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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 computationWed, 20 Oct 2010 11:25:09 +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/2010/Oct/20/t1287574041u4l1b64ik9oopn8.htm/, Retrieved Sat, 04 May 2024 02:46:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=87167, Retrieved Sat, 04 May 2024 02:46:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W52
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Opgave 5 Oefening...] [2010-10-20 11:25:09] [cf38f7df7be58a8c28b053c2e6c1601e] [Current]
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Dataseries X:
361,58
363,19
363,61
364,14
365,51
365,51
365,5
365,5
364,59
364,63
364,54
363,67
365,22
369,05
370,45
370,46
370,46
370,58
370,58
370,22
370,21
370,29
370,29
370,2
370,2
372,55
374,51
375,58
375,75
375,75
375,75
375,69
375,76
377,5
377,51
377,74
369,82
373,1
374,55
375,01
374,81
375,31
375,31
375,39
375,59
376,26
377,18
377,26
377,26
381,87
387,09
387,14
388,78
389,16
389,16
389,42
389,49
388,97
388,97
389,09
389,09
391,76
390,96
391,76
392,8
393,06
393,06
393,26
393,87
394,47
394,57
394,57
394,57
399,57
406,13
407,03
409,46
409,9
409,9
410,14
410,54
410,69
410,79
410,97




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87167&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87167&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'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean381.7045238095241.55045577853490246.188591183307
Geometric Mean381.447006579910
Harmonic Mean381.193362668583
Quadratic Mean381.965794654069
Winsorized Mean ( 1 / 28 )381.7215476190481.54708774117318246.735551876057
Winsorized Mean ( 2 / 28 )381.7291666666671.5451213842397247.05448423685
Winsorized Mean ( 3 / 28 )381.7259523809521.54361171391099247.294024100004
Winsorized Mean ( 4 / 28 )381.7292857142861.53622684144242248.484973323253
Winsorized Mean ( 5 / 28 )381.7388095238101.52979624340019249.535721616978
Winsorized Mean ( 6 / 28 )381.7423809523811.52931306148172249.616897002449
Winsorized Mean ( 7 / 28 )381.7090476190481.52076464916821250.998106661557
Winsorized Mean ( 8 / 28 )381.533809523811.46343758560978260.710680985300
Winsorized Mean ( 9 / 28 )381.4673809523811.43934278843620265.028861795205
Winsorized Mean ( 10 / 28 )380.6864285714291.28917754141955295.294027657544
Winsorized Mean ( 11 / 28 )380.0329761904761.18231342089862321.431669025317
Winsorized Mean ( 12 / 28 )380.0329761904761.18231342089862321.431669025317
Winsorized Mean ( 13 / 28 )380.5808333333331.10720004748988343.732674322172
Winsorized Mean ( 14 / 28 )380.69251.08888778906874349.615914350166
Winsorized Mean ( 15 / 28 )380.6532142857141.06461041173005357.551654663165
Winsorized Mean ( 16 / 28 )380.5370238095241.04741712729332363.309911489502
Winsorized Mean ( 17 / 28 )380.4985714285711.04127297174583365.416736776157
Winsorized Mean ( 18 / 28 )380.5007142857141.04101794076944365.508315836014
Winsorized Mean ( 19 / 28 )380.4577380952381.03061806218828369.154929506497
Winsorized Mean ( 20 / 28 )380.2101190476190.995436928461119381.952997901534
Winsorized Mean ( 21 / 28 )380.2501190476190.990651780062795383.838324121838
Winsorized Mean ( 22 / 28 )380.0432142857140.961335430893789395.328417191879
Winsorized Mean ( 23 / 28 )379.6407142857140.907448551679246418.360593097189
Winsorized Mean ( 24 / 28 )379.6550.900663895824375421.527943731444
Winsorized Mean ( 25 / 28 )379.5776190476190.890594115054431426.207194311429
Winsorized Mean ( 26 / 28 )380.1873809523810.819114380476344464.144434543181
Winsorized Mean ( 27 / 28 )380.3416666666670.796525512788177477.500921891767
Winsorized Mean ( 28 / 28 )380.8116666666670.746834471528889509.901030528337
Trimmed Mean ( 1 / 28 )381.5930487804881.52750545677470249.814524123674
Trimmed Mean ( 2 / 28 )381.4581251.50447687503788253.548679497248
Trimmed Mean ( 3 / 28 )381.3121794871791.47857879724243257.891010068812
Trimmed Mean ( 4 / 28 )381.1597368421051.44871452969532263.102032201105
Trimmed Mean ( 5 / 28 )380.9981081081081.41601554547108269.063506630754
Trimmed Mean ( 6 / 28 )380.8252777777781.37914342238504276.131743513081
Trimmed Mean ( 7 / 28 )380.6418571428571.33529350675671285.062314177950
Trimmed Mean ( 8 / 28 )380.4535294117651.28497219636134296.079191821502
Trimmed Mean ( 9 / 28 )380.2816666666671.23868650982372307.003962383336
Trimmed Mean ( 10 / 28 )380.108751.18833922934823319.865523759979
Trimmed Mean ( 11 / 28 )380.0304838709681.16138897375358327.220674949857
Trimmed Mean ( 12 / 28 )380.0301666666671.14967591826711330.554168029789
Trimmed Mean ( 13 / 28 )380.0298275862071.13471985107969334.910707012490
Trimmed Mean ( 14 / 28 )379.966251.12880958336073336.607923604576
Trimmed Mean ( 15 / 28 )379.8855555555561.12324299217648338.2042516192
Trimmed Mean ( 16 / 28 )379.8028846153851.11907620328490339.389653269833
Trimmed Mean ( 17 / 28 )379.72581.11530664182821340.467621870836
Trimmed Mean ( 18 / 28 )379.646251.10986104750527342.066469359711
Trimmed Mean ( 19 / 28 )379.5595652173911.10111783151986344.703858526649
Trimmed Mean ( 20 / 28 )379.4693181818181.09007653385166348.112546594327
Trimmed Mean ( 21 / 28 )379.3952380952381.08110410709196350.933120692479
Trimmed Mean ( 22 / 28 )379.309751.06802378535768355.151032402307
Trimmed Mean ( 23 / 28 )379.2360526315791.05509665575409359.432522663562
Trimmed Mean ( 24 / 28 )379.1951.04766433343679361.943217782433
Trimmed Mean ( 25 / 28 )379.1476470588241.03595418817832365.988816286886
Trimmed Mean ( 26 / 28 )379.10251.01917829409838371.968773467035
Trimmed Mean ( 27 / 28 )378.9856666666671.00910597547126375.565773941313
Trimmed Mean ( 28 / 28 )378.8350.995055434365502380.717482580822
Median376.01
Midrange386.275
Midmean - Weighted Average at Xnp379.265333333333
Midmean - Weighted Average at X(n+1)p379.682790697674
Midmean - Empirical Distribution Function379.265333333333
Midmean - Empirical Distribution Function - Averaging379.682790697674
Midmean - Empirical Distribution Function - Interpolation379.682790697674
Midmean - Closest Observation379.265333333333
Midmean - True Basic - Statistics Graphics Toolkit379.682790697674
Midmean - MS Excel (old versions)379.265333333333
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 381.704523809524 & 1.55045577853490 & 246.188591183307 \tabularnewline
Geometric Mean & 381.447006579910 &  &  \tabularnewline
Harmonic Mean & 381.193362668583 &  &  \tabularnewline
Quadratic Mean & 381.965794654069 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 381.721547619048 & 1.54708774117318 & 246.735551876057 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 381.729166666667 & 1.5451213842397 & 247.05448423685 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 381.725952380952 & 1.54361171391099 & 247.294024100004 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 381.729285714286 & 1.53622684144242 & 248.484973323253 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 381.738809523810 & 1.52979624340019 & 249.535721616978 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 381.742380952381 & 1.52931306148172 & 249.616897002449 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 381.709047619048 & 1.52076464916821 & 250.998106661557 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 381.53380952381 & 1.46343758560978 & 260.710680985300 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 381.467380952381 & 1.43934278843620 & 265.028861795205 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 380.686428571429 & 1.28917754141955 & 295.294027657544 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 380.032976190476 & 1.18231342089862 & 321.431669025317 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 380.032976190476 & 1.18231342089862 & 321.431669025317 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 380.580833333333 & 1.10720004748988 & 343.732674322172 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 380.6925 & 1.08888778906874 & 349.615914350166 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 380.653214285714 & 1.06461041173005 & 357.551654663165 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 380.537023809524 & 1.04741712729332 & 363.309911489502 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 380.498571428571 & 1.04127297174583 & 365.416736776157 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 380.500714285714 & 1.04101794076944 & 365.508315836014 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 380.457738095238 & 1.03061806218828 & 369.154929506497 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 380.210119047619 & 0.995436928461119 & 381.952997901534 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 380.250119047619 & 0.990651780062795 & 383.838324121838 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 380.043214285714 & 0.961335430893789 & 395.328417191879 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 379.640714285714 & 0.907448551679246 & 418.360593097189 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 379.655 & 0.900663895824375 & 421.527943731444 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 379.577619047619 & 0.890594115054431 & 426.207194311429 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 380.187380952381 & 0.819114380476344 & 464.144434543181 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 380.341666666667 & 0.796525512788177 & 477.500921891767 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 380.811666666667 & 0.746834471528889 & 509.901030528337 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 381.593048780488 & 1.52750545677470 & 249.814524123674 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 381.458125 & 1.50447687503788 & 253.548679497248 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 381.312179487179 & 1.47857879724243 & 257.891010068812 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 381.159736842105 & 1.44871452969532 & 263.102032201105 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 380.998108108108 & 1.41601554547108 & 269.063506630754 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 380.825277777778 & 1.37914342238504 & 276.131743513081 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 380.641857142857 & 1.33529350675671 & 285.062314177950 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 380.453529411765 & 1.28497219636134 & 296.079191821502 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 380.281666666667 & 1.23868650982372 & 307.003962383336 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 380.10875 & 1.18833922934823 & 319.865523759979 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 380.030483870968 & 1.16138897375358 & 327.220674949857 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 380.030166666667 & 1.14967591826711 & 330.554168029789 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 380.029827586207 & 1.13471985107969 & 334.910707012490 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 379.96625 & 1.12880958336073 & 336.607923604576 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 379.885555555556 & 1.12324299217648 & 338.2042516192 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 379.802884615385 & 1.11907620328490 & 339.389653269833 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 379.7258 & 1.11530664182821 & 340.467621870836 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 379.64625 & 1.10986104750527 & 342.066469359711 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 379.559565217391 & 1.10111783151986 & 344.703858526649 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 379.469318181818 & 1.09007653385166 & 348.112546594327 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 379.395238095238 & 1.08110410709196 & 350.933120692479 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 379.30975 & 1.06802378535768 & 355.151032402307 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 379.236052631579 & 1.05509665575409 & 359.432522663562 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 379.195 & 1.04766433343679 & 361.943217782433 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 379.147647058824 & 1.03595418817832 & 365.988816286886 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 379.1025 & 1.01917829409838 & 371.968773467035 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 378.985666666667 & 1.00910597547126 & 375.565773941313 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 378.835 & 0.995055434365502 & 380.717482580822 \tabularnewline
Median & 376.01 &  &  \tabularnewline
Midrange & 386.275 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 379.265333333333 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 379.682790697674 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 379.265333333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 379.682790697674 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 379.682790697674 &  &  \tabularnewline
Midmean - Closest Observation & 379.265333333333 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 379.682790697674 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 379.265333333333 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=87167&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]381.704523809524[/C][C]1.55045577853490[/C][C]246.188591183307[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]381.447006579910[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]381.193362668583[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]381.965794654069[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]381.721547619048[/C][C]1.54708774117318[/C][C]246.735551876057[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]381.729166666667[/C][C]1.5451213842397[/C][C]247.05448423685[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]381.725952380952[/C][C]1.54361171391099[/C][C]247.294024100004[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]381.729285714286[/C][C]1.53622684144242[/C][C]248.484973323253[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]381.738809523810[/C][C]1.52979624340019[/C][C]249.535721616978[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]381.742380952381[/C][C]1.52931306148172[/C][C]249.616897002449[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]381.709047619048[/C][C]1.52076464916821[/C][C]250.998106661557[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]381.53380952381[/C][C]1.46343758560978[/C][C]260.710680985300[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]381.467380952381[/C][C]1.43934278843620[/C][C]265.028861795205[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]380.686428571429[/C][C]1.28917754141955[/C][C]295.294027657544[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]380.032976190476[/C][C]1.18231342089862[/C][C]321.431669025317[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]380.032976190476[/C][C]1.18231342089862[/C][C]321.431669025317[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]380.580833333333[/C][C]1.10720004748988[/C][C]343.732674322172[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]380.6925[/C][C]1.08888778906874[/C][C]349.615914350166[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]380.653214285714[/C][C]1.06461041173005[/C][C]357.551654663165[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]380.537023809524[/C][C]1.04741712729332[/C][C]363.309911489502[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]380.498571428571[/C][C]1.04127297174583[/C][C]365.416736776157[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]380.500714285714[/C][C]1.04101794076944[/C][C]365.508315836014[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]380.457738095238[/C][C]1.03061806218828[/C][C]369.154929506497[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]380.210119047619[/C][C]0.995436928461119[/C][C]381.952997901534[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]380.250119047619[/C][C]0.990651780062795[/C][C]383.838324121838[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]380.043214285714[/C][C]0.961335430893789[/C][C]395.328417191879[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]379.640714285714[/C][C]0.907448551679246[/C][C]418.360593097189[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]379.655[/C][C]0.900663895824375[/C][C]421.527943731444[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]379.577619047619[/C][C]0.890594115054431[/C][C]426.207194311429[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]380.187380952381[/C][C]0.819114380476344[/C][C]464.144434543181[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]380.341666666667[/C][C]0.796525512788177[/C][C]477.500921891767[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]380.811666666667[/C][C]0.746834471528889[/C][C]509.901030528337[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]381.593048780488[/C][C]1.52750545677470[/C][C]249.814524123674[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]381.458125[/C][C]1.50447687503788[/C][C]253.548679497248[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]381.312179487179[/C][C]1.47857879724243[/C][C]257.891010068812[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]381.159736842105[/C][C]1.44871452969532[/C][C]263.102032201105[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]380.998108108108[/C][C]1.41601554547108[/C][C]269.063506630754[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]380.825277777778[/C][C]1.37914342238504[/C][C]276.131743513081[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]380.641857142857[/C][C]1.33529350675671[/C][C]285.062314177950[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]380.453529411765[/C][C]1.28497219636134[/C][C]296.079191821502[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]380.281666666667[/C][C]1.23868650982372[/C][C]307.003962383336[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]380.10875[/C][C]1.18833922934823[/C][C]319.865523759979[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]380.030483870968[/C][C]1.16138897375358[/C][C]327.220674949857[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]380.030166666667[/C][C]1.14967591826711[/C][C]330.554168029789[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]380.029827586207[/C][C]1.13471985107969[/C][C]334.910707012490[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]379.96625[/C][C]1.12880958336073[/C][C]336.607923604576[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]379.885555555556[/C][C]1.12324299217648[/C][C]338.2042516192[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]379.802884615385[/C][C]1.11907620328490[/C][C]339.389653269833[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]379.7258[/C][C]1.11530664182821[/C][C]340.467621870836[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]379.64625[/C][C]1.10986104750527[/C][C]342.066469359711[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]379.559565217391[/C][C]1.10111783151986[/C][C]344.703858526649[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]379.469318181818[/C][C]1.09007653385166[/C][C]348.112546594327[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]379.395238095238[/C][C]1.08110410709196[/C][C]350.933120692479[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]379.30975[/C][C]1.06802378535768[/C][C]355.151032402307[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]379.236052631579[/C][C]1.05509665575409[/C][C]359.432522663562[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]379.195[/C][C]1.04766433343679[/C][C]361.943217782433[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]379.147647058824[/C][C]1.03595418817832[/C][C]365.988816286886[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]379.1025[/C][C]1.01917829409838[/C][C]371.968773467035[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]378.985666666667[/C][C]1.00910597547126[/C][C]375.565773941313[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]378.835[/C][C]0.995055434365502[/C][C]380.717482580822[/C][/ROW]
[ROW][C]Median[/C][C]376.01[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]386.275[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]379.265333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]379.682790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]379.265333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]379.682790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]379.682790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]379.265333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]379.682790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]379.265333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=87167&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=87167&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 Mean381.7045238095241.55045577853490246.188591183307
Geometric Mean381.447006579910
Harmonic Mean381.193362668583
Quadratic Mean381.965794654069
Winsorized Mean ( 1 / 28 )381.7215476190481.54708774117318246.735551876057
Winsorized Mean ( 2 / 28 )381.7291666666671.5451213842397247.05448423685
Winsorized Mean ( 3 / 28 )381.7259523809521.54361171391099247.294024100004
Winsorized Mean ( 4 / 28 )381.7292857142861.53622684144242248.484973323253
Winsorized Mean ( 5 / 28 )381.7388095238101.52979624340019249.535721616978
Winsorized Mean ( 6 / 28 )381.7423809523811.52931306148172249.616897002449
Winsorized Mean ( 7 / 28 )381.7090476190481.52076464916821250.998106661557
Winsorized Mean ( 8 / 28 )381.533809523811.46343758560978260.710680985300
Winsorized Mean ( 9 / 28 )381.4673809523811.43934278843620265.028861795205
Winsorized Mean ( 10 / 28 )380.6864285714291.28917754141955295.294027657544
Winsorized Mean ( 11 / 28 )380.0329761904761.18231342089862321.431669025317
Winsorized Mean ( 12 / 28 )380.0329761904761.18231342089862321.431669025317
Winsorized Mean ( 13 / 28 )380.5808333333331.10720004748988343.732674322172
Winsorized Mean ( 14 / 28 )380.69251.08888778906874349.615914350166
Winsorized Mean ( 15 / 28 )380.6532142857141.06461041173005357.551654663165
Winsorized Mean ( 16 / 28 )380.5370238095241.04741712729332363.309911489502
Winsorized Mean ( 17 / 28 )380.4985714285711.04127297174583365.416736776157
Winsorized Mean ( 18 / 28 )380.5007142857141.04101794076944365.508315836014
Winsorized Mean ( 19 / 28 )380.4577380952381.03061806218828369.154929506497
Winsorized Mean ( 20 / 28 )380.2101190476190.995436928461119381.952997901534
Winsorized Mean ( 21 / 28 )380.2501190476190.990651780062795383.838324121838
Winsorized Mean ( 22 / 28 )380.0432142857140.961335430893789395.328417191879
Winsorized Mean ( 23 / 28 )379.6407142857140.907448551679246418.360593097189
Winsorized Mean ( 24 / 28 )379.6550.900663895824375421.527943731444
Winsorized Mean ( 25 / 28 )379.5776190476190.890594115054431426.207194311429
Winsorized Mean ( 26 / 28 )380.1873809523810.819114380476344464.144434543181
Winsorized Mean ( 27 / 28 )380.3416666666670.796525512788177477.500921891767
Winsorized Mean ( 28 / 28 )380.8116666666670.746834471528889509.901030528337
Trimmed Mean ( 1 / 28 )381.5930487804881.52750545677470249.814524123674
Trimmed Mean ( 2 / 28 )381.4581251.50447687503788253.548679497248
Trimmed Mean ( 3 / 28 )381.3121794871791.47857879724243257.891010068812
Trimmed Mean ( 4 / 28 )381.1597368421051.44871452969532263.102032201105
Trimmed Mean ( 5 / 28 )380.9981081081081.41601554547108269.063506630754
Trimmed Mean ( 6 / 28 )380.8252777777781.37914342238504276.131743513081
Trimmed Mean ( 7 / 28 )380.6418571428571.33529350675671285.062314177950
Trimmed Mean ( 8 / 28 )380.4535294117651.28497219636134296.079191821502
Trimmed Mean ( 9 / 28 )380.2816666666671.23868650982372307.003962383336
Trimmed Mean ( 10 / 28 )380.108751.18833922934823319.865523759979
Trimmed Mean ( 11 / 28 )380.0304838709681.16138897375358327.220674949857
Trimmed Mean ( 12 / 28 )380.0301666666671.14967591826711330.554168029789
Trimmed Mean ( 13 / 28 )380.0298275862071.13471985107969334.910707012490
Trimmed Mean ( 14 / 28 )379.966251.12880958336073336.607923604576
Trimmed Mean ( 15 / 28 )379.8855555555561.12324299217648338.2042516192
Trimmed Mean ( 16 / 28 )379.8028846153851.11907620328490339.389653269833
Trimmed Mean ( 17 / 28 )379.72581.11530664182821340.467621870836
Trimmed Mean ( 18 / 28 )379.646251.10986104750527342.066469359711
Trimmed Mean ( 19 / 28 )379.5595652173911.10111783151986344.703858526649
Trimmed Mean ( 20 / 28 )379.4693181818181.09007653385166348.112546594327
Trimmed Mean ( 21 / 28 )379.3952380952381.08110410709196350.933120692479
Trimmed Mean ( 22 / 28 )379.309751.06802378535768355.151032402307
Trimmed Mean ( 23 / 28 )379.2360526315791.05509665575409359.432522663562
Trimmed Mean ( 24 / 28 )379.1951.04766433343679361.943217782433
Trimmed Mean ( 25 / 28 )379.1476470588241.03595418817832365.988816286886
Trimmed Mean ( 26 / 28 )379.10251.01917829409838371.968773467035
Trimmed Mean ( 27 / 28 )378.9856666666671.00910597547126375.565773941313
Trimmed Mean ( 28 / 28 )378.8350.995055434365502380.717482580822
Median376.01
Midrange386.275
Midmean - Weighted Average at Xnp379.265333333333
Midmean - Weighted Average at X(n+1)p379.682790697674
Midmean - Empirical Distribution Function379.265333333333
Midmean - Empirical Distribution Function - Averaging379.682790697674
Midmean - Empirical Distribution Function - Interpolation379.682790697674
Midmean - Closest Observation379.265333333333
Midmean - True Basic - Statistics Graphics Toolkit379.682790697674
Midmean - MS Excel (old versions)379.265333333333
Number of observations84



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')