Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 21 Oct 2008 00:15:16 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/21/t1224569761eb8ie9lkbxnir53.htm/, Retrieved Sun, 19 May 2024 17:14:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18330, Retrieved Sun, 19 May 2024 17:14:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Central Tendency] [Robustness of cen...] [2008-10-21 06:15:16] [81dc0ee785f23261ccd6abf7aef76c2a] [Current]
Feedback Forum
2008-10-27 14:34:51 [Bernard Femont] [reply
Gebaseerd op de grafiek van de trimmed mean, die een voorstelling geeft van alle waarden met uitzondering van de outliers, kunnen we stellen dat de waarde van de uitvoer van het totale Koninkrijk over een periode van jaren vrij constant blijft. De grafiek toont een horizontaal lopende rechte.
Aangezien we hier spreken over een periode van 20 jaar waarbinnen de waarde van de totale uitvoer min of meer constant verloopt, is het hoogstwaarschijnlijk dat deze ook in de komende jaren niet veel meer zal fluctueren.
2008-10-27 14:37:27 [Bernard Femont] [reply
Dit integenstelling tot de Windsorized mean die nog wel rekening houdt met de outliers maar de outliers worden gelijkgesteld aan de volgende observaties zien we dat er een veel woeliger resultaat wordt weergegeven.
2008-10-27 19:16:29 [Jens Peeters] [reply
Ik heb weinig aan het voorgaande toe te voegen enkel dat de student een goede voorspelling heeft gemaakt.

Post a new message
Dataseries X:
15370,6
14956,9
15469,7
15101,8
11703,7
16283,6
16726,5
14968,9
14861
14583,3
15305,8
17903,9
16379,4
15420,3
17870,5
15912,8
13866,5
17823,2
17872
17422
16704,5
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22238,5
20682,2
17818,6
21872,1
22117
20769,2249




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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 & 8 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18330&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]8 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=18330&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18330&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 time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean17788.375415286.18834318242562.156184340678
Geometric Mean17649.1331648893
Harmonic Mean17505.7099418964
Quadratic Mean17923.6888559139
Winsorized Mean ( 1 / 20 )17822.3970816667274.71665080410664.8755618907694
Winsorized Mean ( 2 / 20 )17838.1270816667267.20169106451966.7590351340981
Winsorized Mean ( 3 / 20 )17825.9370816667258.05514533202569.0780145411596
Winsorized Mean ( 4 / 20 )17813.7837483333252.64455385830870.5092727164977
Winsorized Mean ( 5 / 20 )17795.7837483333248.39845587560071.6420868463274
Winsorized Mean ( 6 / 20 )17801.5562383333244.31603777671672.8628230890123
Winsorized Mean ( 7 / 20 )17796.0466666667241.37440518251573.7279773023582
Winsorized Mean ( 8 / 20 )17721.8066666667219.15436839289280.8644919862864
Winsorized Mean ( 9 / 20 )17727.1616666667216.59540983095681.8445860902684
Winsorized Mean ( 10 / 20 )17717.2783333333211.97384548573383.5823791974647
Winsorized Mean ( 11 / 20 )17724.5933333333210.02465480596684.3929173444347
Winsorized Mean ( 12 / 20 )17809.5733333333193.96653077630191.8177649621052
Winsorized Mean ( 13 / 20 )17792.9333333333185.40100546821595.9699937354639
Winsorized Mean ( 14 / 20 )17792.6066666667171.951295953353103.474687806328
Winsorized Mean ( 15 / 20 )17809.5066666667167.234905948514106.493955706530
Winsorized Mean ( 16 / 20 )17753155.934291445428113.849236338198
Winsorized Mean ( 17 / 20 )17757.8733333333148.131295038787119.879282285918
Winsorized Mean ( 18 / 20 )17809.1133333333137.075425533253129.921999250063
Winsorized Mean ( 19 / 20 )17794.8633333333123.047530455609144.617801490563
Winsorized Mean ( 20 / 20 )17692.33105.365898928743167.913244986074
Trimmed Mean ( 1 / 20 )17816.5573258621265.51459551383767.1019884665195
Trimmed Mean ( 2 / 20 )17810.3004446429254.16494097096870.0737889993933
Trimmed Mean ( 3 / 20 )17794.8412018519245.17908297871472.578953251884
Trimmed Mean ( 4 / 20 )17782.8812480769238.44685135285174.5779663148582
Trimmed Mean ( 5 / 20 )17773.610498232.09173086764376.5801109395659
Trimmed Mean ( 6 / 20 )17768.0671854167225.45804063451078.8087536617088
Trimmed Mean ( 7 / 20 )17760.7869565217218.20204012579781.396062778709
Trimmed Mean ( 8 / 20 )17753.9181818182209.65117427773584.6831325556934
Trimmed Mean ( 9 / 20 )17759.6523809524204.89577346021486.6765189004784
Trimmed Mean ( 10 / 20 )17765.0675199.14112024943289.2084340880908
Trimmed Mean ( 11 / 20 )17772.6131578947192.55269143341392.2999986424014
Trimmed Mean ( 12 / 20 )17779.8888888889184.00024110481996.6297042989215
Trimmed Mean ( 13 / 20 )17775.5235294118176.895685952805100.485907463872
Trimmed Mean ( 14 / 20 )17773.0125169.346131497074104.950803085260
Trimmed Mean ( 15 / 20 )17770.2133333333162.602986197384109.285897811016
Trimmed Mean ( 16 / 20 )17764.6153.997350609382115.356530029275
Trimmed Mean ( 17 / 20 )17766.2730769231145.013734475016122.514416591236
Trimmed Mean ( 18 / 20 )17767.5083333333133.943264800387132.649509176979
Trimmed Mean ( 19 / 20 )17761.2045454545120.887399842062146.923538504917
Trimmed Mean ( 20 / 20 )17755.89106.150475344152167.270941957003
Median17785.2
Midrange16971.1
Midmean - Weighted Average at Xnp17718.4451612903
Midmean - Weighted Average at X(n+1)p17770.2133333333
Midmean - Empirical Distribution Function17718.4451612903
Midmean - Empirical Distribution Function - Averaging17770.2133333333
Midmean - Empirical Distribution Function - Interpolation17770.2133333333
Midmean - Closest Observation17718.4451612903
Midmean - True Basic - Statistics Graphics Toolkit17770.2133333333
Midmean - MS Excel (old versions)17773.0125
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 17788.375415 & 286.188343182425 & 62.156184340678 \tabularnewline
Geometric Mean & 17649.1331648893 &  &  \tabularnewline
Harmonic Mean & 17505.7099418964 &  &  \tabularnewline
Quadratic Mean & 17923.6888559139 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 17822.3970816667 & 274.716650804106 & 64.8755618907694 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 17838.1270816667 & 267.201691064519 & 66.7590351340981 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 17825.9370816667 & 258.055145332025 & 69.0780145411596 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 17813.7837483333 & 252.644553858308 & 70.5092727164977 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 17795.7837483333 & 248.398455875600 & 71.6420868463274 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 17801.5562383333 & 244.316037776716 & 72.8628230890123 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 17796.0466666667 & 241.374405182515 & 73.7279773023582 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 17721.8066666667 & 219.154368392892 & 80.8644919862864 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 17727.1616666667 & 216.595409830956 & 81.8445860902684 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 17717.2783333333 & 211.973845485733 & 83.5823791974647 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 17724.5933333333 & 210.024654805966 & 84.3929173444347 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 17809.5733333333 & 193.966530776301 & 91.8177649621052 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 17792.9333333333 & 185.401005468215 & 95.9699937354639 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 17792.6066666667 & 171.951295953353 & 103.474687806328 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 17809.5066666667 & 167.234905948514 & 106.493955706530 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 17753 & 155.934291445428 & 113.849236338198 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 17757.8733333333 & 148.131295038787 & 119.879282285918 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 17809.1133333333 & 137.075425533253 & 129.921999250063 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 17794.8633333333 & 123.047530455609 & 144.617801490563 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 17692.33 & 105.365898928743 & 167.913244986074 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 17816.5573258621 & 265.514595513837 & 67.1019884665195 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 17810.3004446429 & 254.164940970968 & 70.0737889993933 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 17794.8412018519 & 245.179082978714 & 72.578953251884 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 17782.8812480769 & 238.446851352851 & 74.5779663148582 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 17773.610498 & 232.091730867643 & 76.5801109395659 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 17768.0671854167 & 225.458040634510 & 78.8087536617088 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 17760.7869565217 & 218.202040125797 & 81.396062778709 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 17753.9181818182 & 209.651174277735 & 84.6831325556934 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 17759.6523809524 & 204.895773460214 & 86.6765189004784 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 17765.0675 & 199.141120249432 & 89.2084340880908 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 17772.6131578947 & 192.552691433413 & 92.2999986424014 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 17779.8888888889 & 184.000241104819 & 96.6297042989215 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 17775.5235294118 & 176.895685952805 & 100.485907463872 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 17773.0125 & 169.346131497074 & 104.950803085260 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 17770.2133333333 & 162.602986197384 & 109.285897811016 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 17764.6 & 153.997350609382 & 115.356530029275 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 17766.2730769231 & 145.013734475016 & 122.514416591236 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 17767.5083333333 & 133.943264800387 & 132.649509176979 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 17761.2045454545 & 120.887399842062 & 146.923538504917 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 17755.89 & 106.150475344152 & 167.270941957003 \tabularnewline
Median & 17785.2 &  &  \tabularnewline
Midrange & 16971.1 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 17718.4451612903 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 17770.2133333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 17718.4451612903 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 17770.2133333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 17770.2133333333 &  &  \tabularnewline
Midmean - Closest Observation & 17718.4451612903 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 17770.2133333333 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 17773.0125 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18330&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]17788.375415[/C][C]286.188343182425[/C][C]62.156184340678[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]17649.1331648893[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]17505.7099418964[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]17923.6888559139[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]17822.3970816667[/C][C]274.716650804106[/C][C]64.8755618907694[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]17838.1270816667[/C][C]267.201691064519[/C][C]66.7590351340981[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]17825.9370816667[/C][C]258.055145332025[/C][C]69.0780145411596[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]17813.7837483333[/C][C]252.644553858308[/C][C]70.5092727164977[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]17795.7837483333[/C][C]248.398455875600[/C][C]71.6420868463274[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]17801.5562383333[/C][C]244.316037776716[/C][C]72.8628230890123[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]17796.0466666667[/C][C]241.374405182515[/C][C]73.7279773023582[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]17721.8066666667[/C][C]219.154368392892[/C][C]80.8644919862864[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]17727.1616666667[/C][C]216.595409830956[/C][C]81.8445860902684[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]17717.2783333333[/C][C]211.973845485733[/C][C]83.5823791974647[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]17724.5933333333[/C][C]210.024654805966[/C][C]84.3929173444347[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]17809.5733333333[/C][C]193.966530776301[/C][C]91.8177649621052[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]17792.9333333333[/C][C]185.401005468215[/C][C]95.9699937354639[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]17792.6066666667[/C][C]171.951295953353[/C][C]103.474687806328[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]17809.5066666667[/C][C]167.234905948514[/C][C]106.493955706530[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]17753[/C][C]155.934291445428[/C][C]113.849236338198[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]17757.8733333333[/C][C]148.131295038787[/C][C]119.879282285918[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]17809.1133333333[/C][C]137.075425533253[/C][C]129.921999250063[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]17794.8633333333[/C][C]123.047530455609[/C][C]144.617801490563[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]17692.33[/C][C]105.365898928743[/C][C]167.913244986074[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]17816.5573258621[/C][C]265.514595513837[/C][C]67.1019884665195[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]17810.3004446429[/C][C]254.164940970968[/C][C]70.0737889993933[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]17794.8412018519[/C][C]245.179082978714[/C][C]72.578953251884[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]17782.8812480769[/C][C]238.446851352851[/C][C]74.5779663148582[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]17773.610498[/C][C]232.091730867643[/C][C]76.5801109395659[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]17768.0671854167[/C][C]225.458040634510[/C][C]78.8087536617088[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]17760.7869565217[/C][C]218.202040125797[/C][C]81.396062778709[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]17753.9181818182[/C][C]209.651174277735[/C][C]84.6831325556934[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]17759.6523809524[/C][C]204.895773460214[/C][C]86.6765189004784[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]17765.0675[/C][C]199.141120249432[/C][C]89.2084340880908[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]17772.6131578947[/C][C]192.552691433413[/C][C]92.2999986424014[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]17779.8888888889[/C][C]184.000241104819[/C][C]96.6297042989215[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]17775.5235294118[/C][C]176.895685952805[/C][C]100.485907463872[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]17773.0125[/C][C]169.346131497074[/C][C]104.950803085260[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]17770.2133333333[/C][C]162.602986197384[/C][C]109.285897811016[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]17764.6[/C][C]153.997350609382[/C][C]115.356530029275[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]17766.2730769231[/C][C]145.013734475016[/C][C]122.514416591236[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]17767.5083333333[/C][C]133.943264800387[/C][C]132.649509176979[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]17761.2045454545[/C][C]120.887399842062[/C][C]146.923538504917[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]17755.89[/C][C]106.150475344152[/C][C]167.270941957003[/C][/ROW]
[ROW][C]Median[/C][C]17785.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]16971.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]17718.4451612903[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]17770.2133333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]17718.4451612903[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]17770.2133333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]17770.2133333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]17718.4451612903[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]17770.2133333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]17773.0125[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]60[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18330&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18330&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 Mean17788.375415286.18834318242562.156184340678
Geometric Mean17649.1331648893
Harmonic Mean17505.7099418964
Quadratic Mean17923.6888559139
Winsorized Mean ( 1 / 20 )17822.3970816667274.71665080410664.8755618907694
Winsorized Mean ( 2 / 20 )17838.1270816667267.20169106451966.7590351340981
Winsorized Mean ( 3 / 20 )17825.9370816667258.05514533202569.0780145411596
Winsorized Mean ( 4 / 20 )17813.7837483333252.64455385830870.5092727164977
Winsorized Mean ( 5 / 20 )17795.7837483333248.39845587560071.6420868463274
Winsorized Mean ( 6 / 20 )17801.5562383333244.31603777671672.8628230890123
Winsorized Mean ( 7 / 20 )17796.0466666667241.37440518251573.7279773023582
Winsorized Mean ( 8 / 20 )17721.8066666667219.15436839289280.8644919862864
Winsorized Mean ( 9 / 20 )17727.1616666667216.59540983095681.8445860902684
Winsorized Mean ( 10 / 20 )17717.2783333333211.97384548573383.5823791974647
Winsorized Mean ( 11 / 20 )17724.5933333333210.02465480596684.3929173444347
Winsorized Mean ( 12 / 20 )17809.5733333333193.96653077630191.8177649621052
Winsorized Mean ( 13 / 20 )17792.9333333333185.40100546821595.9699937354639
Winsorized Mean ( 14 / 20 )17792.6066666667171.951295953353103.474687806328
Winsorized Mean ( 15 / 20 )17809.5066666667167.234905948514106.493955706530
Winsorized Mean ( 16 / 20 )17753155.934291445428113.849236338198
Winsorized Mean ( 17 / 20 )17757.8733333333148.131295038787119.879282285918
Winsorized Mean ( 18 / 20 )17809.1133333333137.075425533253129.921999250063
Winsorized Mean ( 19 / 20 )17794.8633333333123.047530455609144.617801490563
Winsorized Mean ( 20 / 20 )17692.33105.365898928743167.913244986074
Trimmed Mean ( 1 / 20 )17816.5573258621265.51459551383767.1019884665195
Trimmed Mean ( 2 / 20 )17810.3004446429254.16494097096870.0737889993933
Trimmed Mean ( 3 / 20 )17794.8412018519245.17908297871472.578953251884
Trimmed Mean ( 4 / 20 )17782.8812480769238.44685135285174.5779663148582
Trimmed Mean ( 5 / 20 )17773.610498232.09173086764376.5801109395659
Trimmed Mean ( 6 / 20 )17768.0671854167225.45804063451078.8087536617088
Trimmed Mean ( 7 / 20 )17760.7869565217218.20204012579781.396062778709
Trimmed Mean ( 8 / 20 )17753.9181818182209.65117427773584.6831325556934
Trimmed Mean ( 9 / 20 )17759.6523809524204.89577346021486.6765189004784
Trimmed Mean ( 10 / 20 )17765.0675199.14112024943289.2084340880908
Trimmed Mean ( 11 / 20 )17772.6131578947192.55269143341392.2999986424014
Trimmed Mean ( 12 / 20 )17779.8888888889184.00024110481996.6297042989215
Trimmed Mean ( 13 / 20 )17775.5235294118176.895685952805100.485907463872
Trimmed Mean ( 14 / 20 )17773.0125169.346131497074104.950803085260
Trimmed Mean ( 15 / 20 )17770.2133333333162.602986197384109.285897811016
Trimmed Mean ( 16 / 20 )17764.6153.997350609382115.356530029275
Trimmed Mean ( 17 / 20 )17766.2730769231145.013734475016122.514416591236
Trimmed Mean ( 18 / 20 )17767.5083333333133.943264800387132.649509176979
Trimmed Mean ( 19 / 20 )17761.2045454545120.887399842062146.923538504917
Trimmed Mean ( 20 / 20 )17755.89106.150475344152167.270941957003
Median17785.2
Midrange16971.1
Midmean - Weighted Average at Xnp17718.4451612903
Midmean - Weighted Average at X(n+1)p17770.2133333333
Midmean - Empirical Distribution Function17718.4451612903
Midmean - Empirical Distribution Function - Averaging17770.2133333333
Midmean - Empirical Distribution Function - Interpolation17770.2133333333
Midmean - Closest Observation17718.4451612903
Midmean - True Basic - Statistics Graphics Toolkit17770.2133333333
Midmean - MS Excel (old versions)17773.0125
Number of observations60



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')