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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 07 Mar 2016 18:19:32 +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/2016/Mar/07/t1457374946arzzmny2qptojnd.htm/, Retrieved Wed, 01 May 2024 12:50:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293607, Retrieved Wed, 01 May 2024 12:50:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-03-07 18:19:32] [409b006d8fa6179b2438b444258b53f7] [Current]
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Dataseries X:
99
99
99
100
101
101
100
101
100
101
100
100
102
102
102
102
102
102
103
103
103
103
103
103
104
104
104
106
106
106
106
107
106
106
106
106
106
106
106
105
105
105
105
105
104
104
104
104
103
104
104
103
103
103
103
103
103
104
104
104
104
104
105
105
104
104
104
104
103




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293607&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293607&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293607&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean103.4057971014490.237490826833851435.40964710099
Geometric Mean103.387128827147
Harmonic Mean103.368336764749
Quadratic Mean103.424340476014
Winsorized Mean ( 1 / 23 )103.3913043478260.234691024415773440.542217603775
Winsorized Mean ( 2 / 23 )103.3913043478260.234691024415773440.542217603775
Winsorized Mean ( 3 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 4 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 5 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 6 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 7 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 8 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 9 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 10 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 11 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 12 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 13 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 14 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 15 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 16 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 17 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 18 / 23 )103.8115942028990.1017229289324961020.53288567604
Winsorized Mean ( 19 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 20 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 21 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 22 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 23 / 23 )103.5362318840580.06047450247559491712.06421955834
Trimmed Mean ( 1 / 23 )103.4179104477610.229199592205338451.213326571323
Trimmed Mean ( 2 / 23 )103.4461538461540.222562403987374464.796173984634
Trimmed Mean ( 3 / 23 )103.476190476190.214498955172678482.408832215006
Trimmed Mean ( 4 / 23 )103.4918032786890.20989582482391493.062705585078
Trimmed Mean ( 5 / 23 )103.5084745762710.204240380138156506.79730671405
Trimmed Mean ( 6 / 23 )103.5263157894740.197263965675613524.811084654537
Trimmed Mean ( 7 / 23 )103.5454545454550.188594271398054549.038174796454
Trimmed Mean ( 8 / 23 )103.5660377358490.177691685908825582.841212891578
Trimmed Mean ( 9 / 23 )103.568627450980.170937213472183605.886953152154
Trimmed Mean ( 10 / 23 )103.5714285714290.162359305916498637.914950342887
Trimmed Mean ( 11 / 23 )103.5714285714290.15129622129527684.560577156109
Trimmed Mean ( 12 / 23 )103.5777777777780.13665886485081757.929446368906
Trimmed Mean ( 13 / 23 )103.5813953488370.13407555653831772.559876111651
Trimmed Mean ( 14 / 23 )103.5853658536590.130550475034855793.450700397703
Trimmed Mean ( 15 / 23 )103.5897435897440.125752518764593823.758797099422
Trimmed Mean ( 16 / 23 )103.5945945945950.119177986984891869.242695026621
Trimmed Mean ( 17 / 23 )103.60.110003819643385941.785479230217
Trimmed Mean ( 18 / 23 )103.6060606060610.09672079799093711071.18699140353
Trimmed Mean ( 19 / 23 )103.580645161290.09009187125012221149.72243027031
Trimmed Mean ( 20 / 23 )103.5862068965520.09307607698370041112.91977759969
Trimmed Mean ( 21 / 23 )103.5925925925930.09636202008710981075.03550152795
Trimmed Mean ( 22 / 23 )103.5925925925930.11035.92592592593
Trimmed Mean ( 23 / 23 )103.6086956521740.104050961115322995.749530245496
Median104
Midrange103
Midmean - Weighted Average at Xnp103.577777777778
Midmean - Weighted Average at X(n+1)p103.577777777778
Midmean - Empirical Distribution Function103.577777777778
Midmean - Empirical Distribution Function - Averaging103.577777777778
Midmean - Empirical Distribution Function - Interpolation103.577777777778
Midmean - Closest Observation103.577777777778
Midmean - True Basic - Statistics Graphics Toolkit103.577777777778
Midmean - MS Excel (old versions)103.577777777778
Number of observations69

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 103.405797101449 & 0.237490826833851 & 435.40964710099 \tabularnewline
Geometric Mean & 103.387128827147 &  &  \tabularnewline
Harmonic Mean & 103.368336764749 &  &  \tabularnewline
Quadratic Mean & 103.424340476014 &  &  \tabularnewline
Winsorized Mean ( 1 / 23 ) & 103.391304347826 & 0.234691024415773 & 440.542217603775 \tabularnewline
Winsorized Mean ( 2 / 23 ) & 103.391304347826 & 0.234691024415773 & 440.542217603775 \tabularnewline
Winsorized Mean ( 3 / 23 ) & 103.434782608696 & 0.223776640928829 & 462.223323128675 \tabularnewline
Winsorized Mean ( 4 / 23 ) & 103.434782608696 & 0.223776640928829 & 462.223323128675 \tabularnewline
Winsorized Mean ( 5 / 23 ) & 103.434782608696 & 0.223776640928829 & 462.223323128675 \tabularnewline
Winsorized Mean ( 6 / 23 ) & 103.434782608696 & 0.223776640928829 & 462.223323128675 \tabularnewline
Winsorized Mean ( 7 / 23 ) & 103.434782608696 & 0.223776640928829 & 462.223323128675 \tabularnewline
Winsorized Mean ( 8 / 23 ) & 103.550724637681 & 0.199676029043598 & 518.593669624067 \tabularnewline
Winsorized Mean ( 9 / 23 ) & 103.550724637681 & 0.199676029043598 & 518.593669624067 \tabularnewline
Winsorized Mean ( 10 / 23 ) & 103.550724637681 & 0.199676029043598 & 518.593669624067 \tabularnewline
Winsorized Mean ( 11 / 23 ) & 103.550724637681 & 0.199676029043598 & 518.593669624067 \tabularnewline
Winsorized Mean ( 12 / 23 ) & 103.550724637681 & 0.139320344954905 & 743.25630381692 \tabularnewline
Winsorized Mean ( 13 / 23 ) & 103.550724637681 & 0.139320344954905 & 743.25630381692 \tabularnewline
Winsorized Mean ( 14 / 23 ) & 103.550724637681 & 0.139320344954905 & 743.25630381692 \tabularnewline
Winsorized Mean ( 15 / 23 ) & 103.550724637681 & 0.139320344954905 & 743.25630381692 \tabularnewline
Winsorized Mean ( 16 / 23 ) & 103.550724637681 & 0.139320344954905 & 743.25630381692 \tabularnewline
Winsorized Mean ( 17 / 23 ) & 103.550724637681 & 0.139320344954905 & 743.25630381692 \tabularnewline
Winsorized Mean ( 18 / 23 ) & 103.811594202899 & 0.101722928932496 & 1020.53288567604 \tabularnewline
Winsorized Mean ( 19 / 23 ) & 103.536231884058 & 0.0604745024755949 & 1712.06421955834 \tabularnewline
Winsorized Mean ( 20 / 23 ) & 103.536231884058 & 0.0604745024755949 & 1712.06421955834 \tabularnewline
Winsorized Mean ( 21 / 23 ) & 103.536231884058 & 0.0604745024755949 & 1712.06421955834 \tabularnewline
Winsorized Mean ( 22 / 23 ) & 103.536231884058 & 0.0604745024755949 & 1712.06421955834 \tabularnewline
Winsorized Mean ( 23 / 23 ) & 103.536231884058 & 0.0604745024755949 & 1712.06421955834 \tabularnewline
Trimmed Mean ( 1 / 23 ) & 103.417910447761 & 0.229199592205338 & 451.213326571323 \tabularnewline
Trimmed Mean ( 2 / 23 ) & 103.446153846154 & 0.222562403987374 & 464.796173984634 \tabularnewline
Trimmed Mean ( 3 / 23 ) & 103.47619047619 & 0.214498955172678 & 482.408832215006 \tabularnewline
Trimmed Mean ( 4 / 23 ) & 103.491803278689 & 0.20989582482391 & 493.062705585078 \tabularnewline
Trimmed Mean ( 5 / 23 ) & 103.508474576271 & 0.204240380138156 & 506.79730671405 \tabularnewline
Trimmed Mean ( 6 / 23 ) & 103.526315789474 & 0.197263965675613 & 524.811084654537 \tabularnewline
Trimmed Mean ( 7 / 23 ) & 103.545454545455 & 0.188594271398054 & 549.038174796454 \tabularnewline
Trimmed Mean ( 8 / 23 ) & 103.566037735849 & 0.177691685908825 & 582.841212891578 \tabularnewline
Trimmed Mean ( 9 / 23 ) & 103.56862745098 & 0.170937213472183 & 605.886953152154 \tabularnewline
Trimmed Mean ( 10 / 23 ) & 103.571428571429 & 0.162359305916498 & 637.914950342887 \tabularnewline
Trimmed Mean ( 11 / 23 ) & 103.571428571429 & 0.15129622129527 & 684.560577156109 \tabularnewline
Trimmed Mean ( 12 / 23 ) & 103.577777777778 & 0.13665886485081 & 757.929446368906 \tabularnewline
Trimmed Mean ( 13 / 23 ) & 103.581395348837 & 0.13407555653831 & 772.559876111651 \tabularnewline
Trimmed Mean ( 14 / 23 ) & 103.585365853659 & 0.130550475034855 & 793.450700397703 \tabularnewline
Trimmed Mean ( 15 / 23 ) & 103.589743589744 & 0.125752518764593 & 823.758797099422 \tabularnewline
Trimmed Mean ( 16 / 23 ) & 103.594594594595 & 0.119177986984891 & 869.242695026621 \tabularnewline
Trimmed Mean ( 17 / 23 ) & 103.6 & 0.110003819643385 & 941.785479230217 \tabularnewline
Trimmed Mean ( 18 / 23 ) & 103.606060606061 & 0.0967207979909371 & 1071.18699140353 \tabularnewline
Trimmed Mean ( 19 / 23 ) & 103.58064516129 & 0.0900918712501222 & 1149.72243027031 \tabularnewline
Trimmed Mean ( 20 / 23 ) & 103.586206896552 & 0.0930760769837004 & 1112.91977759969 \tabularnewline
Trimmed Mean ( 21 / 23 ) & 103.592592592593 & 0.0963620200871098 & 1075.03550152795 \tabularnewline
Trimmed Mean ( 22 / 23 ) & 103.592592592593 & 0.1 & 1035.92592592593 \tabularnewline
Trimmed Mean ( 23 / 23 ) & 103.608695652174 & 0.104050961115322 & 995.749530245496 \tabularnewline
Median & 104 &  &  \tabularnewline
Midrange & 103 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 103.577777777778 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 103.577777777778 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 103.577777777778 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 103.577777777778 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 103.577777777778 &  &  \tabularnewline
Midmean - Closest Observation & 103.577777777778 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 103.577777777778 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 103.577777777778 &  &  \tabularnewline
Number of observations & 69 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293607&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]103.405797101449[/C][C]0.237490826833851[/C][C]435.40964710099[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]103.387128827147[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]103.368336764749[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]103.424340476014[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 23 )[/C][C]103.391304347826[/C][C]0.234691024415773[/C][C]440.542217603775[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 23 )[/C][C]103.391304347826[/C][C]0.234691024415773[/C][C]440.542217603775[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 23 )[/C][C]103.434782608696[/C][C]0.223776640928829[/C][C]462.223323128675[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 23 )[/C][C]103.434782608696[/C][C]0.223776640928829[/C][C]462.223323128675[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 23 )[/C][C]103.434782608696[/C][C]0.223776640928829[/C][C]462.223323128675[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 23 )[/C][C]103.434782608696[/C][C]0.223776640928829[/C][C]462.223323128675[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 23 )[/C][C]103.434782608696[/C][C]0.223776640928829[/C][C]462.223323128675[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 23 )[/C][C]103.550724637681[/C][C]0.199676029043598[/C][C]518.593669624067[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 23 )[/C][C]103.550724637681[/C][C]0.199676029043598[/C][C]518.593669624067[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 23 )[/C][C]103.550724637681[/C][C]0.199676029043598[/C][C]518.593669624067[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 23 )[/C][C]103.550724637681[/C][C]0.199676029043598[/C][C]518.593669624067[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 23 )[/C][C]103.550724637681[/C][C]0.139320344954905[/C][C]743.25630381692[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 23 )[/C][C]103.550724637681[/C][C]0.139320344954905[/C][C]743.25630381692[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 23 )[/C][C]103.550724637681[/C][C]0.139320344954905[/C][C]743.25630381692[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 23 )[/C][C]103.550724637681[/C][C]0.139320344954905[/C][C]743.25630381692[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 23 )[/C][C]103.550724637681[/C][C]0.139320344954905[/C][C]743.25630381692[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 23 )[/C][C]103.550724637681[/C][C]0.139320344954905[/C][C]743.25630381692[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 23 )[/C][C]103.811594202899[/C][C]0.101722928932496[/C][C]1020.53288567604[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 23 )[/C][C]103.536231884058[/C][C]0.0604745024755949[/C][C]1712.06421955834[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 23 )[/C][C]103.536231884058[/C][C]0.0604745024755949[/C][C]1712.06421955834[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 23 )[/C][C]103.536231884058[/C][C]0.0604745024755949[/C][C]1712.06421955834[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 23 )[/C][C]103.536231884058[/C][C]0.0604745024755949[/C][C]1712.06421955834[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 23 )[/C][C]103.536231884058[/C][C]0.0604745024755949[/C][C]1712.06421955834[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 23 )[/C][C]103.417910447761[/C][C]0.229199592205338[/C][C]451.213326571323[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 23 )[/C][C]103.446153846154[/C][C]0.222562403987374[/C][C]464.796173984634[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 23 )[/C][C]103.47619047619[/C][C]0.214498955172678[/C][C]482.408832215006[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 23 )[/C][C]103.491803278689[/C][C]0.20989582482391[/C][C]493.062705585078[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 23 )[/C][C]103.508474576271[/C][C]0.204240380138156[/C][C]506.79730671405[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 23 )[/C][C]103.526315789474[/C][C]0.197263965675613[/C][C]524.811084654537[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 23 )[/C][C]103.545454545455[/C][C]0.188594271398054[/C][C]549.038174796454[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 23 )[/C][C]103.566037735849[/C][C]0.177691685908825[/C][C]582.841212891578[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 23 )[/C][C]103.56862745098[/C][C]0.170937213472183[/C][C]605.886953152154[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 23 )[/C][C]103.571428571429[/C][C]0.162359305916498[/C][C]637.914950342887[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 23 )[/C][C]103.571428571429[/C][C]0.15129622129527[/C][C]684.560577156109[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 23 )[/C][C]103.577777777778[/C][C]0.13665886485081[/C][C]757.929446368906[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 23 )[/C][C]103.581395348837[/C][C]0.13407555653831[/C][C]772.559876111651[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 23 )[/C][C]103.585365853659[/C][C]0.130550475034855[/C][C]793.450700397703[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 23 )[/C][C]103.589743589744[/C][C]0.125752518764593[/C][C]823.758797099422[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 23 )[/C][C]103.594594594595[/C][C]0.119177986984891[/C][C]869.242695026621[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 23 )[/C][C]103.6[/C][C]0.110003819643385[/C][C]941.785479230217[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 23 )[/C][C]103.606060606061[/C][C]0.0967207979909371[/C][C]1071.18699140353[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 23 )[/C][C]103.58064516129[/C][C]0.0900918712501222[/C][C]1149.72243027031[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 23 )[/C][C]103.586206896552[/C][C]0.0930760769837004[/C][C]1112.91977759969[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 23 )[/C][C]103.592592592593[/C][C]0.0963620200871098[/C][C]1075.03550152795[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 23 )[/C][C]103.592592592593[/C][C]0.1[/C][C]1035.92592592593[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 23 )[/C][C]103.608695652174[/C][C]0.104050961115322[/C][C]995.749530245496[/C][/ROW]
[ROW][C]Median[/C][C]104[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]103[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]103.577777777778[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]69[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293607&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293607&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 Mean103.4057971014490.237490826833851435.40964710099
Geometric Mean103.387128827147
Harmonic Mean103.368336764749
Quadratic Mean103.424340476014
Winsorized Mean ( 1 / 23 )103.3913043478260.234691024415773440.542217603775
Winsorized Mean ( 2 / 23 )103.3913043478260.234691024415773440.542217603775
Winsorized Mean ( 3 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 4 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 5 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 6 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 7 / 23 )103.4347826086960.223776640928829462.223323128675
Winsorized Mean ( 8 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 9 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 10 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 11 / 23 )103.5507246376810.199676029043598518.593669624067
Winsorized Mean ( 12 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 13 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 14 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 15 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 16 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 17 / 23 )103.5507246376810.139320344954905743.25630381692
Winsorized Mean ( 18 / 23 )103.8115942028990.1017229289324961020.53288567604
Winsorized Mean ( 19 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 20 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 21 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 22 / 23 )103.5362318840580.06047450247559491712.06421955834
Winsorized Mean ( 23 / 23 )103.5362318840580.06047450247559491712.06421955834
Trimmed Mean ( 1 / 23 )103.4179104477610.229199592205338451.213326571323
Trimmed Mean ( 2 / 23 )103.4461538461540.222562403987374464.796173984634
Trimmed Mean ( 3 / 23 )103.476190476190.214498955172678482.408832215006
Trimmed Mean ( 4 / 23 )103.4918032786890.20989582482391493.062705585078
Trimmed Mean ( 5 / 23 )103.5084745762710.204240380138156506.79730671405
Trimmed Mean ( 6 / 23 )103.5263157894740.197263965675613524.811084654537
Trimmed Mean ( 7 / 23 )103.5454545454550.188594271398054549.038174796454
Trimmed Mean ( 8 / 23 )103.5660377358490.177691685908825582.841212891578
Trimmed Mean ( 9 / 23 )103.568627450980.170937213472183605.886953152154
Trimmed Mean ( 10 / 23 )103.5714285714290.162359305916498637.914950342887
Trimmed Mean ( 11 / 23 )103.5714285714290.15129622129527684.560577156109
Trimmed Mean ( 12 / 23 )103.5777777777780.13665886485081757.929446368906
Trimmed Mean ( 13 / 23 )103.5813953488370.13407555653831772.559876111651
Trimmed Mean ( 14 / 23 )103.5853658536590.130550475034855793.450700397703
Trimmed Mean ( 15 / 23 )103.5897435897440.125752518764593823.758797099422
Trimmed Mean ( 16 / 23 )103.5945945945950.119177986984891869.242695026621
Trimmed Mean ( 17 / 23 )103.60.110003819643385941.785479230217
Trimmed Mean ( 18 / 23 )103.6060606060610.09672079799093711071.18699140353
Trimmed Mean ( 19 / 23 )103.580645161290.09009187125012221149.72243027031
Trimmed Mean ( 20 / 23 )103.5862068965520.09307607698370041112.91977759969
Trimmed Mean ( 21 / 23 )103.5925925925930.09636202008710981075.03550152795
Trimmed Mean ( 22 / 23 )103.5925925925930.11035.92592592593
Trimmed Mean ( 23 / 23 )103.6086956521740.104050961115322995.749530245496
Median104
Midrange103
Midmean - Weighted Average at Xnp103.577777777778
Midmean - Weighted Average at X(n+1)p103.577777777778
Midmean - Empirical Distribution Function103.577777777778
Midmean - Empirical Distribution Function - Averaging103.577777777778
Midmean - Empirical Distribution Function - Interpolation103.577777777778
Midmean - Closest Observation103.577777777778
Midmean - True Basic - Statistics Graphics Toolkit103.577777777778
Midmean - MS Excel (old versions)103.577777777778
Number of observations69



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')