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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 computationSun, 12 Oct 2014 09:55:01 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/12/t1413104224q10zaahdakmew0r.htm/, Retrieved Wed, 15 May 2024 02:51:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=240521, Retrieved Wed, 15 May 2024 02:51:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2014-10-12 08:55:01] [9c8c71143ae36c30e98dcd90d9bfe9d4] [Current]
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Dataseries X:
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523
564478
557560
575093
580112
574761
563250
551531
537034
544686
600991
604378
586111
563668
548604
551174
555654
547970
540324
530577
520579
518654
572273
581302
563280
547612
538712
540735
561649
558685
545732
536352
527676
530455
581744
598714
583775
571477
563278
564872
577537
572399
565430
560619
551227
553397
610893
621668
613148
598778
590623
595902




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240521&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=240521&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240521&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' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean550026.5952380953499.28130462748157.182731925763
Geometric Mean549096.912998204
Harmonic Mean548161.039654055
Quadratic Mean550949.714538515
Winsorized Mean ( 1 / 28 )550023.0595238093449.59345910353159.445762535377
Winsorized Mean ( 2 / 28 )550270.8690476193367.26027060575163.417979254876
Winsorized Mean ( 3 / 28 )550123.1547619053300.9226226159166.657391782769
Winsorized Mean ( 4 / 28 )550249.4880952383211.54749940484171.334687778154
Winsorized Mean ( 5 / 28 )550308.4761904763150.67264633248174.663806102185
Winsorized Mean ( 6 / 28 )550611.6190476193094.68502901846177.921699263287
Winsorized Mean ( 7 / 28 )550550.5357142863042.19266589442180.97162020224
Winsorized Mean ( 8 / 28 )550702.252993.76843479209183.949514464783
Winsorized Mean ( 9 / 28 )550264.3571428572873.39221154879191.503392725582
Winsorized Mean ( 10 / 28 )550165.1904761912731.87391770912201.387475062372
Winsorized Mean ( 11 / 28 )550351.6666666672683.75913779102205.067458892625
Winsorized Mean ( 12 / 28 )550129.5238095242613.97868245811210.456775145617
Winsorized Mean ( 13 / 28 )549973.5238095242541.7940680132216.372180079644
Winsorized Mean ( 14 / 28 )550018.0238095242512.86717779406218.880658981889
Winsorized Mean ( 15 / 28 )550222.6666666672441.02834757606225.406094612968
Winsorized Mean ( 16 / 28 )550719.2380952382347.15928600715234.632238799647
Winsorized Mean ( 17 / 28 )550668.0357142862205.04483658238249.730992575993
Winsorized Mean ( 18 / 28 )550390.9642857142096.18096549811262.568439149492
Winsorized Mean ( 19 / 28 )550452.9404761912067.2453142147266.273642847896
Winsorized Mean ( 20 / 28 )550020.5595238091971.63729699701278.966400342265
Winsorized Mean ( 21 / 28 )550028.3095238091962.10912424012280.325035304457
Winsorized Mean ( 22 / 28 )550363.5476190481862.45288715107295.504681710859
Winsorized Mean ( 23 / 28 )548741.2261904761642.95760680198333.995974040136
Winsorized Mean ( 24 / 28 )548894.9404761911582.10593387015346.939436055007
Winsorized Mean ( 25 / 28 )549098.5119047621534.5357748578357.827116774547
Winsorized Mean ( 26 / 28 )549358.2023809521492.47499921686368.085363352294
Winsorized Mean ( 27 / 28 )549941.2738095241355.458615606405.72339684724
Winsorized Mean ( 28 / 28 )549847.9404761911335.33803700725411.766852465693
Trimmed Mean ( 1 / 28 )550136.6951219513331.77153830594165.118372852681
Trimmed Mean ( 2 / 28 )550256.01253194.50731222794172.250666133625
Trimmed Mean ( 3 / 28 )550248.0128205133086.50968654229178.275161493802
Trimmed Mean ( 4 / 28 )550294.0131578952990.20147883596184.03241957198
Trimmed Mean ( 5 / 28 )550306.6486486492909.51333054121189.140445885596
Trimmed Mean ( 6 / 28 )550306.2222222222833.1748233224194.236591999957
Trimmed Mean ( 7 / 28 )550245.1428571432758.09297675791199.502028210792
Trimmed Mean ( 8 / 28 )550191.252681.99829034263205.142282148775
Trimmed Mean ( 9 / 28 )550109.9545454552602.40981692219211.384829156561
Trimmed Mean ( 10 / 28 )550087.43752533.81036860792217.098897500455
Trimmed Mean ( 11 / 28 )550076.9032258062480.5692985273221.754297915557
Trimmed Mean ( 12 / 28 )550041.9333333332425.22748107325226.800140451121
Trimmed Mean ( 13 / 28 )550031.3620689662371.08400074638231.974641934164
Trimmed Mean ( 14 / 28 )550038.0357142862318.14087539102237.275500187842
Trimmed Mean ( 15 / 28 )550040.2592592592257.74852573097243.623349983664
Trimmed Mean ( 16 / 28 )550020.6153846152196.22402802226250.439212196362
Trimmed Mean ( 17 / 28 )549947.262136.91450476177257.355761671575
Trimmed Mean ( 18 / 28 )549873.06252089.41030747536263.171412782209
Trimmed Mean ( 19 / 28 )549820.521739132049.23947781344268.304669947992
Trimmed Mean ( 20 / 28 )549756.9772727272001.60304136181274.65834429323
Trimmed Mean ( 21 / 28 )549730.6190476191958.28907107487280.719852430102
Trimmed Mean ( 22 / 28 )549700.851901.34989784586289.110831532263
Trimmed Mean ( 23 / 28 )549634.2631578951846.69038111548297.632060457202
Trimmed Mean ( 24 / 28 )549724.8611111111821.79334119441301.749297618301
Trimmed Mean ( 25 / 28 )549810.2941176471797.77525592576305.828157499323
Trimmed Mean ( 26 / 28 )549885.031251771.40244095784310.423548334202
Trimmed Mean ( 27 / 28 )549941.7666666671740.05691787164316.04814820617
Trimmed Mean ( 28 / 28 )549941.8214285711727.96913709883318.259053140206
Median550014
Midrange545512.5
Midmean - Weighted Average at Xnp549230.418604651
Midmean - Weighted Average at X(n+1)p549730.619047619
Midmean - Empirical Distribution Function549230.418604651
Midmean - Empirical Distribution Function - Averaging549730.619047619
Midmean - Empirical Distribution Function - Interpolation549730.619047619
Midmean - Closest Observation549230.418604651
Midmean - True Basic - Statistics Graphics Toolkit549730.619047619
Midmean - MS Excel (old versions)549756.977272727
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 550026.595238095 & 3499.28130462748 & 157.182731925763 \tabularnewline
Geometric Mean & 549096.912998204 &  &  \tabularnewline
Harmonic Mean & 548161.039654055 &  &  \tabularnewline
Quadratic Mean & 550949.714538515 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 550023.059523809 & 3449.59345910353 & 159.445762535377 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 550270.869047619 & 3367.26027060575 & 163.417979254876 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 550123.154761905 & 3300.9226226159 & 166.657391782769 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 550249.488095238 & 3211.54749940484 & 171.334687778154 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 550308.476190476 & 3150.67264633248 & 174.663806102185 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 550611.619047619 & 3094.68502901846 & 177.921699263287 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 550550.535714286 & 3042.19266589442 & 180.97162020224 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 550702.25 & 2993.76843479209 & 183.949514464783 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 550264.357142857 & 2873.39221154879 & 191.503392725582 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 550165.190476191 & 2731.87391770912 & 201.387475062372 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 550351.666666667 & 2683.75913779102 & 205.067458892625 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 550129.523809524 & 2613.97868245811 & 210.456775145617 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 549973.523809524 & 2541.7940680132 & 216.372180079644 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 550018.023809524 & 2512.86717779406 & 218.880658981889 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 550222.666666667 & 2441.02834757606 & 225.406094612968 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 550719.238095238 & 2347.15928600715 & 234.632238799647 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 550668.035714286 & 2205.04483658238 & 249.730992575993 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 550390.964285714 & 2096.18096549811 & 262.568439149492 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 550452.940476191 & 2067.2453142147 & 266.273642847896 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 550020.559523809 & 1971.63729699701 & 278.966400342265 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 550028.309523809 & 1962.10912424012 & 280.325035304457 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 550363.547619048 & 1862.45288715107 & 295.504681710859 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 548741.226190476 & 1642.95760680198 & 333.995974040136 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 548894.940476191 & 1582.10593387015 & 346.939436055007 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 549098.511904762 & 1534.5357748578 & 357.827116774547 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 549358.202380952 & 1492.47499921686 & 368.085363352294 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 549941.273809524 & 1355.458615606 & 405.72339684724 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 549847.940476191 & 1335.33803700725 & 411.766852465693 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 550136.695121951 & 3331.77153830594 & 165.118372852681 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 550256.0125 & 3194.50731222794 & 172.250666133625 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 550248.012820513 & 3086.50968654229 & 178.275161493802 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 550294.013157895 & 2990.20147883596 & 184.03241957198 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 550306.648648649 & 2909.51333054121 & 189.140445885596 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 550306.222222222 & 2833.1748233224 & 194.236591999957 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 550245.142857143 & 2758.09297675791 & 199.502028210792 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 550191.25 & 2681.99829034263 & 205.142282148775 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 550109.954545455 & 2602.40981692219 & 211.384829156561 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 550087.4375 & 2533.81036860792 & 217.098897500455 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 550076.903225806 & 2480.5692985273 & 221.754297915557 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 550041.933333333 & 2425.22748107325 & 226.800140451121 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 550031.362068966 & 2371.08400074638 & 231.974641934164 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 550038.035714286 & 2318.14087539102 & 237.275500187842 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 550040.259259259 & 2257.74852573097 & 243.623349983664 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 550020.615384615 & 2196.22402802226 & 250.439212196362 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 549947.26 & 2136.91450476177 & 257.355761671575 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 549873.0625 & 2089.41030747536 & 263.171412782209 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 549820.52173913 & 2049.23947781344 & 268.304669947992 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 549756.977272727 & 2001.60304136181 & 274.65834429323 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 549730.619047619 & 1958.28907107487 & 280.719852430102 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 549700.85 & 1901.34989784586 & 289.110831532263 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 549634.263157895 & 1846.69038111548 & 297.632060457202 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 549724.861111111 & 1821.79334119441 & 301.749297618301 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 549810.294117647 & 1797.77525592576 & 305.828157499323 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 549885.03125 & 1771.40244095784 & 310.423548334202 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 549941.766666667 & 1740.05691787164 & 316.04814820617 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 549941.821428571 & 1727.96913709883 & 318.259053140206 \tabularnewline
Median & 550014 &  &  \tabularnewline
Midrange & 545512.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 549230.418604651 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 549730.619047619 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 549230.418604651 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 549730.619047619 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 549730.619047619 &  &  \tabularnewline
Midmean - Closest Observation & 549230.418604651 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 549730.619047619 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 549756.977272727 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=240521&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]550026.595238095[/C][C]3499.28130462748[/C][C]157.182731925763[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]549096.912998204[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]548161.039654055[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]550949.714538515[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]550023.059523809[/C][C]3449.59345910353[/C][C]159.445762535377[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]550270.869047619[/C][C]3367.26027060575[/C][C]163.417979254876[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]550123.154761905[/C][C]3300.9226226159[/C][C]166.657391782769[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]550249.488095238[/C][C]3211.54749940484[/C][C]171.334687778154[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]550308.476190476[/C][C]3150.67264633248[/C][C]174.663806102185[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]550611.619047619[/C][C]3094.68502901846[/C][C]177.921699263287[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]550550.535714286[/C][C]3042.19266589442[/C][C]180.97162020224[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]550702.25[/C][C]2993.76843479209[/C][C]183.949514464783[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]550264.357142857[/C][C]2873.39221154879[/C][C]191.503392725582[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]550165.190476191[/C][C]2731.87391770912[/C][C]201.387475062372[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]550351.666666667[/C][C]2683.75913779102[/C][C]205.067458892625[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]550129.523809524[/C][C]2613.97868245811[/C][C]210.456775145617[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]549973.523809524[/C][C]2541.7940680132[/C][C]216.372180079644[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]550018.023809524[/C][C]2512.86717779406[/C][C]218.880658981889[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]550222.666666667[/C][C]2441.02834757606[/C][C]225.406094612968[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]550719.238095238[/C][C]2347.15928600715[/C][C]234.632238799647[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]550668.035714286[/C][C]2205.04483658238[/C][C]249.730992575993[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]550390.964285714[/C][C]2096.18096549811[/C][C]262.568439149492[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]550452.940476191[/C][C]2067.2453142147[/C][C]266.273642847896[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]550020.559523809[/C][C]1971.63729699701[/C][C]278.966400342265[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]550028.309523809[/C][C]1962.10912424012[/C][C]280.325035304457[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]550363.547619048[/C][C]1862.45288715107[/C][C]295.504681710859[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]548741.226190476[/C][C]1642.95760680198[/C][C]333.995974040136[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]548894.940476191[/C][C]1582.10593387015[/C][C]346.939436055007[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]549098.511904762[/C][C]1534.5357748578[/C][C]357.827116774547[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]549358.202380952[/C][C]1492.47499921686[/C][C]368.085363352294[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]549941.273809524[/C][C]1355.458615606[/C][C]405.72339684724[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]549847.940476191[/C][C]1335.33803700725[/C][C]411.766852465693[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]550136.695121951[/C][C]3331.77153830594[/C][C]165.118372852681[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]550256.0125[/C][C]3194.50731222794[/C][C]172.250666133625[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]550248.012820513[/C][C]3086.50968654229[/C][C]178.275161493802[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]550294.013157895[/C][C]2990.20147883596[/C][C]184.03241957198[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]550306.648648649[/C][C]2909.51333054121[/C][C]189.140445885596[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]550306.222222222[/C][C]2833.1748233224[/C][C]194.236591999957[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]550245.142857143[/C][C]2758.09297675791[/C][C]199.502028210792[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]550191.25[/C][C]2681.99829034263[/C][C]205.142282148775[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]550109.954545455[/C][C]2602.40981692219[/C][C]211.384829156561[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]550087.4375[/C][C]2533.81036860792[/C][C]217.098897500455[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]550076.903225806[/C][C]2480.5692985273[/C][C]221.754297915557[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]550041.933333333[/C][C]2425.22748107325[/C][C]226.800140451121[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]550031.362068966[/C][C]2371.08400074638[/C][C]231.974641934164[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]550038.035714286[/C][C]2318.14087539102[/C][C]237.275500187842[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]550040.259259259[/C][C]2257.74852573097[/C][C]243.623349983664[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]550020.615384615[/C][C]2196.22402802226[/C][C]250.439212196362[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]549947.26[/C][C]2136.91450476177[/C][C]257.355761671575[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]549873.0625[/C][C]2089.41030747536[/C][C]263.171412782209[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]549820.52173913[/C][C]2049.23947781344[/C][C]268.304669947992[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]549756.977272727[/C][C]2001.60304136181[/C][C]274.65834429323[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]549730.619047619[/C][C]1958.28907107487[/C][C]280.719852430102[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]549700.85[/C][C]1901.34989784586[/C][C]289.110831532263[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]549634.263157895[/C][C]1846.69038111548[/C][C]297.632060457202[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]549724.861111111[/C][C]1821.79334119441[/C][C]301.749297618301[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]549810.294117647[/C][C]1797.77525592576[/C][C]305.828157499323[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]549885.03125[/C][C]1771.40244095784[/C][C]310.423548334202[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]549941.766666667[/C][C]1740.05691787164[/C][C]316.04814820617[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]549941.821428571[/C][C]1727.96913709883[/C][C]318.259053140206[/C][/ROW]
[ROW][C]Median[/C][C]550014[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]545512.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]549230.418604651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]549730.619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]549230.418604651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]549730.619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]549730.619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]549230.418604651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]549730.619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]549756.977272727[/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=240521&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=240521&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 Mean550026.5952380953499.28130462748157.182731925763
Geometric Mean549096.912998204
Harmonic Mean548161.039654055
Quadratic Mean550949.714538515
Winsorized Mean ( 1 / 28 )550023.0595238093449.59345910353159.445762535377
Winsorized Mean ( 2 / 28 )550270.8690476193367.26027060575163.417979254876
Winsorized Mean ( 3 / 28 )550123.1547619053300.9226226159166.657391782769
Winsorized Mean ( 4 / 28 )550249.4880952383211.54749940484171.334687778154
Winsorized Mean ( 5 / 28 )550308.4761904763150.67264633248174.663806102185
Winsorized Mean ( 6 / 28 )550611.6190476193094.68502901846177.921699263287
Winsorized Mean ( 7 / 28 )550550.5357142863042.19266589442180.97162020224
Winsorized Mean ( 8 / 28 )550702.252993.76843479209183.949514464783
Winsorized Mean ( 9 / 28 )550264.3571428572873.39221154879191.503392725582
Winsorized Mean ( 10 / 28 )550165.1904761912731.87391770912201.387475062372
Winsorized Mean ( 11 / 28 )550351.6666666672683.75913779102205.067458892625
Winsorized Mean ( 12 / 28 )550129.5238095242613.97868245811210.456775145617
Winsorized Mean ( 13 / 28 )549973.5238095242541.7940680132216.372180079644
Winsorized Mean ( 14 / 28 )550018.0238095242512.86717779406218.880658981889
Winsorized Mean ( 15 / 28 )550222.6666666672441.02834757606225.406094612968
Winsorized Mean ( 16 / 28 )550719.2380952382347.15928600715234.632238799647
Winsorized Mean ( 17 / 28 )550668.0357142862205.04483658238249.730992575993
Winsorized Mean ( 18 / 28 )550390.9642857142096.18096549811262.568439149492
Winsorized Mean ( 19 / 28 )550452.9404761912067.2453142147266.273642847896
Winsorized Mean ( 20 / 28 )550020.5595238091971.63729699701278.966400342265
Winsorized Mean ( 21 / 28 )550028.3095238091962.10912424012280.325035304457
Winsorized Mean ( 22 / 28 )550363.5476190481862.45288715107295.504681710859
Winsorized Mean ( 23 / 28 )548741.2261904761642.95760680198333.995974040136
Winsorized Mean ( 24 / 28 )548894.9404761911582.10593387015346.939436055007
Winsorized Mean ( 25 / 28 )549098.5119047621534.5357748578357.827116774547
Winsorized Mean ( 26 / 28 )549358.2023809521492.47499921686368.085363352294
Winsorized Mean ( 27 / 28 )549941.2738095241355.458615606405.72339684724
Winsorized Mean ( 28 / 28 )549847.9404761911335.33803700725411.766852465693
Trimmed Mean ( 1 / 28 )550136.6951219513331.77153830594165.118372852681
Trimmed Mean ( 2 / 28 )550256.01253194.50731222794172.250666133625
Trimmed Mean ( 3 / 28 )550248.0128205133086.50968654229178.275161493802
Trimmed Mean ( 4 / 28 )550294.0131578952990.20147883596184.03241957198
Trimmed Mean ( 5 / 28 )550306.6486486492909.51333054121189.140445885596
Trimmed Mean ( 6 / 28 )550306.2222222222833.1748233224194.236591999957
Trimmed Mean ( 7 / 28 )550245.1428571432758.09297675791199.502028210792
Trimmed Mean ( 8 / 28 )550191.252681.99829034263205.142282148775
Trimmed Mean ( 9 / 28 )550109.9545454552602.40981692219211.384829156561
Trimmed Mean ( 10 / 28 )550087.43752533.81036860792217.098897500455
Trimmed Mean ( 11 / 28 )550076.9032258062480.5692985273221.754297915557
Trimmed Mean ( 12 / 28 )550041.9333333332425.22748107325226.800140451121
Trimmed Mean ( 13 / 28 )550031.3620689662371.08400074638231.974641934164
Trimmed Mean ( 14 / 28 )550038.0357142862318.14087539102237.275500187842
Trimmed Mean ( 15 / 28 )550040.2592592592257.74852573097243.623349983664
Trimmed Mean ( 16 / 28 )550020.6153846152196.22402802226250.439212196362
Trimmed Mean ( 17 / 28 )549947.262136.91450476177257.355761671575
Trimmed Mean ( 18 / 28 )549873.06252089.41030747536263.171412782209
Trimmed Mean ( 19 / 28 )549820.521739132049.23947781344268.304669947992
Trimmed Mean ( 20 / 28 )549756.9772727272001.60304136181274.65834429323
Trimmed Mean ( 21 / 28 )549730.6190476191958.28907107487280.719852430102
Trimmed Mean ( 22 / 28 )549700.851901.34989784586289.110831532263
Trimmed Mean ( 23 / 28 )549634.2631578951846.69038111548297.632060457202
Trimmed Mean ( 24 / 28 )549724.8611111111821.79334119441301.749297618301
Trimmed Mean ( 25 / 28 )549810.2941176471797.77525592576305.828157499323
Trimmed Mean ( 26 / 28 )549885.031251771.40244095784310.423548334202
Trimmed Mean ( 27 / 28 )549941.7666666671740.05691787164316.04814820617
Trimmed Mean ( 28 / 28 )549941.8214285711727.96913709883318.259053140206
Median550014
Midrange545512.5
Midmean - Weighted Average at Xnp549230.418604651
Midmean - Weighted Average at X(n+1)p549730.619047619
Midmean - Empirical Distribution Function549230.418604651
Midmean - Empirical Distribution Function - Averaging549730.619047619
Midmean - Empirical Distribution Function - Interpolation549730.619047619
Midmean - Closest Observation549230.418604651
Midmean - True Basic - Statistics Graphics Toolkit549730.619047619
Midmean - MS Excel (old versions)549756.977272727
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')