Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 06 Mar 2012 07:11:33 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Mar/06/t1331035946wom8dnjh1c2zp83.htm/, Retrieved Wed, 01 May 2024 17:24:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=163517, Retrieved Wed, 01 May 2024 17:24:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Robustheid v/d pr...] [2012-03-06 12:11:33] [732e4567293b40941604fcb6ea096e93] [Current]
Feedback Forum

Post a new message
Dataseries X:
15,13
15,25
15,33
15,36
15,4
15,4
15,41
15,47
15,54
15,55
15,59
15,65
15,75
15,86
15,89
15,94
15,93
15,95
15,99
15,99
16,06
16,08
16,07
16,11
16,15
16,18
16,3
16,42
16,49
16,5
16,58
16,64
16,66
16,81
16,91
16,92
16,95
17,11
17,16
17,16
17,27
17,34
17,39
17,43
17,45
17,5
17,56
17,65
17,62
17,7
17,72
17,71
17,74
17,75
17,78
17,8
17,86
17,88
17,89
17,94




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=163517&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=163517&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163517&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 Mean16.61033333333330.114341881711694145.269022030049
Geometric Mean16.5870912215126
Harmonic Mean16.5638560685033
Quadratic Mean16.6335367055035
Winsorized Mean ( 1 / 20 )16.61150.113758050562572146.024830048076
Winsorized Mean ( 2 / 20 )16.61383333333330.113167814909762146.807052398961
Winsorized Mean ( 3 / 20 )16.61433333333330.112693616607621147.429231871948
Winsorized Mean ( 4 / 20 )16.6130.111460337249001149.048535201242
Winsorized Mean ( 5 / 20 )16.61133333333330.111161425519559149.434331699988
Winsorized Mean ( 6 / 20 )16.60933333333330.110447182117358150.382590256443
Winsorized Mean ( 7 / 20 )16.61516666666670.10897532288604152.467239615723
Winsorized Mean ( 8 / 20 )16.62183333333330.106877746217512155.521929696248
Winsorized Mean ( 9 / 20 )16.62183333333330.10636030111599156.278547154606
Winsorized Mean ( 10 / 20 )16.62683333333330.104943754552549158.435663029453
Winsorized Mean ( 11 / 20 )16.62866666666670.101548036743594163.751729722295
Winsorized Mean ( 12 / 20 )16.64266666666670.0973365257583418170.980693393409
Winsorized Mean ( 13 / 20 )16.65350.0915324106717933181.941018244502
Winsorized Mean ( 14 / 20 )16.64650.088185354677866188.767171837187
Winsorized Mean ( 15 / 20 )16.6440.0847102739251537196.481480094208
Winsorized Mean ( 16 / 20 )16.64133333333330.0834728098315111199.36232369467
Winsorized Mean ( 17 / 20 )16.63283333333330.081266838035071204.669379730947
Winsorized Mean ( 18 / 20 )16.62983333333330.0772154852837712215.369148716968
Winsorized Mean ( 19 / 20 )16.60766666666670.0738009104818312225.033357423893
Winsorized Mean ( 20 / 20 )16.59433333333330.0650216681253287255.212359383766
Trimmed Mean ( 1 / 20 )16.61293103448280.113144573053306146.829234369516
Trimmed Mean ( 2 / 20 )16.61446428571430.112287004614872147.964266592554
Trimmed Mean ( 3 / 20 )16.61481481481480.111501956418563149.009177493219
Trimmed Mean ( 4 / 20 )16.6150.110629114183281150.186504905695
Trimmed Mean ( 5 / 20 )16.61560.109873455968813151.224878233705
Trimmed Mean ( 6 / 20 )16.61666666666670.108877384566201152.618165222028
Trimmed Mean ( 7 / 20 )16.61826086956520.107682349262937154.326693123931
Trimmed Mean ( 8 / 20 )16.61886363636360.106416358836517156.168316770681
Trimmed Mean ( 9 / 20 )16.61833333333330.105177752682356158.002361806701
Trimmed Mean ( 10 / 20 )16.617750.103516063103814160.533056433323
Trimmed Mean ( 11 / 20 )16.61631578947370.101513035168157163.686523232693
Trimmed Mean ( 12 / 20 )16.61444444444440.0995477427489933166.899258442628
Trimmed Mean ( 13 / 20 )16.61029411764710.0977797055575225169.874658784644
Trimmed Mean ( 14 / 20 )16.60406250.0966222476708117171.845127807101
Trimmed Mean ( 15 / 20 )16.5980.0955773743244635173.660347099027
Trimmed Mean ( 16 / 20 )16.59142857142860.0946599515359698175.274002386574
Trimmed Mean ( 17 / 20 )16.58423076923080.0931932204152263177.95533511278
Trimmed Mean ( 18 / 20 )16.57708333333330.0912126023557185181.741150950662
Trimmed Mean ( 19 / 20 )16.56909090909090.0890593194282155186.045559470574
Trimmed Mean ( 20 / 20 )16.5630.0864051046250345191.69006358915
Median16.54
Midrange16.535
Midmean - Weighted Average at Xnp16.5751612903226
Midmean - Weighted Average at X(n+1)p16.598
Midmean - Empirical Distribution Function16.5751612903226
Midmean - Empirical Distribution Function - Averaging16.598
Midmean - Empirical Distribution Function - Interpolation16.598
Midmean - Closest Observation16.5751612903226
Midmean - True Basic - Statistics Graphics Toolkit16.598
Midmean - MS Excel (old versions)16.6040625
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 16.6103333333333 & 0.114341881711694 & 145.269022030049 \tabularnewline
Geometric Mean & 16.5870912215126 &  &  \tabularnewline
Harmonic Mean & 16.5638560685033 &  &  \tabularnewline
Quadratic Mean & 16.6335367055035 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 16.6115 & 0.113758050562572 & 146.024830048076 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 16.6138333333333 & 0.113167814909762 & 146.807052398961 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 16.6143333333333 & 0.112693616607621 & 147.429231871948 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 16.613 & 0.111460337249001 & 149.048535201242 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 16.6113333333333 & 0.111161425519559 & 149.434331699988 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 16.6093333333333 & 0.110447182117358 & 150.382590256443 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 16.6151666666667 & 0.10897532288604 & 152.467239615723 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 16.6218333333333 & 0.106877746217512 & 155.521929696248 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 16.6218333333333 & 0.10636030111599 & 156.278547154606 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 16.6268333333333 & 0.104943754552549 & 158.435663029453 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 16.6286666666667 & 0.101548036743594 & 163.751729722295 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 16.6426666666667 & 0.0973365257583418 & 170.980693393409 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 16.6535 & 0.0915324106717933 & 181.941018244502 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 16.6465 & 0.088185354677866 & 188.767171837187 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 16.644 & 0.0847102739251537 & 196.481480094208 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 16.6413333333333 & 0.0834728098315111 & 199.36232369467 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 16.6328333333333 & 0.081266838035071 & 204.669379730947 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 16.6298333333333 & 0.0772154852837712 & 215.369148716968 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 16.6076666666667 & 0.0738009104818312 & 225.033357423893 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 16.5943333333333 & 0.0650216681253287 & 255.212359383766 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 16.6129310344828 & 0.113144573053306 & 146.829234369516 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 16.6144642857143 & 0.112287004614872 & 147.964266592554 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 16.6148148148148 & 0.111501956418563 & 149.009177493219 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 16.615 & 0.110629114183281 & 150.186504905695 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 16.6156 & 0.109873455968813 & 151.224878233705 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 16.6166666666667 & 0.108877384566201 & 152.618165222028 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 16.6182608695652 & 0.107682349262937 & 154.326693123931 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 16.6188636363636 & 0.106416358836517 & 156.168316770681 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 16.6183333333333 & 0.105177752682356 & 158.002361806701 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 16.61775 & 0.103516063103814 & 160.533056433323 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 16.6163157894737 & 0.101513035168157 & 163.686523232693 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 16.6144444444444 & 0.0995477427489933 & 166.899258442628 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 16.6102941176471 & 0.0977797055575225 & 169.874658784644 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 16.6040625 & 0.0966222476708117 & 171.845127807101 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 16.598 & 0.0955773743244635 & 173.660347099027 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 16.5914285714286 & 0.0946599515359698 & 175.274002386574 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 16.5842307692308 & 0.0931932204152263 & 177.95533511278 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 16.5770833333333 & 0.0912126023557185 & 181.741150950662 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 16.5690909090909 & 0.0890593194282155 & 186.045559470574 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 16.563 & 0.0864051046250345 & 191.69006358915 \tabularnewline
Median & 16.54 &  &  \tabularnewline
Midrange & 16.535 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 16.5751612903226 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 16.598 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 16.5751612903226 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 16.598 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 16.598 &  &  \tabularnewline
Midmean - Closest Observation & 16.5751612903226 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 16.598 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 16.6040625 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163517&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]16.6103333333333[/C][C]0.114341881711694[/C][C]145.269022030049[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]16.5870912215126[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]16.5638560685033[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]16.6335367055035[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]16.6115[/C][C]0.113758050562572[/C][C]146.024830048076[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]16.6138333333333[/C][C]0.113167814909762[/C][C]146.807052398961[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]16.6143333333333[/C][C]0.112693616607621[/C][C]147.429231871948[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]16.613[/C][C]0.111460337249001[/C][C]149.048535201242[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]16.6113333333333[/C][C]0.111161425519559[/C][C]149.434331699988[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]16.6093333333333[/C][C]0.110447182117358[/C][C]150.382590256443[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]16.6151666666667[/C][C]0.10897532288604[/C][C]152.467239615723[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]16.6218333333333[/C][C]0.106877746217512[/C][C]155.521929696248[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]16.6218333333333[/C][C]0.10636030111599[/C][C]156.278547154606[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]16.6268333333333[/C][C]0.104943754552549[/C][C]158.435663029453[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]16.6286666666667[/C][C]0.101548036743594[/C][C]163.751729722295[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]16.6426666666667[/C][C]0.0973365257583418[/C][C]170.980693393409[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]16.6535[/C][C]0.0915324106717933[/C][C]181.941018244502[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]16.6465[/C][C]0.088185354677866[/C][C]188.767171837187[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]16.644[/C][C]0.0847102739251537[/C][C]196.481480094208[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]16.6413333333333[/C][C]0.0834728098315111[/C][C]199.36232369467[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]16.6328333333333[/C][C]0.081266838035071[/C][C]204.669379730947[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]16.6298333333333[/C][C]0.0772154852837712[/C][C]215.369148716968[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]16.6076666666667[/C][C]0.0738009104818312[/C][C]225.033357423893[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]16.5943333333333[/C][C]0.0650216681253287[/C][C]255.212359383766[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]16.6129310344828[/C][C]0.113144573053306[/C][C]146.829234369516[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]16.6144642857143[/C][C]0.112287004614872[/C][C]147.964266592554[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]16.6148148148148[/C][C]0.111501956418563[/C][C]149.009177493219[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]16.615[/C][C]0.110629114183281[/C][C]150.186504905695[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]16.6156[/C][C]0.109873455968813[/C][C]151.224878233705[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]16.6166666666667[/C][C]0.108877384566201[/C][C]152.618165222028[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]16.6182608695652[/C][C]0.107682349262937[/C][C]154.326693123931[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]16.6188636363636[/C][C]0.106416358836517[/C][C]156.168316770681[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]16.6183333333333[/C][C]0.105177752682356[/C][C]158.002361806701[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]16.61775[/C][C]0.103516063103814[/C][C]160.533056433323[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]16.6163157894737[/C][C]0.101513035168157[/C][C]163.686523232693[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]16.6144444444444[/C][C]0.0995477427489933[/C][C]166.899258442628[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]16.6102941176471[/C][C]0.0977797055575225[/C][C]169.874658784644[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]16.6040625[/C][C]0.0966222476708117[/C][C]171.845127807101[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]16.598[/C][C]0.0955773743244635[/C][C]173.660347099027[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]16.5914285714286[/C][C]0.0946599515359698[/C][C]175.274002386574[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]16.5842307692308[/C][C]0.0931932204152263[/C][C]177.95533511278[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]16.5770833333333[/C][C]0.0912126023557185[/C][C]181.741150950662[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]16.5690909090909[/C][C]0.0890593194282155[/C][C]186.045559470574[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]16.563[/C][C]0.0864051046250345[/C][C]191.69006358915[/C][/ROW]
[ROW][C]Median[/C][C]16.54[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]16.535[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]16.5751612903226[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]16.598[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]16.5751612903226[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]16.598[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]16.598[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]16.5751612903226[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]16.598[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]16.6040625[/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=163517&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163517&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 Mean16.61033333333330.114341881711694145.269022030049
Geometric Mean16.5870912215126
Harmonic Mean16.5638560685033
Quadratic Mean16.6335367055035
Winsorized Mean ( 1 / 20 )16.61150.113758050562572146.024830048076
Winsorized Mean ( 2 / 20 )16.61383333333330.113167814909762146.807052398961
Winsorized Mean ( 3 / 20 )16.61433333333330.112693616607621147.429231871948
Winsorized Mean ( 4 / 20 )16.6130.111460337249001149.048535201242
Winsorized Mean ( 5 / 20 )16.61133333333330.111161425519559149.434331699988
Winsorized Mean ( 6 / 20 )16.60933333333330.110447182117358150.382590256443
Winsorized Mean ( 7 / 20 )16.61516666666670.10897532288604152.467239615723
Winsorized Mean ( 8 / 20 )16.62183333333330.106877746217512155.521929696248
Winsorized Mean ( 9 / 20 )16.62183333333330.10636030111599156.278547154606
Winsorized Mean ( 10 / 20 )16.62683333333330.104943754552549158.435663029453
Winsorized Mean ( 11 / 20 )16.62866666666670.101548036743594163.751729722295
Winsorized Mean ( 12 / 20 )16.64266666666670.0973365257583418170.980693393409
Winsorized Mean ( 13 / 20 )16.65350.0915324106717933181.941018244502
Winsorized Mean ( 14 / 20 )16.64650.088185354677866188.767171837187
Winsorized Mean ( 15 / 20 )16.6440.0847102739251537196.481480094208
Winsorized Mean ( 16 / 20 )16.64133333333330.0834728098315111199.36232369467
Winsorized Mean ( 17 / 20 )16.63283333333330.081266838035071204.669379730947
Winsorized Mean ( 18 / 20 )16.62983333333330.0772154852837712215.369148716968
Winsorized Mean ( 19 / 20 )16.60766666666670.0738009104818312225.033357423893
Winsorized Mean ( 20 / 20 )16.59433333333330.0650216681253287255.212359383766
Trimmed Mean ( 1 / 20 )16.61293103448280.113144573053306146.829234369516
Trimmed Mean ( 2 / 20 )16.61446428571430.112287004614872147.964266592554
Trimmed Mean ( 3 / 20 )16.61481481481480.111501956418563149.009177493219
Trimmed Mean ( 4 / 20 )16.6150.110629114183281150.186504905695
Trimmed Mean ( 5 / 20 )16.61560.109873455968813151.224878233705
Trimmed Mean ( 6 / 20 )16.61666666666670.108877384566201152.618165222028
Trimmed Mean ( 7 / 20 )16.61826086956520.107682349262937154.326693123931
Trimmed Mean ( 8 / 20 )16.61886363636360.106416358836517156.168316770681
Trimmed Mean ( 9 / 20 )16.61833333333330.105177752682356158.002361806701
Trimmed Mean ( 10 / 20 )16.617750.103516063103814160.533056433323
Trimmed Mean ( 11 / 20 )16.61631578947370.101513035168157163.686523232693
Trimmed Mean ( 12 / 20 )16.61444444444440.0995477427489933166.899258442628
Trimmed Mean ( 13 / 20 )16.61029411764710.0977797055575225169.874658784644
Trimmed Mean ( 14 / 20 )16.60406250.0966222476708117171.845127807101
Trimmed Mean ( 15 / 20 )16.5980.0955773743244635173.660347099027
Trimmed Mean ( 16 / 20 )16.59142857142860.0946599515359698175.274002386574
Trimmed Mean ( 17 / 20 )16.58423076923080.0931932204152263177.95533511278
Trimmed Mean ( 18 / 20 )16.57708333333330.0912126023557185181.741150950662
Trimmed Mean ( 19 / 20 )16.56909090909090.0890593194282155186.045559470574
Trimmed Mean ( 20 / 20 )16.5630.0864051046250345191.69006358915
Median16.54
Midrange16.535
Midmean - Weighted Average at Xnp16.5751612903226
Midmean - Weighted Average at X(n+1)p16.598
Midmean - Empirical Distribution Function16.5751612903226
Midmean - Empirical Distribution Function - Averaging16.598
Midmean - Empirical Distribution Function - Interpolation16.598
Midmean - Closest Observation16.5751612903226
Midmean - True Basic - Statistics Graphics Toolkit16.598
Midmean - MS Excel (old versions)16.6040625
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')