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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 computationThu, 05 Aug 2010 15:40:48 +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/Aug/05/t12810228202ky5dw992bmmfeo.htm/, Retrieved Sun, 05 May 2024 14:43:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78424, Retrieved Sun, 05 May 2024 14:43:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsMathias Goossenaerts
Estimated Impact117
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Tijdreeks 2 - Stap 9] [2010-08-05 15:40:48] [f7fc4e1bbbe57039ee5ebdd2c8b864c0] [Current]
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Dataseries X:
430
429
428
426
424
423
424
426
427
427
428
430
432
435
426
411
405
403
402
399
392
387
380
379
386
385
365
356
338
338
343
338
320
316
317
315
317
321
303
303
290
285
300
291
278
273
277
269
275
278
255
254
245
240
261
247
229
213
218
206
217
219
196
193
188
171
190
180
149
135
151
134
145
151
137
124
125
109
131
133
103
85
104
82




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78424&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78424&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78424&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean286.54761904761911.851701316075224.1777624499326
Geometric Mean262.230393460849
Harmonic Mean234.600889610819
Quadratic Mean306.215532559915
Winsorized Mean ( 1 / 28 )286.54761904761911.838987256779224.2037272980032
Winsorized Mean ( 2 / 28 )286.92857142857111.747581698557424.4244797602732
Winsorized Mean ( 3 / 28 )286.96428571428611.740860466049324.4415038015393
Winsorized Mean ( 4 / 28 )287.15476190476211.689672760138924.5648246787492
Winsorized Mean ( 5 / 28 )287.98809523809511.522403208002524.9937526086645
Winsorized Mean ( 6 / 28 )288.05952380952411.510183462821725.0264928217667
Winsorized Mean ( 7 / 28 )288.47619047619011.413754977822525.2744334390141
Winsorized Mean ( 8 / 28 )288.66666666666711.382230584259225.3611684045368
Winsorized Mean ( 9 / 28 )288.66666666666711.348952316591225.4355343659926
Winsorized Mean ( 10 / 28 )288.78571428571411.329444062356725.4898398099900
Winsorized Mean ( 11 / 28 )289.04761904761911.286773324700125.6094111870806
Winsorized Mean ( 12 / 28 )289.90476190476211.062068912775226.2071014193341
Winsorized Mean ( 13 / 28 )290.52380952381010.9650840547526.4953563577980
Winsorized Mean ( 14 / 28 )290.69047619047610.888984683280826.6958292848744
Winsorized Mean ( 15 / 28 )288.54761904761910.582658347771327.2660809378192
Winsorized Mean ( 16 / 28 )291.2142857142869.8442412262639829.5821972482084
Winsorized Mean ( 17 / 28 )292.6309523809529.5239797567975830.7257007945751
Winsorized Mean ( 18 / 28 )294.1309523809529.2533472221724331.7864384982949
Winsorized Mean ( 19 / 28 )293.9047619047629.0960738607874432.3111670378762
Winsorized Mean ( 20 / 28 )292.9523809523818.7684058485590433.4099933342528
Winsorized Mean ( 21 / 28 )292.4523809523818.496741043802334.4193590748187
Winsorized Mean ( 22 / 28 )294.8095238095248.1094152123439336.3539806619808
Winsorized Mean ( 23 / 28 )296.4523809523817.8225149247609737.8973237895663
Winsorized Mean ( 24 / 28 )296.1666666666677.482353179520439.5820217999453
Winsorized Mean ( 25 / 28 )296.1666666666677.4043108447624839.9992211126797
Winsorized Mean ( 26 / 28 )292.1428571428576.791990635451943.012847458589
Winsorized Mean ( 27 / 28 )292.4642857142866.007249551022948.6852232840045
Winsorized Mean ( 28 / 28 )291.7976190476195.0004813239900658.3539063825127
Trimmed Mean ( 1 / 28 )287.23170731707311.739613202797924.4668799861837
Trimmed Mean ( 2 / 28 )287.9511.620950363105924.7785242172775
Trimmed Mean ( 3 / 28 )288.511.534637783557325.0116219870603
Trimmed Mean ( 4 / 28 )289.06578947368411.432476601213925.2846167595034
Trimmed Mean ( 5 / 28 )289.60810810810811.326101238229925.5699734636461
Trimmed Mean ( 6 / 28 )289.98611111111111.244743043279025.7885938340259
Trimmed Mean ( 7 / 28 )290.37142857142911.146533342725226.0503799381661
Trimmed Mean ( 8 / 28 )290.70588235294111.047329315140426.3145846439581
Trimmed Mean ( 9 / 28 )291.03030303030310.930762597106326.624885541595
Trimmed Mean ( 10 / 28 )291.37510.793114445999626.9963782426116
Trimmed Mean ( 11 / 28 )291.72580645161310.626940843168827.4515319843095
Trimmed Mean ( 12 / 28 )292.06666666666710.430449412797128.0013501919036
Trimmed Mean ( 13 / 28 )292.32758620689710.231630373081828.570968217927
Trimmed Mean ( 14 / 28 )292.53571428571410.003407350852429.2436071056117
Trimmed Mean ( 15 / 28 )292.7407407407419.7335998780735130.0752798972337
Trimmed Mean ( 16 / 28 )293.1923076923089.4547440932280331.0100733347513
Trimmed Mean ( 17 / 28 )293.49.2501296185071731.7184744539126
Trimmed Mean ( 18 / 28 )293.4791666666679.0497536104999332.4295201060678
Trimmed Mean ( 19 / 28 )293.4130434782618.842670814700533.1814956845930
Trimmed Mean ( 20 / 28 )293.3636363636368.6025766156550234.1018336099177
Trimmed Mean ( 21 / 28 )293.4047619047628.3552830223191235.1160769923654
Trimmed Mean ( 22 / 28 )293.58.0847276090676436.3030165259764
Trimmed Mean ( 23 / 28 )293.3684210526327.8096505434712137.5648589421052
Trimmed Mean ( 24 / 28 )293.0555555555567.5009993455310939.0688683008819
Trimmed Mean ( 25 / 28 )292.7352941176477.1616562707973240.8753622135311
Trimmed Mean ( 26 / 28 )292.3756.6988428827478843.6455974737039
Trimmed Mean ( 27 / 28 )292.46.2382947861639646.8717830790106
Trimmed Mean ( 28 / 28 )292.3928571428575.841001600552550.058684646688
Median290.5
Midrange258.5
Midmean - Weighted Average at Xnp291.069767441860
Midmean - Weighted Average at X(n+1)p293.404761904762
Midmean - Empirical Distribution Function291.069767441860
Midmean - Empirical Distribution Function - Averaging293.404761904762
Midmean - Empirical Distribution Function - Interpolation293.404761904762
Midmean - Closest Observation291.069767441860
Midmean - True Basic - Statistics Graphics Toolkit293.404761904762
Midmean - MS Excel (old versions)293.363636363636
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 286.547619047619 & 11.8517013160752 & 24.1777624499326 \tabularnewline
Geometric Mean & 262.230393460849 &  &  \tabularnewline
Harmonic Mean & 234.600889610819 &  &  \tabularnewline
Quadratic Mean & 306.215532559915 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 286.547619047619 & 11.8389872567792 & 24.2037272980032 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 286.928571428571 & 11.7475816985574 & 24.4244797602732 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 286.964285714286 & 11.7408604660493 & 24.4415038015393 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 287.154761904762 & 11.6896727601389 & 24.5648246787492 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 287.988095238095 & 11.5224032080025 & 24.9937526086645 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 288.059523809524 & 11.5101834628217 & 25.0264928217667 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 288.476190476190 & 11.4137549778225 & 25.2744334390141 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 288.666666666667 & 11.3822305842592 & 25.3611684045368 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 288.666666666667 & 11.3489523165912 & 25.4355343659926 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 288.785714285714 & 11.3294440623567 & 25.4898398099900 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 289.047619047619 & 11.2867733247001 & 25.6094111870806 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 289.904761904762 & 11.0620689127752 & 26.2071014193341 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 290.523809523810 & 10.96508405475 & 26.4953563577980 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 290.690476190476 & 10.8889846832808 & 26.6958292848744 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 288.547619047619 & 10.5826583477713 & 27.2660809378192 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 291.214285714286 & 9.84424122626398 & 29.5821972482084 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 292.630952380952 & 9.52397975679758 & 30.7257007945751 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 294.130952380952 & 9.25334722217243 & 31.7864384982949 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 293.904761904762 & 9.09607386078744 & 32.3111670378762 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 292.952380952381 & 8.76840584855904 & 33.4099933342528 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 292.452380952381 & 8.4967410438023 & 34.4193590748187 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 294.809523809524 & 8.10941521234393 & 36.3539806619808 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 296.452380952381 & 7.82251492476097 & 37.8973237895663 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 296.166666666667 & 7.4823531795204 & 39.5820217999453 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 296.166666666667 & 7.40431084476248 & 39.9992211126797 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 292.142857142857 & 6.7919906354519 & 43.012847458589 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 292.464285714286 & 6.0072495510229 & 48.6852232840045 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 291.797619047619 & 5.00048132399006 & 58.3539063825127 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 287.231707317073 & 11.7396132027979 & 24.4668799861837 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 287.95 & 11.6209503631059 & 24.7785242172775 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 288.5 & 11.5346377835573 & 25.0116219870603 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 289.065789473684 & 11.4324766012139 & 25.2846167595034 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 289.608108108108 & 11.3261012382299 & 25.5699734636461 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 289.986111111111 & 11.2447430432790 & 25.7885938340259 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 290.371428571429 & 11.1465333427252 & 26.0503799381661 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 290.705882352941 & 11.0473293151404 & 26.3145846439581 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 291.030303030303 & 10.9307625971063 & 26.624885541595 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 291.375 & 10.7931144459996 & 26.9963782426116 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 291.725806451613 & 10.6269408431688 & 27.4515319843095 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 292.066666666667 & 10.4304494127971 & 28.0013501919036 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 292.327586206897 & 10.2316303730818 & 28.570968217927 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 292.535714285714 & 10.0034073508524 & 29.2436071056117 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 292.740740740741 & 9.73359987807351 & 30.0752798972337 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 293.192307692308 & 9.45474409322803 & 31.0100733347513 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 293.4 & 9.25012961850717 & 31.7184744539126 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 293.479166666667 & 9.04975361049993 & 32.4295201060678 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 293.413043478261 & 8.8426708147005 & 33.1814956845930 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 293.363636363636 & 8.60257661565502 & 34.1018336099177 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 293.404761904762 & 8.35528302231912 & 35.1160769923654 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 293.5 & 8.08472760906764 & 36.3030165259764 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 293.368421052632 & 7.80965054347121 & 37.5648589421052 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 293.055555555556 & 7.50099934553109 & 39.0688683008819 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 292.735294117647 & 7.16165627079732 & 40.8753622135311 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 292.375 & 6.69884288274788 & 43.6455974737039 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 292.4 & 6.23829478616396 & 46.8717830790106 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 292.392857142857 & 5.8410016005525 & 50.058684646688 \tabularnewline
Median & 290.5 &  &  \tabularnewline
Midrange & 258.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 291.069767441860 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 293.404761904762 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 291.069767441860 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 293.404761904762 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 293.404761904762 &  &  \tabularnewline
Midmean - Closest Observation & 291.069767441860 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 293.404761904762 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 293.363636363636 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78424&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]286.547619047619[/C][C]11.8517013160752[/C][C]24.1777624499326[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]262.230393460849[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]234.600889610819[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]306.215532559915[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]286.547619047619[/C][C]11.8389872567792[/C][C]24.2037272980032[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]286.928571428571[/C][C]11.7475816985574[/C][C]24.4244797602732[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]286.964285714286[/C][C]11.7408604660493[/C][C]24.4415038015393[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]287.154761904762[/C][C]11.6896727601389[/C][C]24.5648246787492[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]287.988095238095[/C][C]11.5224032080025[/C][C]24.9937526086645[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]288.059523809524[/C][C]11.5101834628217[/C][C]25.0264928217667[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]288.476190476190[/C][C]11.4137549778225[/C][C]25.2744334390141[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]288.666666666667[/C][C]11.3822305842592[/C][C]25.3611684045368[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]288.666666666667[/C][C]11.3489523165912[/C][C]25.4355343659926[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]288.785714285714[/C][C]11.3294440623567[/C][C]25.4898398099900[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]289.047619047619[/C][C]11.2867733247001[/C][C]25.6094111870806[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]289.904761904762[/C][C]11.0620689127752[/C][C]26.2071014193341[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]290.523809523810[/C][C]10.96508405475[/C][C]26.4953563577980[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]290.690476190476[/C][C]10.8889846832808[/C][C]26.6958292848744[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]288.547619047619[/C][C]10.5826583477713[/C][C]27.2660809378192[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]291.214285714286[/C][C]9.84424122626398[/C][C]29.5821972482084[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]292.630952380952[/C][C]9.52397975679758[/C][C]30.7257007945751[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]294.130952380952[/C][C]9.25334722217243[/C][C]31.7864384982949[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]293.904761904762[/C][C]9.09607386078744[/C][C]32.3111670378762[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]292.952380952381[/C][C]8.76840584855904[/C][C]33.4099933342528[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]292.452380952381[/C][C]8.4967410438023[/C][C]34.4193590748187[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]294.809523809524[/C][C]8.10941521234393[/C][C]36.3539806619808[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]296.452380952381[/C][C]7.82251492476097[/C][C]37.8973237895663[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]296.166666666667[/C][C]7.4823531795204[/C][C]39.5820217999453[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]296.166666666667[/C][C]7.40431084476248[/C][C]39.9992211126797[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]292.142857142857[/C][C]6.7919906354519[/C][C]43.012847458589[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]292.464285714286[/C][C]6.0072495510229[/C][C]48.6852232840045[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]291.797619047619[/C][C]5.00048132399006[/C][C]58.3539063825127[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]287.231707317073[/C][C]11.7396132027979[/C][C]24.4668799861837[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]287.95[/C][C]11.6209503631059[/C][C]24.7785242172775[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]288.5[/C][C]11.5346377835573[/C][C]25.0116219870603[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]289.065789473684[/C][C]11.4324766012139[/C][C]25.2846167595034[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]289.608108108108[/C][C]11.3261012382299[/C][C]25.5699734636461[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]289.986111111111[/C][C]11.2447430432790[/C][C]25.7885938340259[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]290.371428571429[/C][C]11.1465333427252[/C][C]26.0503799381661[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]290.705882352941[/C][C]11.0473293151404[/C][C]26.3145846439581[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]291.030303030303[/C][C]10.9307625971063[/C][C]26.624885541595[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]291.375[/C][C]10.7931144459996[/C][C]26.9963782426116[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]291.725806451613[/C][C]10.6269408431688[/C][C]27.4515319843095[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]292.066666666667[/C][C]10.4304494127971[/C][C]28.0013501919036[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]292.327586206897[/C][C]10.2316303730818[/C][C]28.570968217927[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]292.535714285714[/C][C]10.0034073508524[/C][C]29.2436071056117[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]292.740740740741[/C][C]9.73359987807351[/C][C]30.0752798972337[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]293.192307692308[/C][C]9.45474409322803[/C][C]31.0100733347513[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]293.4[/C][C]9.25012961850717[/C][C]31.7184744539126[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]293.479166666667[/C][C]9.04975361049993[/C][C]32.4295201060678[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]293.413043478261[/C][C]8.8426708147005[/C][C]33.1814956845930[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]293.363636363636[/C][C]8.60257661565502[/C][C]34.1018336099177[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]293.404761904762[/C][C]8.35528302231912[/C][C]35.1160769923654[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]293.5[/C][C]8.08472760906764[/C][C]36.3030165259764[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]293.368421052632[/C][C]7.80965054347121[/C][C]37.5648589421052[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]293.055555555556[/C][C]7.50099934553109[/C][C]39.0688683008819[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]292.735294117647[/C][C]7.16165627079732[/C][C]40.8753622135311[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]292.375[/C][C]6.69884288274788[/C][C]43.6455974737039[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]292.4[/C][C]6.23829478616396[/C][C]46.8717830790106[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]292.392857142857[/C][C]5.8410016005525[/C][C]50.058684646688[/C][/ROW]
[ROW][C]Median[/C][C]290.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]258.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]291.069767441860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]293.404761904762[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]291.069767441860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]293.404761904762[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]293.404761904762[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]291.069767441860[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]293.404761904762[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]293.363636363636[/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=78424&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78424&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 Mean286.54761904761911.851701316075224.1777624499326
Geometric Mean262.230393460849
Harmonic Mean234.600889610819
Quadratic Mean306.215532559915
Winsorized Mean ( 1 / 28 )286.54761904761911.838987256779224.2037272980032
Winsorized Mean ( 2 / 28 )286.92857142857111.747581698557424.4244797602732
Winsorized Mean ( 3 / 28 )286.96428571428611.740860466049324.4415038015393
Winsorized Mean ( 4 / 28 )287.15476190476211.689672760138924.5648246787492
Winsorized Mean ( 5 / 28 )287.98809523809511.522403208002524.9937526086645
Winsorized Mean ( 6 / 28 )288.05952380952411.510183462821725.0264928217667
Winsorized Mean ( 7 / 28 )288.47619047619011.413754977822525.2744334390141
Winsorized Mean ( 8 / 28 )288.66666666666711.382230584259225.3611684045368
Winsorized Mean ( 9 / 28 )288.66666666666711.348952316591225.4355343659926
Winsorized Mean ( 10 / 28 )288.78571428571411.329444062356725.4898398099900
Winsorized Mean ( 11 / 28 )289.04761904761911.286773324700125.6094111870806
Winsorized Mean ( 12 / 28 )289.90476190476211.062068912775226.2071014193341
Winsorized Mean ( 13 / 28 )290.52380952381010.9650840547526.4953563577980
Winsorized Mean ( 14 / 28 )290.69047619047610.888984683280826.6958292848744
Winsorized Mean ( 15 / 28 )288.54761904761910.582658347771327.2660809378192
Winsorized Mean ( 16 / 28 )291.2142857142869.8442412262639829.5821972482084
Winsorized Mean ( 17 / 28 )292.6309523809529.5239797567975830.7257007945751
Winsorized Mean ( 18 / 28 )294.1309523809529.2533472221724331.7864384982949
Winsorized Mean ( 19 / 28 )293.9047619047629.0960738607874432.3111670378762
Winsorized Mean ( 20 / 28 )292.9523809523818.7684058485590433.4099933342528
Winsorized Mean ( 21 / 28 )292.4523809523818.496741043802334.4193590748187
Winsorized Mean ( 22 / 28 )294.8095238095248.1094152123439336.3539806619808
Winsorized Mean ( 23 / 28 )296.4523809523817.8225149247609737.8973237895663
Winsorized Mean ( 24 / 28 )296.1666666666677.482353179520439.5820217999453
Winsorized Mean ( 25 / 28 )296.1666666666677.4043108447624839.9992211126797
Winsorized Mean ( 26 / 28 )292.1428571428576.791990635451943.012847458589
Winsorized Mean ( 27 / 28 )292.4642857142866.007249551022948.6852232840045
Winsorized Mean ( 28 / 28 )291.7976190476195.0004813239900658.3539063825127
Trimmed Mean ( 1 / 28 )287.23170731707311.739613202797924.4668799861837
Trimmed Mean ( 2 / 28 )287.9511.620950363105924.7785242172775
Trimmed Mean ( 3 / 28 )288.511.534637783557325.0116219870603
Trimmed Mean ( 4 / 28 )289.06578947368411.432476601213925.2846167595034
Trimmed Mean ( 5 / 28 )289.60810810810811.326101238229925.5699734636461
Trimmed Mean ( 6 / 28 )289.98611111111111.244743043279025.7885938340259
Trimmed Mean ( 7 / 28 )290.37142857142911.146533342725226.0503799381661
Trimmed Mean ( 8 / 28 )290.70588235294111.047329315140426.3145846439581
Trimmed Mean ( 9 / 28 )291.03030303030310.930762597106326.624885541595
Trimmed Mean ( 10 / 28 )291.37510.793114445999626.9963782426116
Trimmed Mean ( 11 / 28 )291.72580645161310.626940843168827.4515319843095
Trimmed Mean ( 12 / 28 )292.06666666666710.430449412797128.0013501919036
Trimmed Mean ( 13 / 28 )292.32758620689710.231630373081828.570968217927
Trimmed Mean ( 14 / 28 )292.53571428571410.003407350852429.2436071056117
Trimmed Mean ( 15 / 28 )292.7407407407419.7335998780735130.0752798972337
Trimmed Mean ( 16 / 28 )293.1923076923089.4547440932280331.0100733347513
Trimmed Mean ( 17 / 28 )293.49.2501296185071731.7184744539126
Trimmed Mean ( 18 / 28 )293.4791666666679.0497536104999332.4295201060678
Trimmed Mean ( 19 / 28 )293.4130434782618.842670814700533.1814956845930
Trimmed Mean ( 20 / 28 )293.3636363636368.6025766156550234.1018336099177
Trimmed Mean ( 21 / 28 )293.4047619047628.3552830223191235.1160769923654
Trimmed Mean ( 22 / 28 )293.58.0847276090676436.3030165259764
Trimmed Mean ( 23 / 28 )293.3684210526327.8096505434712137.5648589421052
Trimmed Mean ( 24 / 28 )293.0555555555567.5009993455310939.0688683008819
Trimmed Mean ( 25 / 28 )292.7352941176477.1616562707973240.8753622135311
Trimmed Mean ( 26 / 28 )292.3756.6988428827478843.6455974737039
Trimmed Mean ( 27 / 28 )292.46.2382947861639646.8717830790106
Trimmed Mean ( 28 / 28 )292.3928571428575.841001600552550.058684646688
Median290.5
Midrange258.5
Midmean - Weighted Average at Xnp291.069767441860
Midmean - Weighted Average at X(n+1)p293.404761904762
Midmean - Empirical Distribution Function291.069767441860
Midmean - Empirical Distribution Function - Averaging293.404761904762
Midmean - Empirical Distribution Function - Interpolation293.404761904762
Midmean - Closest Observation291.069767441860
Midmean - True Basic - Statistics Graphics Toolkit293.404761904762
Midmean - MS Excel (old versions)293.363636363636
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')