Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 29 Dec 2009 14:57:55 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/29/t1262123958pomsqb91al2dmea.htm/, Retrieved Tue, 30 Apr 2024 03:35:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71211, Retrieved Tue, 30 Apr 2024 03:35:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsRobustness of Central Tendency
Estimated Impact162
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [WS7] [2009-11-18 17:01:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Multiple Regression] [WS7(2)] [2009-11-20 19:01:46] [7d268329e554b8694908ba13e6e6f258]
-   P         [Multiple Regression] [WS7(3)] [2009-11-21 10:22:47] [7d268329e554b8694908ba13e6e6f258]
-   PD          [Multiple Regression] [WS7(4)] [2009-11-21 10:55:20] [7d268329e554b8694908ba13e6e6f258]
- RMPD            [Univariate Data Series] [Niet-werkende wer...] [2009-11-25 19:16:52] [9717cb857c153ca3061376906953b329]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA] [2009-12-17 13:35:10] [9717cb857c153ca3061376906953b329]
- RMP                 [Central Tendency] [Robustness of Cen...] [2009-12-17 22:54:55] [9717cb857c153ca3061376906953b329]
-    D                    [Central Tendency] [Robustness of Cen...] [2009-12-29 21:57:55] [52b85b290d6f50b0921ad6729b8a5af2] [Current]
Feedback Forum

Post a new message
Dataseries X:
-706.026542296181 
-59.4405579520267 
-969.833720383066 
1994.56903063601 
102.064814516947 
1282.18411025837 
-307.754606959943 
225.069461418321 
-862.471322666482 
-2850.16172979440 
-3875.76341994283 
2996.98129088558 
1931.51753614196 
488.179241950267 
-601.581627830989 
-3495.10356420977 
265.163825175723 
640.313274555833 
-3418.45097379814 
2072.03398243007 
2662.9984145817 
-1064.81719671349 
-9.57987333730985 
-2208.8867746199 
-4275.21498681124 
381.837227886395 
1914.99171248840 
1019.08609621188 
884.745394297871 
-1702.08983953302 
-2064.71644375347 
-2452.89205796152 
1313.39939683182 
-569.737683944086 
-187.9171774845 
-128.334928612711 
-2601.14827891639 
581.657297679053 
-299.792761503996 
2868.57371158154 
2723.0124492194 
-1846.18418996859 
-6526.92686969168 
-3652.78139505582 
2790.5729463211 
-7703.28365973859 
-1373.42544129638 
-2976.48819823291 
5585.1945937738 
-2568.07437379205 
-4750.48266905558 
1324.51875012340 
-1689.96832952026 
-7068.09981170815 
1855.55513995599 
2269.56153308754 
-4661.24493442205 
3260.97170059017 
2160.39821896397 
4793.18303923311 
-2209.06420471032 
-2213.50510931699 
-3114.14394163762 
3411.46075067066 
-4693.81993673823 
5920.52037235391 
-2077.91680939984 
-3642.83868232441 
332.648590721953 
2734.67402718683 
7903.1305482291 
5491.06198558059 
4354.83029956606 
1619.51905250655 
5543.22938817069 
-366.008933224093 
-3459.03179080274 
1134.72876550400 
-2525.56367971036 
-926.76612281528 
-2956.34221718809 
-885.143314774538 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71211&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71211&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71211&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' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-241.03271601053336.628696282865-0.716019515484186
Geometric MeanNaN
Harmonic Mean-671.500373256785
Quadratic Mean3039.23114985297
Winsorized Mean ( 1 / 27 )-257.464744398881328.144540480607-0.784607734206983
Winsorized Mean ( 2 / 27 )-252.444081876043323.006691877249-0.78154443305459
Winsorized Mean ( 3 / 27 )-188.987533277275308.900588288296-0.611806971053398
Winsorized Mean ( 4 / 27 )-188.768248900336307.817573988939-0.613247146529453
Winsorized Mean ( 5 / 27 )-229.335562560781298.177791946404-0.769123552306682
Winsorized Mean ( 6 / 27 )-233.164059540506286.617138224641-0.813503550362572
Winsorized Mean ( 7 / 27 )-279.596082396468265.899723319948-1.05150948976370
Winsorized Mean ( 8 / 27 )-272.523597049491259.845117396767-1.04879244905481
Winsorized Mean ( 9 / 27 )-300.40688086362254.922408245584-1.17842477219271
Winsorized Mean ( 10 / 27 )-298.049863935498249.562054373717-1.1942915948639
Winsorized Mean ( 11 / 27 )-303.674484793883247.169890757169-1.22860629934989
Winsorized Mean ( 12 / 27 )-305.916158276273244.977234937487-1.24875341316648
Winsorized Mean ( 13 / 27 )-259.521147245662237.323233246812-1.09353451701783
Winsorized Mean ( 14 / 27 )-246.265245748855232.285541711319-1.06018327242644
Winsorized Mean ( 15 / 27 )-314.550166562759220.977796956624-1.42344692948723
Winsorized Mean ( 16 / 27 )-315.132181534442214.887303549307-1.46649977141220
Winsorized Mean ( 17 / 27 )-281.826856609444204.915658161519-1.37533099782595
Winsorized Mean ( 18 / 27 )-291.571232707675201.505365989708-1.44696510326463
Winsorized Mean ( 19 / 27 )-296.330686461759198.096766999850-1.49588855461727
Winsorized Mean ( 20 / 27 )-282.636589365349195.088170885498-1.44876333650817
Winsorized Mean ( 21 / 27 )-236.551736946391184.700758330599-1.28072964661565
Winsorized Mean ( 22 / 27 )-298.687029904208175.846182292762-1.69856988653260
Winsorized Mean ( 23 / 27 )-381.381250181437164.977112342507-2.31172218234525
Winsorized Mean ( 24 / 27 )-346.303022299931159.367171828832-2.17298844125737
Winsorized Mean ( 25 / 27 )-351.795376241113157.606381875856-2.23211377644731
Winsorized Mean ( 26 / 27 )-329.258795329001142.438219887065-2.31159021497222
Winsorized Mean ( 27 / 27 )-319.890558854938131.426156032812-2.43399463631177
Trimmed Mean ( 1 / 27 )-249.556620016925315.888739829589-0.790014294753122
Trimmed Mean ( 2 / 27 )-241.242950794868301.532832274047-0.800055333860346
Trimmed Mean ( 3 / 27 )-235.200235343182287.950365497764-0.816808254216328
Trimmed Mean ( 4 / 27 )-252.269791962121278.442496179480-0.906003197872181
Trimmed Mean ( 5 / 27 )-270.350092417213267.604536238916-1.01025975200901
Trimmed Mean ( 6 / 27 )-279.95921084072257.860168569972-1.08570165137681
Trimmed Mean ( 7 / 27 )-289.364118700077249.541439887162-1.15958342963366
Trimmed Mean ( 8 / 27 )-291.097839429288244.828942255065-1.18898458959979
Trimmed Mean ( 9 / 27 )-294.072620435428240.508882176985-1.22271002124166
Trimmed Mean ( 10 / 27 )-293.141779297235236.303159395032-1.24053262786548
Trimmed Mean ( 11 / 27 )-292.471007730006232.24205636886-1.25933697067118
Trimmed Mean ( 12 / 27 )-291.031062402046227.696832573908-1.27815156281360
Trimmed Mean ( 13 / 27 )-289.214726298346222.490727012042-1.29989564141562
Trimmed Mean ( 14 / 27 )-292.683207042392217.517402084283-1.34556225956112
Trimmed Mean ( 15 / 27 )-297.911603781499212.249203330206-1.40359350757149
Trimmed Mean ( 16 / 27 )-296.092454250748207.819124438115-1.42476037781075
Trimmed Mean ( 17 / 27 )-294.059566702228203.313331539242-1.44633686574297
Trimmed Mean ( 18 / 27 )-295.342280548275199.435900648481-1.48088824322976
Trimmed Mean ( 19 / 27 )-295.73271731965194.974618529645-1.51677546313386
Trimmed Mean ( 20 / 27 )-295.671271868957189.736327173632-1.55832715997702
Trimmed Mean ( 21 / 27 )-297.007326825577183.364354630426-1.61976588865486
Trimmed Mean ( 22 / 27 )-303.219555359529177.189862096432-1.71126921016794
Trimmed Mean ( 23 / 27 )-303.688831984953170.931036161888-1.77667460985453
Trimmed Mean ( 24 / 27 )-295.542056675348164.957868510098-1.79162145670703
Trimmed Mean ( 25 / 27 )-290.122266074806158.000229857812-1.83621420257359
Trimmed Mean ( 26 / 27 )-283.37933936329148.330417919351-1.91046006165348
Trimmed Mean ( 27 / 27 )-278.211598444075139.384165426935-1.99600577003788
Median-243.854969494248
Midrange99.9234442452548
Midmean - Weighted Average at Xnp-349.589881243527
Midmean - Weighted Average at X(n+1)p-295.671271868958
Midmean - Empirical Distribution Function-295.671271868958
Midmean - Empirical Distribution Function - Averaging-295.671271868958
Midmean - Empirical Distribution Function - Interpolation-297.007326825577
Midmean - Closest Observation-295.671271868958
Midmean - True Basic - Statistics Graphics Toolkit-295.671271868958
Midmean - MS Excel (old versions)-295.671271868958
Number of observations82

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -241.03271601053 & 336.628696282865 & -0.716019515484186 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -671.500373256785 &  &  \tabularnewline
Quadratic Mean & 3039.23114985297 &  &  \tabularnewline
Winsorized Mean ( 1 / 27 ) & -257.464744398881 & 328.144540480607 & -0.784607734206983 \tabularnewline
Winsorized Mean ( 2 / 27 ) & -252.444081876043 & 323.006691877249 & -0.78154443305459 \tabularnewline
Winsorized Mean ( 3 / 27 ) & -188.987533277275 & 308.900588288296 & -0.611806971053398 \tabularnewline
Winsorized Mean ( 4 / 27 ) & -188.768248900336 & 307.817573988939 & -0.613247146529453 \tabularnewline
Winsorized Mean ( 5 / 27 ) & -229.335562560781 & 298.177791946404 & -0.769123552306682 \tabularnewline
Winsorized Mean ( 6 / 27 ) & -233.164059540506 & 286.617138224641 & -0.813503550362572 \tabularnewline
Winsorized Mean ( 7 / 27 ) & -279.596082396468 & 265.899723319948 & -1.05150948976370 \tabularnewline
Winsorized Mean ( 8 / 27 ) & -272.523597049491 & 259.845117396767 & -1.04879244905481 \tabularnewline
Winsorized Mean ( 9 / 27 ) & -300.40688086362 & 254.922408245584 & -1.17842477219271 \tabularnewline
Winsorized Mean ( 10 / 27 ) & -298.049863935498 & 249.562054373717 & -1.1942915948639 \tabularnewline
Winsorized Mean ( 11 / 27 ) & -303.674484793883 & 247.169890757169 & -1.22860629934989 \tabularnewline
Winsorized Mean ( 12 / 27 ) & -305.916158276273 & 244.977234937487 & -1.24875341316648 \tabularnewline
Winsorized Mean ( 13 / 27 ) & -259.521147245662 & 237.323233246812 & -1.09353451701783 \tabularnewline
Winsorized Mean ( 14 / 27 ) & -246.265245748855 & 232.285541711319 & -1.06018327242644 \tabularnewline
Winsorized Mean ( 15 / 27 ) & -314.550166562759 & 220.977796956624 & -1.42344692948723 \tabularnewline
Winsorized Mean ( 16 / 27 ) & -315.132181534442 & 214.887303549307 & -1.46649977141220 \tabularnewline
Winsorized Mean ( 17 / 27 ) & -281.826856609444 & 204.915658161519 & -1.37533099782595 \tabularnewline
Winsorized Mean ( 18 / 27 ) & -291.571232707675 & 201.505365989708 & -1.44696510326463 \tabularnewline
Winsorized Mean ( 19 / 27 ) & -296.330686461759 & 198.096766999850 & -1.49588855461727 \tabularnewline
Winsorized Mean ( 20 / 27 ) & -282.636589365349 & 195.088170885498 & -1.44876333650817 \tabularnewline
Winsorized Mean ( 21 / 27 ) & -236.551736946391 & 184.700758330599 & -1.28072964661565 \tabularnewline
Winsorized Mean ( 22 / 27 ) & -298.687029904208 & 175.846182292762 & -1.69856988653260 \tabularnewline
Winsorized Mean ( 23 / 27 ) & -381.381250181437 & 164.977112342507 & -2.31172218234525 \tabularnewline
Winsorized Mean ( 24 / 27 ) & -346.303022299931 & 159.367171828832 & -2.17298844125737 \tabularnewline
Winsorized Mean ( 25 / 27 ) & -351.795376241113 & 157.606381875856 & -2.23211377644731 \tabularnewline
Winsorized Mean ( 26 / 27 ) & -329.258795329001 & 142.438219887065 & -2.31159021497222 \tabularnewline
Winsorized Mean ( 27 / 27 ) & -319.890558854938 & 131.426156032812 & -2.43399463631177 \tabularnewline
Trimmed Mean ( 1 / 27 ) & -249.556620016925 & 315.888739829589 & -0.790014294753122 \tabularnewline
Trimmed Mean ( 2 / 27 ) & -241.242950794868 & 301.532832274047 & -0.800055333860346 \tabularnewline
Trimmed Mean ( 3 / 27 ) & -235.200235343182 & 287.950365497764 & -0.816808254216328 \tabularnewline
Trimmed Mean ( 4 / 27 ) & -252.269791962121 & 278.442496179480 & -0.906003197872181 \tabularnewline
Trimmed Mean ( 5 / 27 ) & -270.350092417213 & 267.604536238916 & -1.01025975200901 \tabularnewline
Trimmed Mean ( 6 / 27 ) & -279.95921084072 & 257.860168569972 & -1.08570165137681 \tabularnewline
Trimmed Mean ( 7 / 27 ) & -289.364118700077 & 249.541439887162 & -1.15958342963366 \tabularnewline
Trimmed Mean ( 8 / 27 ) & -291.097839429288 & 244.828942255065 & -1.18898458959979 \tabularnewline
Trimmed Mean ( 9 / 27 ) & -294.072620435428 & 240.508882176985 & -1.22271002124166 \tabularnewline
Trimmed Mean ( 10 / 27 ) & -293.141779297235 & 236.303159395032 & -1.24053262786548 \tabularnewline
Trimmed Mean ( 11 / 27 ) & -292.471007730006 & 232.24205636886 & -1.25933697067118 \tabularnewline
Trimmed Mean ( 12 / 27 ) & -291.031062402046 & 227.696832573908 & -1.27815156281360 \tabularnewline
Trimmed Mean ( 13 / 27 ) & -289.214726298346 & 222.490727012042 & -1.29989564141562 \tabularnewline
Trimmed Mean ( 14 / 27 ) & -292.683207042392 & 217.517402084283 & -1.34556225956112 \tabularnewline
Trimmed Mean ( 15 / 27 ) & -297.911603781499 & 212.249203330206 & -1.40359350757149 \tabularnewline
Trimmed Mean ( 16 / 27 ) & -296.092454250748 & 207.819124438115 & -1.42476037781075 \tabularnewline
Trimmed Mean ( 17 / 27 ) & -294.059566702228 & 203.313331539242 & -1.44633686574297 \tabularnewline
Trimmed Mean ( 18 / 27 ) & -295.342280548275 & 199.435900648481 & -1.48088824322976 \tabularnewline
Trimmed Mean ( 19 / 27 ) & -295.73271731965 & 194.974618529645 & -1.51677546313386 \tabularnewline
Trimmed Mean ( 20 / 27 ) & -295.671271868957 & 189.736327173632 & -1.55832715997702 \tabularnewline
Trimmed Mean ( 21 / 27 ) & -297.007326825577 & 183.364354630426 & -1.61976588865486 \tabularnewline
Trimmed Mean ( 22 / 27 ) & -303.219555359529 & 177.189862096432 & -1.71126921016794 \tabularnewline
Trimmed Mean ( 23 / 27 ) & -303.688831984953 & 170.931036161888 & -1.77667460985453 \tabularnewline
Trimmed Mean ( 24 / 27 ) & -295.542056675348 & 164.957868510098 & -1.79162145670703 \tabularnewline
Trimmed Mean ( 25 / 27 ) & -290.122266074806 & 158.000229857812 & -1.83621420257359 \tabularnewline
Trimmed Mean ( 26 / 27 ) & -283.37933936329 & 148.330417919351 & -1.91046006165348 \tabularnewline
Trimmed Mean ( 27 / 27 ) & -278.211598444075 & 139.384165426935 & -1.99600577003788 \tabularnewline
Median & -243.854969494248 &  &  \tabularnewline
Midrange & 99.9234442452548 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -349.589881243527 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -295.671271868958 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -295.671271868958 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -295.671271868958 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -297.007326825577 &  &  \tabularnewline
Midmean - Closest Observation & -295.671271868958 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -295.671271868958 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -295.671271868958 &  &  \tabularnewline
Number of observations & 82 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71211&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]-241.03271601053[/C][C]336.628696282865[/C][C]-0.716019515484186[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-671.500373256785[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]3039.23114985297[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 27 )[/C][C]-257.464744398881[/C][C]328.144540480607[/C][C]-0.784607734206983[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 27 )[/C][C]-252.444081876043[/C][C]323.006691877249[/C][C]-0.78154443305459[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 27 )[/C][C]-188.987533277275[/C][C]308.900588288296[/C][C]-0.611806971053398[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 27 )[/C][C]-188.768248900336[/C][C]307.817573988939[/C][C]-0.613247146529453[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 27 )[/C][C]-229.335562560781[/C][C]298.177791946404[/C][C]-0.769123552306682[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 27 )[/C][C]-233.164059540506[/C][C]286.617138224641[/C][C]-0.813503550362572[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 27 )[/C][C]-279.596082396468[/C][C]265.899723319948[/C][C]-1.05150948976370[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 27 )[/C][C]-272.523597049491[/C][C]259.845117396767[/C][C]-1.04879244905481[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 27 )[/C][C]-300.40688086362[/C][C]254.922408245584[/C][C]-1.17842477219271[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 27 )[/C][C]-298.049863935498[/C][C]249.562054373717[/C][C]-1.1942915948639[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 27 )[/C][C]-303.674484793883[/C][C]247.169890757169[/C][C]-1.22860629934989[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 27 )[/C][C]-305.916158276273[/C][C]244.977234937487[/C][C]-1.24875341316648[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 27 )[/C][C]-259.521147245662[/C][C]237.323233246812[/C][C]-1.09353451701783[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 27 )[/C][C]-246.265245748855[/C][C]232.285541711319[/C][C]-1.06018327242644[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 27 )[/C][C]-314.550166562759[/C][C]220.977796956624[/C][C]-1.42344692948723[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 27 )[/C][C]-315.132181534442[/C][C]214.887303549307[/C][C]-1.46649977141220[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 27 )[/C][C]-281.826856609444[/C][C]204.915658161519[/C][C]-1.37533099782595[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 27 )[/C][C]-291.571232707675[/C][C]201.505365989708[/C][C]-1.44696510326463[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 27 )[/C][C]-296.330686461759[/C][C]198.096766999850[/C][C]-1.49588855461727[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 27 )[/C][C]-282.636589365349[/C][C]195.088170885498[/C][C]-1.44876333650817[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 27 )[/C][C]-236.551736946391[/C][C]184.700758330599[/C][C]-1.28072964661565[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 27 )[/C][C]-298.687029904208[/C][C]175.846182292762[/C][C]-1.69856988653260[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 27 )[/C][C]-381.381250181437[/C][C]164.977112342507[/C][C]-2.31172218234525[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 27 )[/C][C]-346.303022299931[/C][C]159.367171828832[/C][C]-2.17298844125737[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 27 )[/C][C]-351.795376241113[/C][C]157.606381875856[/C][C]-2.23211377644731[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 27 )[/C][C]-329.258795329001[/C][C]142.438219887065[/C][C]-2.31159021497222[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 27 )[/C][C]-319.890558854938[/C][C]131.426156032812[/C][C]-2.43399463631177[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 27 )[/C][C]-249.556620016925[/C][C]315.888739829589[/C][C]-0.790014294753122[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 27 )[/C][C]-241.242950794868[/C][C]301.532832274047[/C][C]-0.800055333860346[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 27 )[/C][C]-235.200235343182[/C][C]287.950365497764[/C][C]-0.816808254216328[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 27 )[/C][C]-252.269791962121[/C][C]278.442496179480[/C][C]-0.906003197872181[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 27 )[/C][C]-270.350092417213[/C][C]267.604536238916[/C][C]-1.01025975200901[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 27 )[/C][C]-279.95921084072[/C][C]257.860168569972[/C][C]-1.08570165137681[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 27 )[/C][C]-289.364118700077[/C][C]249.541439887162[/C][C]-1.15958342963366[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 27 )[/C][C]-291.097839429288[/C][C]244.828942255065[/C][C]-1.18898458959979[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 27 )[/C][C]-294.072620435428[/C][C]240.508882176985[/C][C]-1.22271002124166[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 27 )[/C][C]-293.141779297235[/C][C]236.303159395032[/C][C]-1.24053262786548[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 27 )[/C][C]-292.471007730006[/C][C]232.24205636886[/C][C]-1.25933697067118[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 27 )[/C][C]-291.031062402046[/C][C]227.696832573908[/C][C]-1.27815156281360[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 27 )[/C][C]-289.214726298346[/C][C]222.490727012042[/C][C]-1.29989564141562[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 27 )[/C][C]-292.683207042392[/C][C]217.517402084283[/C][C]-1.34556225956112[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 27 )[/C][C]-297.911603781499[/C][C]212.249203330206[/C][C]-1.40359350757149[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 27 )[/C][C]-296.092454250748[/C][C]207.819124438115[/C][C]-1.42476037781075[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 27 )[/C][C]-294.059566702228[/C][C]203.313331539242[/C][C]-1.44633686574297[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 27 )[/C][C]-295.342280548275[/C][C]199.435900648481[/C][C]-1.48088824322976[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 27 )[/C][C]-295.73271731965[/C][C]194.974618529645[/C][C]-1.51677546313386[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 27 )[/C][C]-295.671271868957[/C][C]189.736327173632[/C][C]-1.55832715997702[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 27 )[/C][C]-297.007326825577[/C][C]183.364354630426[/C][C]-1.61976588865486[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 27 )[/C][C]-303.219555359529[/C][C]177.189862096432[/C][C]-1.71126921016794[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 27 )[/C][C]-303.688831984953[/C][C]170.931036161888[/C][C]-1.77667460985453[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 27 )[/C][C]-295.542056675348[/C][C]164.957868510098[/C][C]-1.79162145670703[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 27 )[/C][C]-290.122266074806[/C][C]158.000229857812[/C][C]-1.83621420257359[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 27 )[/C][C]-283.37933936329[/C][C]148.330417919351[/C][C]-1.91046006165348[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 27 )[/C][C]-278.211598444075[/C][C]139.384165426935[/C][C]-1.99600577003788[/C][/ROW]
[ROW][C]Median[/C][C]-243.854969494248[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]99.9234442452548[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-349.589881243527[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-295.671271868958[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-295.671271868958[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-295.671271868958[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-297.007326825577[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-295.671271868958[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-295.671271868958[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-295.671271868958[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]82[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71211&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71211&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-241.03271601053336.628696282865-0.716019515484186
Geometric MeanNaN
Harmonic Mean-671.500373256785
Quadratic Mean3039.23114985297
Winsorized Mean ( 1 / 27 )-257.464744398881328.144540480607-0.784607734206983
Winsorized Mean ( 2 / 27 )-252.444081876043323.006691877249-0.78154443305459
Winsorized Mean ( 3 / 27 )-188.987533277275308.900588288296-0.611806971053398
Winsorized Mean ( 4 / 27 )-188.768248900336307.817573988939-0.613247146529453
Winsorized Mean ( 5 / 27 )-229.335562560781298.177791946404-0.769123552306682
Winsorized Mean ( 6 / 27 )-233.164059540506286.617138224641-0.813503550362572
Winsorized Mean ( 7 / 27 )-279.596082396468265.899723319948-1.05150948976370
Winsorized Mean ( 8 / 27 )-272.523597049491259.845117396767-1.04879244905481
Winsorized Mean ( 9 / 27 )-300.40688086362254.922408245584-1.17842477219271
Winsorized Mean ( 10 / 27 )-298.049863935498249.562054373717-1.1942915948639
Winsorized Mean ( 11 / 27 )-303.674484793883247.169890757169-1.22860629934989
Winsorized Mean ( 12 / 27 )-305.916158276273244.977234937487-1.24875341316648
Winsorized Mean ( 13 / 27 )-259.521147245662237.323233246812-1.09353451701783
Winsorized Mean ( 14 / 27 )-246.265245748855232.285541711319-1.06018327242644
Winsorized Mean ( 15 / 27 )-314.550166562759220.977796956624-1.42344692948723
Winsorized Mean ( 16 / 27 )-315.132181534442214.887303549307-1.46649977141220
Winsorized Mean ( 17 / 27 )-281.826856609444204.915658161519-1.37533099782595
Winsorized Mean ( 18 / 27 )-291.571232707675201.505365989708-1.44696510326463
Winsorized Mean ( 19 / 27 )-296.330686461759198.096766999850-1.49588855461727
Winsorized Mean ( 20 / 27 )-282.636589365349195.088170885498-1.44876333650817
Winsorized Mean ( 21 / 27 )-236.551736946391184.700758330599-1.28072964661565
Winsorized Mean ( 22 / 27 )-298.687029904208175.846182292762-1.69856988653260
Winsorized Mean ( 23 / 27 )-381.381250181437164.977112342507-2.31172218234525
Winsorized Mean ( 24 / 27 )-346.303022299931159.367171828832-2.17298844125737
Winsorized Mean ( 25 / 27 )-351.795376241113157.606381875856-2.23211377644731
Winsorized Mean ( 26 / 27 )-329.258795329001142.438219887065-2.31159021497222
Winsorized Mean ( 27 / 27 )-319.890558854938131.426156032812-2.43399463631177
Trimmed Mean ( 1 / 27 )-249.556620016925315.888739829589-0.790014294753122
Trimmed Mean ( 2 / 27 )-241.242950794868301.532832274047-0.800055333860346
Trimmed Mean ( 3 / 27 )-235.200235343182287.950365497764-0.816808254216328
Trimmed Mean ( 4 / 27 )-252.269791962121278.442496179480-0.906003197872181
Trimmed Mean ( 5 / 27 )-270.350092417213267.604536238916-1.01025975200901
Trimmed Mean ( 6 / 27 )-279.95921084072257.860168569972-1.08570165137681
Trimmed Mean ( 7 / 27 )-289.364118700077249.541439887162-1.15958342963366
Trimmed Mean ( 8 / 27 )-291.097839429288244.828942255065-1.18898458959979
Trimmed Mean ( 9 / 27 )-294.072620435428240.508882176985-1.22271002124166
Trimmed Mean ( 10 / 27 )-293.141779297235236.303159395032-1.24053262786548
Trimmed Mean ( 11 / 27 )-292.471007730006232.24205636886-1.25933697067118
Trimmed Mean ( 12 / 27 )-291.031062402046227.696832573908-1.27815156281360
Trimmed Mean ( 13 / 27 )-289.214726298346222.490727012042-1.29989564141562
Trimmed Mean ( 14 / 27 )-292.683207042392217.517402084283-1.34556225956112
Trimmed Mean ( 15 / 27 )-297.911603781499212.249203330206-1.40359350757149
Trimmed Mean ( 16 / 27 )-296.092454250748207.819124438115-1.42476037781075
Trimmed Mean ( 17 / 27 )-294.059566702228203.313331539242-1.44633686574297
Trimmed Mean ( 18 / 27 )-295.342280548275199.435900648481-1.48088824322976
Trimmed Mean ( 19 / 27 )-295.73271731965194.974618529645-1.51677546313386
Trimmed Mean ( 20 / 27 )-295.671271868957189.736327173632-1.55832715997702
Trimmed Mean ( 21 / 27 )-297.007326825577183.364354630426-1.61976588865486
Trimmed Mean ( 22 / 27 )-303.219555359529177.189862096432-1.71126921016794
Trimmed Mean ( 23 / 27 )-303.688831984953170.931036161888-1.77667460985453
Trimmed Mean ( 24 / 27 )-295.542056675348164.957868510098-1.79162145670703
Trimmed Mean ( 25 / 27 )-290.122266074806158.000229857812-1.83621420257359
Trimmed Mean ( 26 / 27 )-283.37933936329148.330417919351-1.91046006165348
Trimmed Mean ( 27 / 27 )-278.211598444075139.384165426935-1.99600577003788
Median-243.854969494248
Midrange99.9234442452548
Midmean - Weighted Average at Xnp-349.589881243527
Midmean - Weighted Average at X(n+1)p-295.671271868958
Midmean - Empirical Distribution Function-295.671271868958
Midmean - Empirical Distribution Function - Averaging-295.671271868958
Midmean - Empirical Distribution Function - Interpolation-297.007326825577
Midmean - Closest Observation-295.671271868958
Midmean - True Basic - Statistics Graphics Toolkit-295.671271868958
Midmean - MS Excel (old versions)-295.671271868958
Number of observations82



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')