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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 computationTue, 20 Jan 2015 21:35:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Jan/20/t1421789796xehlrxx63agystv.htm/, Retrieved Wed, 15 May 2024 02:57:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=275476, Retrieved Wed, 15 May 2024 02:57:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact70
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2013-11-04 07:24:05] [0307e7a6407eb638caabc417e3a6b260]
-  M    [Multiple Regression] [oef WS7 5] [2015-01-20 19:57:41] [bb1b6762b7e5624d262776d3f7139d34]
- RMPD    [Spectral Analysis] [oef WS9 2] [2015-01-20 21:09:32] [bb1b6762b7e5624d262776d3f7139d34]
- RM        [(Partial) Autocorrelation Function] [oef WS9 ACF 1 ] [2015-01-20 21:14:46] [bb1b6762b7e5624d262776d3f7139d34]
- RM D          [Central Tendency] [oef WS9 central t...] [2015-01-20 21:35:42] [8568a324fefbb8dbb43f697bfa8d1be6] [Current]
Feedback Forum

Post a new message
Dataseries X:
867.887509505204
-2250.28069475706
33618.356965784
9954.34444592902
354.19174792562
18882.4059848456
20229.4309143634
268402.415800735
-113346.928018808
-45016.3930870888
35069.8581927414
58531.0974683435
-77256.3771966299
-31473.5947870219
-52391.0075621489
32854.9859435725
101107.732677222
-176275.960473942
79531.8855377519
-176414.252881799
151290.583018155
167731.591284544
143237.123984833
80251.9641959216
118735.723920888
75035.8242647686
19198.3069299239
-36364.565244121
-36170.5788957657
-109567.395737977
-100783.334905072
-149267.40456006
38947.3539988643
58613.0612764424
16074.4618904611
-41563.0054471834
-15970.5960147386
-47563.9543407556
59595.3586354662
65897.8398819312
-166489.283404707
46312.3277180123
-15952.8741348381
-87780.6497165994
134744.171799582
75232.8110734522
24408.7565122573
-15406.1428224565
-3766.75426023186
27197.2235783702
-46777.2891917652
-82472.8205054209
-35154.7186673461
-46946.8689402549
-43641.5350003634
-54920.7077875747
54905.4050480593
-10509.5838823069
-13706.8037712772
-42347.6091932919
-28990.4681222014




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=275476&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=275476&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=275476&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1807.7826713466810863.31319102190.166411723528393
Geometric MeanNaN
Harmonic Mean19115.3073001661
Quadratic Mean84166.2788019087
Winsorized Mean ( 1 / 20 )159.70837448874510298.3553695830.0155081436556808
Winsorized Mean ( 2 / 20 )-58.46641886056710067.6346767756-0.00580736396757024
Winsorized Mean ( 3 / 20 )392.4394734996789744.393709302170.040273359760192
Winsorized Mean ( 4 / 20 )2190.965660778439054.613640503720.241972296971088
Winsorized Mean ( 5 / 20 )1188.595529806068680.325204019770.1369298386719
Winsorized Mean ( 6 / 20 )318.7007353049748123.282277561230.0392330002104339
Winsorized Mean ( 7 / 20 )-582.4727573146097352.57471228858-0.0792202432626906
Winsorized Mean ( 8 / 20 )19.19944635867797199.948882853360.00266660870390362
Winsorized Mean ( 9 / 20 )154.5489480049356939.299701511270.0222715482329257
Winsorized Mean ( 10 / 20 )3783.841177574056306.225743668520.600016766189038
Winsorized Mean ( 11 / 20 )2592.183378696545933.687554080470.436858758583261
Winsorized Mean ( 12 / 20 )2301.935242616875572.90050314960.41305873688502
Winsorized Mean ( 13 / 20 )2224.103185882445517.563410181680.403095174543577
Winsorized Mean ( 14 / 20 )2244.211762365575508.582889795070.407402739917573
Winsorized Mean ( 15 / 20 )1785.655291314475294.075070159960.337293156528761
Winsorized Mean ( 16 / 20 )-107.6481167698844872.88803900514-0.0220912354045921
Winsorized Mean ( 17 / 20 )-1799.579502102674500.86866562543-0.399829374237608
Winsorized Mean ( 18 / 20 )-2712.236175549554295.80270187633-0.63136888813932
Winsorized Mean ( 19 / 20 )-1545.156822336523989.50768400466-0.387305137556595
Winsorized Mean ( 20 / 20 )-1731.84032196153943.57669075126-0.43915472115025
Trimmed Mean ( 1 / 20 )309.9420344612119804.551098586210.0316120576398346
Trimmed Mean ( 2 / 20 )470.71840741429192.663106450880.051205880381266
Trimmed Mean ( 3 / 20 )764.1754474392988589.26440802460.0889686719534866
Trimmed Mean ( 4 / 20 )906.7911355544997998.186280178490.113374595663239
Trimmed Mean ( 5 / 20 )522.7977726198917549.31900518390.0692509843948707
Trimmed Mean ( 6 / 20 )357.0277187898667120.042772327180.0501440412938941
Trimmed Mean ( 7 / 20 )365.3183074160316761.928187579060.0540257597066886
Trimmed Mean ( 8 / 20 )548.858799316256540.529309873520.0839165720865584
Trimmed Mean ( 9 / 20 )642.7809520209366295.165918017510.102107070789226
Trimmed Mean ( 10 / 20 )723.4913917092186045.455925649620.119675240479315
Trimmed Mean ( 11 / 20 )244.8212969970265884.081871519930.0416073913216618
Trimmed Mean ( 12 / 20 )-106.9946415377915762.11328015371-0.0185686459699274
Trimmed Mean ( 13 / 20 )-456.8630294745395680.88186912329-0.0804211458713267
Trimmed Mean ( 14 / 20 )-838.0726778120115568.85329986601-0.150492863195404
Trimmed Mean ( 15 / 20 )-1271.296988528225398.91247825308-0.235472790797966
Trimmed Mean ( 16 / 20 )-1699.973055356735209.06438267189-0.32634901979936
Trimmed Mean ( 17 / 20 )-1924.815234184975059.1167620251-0.380464678861155
Trimmed Mean ( 18 / 20 )-1942.790245142664943.49883623011-0.392999029534358
Trimmed Mean ( 19 / 20 )-1829.417777135854813.2958195162-0.380075907597079
Trimmed Mean ( 20 / 20 )-1872.876218847024698.94983627614-0.398573358750995
Median-2250.28069475706
Midrange45994.081459468
Midmean - Weighted Average at Xnp-3143.85372308113
Midmean - Weighted Average at X(n+1)p-1271.29698852822
Midmean - Empirical Distribution Function-1271.29698852822
Midmean - Empirical Distribution Function - Averaging-1271.29698852822
Midmean - Empirical Distribution Function - Interpolation-1271.29698852822
Midmean - Closest Observation-2693.35924487937
Midmean - True Basic - Statistics Graphics Toolkit-1271.29698852822
Midmean - MS Excel (old versions)-1271.29698852822
Number of observations61

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1807.78267134668 & 10863.3131910219 & 0.166411723528393 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 19115.3073001661 &  &  \tabularnewline
Quadratic Mean & 84166.2788019087 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 159.708374488745 & 10298.355369583 & 0.0155081436556808 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -58.466418860567 & 10067.6346767756 & -0.00580736396757024 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 392.439473499678 & 9744.39370930217 & 0.040273359760192 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 2190.96566077843 & 9054.61364050372 & 0.241972296971088 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 1188.59552980606 & 8680.32520401977 & 0.1369298386719 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 318.700735304974 & 8123.28227756123 & 0.0392330002104339 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -582.472757314609 & 7352.57471228858 & -0.0792202432626906 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 19.1994463586779 & 7199.94888285336 & 0.00266660870390362 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 154.548948004935 & 6939.29970151127 & 0.0222715482329257 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 3783.84117757405 & 6306.22574366852 & 0.600016766189038 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 2592.18337869654 & 5933.68755408047 & 0.436858758583261 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 2301.93524261687 & 5572.9005031496 & 0.41305873688502 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 2224.10318588244 & 5517.56341018168 & 0.403095174543577 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 2244.21176236557 & 5508.58288979507 & 0.407402739917573 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 1785.65529131447 & 5294.07507015996 & 0.337293156528761 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -107.648116769884 & 4872.88803900514 & -0.0220912354045921 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -1799.57950210267 & 4500.86866562543 & -0.399829374237608 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -2712.23617554955 & 4295.80270187633 & -0.63136888813932 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -1545.15682233652 & 3989.50768400466 & -0.387305137556595 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -1731.8403219615 & 3943.57669075126 & -0.43915472115025 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 309.942034461211 & 9804.55109858621 & 0.0316120576398346 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 470.7184074142 & 9192.66310645088 & 0.051205880381266 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 764.175447439298 & 8589.2644080246 & 0.0889686719534866 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 906.791135554499 & 7998.18628017849 & 0.113374595663239 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 522.797772619891 & 7549.3190051839 & 0.0692509843948707 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 357.027718789866 & 7120.04277232718 & 0.0501440412938941 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 365.318307416031 & 6761.92818757906 & 0.0540257597066886 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 548.85879931625 & 6540.52930987352 & 0.0839165720865584 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 642.780952020936 & 6295.16591801751 & 0.102107070789226 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 723.491391709218 & 6045.45592564962 & 0.119675240479315 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 244.821296997026 & 5884.08187151993 & 0.0416073913216618 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -106.994641537791 & 5762.11328015371 & -0.0185686459699274 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -456.863029474539 & 5680.88186912329 & -0.0804211458713267 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -838.072677812011 & 5568.85329986601 & -0.150492863195404 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -1271.29698852822 & 5398.91247825308 & -0.235472790797966 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -1699.97305535673 & 5209.06438267189 & -0.32634901979936 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -1924.81523418497 & 5059.1167620251 & -0.380464678861155 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -1942.79024514266 & 4943.49883623011 & -0.392999029534358 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -1829.41777713585 & 4813.2958195162 & -0.380075907597079 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -1872.87621884702 & 4698.94983627614 & -0.398573358750995 \tabularnewline
Median & -2250.28069475706 &  &  \tabularnewline
Midrange & 45994.081459468 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -3143.85372308113 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -1271.29698852822 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -1271.29698852822 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -1271.29698852822 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -1271.29698852822 &  &  \tabularnewline
Midmean - Closest Observation & -2693.35924487937 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -1271.29698852822 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -1271.29698852822 &  &  \tabularnewline
Number of observations & 61 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=275476&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]1807.78267134668[/C][C]10863.3131910219[/C][C]0.166411723528393[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]19115.3073001661[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]84166.2788019087[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]159.708374488745[/C][C]10298.355369583[/C][C]0.0155081436556808[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-58.466418860567[/C][C]10067.6346767756[/C][C]-0.00580736396757024[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]392.439473499678[/C][C]9744.39370930217[/C][C]0.040273359760192[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]2190.96566077843[/C][C]9054.61364050372[/C][C]0.241972296971088[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]1188.59552980606[/C][C]8680.32520401977[/C][C]0.1369298386719[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]318.700735304974[/C][C]8123.28227756123[/C][C]0.0392330002104339[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-582.472757314609[/C][C]7352.57471228858[/C][C]-0.0792202432626906[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]19.1994463586779[/C][C]7199.94888285336[/C][C]0.00266660870390362[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]154.548948004935[/C][C]6939.29970151127[/C][C]0.0222715482329257[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]3783.84117757405[/C][C]6306.22574366852[/C][C]0.600016766189038[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]2592.18337869654[/C][C]5933.68755408047[/C][C]0.436858758583261[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]2301.93524261687[/C][C]5572.9005031496[/C][C]0.41305873688502[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]2224.10318588244[/C][C]5517.56341018168[/C][C]0.403095174543577[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]2244.21176236557[/C][C]5508.58288979507[/C][C]0.407402739917573[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]1785.65529131447[/C][C]5294.07507015996[/C][C]0.337293156528761[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-107.648116769884[/C][C]4872.88803900514[/C][C]-0.0220912354045921[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-1799.57950210267[/C][C]4500.86866562543[/C][C]-0.399829374237608[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-2712.23617554955[/C][C]4295.80270187633[/C][C]-0.63136888813932[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-1545.15682233652[/C][C]3989.50768400466[/C][C]-0.387305137556595[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-1731.8403219615[/C][C]3943.57669075126[/C][C]-0.43915472115025[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]309.942034461211[/C][C]9804.55109858621[/C][C]0.0316120576398346[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]470.7184074142[/C][C]9192.66310645088[/C][C]0.051205880381266[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]764.175447439298[/C][C]8589.2644080246[/C][C]0.0889686719534866[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]906.791135554499[/C][C]7998.18628017849[/C][C]0.113374595663239[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]522.797772619891[/C][C]7549.3190051839[/C][C]0.0692509843948707[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]357.027718789866[/C][C]7120.04277232718[/C][C]0.0501440412938941[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]365.318307416031[/C][C]6761.92818757906[/C][C]0.0540257597066886[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]548.85879931625[/C][C]6540.52930987352[/C][C]0.0839165720865584[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]642.780952020936[/C][C]6295.16591801751[/C][C]0.102107070789226[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]723.491391709218[/C][C]6045.45592564962[/C][C]0.119675240479315[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]244.821296997026[/C][C]5884.08187151993[/C][C]0.0416073913216618[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-106.994641537791[/C][C]5762.11328015371[/C][C]-0.0185686459699274[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-456.863029474539[/C][C]5680.88186912329[/C][C]-0.0804211458713267[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-838.072677812011[/C][C]5568.85329986601[/C][C]-0.150492863195404[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-1271.29698852822[/C][C]5398.91247825308[/C][C]-0.235472790797966[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-1699.97305535673[/C][C]5209.06438267189[/C][C]-0.32634901979936[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-1924.81523418497[/C][C]5059.1167620251[/C][C]-0.380464678861155[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-1942.79024514266[/C][C]4943.49883623011[/C][C]-0.392999029534358[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-1829.41777713585[/C][C]4813.2958195162[/C][C]-0.380075907597079[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-1872.87621884702[/C][C]4698.94983627614[/C][C]-0.398573358750995[/C][/ROW]
[ROW][C]Median[/C][C]-2250.28069475706[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]45994.081459468[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-3143.85372308113[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-1271.29698852822[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-1271.29698852822[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-1271.29698852822[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-1271.29698852822[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-2693.35924487937[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-1271.29698852822[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-1271.29698852822[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]61[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=275476&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=275476&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 Mean1807.7826713466810863.31319102190.166411723528393
Geometric MeanNaN
Harmonic Mean19115.3073001661
Quadratic Mean84166.2788019087
Winsorized Mean ( 1 / 20 )159.70837448874510298.3553695830.0155081436556808
Winsorized Mean ( 2 / 20 )-58.46641886056710067.6346767756-0.00580736396757024
Winsorized Mean ( 3 / 20 )392.4394734996789744.393709302170.040273359760192
Winsorized Mean ( 4 / 20 )2190.965660778439054.613640503720.241972296971088
Winsorized Mean ( 5 / 20 )1188.595529806068680.325204019770.1369298386719
Winsorized Mean ( 6 / 20 )318.7007353049748123.282277561230.0392330002104339
Winsorized Mean ( 7 / 20 )-582.4727573146097352.57471228858-0.0792202432626906
Winsorized Mean ( 8 / 20 )19.19944635867797199.948882853360.00266660870390362
Winsorized Mean ( 9 / 20 )154.5489480049356939.299701511270.0222715482329257
Winsorized Mean ( 10 / 20 )3783.841177574056306.225743668520.600016766189038
Winsorized Mean ( 11 / 20 )2592.183378696545933.687554080470.436858758583261
Winsorized Mean ( 12 / 20 )2301.935242616875572.90050314960.41305873688502
Winsorized Mean ( 13 / 20 )2224.103185882445517.563410181680.403095174543577
Winsorized Mean ( 14 / 20 )2244.211762365575508.582889795070.407402739917573
Winsorized Mean ( 15 / 20 )1785.655291314475294.075070159960.337293156528761
Winsorized Mean ( 16 / 20 )-107.6481167698844872.88803900514-0.0220912354045921
Winsorized Mean ( 17 / 20 )-1799.579502102674500.86866562543-0.399829374237608
Winsorized Mean ( 18 / 20 )-2712.236175549554295.80270187633-0.63136888813932
Winsorized Mean ( 19 / 20 )-1545.156822336523989.50768400466-0.387305137556595
Winsorized Mean ( 20 / 20 )-1731.84032196153943.57669075126-0.43915472115025
Trimmed Mean ( 1 / 20 )309.9420344612119804.551098586210.0316120576398346
Trimmed Mean ( 2 / 20 )470.71840741429192.663106450880.051205880381266
Trimmed Mean ( 3 / 20 )764.1754474392988589.26440802460.0889686719534866
Trimmed Mean ( 4 / 20 )906.7911355544997998.186280178490.113374595663239
Trimmed Mean ( 5 / 20 )522.7977726198917549.31900518390.0692509843948707
Trimmed Mean ( 6 / 20 )357.0277187898667120.042772327180.0501440412938941
Trimmed Mean ( 7 / 20 )365.3183074160316761.928187579060.0540257597066886
Trimmed Mean ( 8 / 20 )548.858799316256540.529309873520.0839165720865584
Trimmed Mean ( 9 / 20 )642.7809520209366295.165918017510.102107070789226
Trimmed Mean ( 10 / 20 )723.4913917092186045.455925649620.119675240479315
Trimmed Mean ( 11 / 20 )244.8212969970265884.081871519930.0416073913216618
Trimmed Mean ( 12 / 20 )-106.9946415377915762.11328015371-0.0185686459699274
Trimmed Mean ( 13 / 20 )-456.8630294745395680.88186912329-0.0804211458713267
Trimmed Mean ( 14 / 20 )-838.0726778120115568.85329986601-0.150492863195404
Trimmed Mean ( 15 / 20 )-1271.296988528225398.91247825308-0.235472790797966
Trimmed Mean ( 16 / 20 )-1699.973055356735209.06438267189-0.32634901979936
Trimmed Mean ( 17 / 20 )-1924.815234184975059.1167620251-0.380464678861155
Trimmed Mean ( 18 / 20 )-1942.790245142664943.49883623011-0.392999029534358
Trimmed Mean ( 19 / 20 )-1829.417777135854813.2958195162-0.380075907597079
Trimmed Mean ( 20 / 20 )-1872.876218847024698.94983627614-0.398573358750995
Median-2250.28069475706
Midrange45994.081459468
Midmean - Weighted Average at Xnp-3143.85372308113
Midmean - Weighted Average at X(n+1)p-1271.29698852822
Midmean - Empirical Distribution Function-1271.29698852822
Midmean - Empirical Distribution Function - Averaging-1271.29698852822
Midmean - Empirical Distribution Function - Interpolation-1271.29698852822
Midmean - Closest Observation-2693.35924487937
Midmean - True Basic - Statistics Graphics Toolkit-1271.29698852822
Midmean - MS Excel (old versions)-1271.29698852822
Number of observations61



Parameters (Session):
par1 = 12 ;
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')