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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 23 Feb 2015 21:14:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Feb/23/t14247268933kegwgwfgo56kf7.htm/, Retrieved Sat, 18 May 2024 12:41:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=277443, Retrieved Sat, 18 May 2024 12:41:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2015-02-23 21:14:42] [36d9fcfacb97c24df6a506fb08c7a09a] [Current]
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Dataseries X:
599
599
599
599
599
599
599
599
599
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
665,27
665,27
665,27
665,27
665,27
665,27
665,27
665,27
665,27
665,27
665,27
665,27
674,3
674,3
674,3
674,3
674,3
674,3
674,3
674,3
674,3
674,3
674,3
674,3
685,34
685,34
685,34
685,34
685,34
685,34
685,34
685,34
685,34
685,34
685,34
685,34
694,3
694,3
694,3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277443&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277443&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277443&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'Herman Ole Andreas Wold' @ wold.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean650.2831252.92125518756718222.604012058787
Geometric Mean649.652850462815
Harmonic Mean649.016047317788
Quadratic Mean650.906173874161
Winsorized Mean ( 1 / 32 )650.2831252.92125518756718222.604012058787
Winsorized Mean ( 2 / 32 )650.2831252.92125518756718222.604012058787
Winsorized Mean ( 3 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 4 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 5 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 6 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 7 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 8 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 9 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 10 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 11 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 12 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 13 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 14 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 15 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 16 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 17 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 18 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 19 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 20 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 21 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 22 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 23 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 24 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 25 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 26 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 27 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 28 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 29 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 30 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 31 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 32 / 32 )650.69093751.88342582879987345.482645268078
Trimmed Mean ( 1 / 32 )650.3604255319152.89485593641291224.660722266474
Trimmed Mean ( 2 / 32 )650.4410869565222.86439939354252227.077651399756
Trimmed Mean ( 3 / 32 )650.5253333333332.829310257701229.92364713721
Trimmed Mean ( 4 / 32 )650.7152272727272.80528702954093231.960302250858
Trimmed Mean ( 5 / 32 )650.9139534883722.77701115930554234.393711853556
Trimmed Mean ( 6 / 32 )651.1221428571432.74382789382675237.304294603201
Trimmed Mean ( 7 / 32 )651.3404878048782.70494910317756240.795838649879
Trimmed Mean ( 8 / 32 )651.569752.65941582511168245.004840479445
Trimmed Mean ( 9 / 32 )651.8107692307692.60604631863918250.1148059299
Trimmed Mean ( 10 / 32 )651.8268421052632.5974943541166250.944469262166
Trimmed Mean ( 11 / 32 )651.8437837837842.58602036376993252.064443465371
Trimmed Mean ( 12 / 32 )651.8616666666672.57113015802679253.531181465716
Trimmed Mean ( 13 / 32 )651.8805714285712.55222758940999255.416317155035
Trimmed Mean ( 14 / 32 )651.9005882352942.52858714226186257.812189795508
Trimmed Mean ( 15 / 32 )651.9218181818182.49931681955817260.84000758938
Trimmed Mean ( 16 / 32 )652.1168752.49400488388918261.473776259444
Trimmed Mean ( 17 / 32 )652.3245161290322.48504435805964262.500149751201
Trimmed Mean ( 18 / 32 )652.5462.47165190078297264.012096441771
Trimmed Mean ( 19 / 32 )652.782758620692.45284256488276266.133166460233
Trimmed Mean ( 20 / 32 )653.0364285714292.42736221041619269.031307222773
Trimmed Mean ( 21 / 32 )653.3088888888892.39358983615621272.941035686389
Trimmed Mean ( 22 / 32 )653.3884615384622.40386505935251271.807462318395
Trimmed Mean ( 23 / 32 )653.47442.41184424582568270.943864277723
Trimmed Mean ( 24 / 32 )653.56752.41685347468255270.420820644017
Trimmed Mean ( 25 / 32 )653.6686956521742.41801520812709270.332747889739
Trimmed Mean ( 26 / 32 )653.7790909090912.41417264898122270.808755614469
Trimmed Mean ( 27 / 32 )653.92.40377838467861272.030069064553
Trimmed Mean ( 28 / 32 )654.185252.41263049301656271.150203851589
Trimmed Mean ( 29 / 32 )654.5005263157892.41552620537292270.955672043618
Trimmed Mean ( 30 / 32 )654.8508333333332.41005576484913271.716050260906
Trimmed Mean ( 31 / 32 )655.2423529411762.39271253445071273.849174736571
Trimmed Mean ( 32 / 32 )655.68281252.35823737460735278.039360905801
Median665.27
Midrange646.65
Midmean - Weighted Average at Xnp655.408
Midmean - Weighted Average at X(n+1)p655.408
Midmean - Empirical Distribution Function655.408
Midmean - Empirical Distribution Function - Averaging655.408
Midmean - Empirical Distribution Function - Interpolation655.408
Midmean - Closest Observation655.408
Midmean - True Basic - Statistics Graphics Toolkit655.408
Midmean - MS Excel (old versions)655.408
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 650.283125 & 2.92125518756718 & 222.604012058787 \tabularnewline
Geometric Mean & 649.652850462815 &  &  \tabularnewline
Harmonic Mean & 649.016047317788 &  &  \tabularnewline
Quadratic Mean & 650.906173874161 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 650.283125 & 2.92125518756718 & 222.604012058787 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 650.283125 & 2.92125518756718 & 222.604012058787 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 650.003125 & 2.88094552778182 & 225.621456126756 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 650.003125 & 2.88094552778182 & 225.621456126756 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 650.003125 & 2.88094552778182 & 225.621456126756 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 650.003125 & 2.88094552778182 & 225.621456126756 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 650.003125 & 2.88094552778182 & 225.621456126756 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 650.003125 & 2.88094552778182 & 225.621456126756 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 651.69625 & 2.60260458799399 & 250.401560423863 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 651.69625 & 2.60260458799399 & 250.401560423863 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 651.69625 & 2.60260458799399 & 250.401560423863 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 651.69625 & 2.60260458799399 & 250.401560423863 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 651.69625 & 2.60260458799399 & 250.401560423863 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 651.69625 & 2.60260458799399 & 250.401560423863 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 649.97125 & 2.39183864188532 & 271.7454424466 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 649.97125 & 2.39183864188532 & 271.7454424466 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 649.97125 & 2.39183864188532 & 271.7454424466 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 649.97125 & 2.39183864188532 & 271.7454424466 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 649.97125 & 2.39183864188532 & 271.7454424466 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 649.97125 & 2.39183864188532 & 271.7454424466 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 652.40375 & 2.06347652719615 & 316.167274694656 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 652.40375 & 2.06347652719615 & 316.167274694656 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 652.40375 & 2.06347652719615 & 316.167274694656 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 652.40375 & 2.06347652719615 & 316.167274694656 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 652.40375 & 2.06347652719615 & 316.167274694656 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 652.40375 & 2.06347652719615 & 316.167274694656 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 650.6909375 & 1.88342582879987 & 345.482645268078 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 650.6909375 & 1.88342582879987 & 345.482645268078 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 650.6909375 & 1.88342582879987 & 345.482645268078 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 650.6909375 & 1.88342582879987 & 345.482645268078 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 650.6909375 & 1.88342582879987 & 345.482645268078 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 650.6909375 & 1.88342582879987 & 345.482645268078 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 650.360425531915 & 2.89485593641291 & 224.660722266474 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 650.441086956522 & 2.86439939354252 & 227.077651399756 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 650.525333333333 & 2.829310257701 & 229.92364713721 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 650.715227272727 & 2.80528702954093 & 231.960302250858 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 650.913953488372 & 2.77701115930554 & 234.393711853556 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 651.122142857143 & 2.74382789382675 & 237.304294603201 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 651.340487804878 & 2.70494910317756 & 240.795838649879 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 651.56975 & 2.65941582511168 & 245.004840479445 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 651.810769230769 & 2.60604631863918 & 250.1148059299 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 651.826842105263 & 2.5974943541166 & 250.944469262166 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 651.843783783784 & 2.58602036376993 & 252.064443465371 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 651.861666666667 & 2.57113015802679 & 253.531181465716 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 651.880571428571 & 2.55222758940999 & 255.416317155035 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 651.900588235294 & 2.52858714226186 & 257.812189795508 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 651.921818181818 & 2.49931681955817 & 260.84000758938 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 652.116875 & 2.49400488388918 & 261.473776259444 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 652.324516129032 & 2.48504435805964 & 262.500149751201 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 652.546 & 2.47165190078297 & 264.012096441771 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 652.78275862069 & 2.45284256488276 & 266.133166460233 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 653.036428571429 & 2.42736221041619 & 269.031307222773 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 653.308888888889 & 2.39358983615621 & 272.941035686389 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 653.388461538462 & 2.40386505935251 & 271.807462318395 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 653.4744 & 2.41184424582568 & 270.943864277723 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 653.5675 & 2.41685347468255 & 270.420820644017 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 653.668695652174 & 2.41801520812709 & 270.332747889739 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 653.779090909091 & 2.41417264898122 & 270.808755614469 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 653.9 & 2.40377838467861 & 272.030069064553 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 654.18525 & 2.41263049301656 & 271.150203851589 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 654.500526315789 & 2.41552620537292 & 270.955672043618 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 654.850833333333 & 2.41005576484913 & 271.716050260906 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 655.242352941176 & 2.39271253445071 & 273.849174736571 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 655.6828125 & 2.35823737460735 & 278.039360905801 \tabularnewline
Median & 665.27 &  &  \tabularnewline
Midrange & 646.65 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 655.408 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 655.408 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 655.408 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 655.408 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 655.408 &  &  \tabularnewline
Midmean - Closest Observation & 655.408 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 655.408 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 655.408 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277443&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]650.283125[/C][C]2.92125518756718[/C][C]222.604012058787[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]649.652850462815[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]649.016047317788[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]650.906173874161[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]650.283125[/C][C]2.92125518756718[/C][C]222.604012058787[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]650.283125[/C][C]2.92125518756718[/C][C]222.604012058787[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]650.003125[/C][C]2.88094552778182[/C][C]225.621456126756[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]650.003125[/C][C]2.88094552778182[/C][C]225.621456126756[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]650.003125[/C][C]2.88094552778182[/C][C]225.621456126756[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]650.003125[/C][C]2.88094552778182[/C][C]225.621456126756[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]650.003125[/C][C]2.88094552778182[/C][C]225.621456126756[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]650.003125[/C][C]2.88094552778182[/C][C]225.621456126756[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]651.69625[/C][C]2.60260458799399[/C][C]250.401560423863[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]651.69625[/C][C]2.60260458799399[/C][C]250.401560423863[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]651.69625[/C][C]2.60260458799399[/C][C]250.401560423863[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]651.69625[/C][C]2.60260458799399[/C][C]250.401560423863[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]651.69625[/C][C]2.60260458799399[/C][C]250.401560423863[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]651.69625[/C][C]2.60260458799399[/C][C]250.401560423863[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]649.97125[/C][C]2.39183864188532[/C][C]271.7454424466[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]649.97125[/C][C]2.39183864188532[/C][C]271.7454424466[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]649.97125[/C][C]2.39183864188532[/C][C]271.7454424466[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]649.97125[/C][C]2.39183864188532[/C][C]271.7454424466[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]649.97125[/C][C]2.39183864188532[/C][C]271.7454424466[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]649.97125[/C][C]2.39183864188532[/C][C]271.7454424466[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]652.40375[/C][C]2.06347652719615[/C][C]316.167274694656[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]652.40375[/C][C]2.06347652719615[/C][C]316.167274694656[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]652.40375[/C][C]2.06347652719615[/C][C]316.167274694656[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]652.40375[/C][C]2.06347652719615[/C][C]316.167274694656[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]652.40375[/C][C]2.06347652719615[/C][C]316.167274694656[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]652.40375[/C][C]2.06347652719615[/C][C]316.167274694656[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]650.6909375[/C][C]1.88342582879987[/C][C]345.482645268078[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]650.6909375[/C][C]1.88342582879987[/C][C]345.482645268078[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]650.6909375[/C][C]1.88342582879987[/C][C]345.482645268078[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]650.6909375[/C][C]1.88342582879987[/C][C]345.482645268078[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]650.6909375[/C][C]1.88342582879987[/C][C]345.482645268078[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]650.6909375[/C][C]1.88342582879987[/C][C]345.482645268078[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]650.360425531915[/C][C]2.89485593641291[/C][C]224.660722266474[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]650.441086956522[/C][C]2.86439939354252[/C][C]227.077651399756[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]650.525333333333[/C][C]2.829310257701[/C][C]229.92364713721[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]650.715227272727[/C][C]2.80528702954093[/C][C]231.960302250858[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]650.913953488372[/C][C]2.77701115930554[/C][C]234.393711853556[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]651.122142857143[/C][C]2.74382789382675[/C][C]237.304294603201[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]651.340487804878[/C][C]2.70494910317756[/C][C]240.795838649879[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]651.56975[/C][C]2.65941582511168[/C][C]245.004840479445[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]651.810769230769[/C][C]2.60604631863918[/C][C]250.1148059299[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]651.826842105263[/C][C]2.5974943541166[/C][C]250.944469262166[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]651.843783783784[/C][C]2.58602036376993[/C][C]252.064443465371[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]651.861666666667[/C][C]2.57113015802679[/C][C]253.531181465716[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]651.880571428571[/C][C]2.55222758940999[/C][C]255.416317155035[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]651.900588235294[/C][C]2.52858714226186[/C][C]257.812189795508[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]651.921818181818[/C][C]2.49931681955817[/C][C]260.84000758938[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]652.116875[/C][C]2.49400488388918[/C][C]261.473776259444[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]652.324516129032[/C][C]2.48504435805964[/C][C]262.500149751201[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]652.546[/C][C]2.47165190078297[/C][C]264.012096441771[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]652.78275862069[/C][C]2.45284256488276[/C][C]266.133166460233[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]653.036428571429[/C][C]2.42736221041619[/C][C]269.031307222773[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]653.308888888889[/C][C]2.39358983615621[/C][C]272.941035686389[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]653.388461538462[/C][C]2.40386505935251[/C][C]271.807462318395[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]653.4744[/C][C]2.41184424582568[/C][C]270.943864277723[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]653.5675[/C][C]2.41685347468255[/C][C]270.420820644017[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]653.668695652174[/C][C]2.41801520812709[/C][C]270.332747889739[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]653.779090909091[/C][C]2.41417264898122[/C][C]270.808755614469[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]653.9[/C][C]2.40377838467861[/C][C]272.030069064553[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]654.18525[/C][C]2.41263049301656[/C][C]271.150203851589[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]654.500526315789[/C][C]2.41552620537292[/C][C]270.955672043618[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]654.850833333333[/C][C]2.41005576484913[/C][C]271.716050260906[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]655.242352941176[/C][C]2.39271253445071[/C][C]273.849174736571[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]655.6828125[/C][C]2.35823737460735[/C][C]278.039360905801[/C][/ROW]
[ROW][C]Median[/C][C]665.27[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]646.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]655.408[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]96[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277443&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277443&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 Mean650.2831252.92125518756718222.604012058787
Geometric Mean649.652850462815
Harmonic Mean649.016047317788
Quadratic Mean650.906173874161
Winsorized Mean ( 1 / 32 )650.2831252.92125518756718222.604012058787
Winsorized Mean ( 2 / 32 )650.2831252.92125518756718222.604012058787
Winsorized Mean ( 3 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 4 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 5 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 6 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 7 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 8 / 32 )650.0031252.88094552778182225.621456126756
Winsorized Mean ( 9 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 10 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 11 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 12 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 13 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 14 / 32 )651.696252.60260458799399250.401560423863
Winsorized Mean ( 15 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 16 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 17 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 18 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 19 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 20 / 32 )649.971252.39183864188532271.7454424466
Winsorized Mean ( 21 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 22 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 23 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 24 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 25 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 26 / 32 )652.403752.06347652719615316.167274694656
Winsorized Mean ( 27 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 28 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 29 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 30 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 31 / 32 )650.69093751.88342582879987345.482645268078
Winsorized Mean ( 32 / 32 )650.69093751.88342582879987345.482645268078
Trimmed Mean ( 1 / 32 )650.3604255319152.89485593641291224.660722266474
Trimmed Mean ( 2 / 32 )650.4410869565222.86439939354252227.077651399756
Trimmed Mean ( 3 / 32 )650.5253333333332.829310257701229.92364713721
Trimmed Mean ( 4 / 32 )650.7152272727272.80528702954093231.960302250858
Trimmed Mean ( 5 / 32 )650.9139534883722.77701115930554234.393711853556
Trimmed Mean ( 6 / 32 )651.1221428571432.74382789382675237.304294603201
Trimmed Mean ( 7 / 32 )651.3404878048782.70494910317756240.795838649879
Trimmed Mean ( 8 / 32 )651.569752.65941582511168245.004840479445
Trimmed Mean ( 9 / 32 )651.8107692307692.60604631863918250.1148059299
Trimmed Mean ( 10 / 32 )651.8268421052632.5974943541166250.944469262166
Trimmed Mean ( 11 / 32 )651.8437837837842.58602036376993252.064443465371
Trimmed Mean ( 12 / 32 )651.8616666666672.57113015802679253.531181465716
Trimmed Mean ( 13 / 32 )651.8805714285712.55222758940999255.416317155035
Trimmed Mean ( 14 / 32 )651.9005882352942.52858714226186257.812189795508
Trimmed Mean ( 15 / 32 )651.9218181818182.49931681955817260.84000758938
Trimmed Mean ( 16 / 32 )652.1168752.49400488388918261.473776259444
Trimmed Mean ( 17 / 32 )652.3245161290322.48504435805964262.500149751201
Trimmed Mean ( 18 / 32 )652.5462.47165190078297264.012096441771
Trimmed Mean ( 19 / 32 )652.782758620692.45284256488276266.133166460233
Trimmed Mean ( 20 / 32 )653.0364285714292.42736221041619269.031307222773
Trimmed Mean ( 21 / 32 )653.3088888888892.39358983615621272.941035686389
Trimmed Mean ( 22 / 32 )653.3884615384622.40386505935251271.807462318395
Trimmed Mean ( 23 / 32 )653.47442.41184424582568270.943864277723
Trimmed Mean ( 24 / 32 )653.56752.41685347468255270.420820644017
Trimmed Mean ( 25 / 32 )653.6686956521742.41801520812709270.332747889739
Trimmed Mean ( 26 / 32 )653.7790909090912.41417264898122270.808755614469
Trimmed Mean ( 27 / 32 )653.92.40377838467861272.030069064553
Trimmed Mean ( 28 / 32 )654.185252.41263049301656271.150203851589
Trimmed Mean ( 29 / 32 )654.5005263157892.41552620537292270.955672043618
Trimmed Mean ( 30 / 32 )654.8508333333332.41005576484913271.716050260906
Trimmed Mean ( 31 / 32 )655.2423529411762.39271253445071273.849174736571
Trimmed Mean ( 32 / 32 )655.68281252.35823737460735278.039360905801
Median665.27
Midrange646.65
Midmean - Weighted Average at Xnp655.408
Midmean - Weighted Average at X(n+1)p655.408
Midmean - Empirical Distribution Function655.408
Midmean - Empirical Distribution Function - Averaging655.408
Midmean - Empirical Distribution Function - Interpolation655.408
Midmean - Closest Observation655.408
Midmean - True Basic - Statistics Graphics Toolkit655.408
Midmean - MS Excel (old versions)655.408
Number of observations96



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')