 14 / 24 )430.4322727272732.2444268742915191.778256470551
Trimmed Mean ( 15 / 24 )430.5459523809522.22935538720353193.125759514288
Trimmed Mean ( 16 / 24 )430.670752.21614421414415194.333359377661
Trimmed Mean ( 17 / 24 )430.7457894736842.21119107054048194.802608970557
Trimmed Mean ( 18 / 24 )430.8252777777782.20321595703893195.543826015493
Trimmed Mean ( 19 / 24 )430.9147058823532.18531801734915197.186268754176
Trimmed Mean ( 20 / 24 )431.008752.15590962717933199.919674074608
Trimmed Mean ( 21 / 24 )431.1056666666672.11266398715114204.057847953379
Trimmed Mean ( 22 / 24 )431.2603571428572.05960727764616209.389606369874
Trimmed Mean ( 23 / 24 )431.4607692307691.98222950802504217.664386229749
Trimmed Mean ( 24 / 24 )431.8416666666671.90434444830177226.766574214958
Median428.8
Midrange424.625
Midmean - Weighted Average at Xnp430.25972972973
Midmean - Weighted Average at X(n+1)p430.25972972973
Midmean - Empirical Distribution Function430.25972972973
Midmean - Empirical Distribution Function - Averaging430.25972972973
Midmean - Empirical Distribution Function - Interpolation430.25972972973
Midmean - Closest Observation430.25972972973
Midmean - True Basic - Statistics Graphics Toolkit430.25972972973
Midmean - MS Excel (old versions)430.745789473684
Number of observations72

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 428.168472222222 & 2.7145352367638 & 157.731779062361 \tabularnewline
Geometric Mean & 427.549957466556 &  &  \tabularnewline
Harmonic Mean & 426.924589752367 &  &  \tabularnewline
Quadratic Mean & 428.778985510342 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 428.190694444444 & 2.7087678476027 & 158.07581842918 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 428.205972222222 & 2.70336609611016 & 158.397330216711 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 428.150972222222 & 2.69452548192796 & 158.896612815061 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 428.171527777778 & 2.6778347028163 & 159.894681821647 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 428.188194444444 & 2.67426957782828 & 160.114073014347 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 428.188194444444 & 2.67426957782828 & 160.114073014347 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 428.122083333333 & 2.65755063710761 & 161.096491391519 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 428.12875 & 2.63586596682207 & 162.424324828691 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 428.0925 & 2.60565765768063 & 164.293455334826 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 427.724444444444 & 2.54879769201856 & 167.814199527818 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 427.345555555556 & 2.49850237528076 & 171.040684124839 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 427.325555555556 & 2.49594353914156 & 171.208021677657 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 428.228333333333 & 2.33427622632423 & 183.452296049668 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 429.503888888889 & 2.12463100502048 & 202.154580194855 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 429.505972222222 & 2.07086016938546 & 207.404622761024 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 430.037083333333 & 1.98901707031525 & 216.205828371887 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 430.070138888889 & 1.96443432321201 & 218.92823486493 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 430.065138888889 & 1.96376554534883 & 219.000246698235 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 430.120555555556 & 1.95356495575179 & 220.172129055228 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 430.201111111111 & 1.93351662110331 & 222.496722508456 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 429.842361111111 & 1.87405770263651 & 229.36452837412 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 429.668194444444 & 1.84312624937685 & 233.119242151596 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 428.540555555556 & 1.68763654045518 & 253.929412692126 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 428.540555555556 & 1.68763654045518 & 253.929412692126 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 428.269714285714 & 2.69642428645129 & 158.828755710902 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 428.353382352941 & 2.68008813564974 & 159.828095447725 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 428.433787878788 & 2.6622988100674 & 160.926259012955 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 428.53984375 & 2.64312242534591 & 162.133936604891 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 428.646774193548 & 2.62410082078032 & 163.349963842503 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 428.756833333333 & 2.60026728843029 & 164.889523181351 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 428.874482758621 & 2.56945822264534 & 166.912417169827 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 429.012678571429 & 2.53418758583485 & 169.290024530721 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 429.16 & 2.49421121553507 & 172.062412889093 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 429.324230769231 & 2.44980816723902 & 175.248101672012 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 429.5546 & 2.40456421797534 & 178.641350806463 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 429.855833333333 & 2.35540689730909 & 182.497484330379 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 430.185869565217 & 2.29069513690712 & 187.797085100574 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 430.432272727273 & 2.2444268742915 & 191.778256470551 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 430.545952380952 & 2.22935538720353 & 193.125759514288 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 430.67075 & 2.21614421414415 & 194.333359377661 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 430.745789473684 & 2.21119107054048 & 194.802608970557 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 430.825277777778 & 2.20321595703893 & 195.543826015493 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 430.914705882353 & 2.18531801734915 & 197.186268754176 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 431.00875 & 2.15590962717933 & 199.919674074608 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 431.105666666667 & 2.11266398715114 & 204.057847953379 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 431.260357142857 & 2.05960727764616 & 209.389606369874 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 431.460769230769 & 1.98222950802504 & 217.664386229749 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 431.841666666667 & 1.90434444830177 & 226.766574214958 \tabularnewline
Median & 428.8 &  &  \tabularnewline
Midrange & 424.625 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 430.25972972973 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 430.25972972973 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 430.25972972973 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 430.25972972973 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 430.25972972973 &  &  \tabularnewline
Midmean - Closest Observation & 430.25972972973 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 430.25972972973 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 430.745789473684 &  &  \tabularnewline
Number of observations & 72 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240438&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]428.168472222222[/C][C]2.7145352367638[/C][C]157.731779062361[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]427.549957466556[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]426.924589752367[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]428.778985510342[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]428.190694444444[/C][C]2.7087678476027[/C][C]158.07581842918[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]428.205972222222[/C][C]2.70336609611016[/C][C]158.397330216711[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]428.150972222222[/C][C]2.69452548192796[/C][C]158.896612815061[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]428.171527777778[/C][C]2.6778347028163[/C][C]159.894681821647[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]428.188194444444[/C][C]2.67426957782828[/C][C]160.114073014347[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]428.188194444444[/C][C]2.67426957782828[/C][C]160.114073014347[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]428.122083333333[/C][C]2.65755063710761[/C][C]161.096491391519[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]428.12875[/C][C]2.63586596682207[/C][C]162.424324828691[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]428.0925[/C][C]2.60565765768063[/C][C]164.293455334826[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]427.724444444444[/C][C]2.54879769201856[/C][C]167.814199527818[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]427.345555555556[/C][C]2.49850237528076[/C][C]171.040684124839[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]427.325555555556[/C][C]2.49594353914156[/C][C]171.208021677657[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]428.228333333333[/C][C]2.33427622632423[/C][C]183.452296049668[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]429.503888888889[/C][C]2.12463100502048[/C][C]202.154580194855[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]429.505972222222[/C][C]2.07086016938546[/C][C]207.404622761024[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]430.037083333333[/C][C]1.98901707031525[/C][C]216.205828371887[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]430.070138888889[/C][C]1.96443432321201[/C][C]218.92823486493[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]430.065138888889[/C][C]1.96376554534883[/C][C]219.000246698235[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]430.120555555556[/C][C]1.95356495575179[/C][C]220.172129055228[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]430.201111111111[/C][C]1.93351662110331[/C][C]222.496722508456[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]429.842361111111[/C][C]1.87405770263651[/C][C]229.36452837412[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]429.668194444444[/C][C]1.84312624937685[/C][C]233.119242151596[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]428.540555555556[/C][C]1.68763654045518[/C][C]253.929412692126[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]428.540555555556[/C][C]1.68763654045518[/C][C]253.929412692126[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]428.269714285714[/C][C]2.69642428645129[/C][C]158.828755710902[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]428.353382352941[/C][C]2.68008813564974[/C][C]159.828095447725[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]428.433787878788[/C][C]2.6622988100674[/C][C]160.926259012955[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]428.53984375[/C][C]2.64312242534591[/C][C]162.133936604891[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]428.646774193548[/C][C]2.62410082078032[/C][C]163.349963842503[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]428.756833333333[/C][C]2.60026728843029[/C][C]164.889523181351[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]428.874482758621[/C][C]2.56945822264534[/C][C]166.912417169827[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]429.012678571429[/C][C]2.53418758583485[/C][C]169.290024530721[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]429.16[/C][C]2.49421121553507[/C][C]172.062412889093[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]429.324230769231[/C][C]2.44980816723902[/C][C]175.248101672012[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]429.5546[/C][C]2.40456421797534[/C][C]178.641350806463[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]429.855833333333[/C][C]2.35540689730909[/C][C]182.497484330379[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]430.185869565217[/C][C]2.29069513690712[/C][C]187.797085100574[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]430.432272727273[/C][C]2.2444268742915[/C][C]191.778256470551[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]430.545952380952[/C][C]2.22935538720353[/C][C]193.125759514288[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]430.67075[/C][C]2.21614421414415[/C][C]194.333359377661[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]430.745789473684[/C][C]2.21119107054048[/C][C]194.802608970557[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]430.825277777778[/C][C]2.20321595703893[/C][C]195.543826015493[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]430.914705882353[/C][C]2.18531801734915[/C][C]197.186268754176[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]431.00875[/C][C]2.15590962717933[/C][C]199.919674074608[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]431.105666666667[/C][C]2.11266398715114[/C][C]204.057847953379[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]431.260357142857[/C][C]2.05960727764616[/C][C]209.389606369874[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]431.460769230769[/C][C]1.98222950802504[/C][C]217.664386229749[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]431.841666666667[/C][C]1.90434444830177[/C][C]226.766574214958[/C][/ROW]
[ROW][C]Median[/C][C]428.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]424.625[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]430.25972972973[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]430.745789473684[/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=240438&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240438&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 Mean428.1684722222222.7145352367638157.731779062361
Geometric Mean427.549957466556
Harmonic Mean426.924589752367
Quadratic Mean428.778985510342
Winsorized Mean ( 1 / 24 )428.1906944444442.7087678476027158.07581842918
Winsorized Mean ( 2 / 24 )428.2059722222222.70336609611016158.397330216711
Winsorized Mean ( 3 / 24 )428.1509722222222.69452548192796158.896612815061
Winsorized Mean ( 4 / 24 )428.1715277777782.6778347028163159.894681821647
Winsorized Mean ( 5 / 24 )428.1881944444442.67426957782828160.114073014347
Winsorized Mean ( 6 / 24 )428.1881944444442.67426957782828160.114073014347
Winsorized Mean ( 7 / 24 )428.1220833333332.65755063710761161.096491391519
Winsorized Mean ( 8 / 24 )428.128752.63586596682207162.424324828691
Winsorized Mean ( 9 / 24 )428.09252.60565765768063164.293455334826
Winsorized Mean ( 10 / 24 )427.7244444444442.54879769201856167.814199527818
Winsorized Mean ( 11 / 24 )427.3455555555562.49850237528076171.040684124839
Winsorized Mean ( 12 / 24 )427.3255555555562.49594353914156171.208021677657
Winsorized Mean ( 13 / 24 )428.2283333333332.33427622632423183.452296049668
Winsorized Mean ( 14 / 24 )429.5038888888892.12463100502048202.154580194855
Winsorized Mean ( 15 / 24 )429.5059722222222.07086016938546207.404622761024
Winsorized Mean ( 16 / 24 )430.0370833333331.98901707031525216.205828371887
Winsorized Mean ( 17 / 24 )430.0701388888891.96443432321201218.92823486493
Winsorized Mean ( 18 / 24 )430.0651388888891.96376554534883219.000246698235
Winsorized Mean ( 19 / 24 )430.1205555555561.95356495575179220.172129055228
Winsorized Mean ( 20 / 24 )430.2011111111111.93351662110331222.496722508456
Winsorized Mean ( 21 / 24 )429.8423611111111.87405770263651229.36452837412
Winsorized Mean ( 22 / 24 )429.6681944444441.84312624937685233.119242151596
Winsorized Mean ( 23 / 24 )428.5405555555561.68763654045518253.929412692126
Winsorized Mean ( 24 / 24 )428.5405555555561.68763654045518253.929412692126
Trimmed Mean ( 1 / 24 )428.2697142857142.69642428645129158.828755710902
Trimmed Mean ( 2 / 24 )428.3533823529412.68008813564974159.828095447725
Trimmed Mean ( 3 / 24 )428.4337878787882.6622988100674160.926259012955
Trimmed Mean ( 4 / 24 )428.539843752.64312242534591162.133936604891
Trimmed Mean ( 5 / 24 )428.6467741935482.62410082078032163.349963842503
Trimmed Mean ( 6 / 24 )428.7568333333332.60026728843029164.889523181351
Trimmed Mean ( 7 / 24 )428.8744827586212.56945822264534166.912417169827
Trimmed Mean ( 8 / 24 )429.0126785714292.53418758583485169.290024530721
Trimmed Mean ( 9 / 24 )429.162.49421121553507172.062412889093
Trimmed Mean ( 10 / 24 )429.3242307692312.44980816723902175.248101672012
Trimmed Mean ( 11 / 24 )429.55462.40456421797534178.641350806463
Trimmed Mean ( 12 / 24 )429.8558333333332.35540689730909182.497484330379
Trimmed Mean ( 13 / 24 )430.1858695652172.29069513690712187.797085100574
Trimmed Mean ( 14 / 24 )430.4322727272732.2444268742915191.778256470551
Trimmed Mean ( 15 / 24 )430.5459523809522.22935538720353193.125759514288
Trimmed Mean ( 16 / 24 )430.670752.21614421414415194.333359377661
Trimmed Mean ( 17 / 24 )430.7457894736842.21119107054048194.802608970557
Trimmed Mean ( 18 / 24 )430.8252777777782.20321595703893195.543826015493
Trimmed Mean ( 19 / 24 )430.9147058823532.18531801734915197.186268754176
Trimmed Mean ( 20 / 24 )431.008752.15590962717933199.919674074608
Trimmed Mean ( 21 / 24 )431.1056666666672.11266398715114204.057847953379
Trimmed Mean ( 22 / 24 )431.2603571428572.05960727764616209.389606369874
Trimmed Mean ( 23 / 24 )431.4607692307691.98222950802504217.664386229749
Trimmed Mean ( 24 / 24 )431.8416666666671.90434444830177226.766574214958
Median428.8
Midrange424.625
Midmean - Weighted Average at Xnp430.25972972973
Midmean - Weighted Average at X(n+1)p430.25972972973
Midmean - Empirical Distribution Function430.25972972973
Midmean - Empirical Distribution Function - Averaging430.25972972973
Midmean - Empirical Distribution Function - Interpolation430.25972972973
Midmean - Closest Observation430.25972972973
Midmean - True Basic - Statistics Graphics Toolkit430.25972972973
Midmean - MS Excel (old versions)430.745789473684
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')