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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 02 Nov 2009 10:44:31 -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/2009/Nov/02/t1257183918ip165b7jyc6ms9f.htm/, Retrieved Fri, 03 May 2024 17:53:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52840, Retrieved Fri, 03 May 2024 17:53:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD    [Central Tendency] [Mediaan et ws4 ] [2009-11-02 17:44:31] [85defb7a20869746625978e6577e6e44] [Current]
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Dataseries X:
-50566.58
-50456.92
-51804.40
-53008.76
-51497.14
-48996.68
-47558.58
-44905.97
-42342.64
-42983.58
-44028.86
-46258.19
-47048.52
-45316.23
-44893.36
-43923.51
-44595.87
-43017.49
-48058.59
-45622.71
-47664.51
-47983.56
-50060.14
-47405.39
-49135.11
-50770.80
-50437.73
-50217.07
-49156.11
-47104.38
-48461.36
-49043.39
-53382.58
-49500.68
-47858.33
-52031.39
-51444.72
-54766.25
-54798.28
-55588.03
-57106.30
-59181.36
-58235.45
-56786.09
-56330.99
-59279.59
-59798.96
-58381.20
-56082.79
-50409.22
-52538.82
-63398.94
-59937.19
-52781.35
-50701.03
-50369.41
-52630.49
-54779.01
-53888.16
-51194.23
-47620.97
-42658.42
-50855.26
-53888.66
-45698.38
-49194.04
-45740.82
-40692.82
-34532.97
-19367.74




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52840&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]3 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=52840&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52840&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-49825.0721428571764.395271521012-65.1823395554424
Geometric MeanNaN
Harmonic Mean-48620.8907047857
Quadratic Mean50228.0252756213
Winsorized Mean ( 1 / 23 )-49992.2647142857650.5957206509-76.8407524480334
Winsorized Mean ( 2 / 23 )-50164.311598.802198834812-83.7744268434768
Winsorized Mean ( 3 / 23 )-50212.7588571429578.585035405387-86.7854434257207
Winsorized Mean ( 4 / 23 )-50225.1902857143573.809626729071-87.5293615619812
Winsorized Mean ( 5 / 23 )-50191.2617142857556.849912086483-90.1342724940409
Winsorized Mean ( 6 / 23 )-50181.6754285714553.656392345317-90.6368573042194
Winsorized Mean ( 7 / 23 )-50159.3624285714514.190894070548-97.5500791767997
Winsorized Mean ( 8 / 23 )-50134.807505.001636356505-99.2765238578504
Winsorized Mean ( 9 / 23 )-50149.1954285714481.482659592544-104.155766421599
Winsorized Mean ( 10 / 23 )-50156.2368571429467.911835071503-107.191639744437
Winsorized Mean ( 11 / 23 )-50080.4704285714453.605534572953-110.405333735003
Winsorized Mean ( 12 / 23 )-50015.415418.93074884325-119.388264380455
Winsorized Mean ( 13 / 23 )-50068.754409.227026596275-122.349577974955
Winsorized Mean ( 14 / 23 )-50081.336406.426844793392-123.2234943178
Winsorized Mean ( 15 / 23 )-49902.3752857143374.731659169771-133.168292735859
Winsorized Mean ( 16 / 23 )-50020.517356.132590419955-140.454758552188
Winsorized Mean ( 17 / 23 )-50089.6705714286308.485286643032-162.372964741721
Winsorized Mean ( 18 / 23 )-50007.9094285714291.817913014227-171.366825675754
Winsorized Mean ( 19 / 23 )-50027.8865714286271.047385218191-184.572474407589
Winsorized Mean ( 20 / 23 )-50028.5522857143258.63291904071-193.43458857161
Winsorized Mean ( 21 / 23 )-50019.7682857143252.050057741993-198.451723176815
Winsorized Mean ( 22 / 23 )-49873.9742857143227.610901248481-219.119444684538
Winsorized Mean ( 23 / 23 )-49863.0755714286208.535032086789-239.111266210064
Trimmed Mean ( 1 / 23 )-50073.3583823529611.938357931917-81.8274548952592
Trimmed Mean ( 2 / 23 )-50159.3668181818564.446147371661-88.8647518487786
Trimmed Mean ( 3 / 23 )-50156.66296875541.953660536199-92.5478811585587
Trimmed Mean ( 4 / 23 )-50135.5516129032524.376574777334-95.6098232156773
Trimmed Mean ( 5 / 23 )-50109.407504.825409498555-99.2608653549627
Trimmed Mean ( 6 / 23 )-50089.6489655172486.646165460732-102.928272162784
Trimmed Mean ( 7 / 23 )-50070.4767857143465.201978943758-107.631693440770
Trimmed Mean ( 8 / 23 )-50054.0164814815449.881199599773-111.260520613022
Trimmed Mean ( 9 / 23 )-50040.4219230769433.172075058934-115.520886050350
Trimmed Mean ( 10 / 23 )-50023.5016418.153078293677-119.629638514505
Trimmed Mean ( 11 / 23 )-50004.144375402.417383881562-124.259404235174
Trimmed Mean ( 12 / 23 )-49993.5854347826385.836057329566-129.572092823041
Trimmed Mean ( 13 / 23 )-49990.6913636364372.974924221811-134.03231187174
Trimmed Mean ( 14 / 23 )-49980.6833333333358.394611454941-139.457128360361
Trimmed Mean ( 15 / 23 )-49968.10175339.625652816844-147.12699507698
Trimmed Mean ( 16 / 23 )-49976.1734210526323.010319785527-154.720051836845
Trimmed Mean ( 17 / 23 )-49970.7844444444305.463299138191-163.590141877692
Trimmed Mean ( 18 / 23 )-49956.3864705882294.605140009375-169.570654704119
Trimmed Mean ( 19 / 23 )-49950.125283.854261532074-175.971023758457
Trimmed Mean ( 20 / 23 )-49940.5753333333274.247997406213-182.100054715667
Trimmed Mean ( 21 / 23 )-49929.5782142857263.577041745794-189.430679863386
Trimmed Mean ( 22 / 23 )-49918.0153846154249.245597399729-200.276417739725
Trimmed Mean ( 23 / 23 )-49923.8541666667236.347248631837-211.230951304341
Median-50293.24
Midrange-41383.34
Midmean - Weighted Average at Xnp-50054.2777142857
Midmean - Weighted Average at X(n+1)p-49970.7844444444
Midmean - Empirical Distribution Function-49970.7844444444
Midmean - Empirical Distribution Function - Averaging-49970.7844444444
Midmean - Empirical Distribution Function - Interpolation-49956.3864705882
Midmean - Closest Observation-49970.7844444444
Midmean - True Basic - Statistics Graphics Toolkit-49970.7844444444
Midmean - MS Excel (old versions)-49970.7844444444
Number of observations70

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -49825.0721428571 & 764.395271521012 & -65.1823395554424 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -48620.8907047857 &  &  \tabularnewline
Quadratic Mean & 50228.0252756213 &  &  \tabularnewline
Winsorized Mean ( 1 / 23 ) & -49992.2647142857 & 650.5957206509 & -76.8407524480334 \tabularnewline
Winsorized Mean ( 2 / 23 ) & -50164.311 & 598.802198834812 & -83.7744268434768 \tabularnewline
Winsorized Mean ( 3 / 23 ) & -50212.7588571429 & 578.585035405387 & -86.7854434257207 \tabularnewline
Winsorized Mean ( 4 / 23 ) & -50225.1902857143 & 573.809626729071 & -87.5293615619812 \tabularnewline
Winsorized Mean ( 5 / 23 ) & -50191.2617142857 & 556.849912086483 & -90.1342724940409 \tabularnewline
Winsorized Mean ( 6 / 23 ) & -50181.6754285714 & 553.656392345317 & -90.6368573042194 \tabularnewline
Winsorized Mean ( 7 / 23 ) & -50159.3624285714 & 514.190894070548 & -97.5500791767997 \tabularnewline
Winsorized Mean ( 8 / 23 ) & -50134.807 & 505.001636356505 & -99.2765238578504 \tabularnewline
Winsorized Mean ( 9 / 23 ) & -50149.1954285714 & 481.482659592544 & -104.155766421599 \tabularnewline
Winsorized Mean ( 10 / 23 ) & -50156.2368571429 & 467.911835071503 & -107.191639744437 \tabularnewline
Winsorized Mean ( 11 / 23 ) & -50080.4704285714 & 453.605534572953 & -110.405333735003 \tabularnewline
Winsorized Mean ( 12 / 23 ) & -50015.415 & 418.93074884325 & -119.388264380455 \tabularnewline
Winsorized Mean ( 13 / 23 ) & -50068.754 & 409.227026596275 & -122.349577974955 \tabularnewline
Winsorized Mean ( 14 / 23 ) & -50081.336 & 406.426844793392 & -123.2234943178 \tabularnewline
Winsorized Mean ( 15 / 23 ) & -49902.3752857143 & 374.731659169771 & -133.168292735859 \tabularnewline
Winsorized Mean ( 16 / 23 ) & -50020.517 & 356.132590419955 & -140.454758552188 \tabularnewline
Winsorized Mean ( 17 / 23 ) & -50089.6705714286 & 308.485286643032 & -162.372964741721 \tabularnewline
Winsorized Mean ( 18 / 23 ) & -50007.9094285714 & 291.817913014227 & -171.366825675754 \tabularnewline
Winsorized Mean ( 19 / 23 ) & -50027.8865714286 & 271.047385218191 & -184.572474407589 \tabularnewline
Winsorized Mean ( 20 / 23 ) & -50028.5522857143 & 258.63291904071 & -193.43458857161 \tabularnewline
Winsorized Mean ( 21 / 23 ) & -50019.7682857143 & 252.050057741993 & -198.451723176815 \tabularnewline
Winsorized Mean ( 22 / 23 ) & -49873.9742857143 & 227.610901248481 & -219.119444684538 \tabularnewline
Winsorized Mean ( 23 / 23 ) & -49863.0755714286 & 208.535032086789 & -239.111266210064 \tabularnewline
Trimmed Mean ( 1 / 23 ) & -50073.3583823529 & 611.938357931917 & -81.8274548952592 \tabularnewline
Trimmed Mean ( 2 / 23 ) & -50159.3668181818 & 564.446147371661 & -88.8647518487786 \tabularnewline
Trimmed Mean ( 3 / 23 ) & -50156.66296875 & 541.953660536199 & -92.5478811585587 \tabularnewline
Trimmed Mean ( 4 / 23 ) & -50135.5516129032 & 524.376574777334 & -95.6098232156773 \tabularnewline
Trimmed Mean ( 5 / 23 ) & -50109.407 & 504.825409498555 & -99.2608653549627 \tabularnewline
Trimmed Mean ( 6 / 23 ) & -50089.6489655172 & 486.646165460732 & -102.928272162784 \tabularnewline
Trimmed Mean ( 7 / 23 ) & -50070.4767857143 & 465.201978943758 & -107.631693440770 \tabularnewline
Trimmed Mean ( 8 / 23 ) & -50054.0164814815 & 449.881199599773 & -111.260520613022 \tabularnewline
Trimmed Mean ( 9 / 23 ) & -50040.4219230769 & 433.172075058934 & -115.520886050350 \tabularnewline
Trimmed Mean ( 10 / 23 ) & -50023.5016 & 418.153078293677 & -119.629638514505 \tabularnewline
Trimmed Mean ( 11 / 23 ) & -50004.144375 & 402.417383881562 & -124.259404235174 \tabularnewline
Trimmed Mean ( 12 / 23 ) & -49993.5854347826 & 385.836057329566 & -129.572092823041 \tabularnewline
Trimmed Mean ( 13 / 23 ) & -49990.6913636364 & 372.974924221811 & -134.03231187174 \tabularnewline
Trimmed Mean ( 14 / 23 ) & -49980.6833333333 & 358.394611454941 & -139.457128360361 \tabularnewline
Trimmed Mean ( 15 / 23 ) & -49968.10175 & 339.625652816844 & -147.12699507698 \tabularnewline
Trimmed Mean ( 16 / 23 ) & -49976.1734210526 & 323.010319785527 & -154.720051836845 \tabularnewline
Trimmed Mean ( 17 / 23 ) & -49970.7844444444 & 305.463299138191 & -163.590141877692 \tabularnewline
Trimmed Mean ( 18 / 23 ) & -49956.3864705882 & 294.605140009375 & -169.570654704119 \tabularnewline
Trimmed Mean ( 19 / 23 ) & -49950.125 & 283.854261532074 & -175.971023758457 \tabularnewline
Trimmed Mean ( 20 / 23 ) & -49940.5753333333 & 274.247997406213 & -182.100054715667 \tabularnewline
Trimmed Mean ( 21 / 23 ) & -49929.5782142857 & 263.577041745794 & -189.430679863386 \tabularnewline
Trimmed Mean ( 22 / 23 ) & -49918.0153846154 & 249.245597399729 & -200.276417739725 \tabularnewline
Trimmed Mean ( 23 / 23 ) & -49923.8541666667 & 236.347248631837 & -211.230951304341 \tabularnewline
Median & -50293.24 &  &  \tabularnewline
Midrange & -41383.34 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -50054.2777142857 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -49970.7844444444 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -49970.7844444444 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -49970.7844444444 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -49956.3864705882 &  &  \tabularnewline
Midmean - Closest Observation & -49970.7844444444 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -49970.7844444444 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -49970.7844444444 &  &  \tabularnewline
Number of observations & 70 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52840&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]-49825.0721428571[/C][C]764.395271521012[/C][C]-65.1823395554424[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-48620.8907047857[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]50228.0252756213[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 23 )[/C][C]-49992.2647142857[/C][C]650.5957206509[/C][C]-76.8407524480334[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 23 )[/C][C]-50164.311[/C][C]598.802198834812[/C][C]-83.7744268434768[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 23 )[/C][C]-50212.7588571429[/C][C]578.585035405387[/C][C]-86.7854434257207[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 23 )[/C][C]-50225.1902857143[/C][C]573.809626729071[/C][C]-87.5293615619812[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 23 )[/C][C]-50191.2617142857[/C][C]556.849912086483[/C][C]-90.1342724940409[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 23 )[/C][C]-50181.6754285714[/C][C]553.656392345317[/C][C]-90.6368573042194[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 23 )[/C][C]-50159.3624285714[/C][C]514.190894070548[/C][C]-97.5500791767997[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 23 )[/C][C]-50134.807[/C][C]505.001636356505[/C][C]-99.2765238578504[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 23 )[/C][C]-50149.1954285714[/C][C]481.482659592544[/C][C]-104.155766421599[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 23 )[/C][C]-50156.2368571429[/C][C]467.911835071503[/C][C]-107.191639744437[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 23 )[/C][C]-50080.4704285714[/C][C]453.605534572953[/C][C]-110.405333735003[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 23 )[/C][C]-50015.415[/C][C]418.93074884325[/C][C]-119.388264380455[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 23 )[/C][C]-50068.754[/C][C]409.227026596275[/C][C]-122.349577974955[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 23 )[/C][C]-50081.336[/C][C]406.426844793392[/C][C]-123.2234943178[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 23 )[/C][C]-49902.3752857143[/C][C]374.731659169771[/C][C]-133.168292735859[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 23 )[/C][C]-50020.517[/C][C]356.132590419955[/C][C]-140.454758552188[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 23 )[/C][C]-50089.6705714286[/C][C]308.485286643032[/C][C]-162.372964741721[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 23 )[/C][C]-50007.9094285714[/C][C]291.817913014227[/C][C]-171.366825675754[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 23 )[/C][C]-50027.8865714286[/C][C]271.047385218191[/C][C]-184.572474407589[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 23 )[/C][C]-50028.5522857143[/C][C]258.63291904071[/C][C]-193.43458857161[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 23 )[/C][C]-50019.7682857143[/C][C]252.050057741993[/C][C]-198.451723176815[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 23 )[/C][C]-49873.9742857143[/C][C]227.610901248481[/C][C]-219.119444684538[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 23 )[/C][C]-49863.0755714286[/C][C]208.535032086789[/C][C]-239.111266210064[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 23 )[/C][C]-50073.3583823529[/C][C]611.938357931917[/C][C]-81.8274548952592[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 23 )[/C][C]-50159.3668181818[/C][C]564.446147371661[/C][C]-88.8647518487786[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 23 )[/C][C]-50156.66296875[/C][C]541.953660536199[/C][C]-92.5478811585587[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 23 )[/C][C]-50135.5516129032[/C][C]524.376574777334[/C][C]-95.6098232156773[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 23 )[/C][C]-50109.407[/C][C]504.825409498555[/C][C]-99.2608653549627[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 23 )[/C][C]-50089.6489655172[/C][C]486.646165460732[/C][C]-102.928272162784[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 23 )[/C][C]-50070.4767857143[/C][C]465.201978943758[/C][C]-107.631693440770[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 23 )[/C][C]-50054.0164814815[/C][C]449.881199599773[/C][C]-111.260520613022[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 23 )[/C][C]-50040.4219230769[/C][C]433.172075058934[/C][C]-115.520886050350[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 23 )[/C][C]-50023.5016[/C][C]418.153078293677[/C][C]-119.629638514505[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 23 )[/C][C]-50004.144375[/C][C]402.417383881562[/C][C]-124.259404235174[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 23 )[/C][C]-49993.5854347826[/C][C]385.836057329566[/C][C]-129.572092823041[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 23 )[/C][C]-49990.6913636364[/C][C]372.974924221811[/C][C]-134.03231187174[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 23 )[/C][C]-49980.6833333333[/C][C]358.394611454941[/C][C]-139.457128360361[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 23 )[/C][C]-49968.10175[/C][C]339.625652816844[/C][C]-147.12699507698[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 23 )[/C][C]-49976.1734210526[/C][C]323.010319785527[/C][C]-154.720051836845[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 23 )[/C][C]-49970.7844444444[/C][C]305.463299138191[/C][C]-163.590141877692[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 23 )[/C][C]-49956.3864705882[/C][C]294.605140009375[/C][C]-169.570654704119[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 23 )[/C][C]-49950.125[/C][C]283.854261532074[/C][C]-175.971023758457[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 23 )[/C][C]-49940.5753333333[/C][C]274.247997406213[/C][C]-182.100054715667[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 23 )[/C][C]-49929.5782142857[/C][C]263.577041745794[/C][C]-189.430679863386[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 23 )[/C][C]-49918.0153846154[/C][C]249.245597399729[/C][C]-200.276417739725[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 23 )[/C][C]-49923.8541666667[/C][C]236.347248631837[/C][C]-211.230951304341[/C][/ROW]
[ROW][C]Median[/C][C]-50293.24[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-41383.34[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-50054.2777142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-49970.7844444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-49970.7844444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-49970.7844444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-49956.3864705882[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-49970.7844444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-49970.7844444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-49970.7844444444[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]70[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52840&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52840&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 Mean-49825.0721428571764.395271521012-65.1823395554424
Geometric MeanNaN
Harmonic Mean-48620.8907047857
Quadratic Mean50228.0252756213
Winsorized Mean ( 1 / 23 )-49992.2647142857650.5957206509-76.8407524480334
Winsorized Mean ( 2 / 23 )-50164.311598.802198834812-83.7744268434768
Winsorized Mean ( 3 / 23 )-50212.7588571429578.585035405387-86.7854434257207
Winsorized Mean ( 4 / 23 )-50225.1902857143573.809626729071-87.5293615619812
Winsorized Mean ( 5 / 23 )-50191.2617142857556.849912086483-90.1342724940409
Winsorized Mean ( 6 / 23 )-50181.6754285714553.656392345317-90.6368573042194
Winsorized Mean ( 7 / 23 )-50159.3624285714514.190894070548-97.5500791767997
Winsorized Mean ( 8 / 23 )-50134.807505.001636356505-99.2765238578504
Winsorized Mean ( 9 / 23 )-50149.1954285714481.482659592544-104.155766421599
Winsorized Mean ( 10 / 23 )-50156.2368571429467.911835071503-107.191639744437
Winsorized Mean ( 11 / 23 )-50080.4704285714453.605534572953-110.405333735003
Winsorized Mean ( 12 / 23 )-50015.415418.93074884325-119.388264380455
Winsorized Mean ( 13 / 23 )-50068.754409.227026596275-122.349577974955
Winsorized Mean ( 14 / 23 )-50081.336406.426844793392-123.2234943178
Winsorized Mean ( 15 / 23 )-49902.3752857143374.731659169771-133.168292735859
Winsorized Mean ( 16 / 23 )-50020.517356.132590419955-140.454758552188
Winsorized Mean ( 17 / 23 )-50089.6705714286308.485286643032-162.372964741721
Winsorized Mean ( 18 / 23 )-50007.9094285714291.817913014227-171.366825675754
Winsorized Mean ( 19 / 23 )-50027.8865714286271.047385218191-184.572474407589
Winsorized Mean ( 20 / 23 )-50028.5522857143258.63291904071-193.43458857161
Winsorized Mean ( 21 / 23 )-50019.7682857143252.050057741993-198.451723176815
Winsorized Mean ( 22 / 23 )-49873.9742857143227.610901248481-219.119444684538
Winsorized Mean ( 23 / 23 )-49863.0755714286208.535032086789-239.111266210064
Trimmed Mean ( 1 / 23 )-50073.3583823529611.938357931917-81.8274548952592
Trimmed Mean ( 2 / 23 )-50159.3668181818564.446147371661-88.8647518487786
Trimmed Mean ( 3 / 23 )-50156.66296875541.953660536199-92.5478811585587
Trimmed Mean ( 4 / 23 )-50135.5516129032524.376574777334-95.6098232156773
Trimmed Mean ( 5 / 23 )-50109.407504.825409498555-99.2608653549627
Trimmed Mean ( 6 / 23 )-50089.6489655172486.646165460732-102.928272162784
Trimmed Mean ( 7 / 23 )-50070.4767857143465.201978943758-107.631693440770
Trimmed Mean ( 8 / 23 )-50054.0164814815449.881199599773-111.260520613022
Trimmed Mean ( 9 / 23 )-50040.4219230769433.172075058934-115.520886050350
Trimmed Mean ( 10 / 23 )-50023.5016418.153078293677-119.629638514505
Trimmed Mean ( 11 / 23 )-50004.144375402.417383881562-124.259404235174
Trimmed Mean ( 12 / 23 )-49993.5854347826385.836057329566-129.572092823041
Trimmed Mean ( 13 / 23 )-49990.6913636364372.974924221811-134.03231187174
Trimmed Mean ( 14 / 23 )-49980.6833333333358.394611454941-139.457128360361
Trimmed Mean ( 15 / 23 )-49968.10175339.625652816844-147.12699507698
Trimmed Mean ( 16 / 23 )-49976.1734210526323.010319785527-154.720051836845
Trimmed Mean ( 17 / 23 )-49970.7844444444305.463299138191-163.590141877692
Trimmed Mean ( 18 / 23 )-49956.3864705882294.605140009375-169.570654704119
Trimmed Mean ( 19 / 23 )-49950.125283.854261532074-175.971023758457
Trimmed Mean ( 20 / 23 )-49940.5753333333274.247997406213-182.100054715667
Trimmed Mean ( 21 / 23 )-49929.5782142857263.577041745794-189.430679863386
Trimmed Mean ( 22 / 23 )-49918.0153846154249.245597399729-200.276417739725
Trimmed Mean ( 23 / 23 )-49923.8541666667236.347248631837-211.230951304341
Median-50293.24
Midrange-41383.34
Midmean - Weighted Average at Xnp-50054.2777142857
Midmean - Weighted Average at X(n+1)p-49970.7844444444
Midmean - Empirical Distribution Function-49970.7844444444
Midmean - Empirical Distribution Function - Averaging-49970.7844444444
Midmean - Empirical Distribution Function - Interpolation-49956.3864705882
Midmean - Closest Observation-49970.7844444444
Midmean - True Basic - Statistics Graphics Toolkit-49970.7844444444
Midmean - MS Excel (old versions)-49970.7844444444
Number of observations70



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')