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Author's title

Aantal vergunningen residentiële renovatie in België(Rekenkundig gemiddelde...

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 07 Mar 2012 16:39:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Mar/07/t1331156579ig3gc4q03iqzlvb.htm/, Retrieved Sun, 28 Apr 2024 21:41:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=163719, Retrieved Sun, 28 Apr 2024 21:41:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG2011W52a
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Aantal vergunning...] [2012-03-07 21:39:19] [e46afc21a91140cf7fea495f009879eb] [Current]
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Dataseries X:
1.974
2.037
2.259
2.550
2.549
2.738
2.228
2.533
2.475
2.260
2.158
2.253
2.670
2.449
2.620
2.205
2.589
2.706
2.352
2.478
2.316
2.295
2.110
1.944
2.202
2.036
2.434
2.297
2.354
2.650
2.555
2.477
2.268
2.510
2.015
1.994
2.271
2.289
2.333
2.795
2.332
2.799
2.294
2.415
2.473
2.236
1.970
2.318
2.108
2.064
2.519
2.298
2.187
2.746
2.364
2.512
2.224
2.209
2.186
2.303
2.381
2.432
2.913
2.392
2.532
2.709
2.387
2.609
2.399
2.184
1.839
2.056
2.151
2.155
2.463
2.155
2.679
2.367
2.052
2.547
2.466




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163719&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163719&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'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2.353740740740740.02523850904511493.2598964753985
Geometric Mean2.34290463747359
Harmonic Mean2.33205509908655
Quadratic Mean2.36454098330488
Winsorized Mean ( 1 / 27 )2.353629629629630.024583125827400795.7416744377657
Winsorized Mean ( 2 / 27 )2.354172839506170.024430840849344696.3606964665453
Winsorized Mean ( 3 / 27 )2.352506172839510.024010974364981597.9762893866768
Winsorized Mean ( 4 / 27 )2.35309876543210.023739771058694399.1205332020384
Winsorized Mean ( 5 / 27 )2.35260493827160.0231451917453655101.645515152955
Winsorized Mean ( 6 / 27 )2.353938271604940.0228251022314521103.129363791471
Winsorized Mean ( 7 / 27 )2.351691358024690.022371565133794105.119661675896
Winsorized Mean ( 8 / 27 )2.352283950617280.0219529395270652107.151206229909
Winsorized Mean ( 9 / 27 )2.350506172839510.0214821424795423109.416748123607
Winsorized Mean ( 10 / 27 )2.347790123456790.0206851449355062113.501265317547
Winsorized Mean ( 11 / 27 )2.352271604938270.0194565360209327120.898787040382
Winsorized Mean ( 12 / 27 )2.34960493827160.0189311836857749124.112943874562
Winsorized Mean ( 13 / 27 )2.350728395061730.0170877366714008137.568154300743
Winsorized Mean ( 14 / 27 )2.350555555555560.0168586351833983139.427393142138
Winsorized Mean ( 15 / 27 )2.350370370370370.016831283744351139.642965211089
Winsorized Mean ( 16 / 27 )2.350567901234570.0166873477083873140.85928706652
Winsorized Mean ( 17 / 27 )2.353086419753090.0154911782694601151.898479174567
Winsorized Mean ( 18 / 27 )2.353308641975310.0153984290722662152.827839186128
Winsorized Mean ( 19 / 27 )2.350493827160490.0149300852479601157.433382872455
Winsorized Mean ( 20 / 27 )2.352469135802470.0141874910824985165.812906744622
Winsorized Mean ( 21 / 27 )2.352728395061730.0140118667998879167.909703158222
Winsorized Mean ( 22 / 27 )2.345123456790120.0126868185545399184.847244934463
Winsorized Mean ( 23 / 27 )2.34909876543210.012088097463604194.33155403528
Winsorized Mean ( 24 / 27 )2.349691358024690.0118570789656356198.167808853649
Winsorized Mean ( 25 / 27 )2.351543209876540.0114614228075071205.170269814697
Winsorized Mean ( 26 / 27 )2.354753086419750.0104884052805208224.510116022408
Winsorized Mean ( 27 / 27 )2.355753086419750.010114979889647232.897456259992
Trimmed Mean ( 1 / 27 )2.353177215189870.024001959237172198.0410470635863
Trimmed Mean ( 2 / 27 )2.35270129870130.0233245480193272100.868033830786
Trimmed Mean ( 3 / 27 )2.351906666666670.0226272352304512103.941407012975
Trimmed Mean ( 4 / 27 )2.351684931506850.0219979405836314106.904776952472
Trimmed Mean ( 5 / 27 )2.351281690140850.0213537719077348110.110836638148
Trimmed Mean ( 6 / 27 )2.350971014492750.0207755837723118113.160286625782
Trimmed Mean ( 7 / 27 )2.350373134328360.0201751022702503116.49869739665
Trimmed Mean ( 8 / 27 )2.350138461538460.0195730004004127120.070424230355
Trimmed Mean ( 9 / 27 )2.349793650793650.0189489593726348124.006474687318
Trimmed Mean ( 10 / 27 )2.349688524590160.0183027147346427128.379235466242
Trimmed Mean ( 11 / 27 )2.349949152542370.0176941583595238132.809320725759
Trimmed Mean ( 12 / 27 )2.349649122807020.0172127242675097136.506521936342
Trimmed Mean ( 13 / 27 )2.349654545454550.0167271471961327140.469532425576
Trimmed Mean ( 14 / 27 )2.349528301886790.016489509436646142.486246235151
Trimmed Mean ( 15 / 27 )2.349411764705880.0162255711152535144.796860955928
Trimmed Mean ( 16 / 27 )2.349306122448980.0158878992823731147.867636916319
Trimmed Mean ( 17 / 27 )2.349170212765960.0154791291896799151.763719003791
Trimmed Mean ( 18 / 27 )2.348755555555560.0151913769917214154.611103182781
Trimmed Mean ( 19 / 27 )2.348279069767440.0148238578460936158.412141707515
Trimmed Mean ( 20 / 27 )2.34804878048780.0144345432235515162.668727657188
Trimmed Mean ( 21 / 27 )2.347589743589740.0140724325386773166.821886488887
Trimmed Mean ( 22 / 27 )2.347054054054050.0136110131363362172.43786561254
Trimmed Mean ( 23 / 27 )2.347257142857140.0133018822739044176.460526001045
Trimmed Mean ( 24 / 27 )2.347060606060610.0130024720401618180.508798543158
Trimmed Mean ( 25 / 27 )2.346774193548390.0126144404090376186.038707818307
Trimmed Mean ( 26 / 27 )2.346241379310340.0121451256386809193.183788221821
Trimmed Mean ( 27 / 27 )2.345259259259260.0117373430154153199.811767976714
Median2.333
Midrange2.376
Midmean - Weighted Average at Xnp2.34395
Midmean - Weighted Average at X(n+1)p2.3480487804878
Midmean - Empirical Distribution Function2.3480487804878
Midmean - Empirical Distribution Function - Averaging2.3480487804878
Midmean - Empirical Distribution Function - Interpolation2.3480487804878
Midmean - Closest Observation2.34421428571428
Midmean - True Basic - Statistics Graphics Toolkit2.3480487804878
Midmean - MS Excel (old versions)2.3480487804878
Number of observations81

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2.35374074074074 & 0.025238509045114 & 93.2598964753985 \tabularnewline
Geometric Mean & 2.34290463747359 &  &  \tabularnewline
Harmonic Mean & 2.33205509908655 &  &  \tabularnewline
Quadratic Mean & 2.36454098330488 &  &  \tabularnewline
Winsorized Mean ( 1 / 27 ) & 2.35362962962963 & 0.0245831258274007 & 95.7416744377657 \tabularnewline
Winsorized Mean ( 2 / 27 ) & 2.35417283950617 & 0.0244308408493446 & 96.3606964665453 \tabularnewline
Winsorized Mean ( 3 / 27 ) & 2.35250617283951 & 0.0240109743649815 & 97.9762893866768 \tabularnewline
Winsorized Mean ( 4 / 27 ) & 2.3530987654321 & 0.0237397710586943 & 99.1205332020384 \tabularnewline
Winsorized Mean ( 5 / 27 ) & 2.3526049382716 & 0.0231451917453655 & 101.645515152955 \tabularnewline
Winsorized Mean ( 6 / 27 ) & 2.35393827160494 & 0.0228251022314521 & 103.129363791471 \tabularnewline
Winsorized Mean ( 7 / 27 ) & 2.35169135802469 & 0.022371565133794 & 105.119661675896 \tabularnewline
Winsorized Mean ( 8 / 27 ) & 2.35228395061728 & 0.0219529395270652 & 107.151206229909 \tabularnewline
Winsorized Mean ( 9 / 27 ) & 2.35050617283951 & 0.0214821424795423 & 109.416748123607 \tabularnewline
Winsorized Mean ( 10 / 27 ) & 2.34779012345679 & 0.0206851449355062 & 113.501265317547 \tabularnewline
Winsorized Mean ( 11 / 27 ) & 2.35227160493827 & 0.0194565360209327 & 120.898787040382 \tabularnewline
Winsorized Mean ( 12 / 27 ) & 2.3496049382716 & 0.0189311836857749 & 124.112943874562 \tabularnewline
Winsorized Mean ( 13 / 27 ) & 2.35072839506173 & 0.0170877366714008 & 137.568154300743 \tabularnewline
Winsorized Mean ( 14 / 27 ) & 2.35055555555556 & 0.0168586351833983 & 139.427393142138 \tabularnewline
Winsorized Mean ( 15 / 27 ) & 2.35037037037037 & 0.016831283744351 & 139.642965211089 \tabularnewline
Winsorized Mean ( 16 / 27 ) & 2.35056790123457 & 0.0166873477083873 & 140.85928706652 \tabularnewline
Winsorized Mean ( 17 / 27 ) & 2.35308641975309 & 0.0154911782694601 & 151.898479174567 \tabularnewline
Winsorized Mean ( 18 / 27 ) & 2.35330864197531 & 0.0153984290722662 & 152.827839186128 \tabularnewline
Winsorized Mean ( 19 / 27 ) & 2.35049382716049 & 0.0149300852479601 & 157.433382872455 \tabularnewline
Winsorized Mean ( 20 / 27 ) & 2.35246913580247 & 0.0141874910824985 & 165.812906744622 \tabularnewline
Winsorized Mean ( 21 / 27 ) & 2.35272839506173 & 0.0140118667998879 & 167.909703158222 \tabularnewline
Winsorized Mean ( 22 / 27 ) & 2.34512345679012 & 0.0126868185545399 & 184.847244934463 \tabularnewline
Winsorized Mean ( 23 / 27 ) & 2.3490987654321 & 0.012088097463604 & 194.33155403528 \tabularnewline
Winsorized Mean ( 24 / 27 ) & 2.34969135802469 & 0.0118570789656356 & 198.167808853649 \tabularnewline
Winsorized Mean ( 25 / 27 ) & 2.35154320987654 & 0.0114614228075071 & 205.170269814697 \tabularnewline
Winsorized Mean ( 26 / 27 ) & 2.35475308641975 & 0.0104884052805208 & 224.510116022408 \tabularnewline
Winsorized Mean ( 27 / 27 ) & 2.35575308641975 & 0.010114979889647 & 232.897456259992 \tabularnewline
Trimmed Mean ( 1 / 27 ) & 2.35317721518987 & 0.0240019592371721 & 98.0410470635863 \tabularnewline
Trimmed Mean ( 2 / 27 ) & 2.3527012987013 & 0.0233245480193272 & 100.868033830786 \tabularnewline
Trimmed Mean ( 3 / 27 ) & 2.35190666666667 & 0.0226272352304512 & 103.941407012975 \tabularnewline
Trimmed Mean ( 4 / 27 ) & 2.35168493150685 & 0.0219979405836314 & 106.904776952472 \tabularnewline
Trimmed Mean ( 5 / 27 ) & 2.35128169014085 & 0.0213537719077348 & 110.110836638148 \tabularnewline
Trimmed Mean ( 6 / 27 ) & 2.35097101449275 & 0.0207755837723118 & 113.160286625782 \tabularnewline
Trimmed Mean ( 7 / 27 ) & 2.35037313432836 & 0.0201751022702503 & 116.49869739665 \tabularnewline
Trimmed Mean ( 8 / 27 ) & 2.35013846153846 & 0.0195730004004127 & 120.070424230355 \tabularnewline
Trimmed Mean ( 9 / 27 ) & 2.34979365079365 & 0.0189489593726348 & 124.006474687318 \tabularnewline
Trimmed Mean ( 10 / 27 ) & 2.34968852459016 & 0.0183027147346427 & 128.379235466242 \tabularnewline
Trimmed Mean ( 11 / 27 ) & 2.34994915254237 & 0.0176941583595238 & 132.809320725759 \tabularnewline
Trimmed Mean ( 12 / 27 ) & 2.34964912280702 & 0.0172127242675097 & 136.506521936342 \tabularnewline
Trimmed Mean ( 13 / 27 ) & 2.34965454545455 & 0.0167271471961327 & 140.469532425576 \tabularnewline
Trimmed Mean ( 14 / 27 ) & 2.34952830188679 & 0.016489509436646 & 142.486246235151 \tabularnewline
Trimmed Mean ( 15 / 27 ) & 2.34941176470588 & 0.0162255711152535 & 144.796860955928 \tabularnewline
Trimmed Mean ( 16 / 27 ) & 2.34930612244898 & 0.0158878992823731 & 147.867636916319 \tabularnewline
Trimmed Mean ( 17 / 27 ) & 2.34917021276596 & 0.0154791291896799 & 151.763719003791 \tabularnewline
Trimmed Mean ( 18 / 27 ) & 2.34875555555556 & 0.0151913769917214 & 154.611103182781 \tabularnewline
Trimmed Mean ( 19 / 27 ) & 2.34827906976744 & 0.0148238578460936 & 158.412141707515 \tabularnewline
Trimmed Mean ( 20 / 27 ) & 2.3480487804878 & 0.0144345432235515 & 162.668727657188 \tabularnewline
Trimmed Mean ( 21 / 27 ) & 2.34758974358974 & 0.0140724325386773 & 166.821886488887 \tabularnewline
Trimmed Mean ( 22 / 27 ) & 2.34705405405405 & 0.0136110131363362 & 172.43786561254 \tabularnewline
Trimmed Mean ( 23 / 27 ) & 2.34725714285714 & 0.0133018822739044 & 176.460526001045 \tabularnewline
Trimmed Mean ( 24 / 27 ) & 2.34706060606061 & 0.0130024720401618 & 180.508798543158 \tabularnewline
Trimmed Mean ( 25 / 27 ) & 2.34677419354839 & 0.0126144404090376 & 186.038707818307 \tabularnewline
Trimmed Mean ( 26 / 27 ) & 2.34624137931034 & 0.0121451256386809 & 193.183788221821 \tabularnewline
Trimmed Mean ( 27 / 27 ) & 2.34525925925926 & 0.0117373430154153 & 199.811767976714 \tabularnewline
Median & 2.333 &  &  \tabularnewline
Midrange & 2.376 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2.34395 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2.3480487804878 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2.3480487804878 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2.3480487804878 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2.3480487804878 &  &  \tabularnewline
Midmean - Closest Observation & 2.34421428571428 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2.3480487804878 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2.3480487804878 &  &  \tabularnewline
Number of observations & 81 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163719&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]2.35374074074074[/C][C]0.025238509045114[/C][C]93.2598964753985[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2.34290463747359[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2.33205509908655[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2.36454098330488[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 27 )[/C][C]2.35362962962963[/C][C]0.0245831258274007[/C][C]95.7416744377657[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 27 )[/C][C]2.35417283950617[/C][C]0.0244308408493446[/C][C]96.3606964665453[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 27 )[/C][C]2.35250617283951[/C][C]0.0240109743649815[/C][C]97.9762893866768[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 27 )[/C][C]2.3530987654321[/C][C]0.0237397710586943[/C][C]99.1205332020384[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 27 )[/C][C]2.3526049382716[/C][C]0.0231451917453655[/C][C]101.645515152955[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 27 )[/C][C]2.35393827160494[/C][C]0.0228251022314521[/C][C]103.129363791471[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 27 )[/C][C]2.35169135802469[/C][C]0.022371565133794[/C][C]105.119661675896[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 27 )[/C][C]2.35228395061728[/C][C]0.0219529395270652[/C][C]107.151206229909[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 27 )[/C][C]2.35050617283951[/C][C]0.0214821424795423[/C][C]109.416748123607[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 27 )[/C][C]2.34779012345679[/C][C]0.0206851449355062[/C][C]113.501265317547[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 27 )[/C][C]2.35227160493827[/C][C]0.0194565360209327[/C][C]120.898787040382[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 27 )[/C][C]2.3496049382716[/C][C]0.0189311836857749[/C][C]124.112943874562[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 27 )[/C][C]2.35072839506173[/C][C]0.0170877366714008[/C][C]137.568154300743[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 27 )[/C][C]2.35055555555556[/C][C]0.0168586351833983[/C][C]139.427393142138[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 27 )[/C][C]2.35037037037037[/C][C]0.016831283744351[/C][C]139.642965211089[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 27 )[/C][C]2.35056790123457[/C][C]0.0166873477083873[/C][C]140.85928706652[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 27 )[/C][C]2.35308641975309[/C][C]0.0154911782694601[/C][C]151.898479174567[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 27 )[/C][C]2.35330864197531[/C][C]0.0153984290722662[/C][C]152.827839186128[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 27 )[/C][C]2.35049382716049[/C][C]0.0149300852479601[/C][C]157.433382872455[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 27 )[/C][C]2.35246913580247[/C][C]0.0141874910824985[/C][C]165.812906744622[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 27 )[/C][C]2.35272839506173[/C][C]0.0140118667998879[/C][C]167.909703158222[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 27 )[/C][C]2.34512345679012[/C][C]0.0126868185545399[/C][C]184.847244934463[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 27 )[/C][C]2.3490987654321[/C][C]0.012088097463604[/C][C]194.33155403528[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 27 )[/C][C]2.34969135802469[/C][C]0.0118570789656356[/C][C]198.167808853649[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 27 )[/C][C]2.35154320987654[/C][C]0.0114614228075071[/C][C]205.170269814697[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 27 )[/C][C]2.35475308641975[/C][C]0.0104884052805208[/C][C]224.510116022408[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 27 )[/C][C]2.35575308641975[/C][C]0.010114979889647[/C][C]232.897456259992[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 27 )[/C][C]2.35317721518987[/C][C]0.0240019592371721[/C][C]98.0410470635863[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 27 )[/C][C]2.3527012987013[/C][C]0.0233245480193272[/C][C]100.868033830786[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 27 )[/C][C]2.35190666666667[/C][C]0.0226272352304512[/C][C]103.941407012975[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 27 )[/C][C]2.35168493150685[/C][C]0.0219979405836314[/C][C]106.904776952472[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 27 )[/C][C]2.35128169014085[/C][C]0.0213537719077348[/C][C]110.110836638148[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 27 )[/C][C]2.35097101449275[/C][C]0.0207755837723118[/C][C]113.160286625782[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 27 )[/C][C]2.35037313432836[/C][C]0.0201751022702503[/C][C]116.49869739665[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 27 )[/C][C]2.35013846153846[/C][C]0.0195730004004127[/C][C]120.070424230355[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 27 )[/C][C]2.34979365079365[/C][C]0.0189489593726348[/C][C]124.006474687318[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 27 )[/C][C]2.34968852459016[/C][C]0.0183027147346427[/C][C]128.379235466242[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 27 )[/C][C]2.34994915254237[/C][C]0.0176941583595238[/C][C]132.809320725759[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 27 )[/C][C]2.34964912280702[/C][C]0.0172127242675097[/C][C]136.506521936342[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 27 )[/C][C]2.34965454545455[/C][C]0.0167271471961327[/C][C]140.469532425576[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 27 )[/C][C]2.34952830188679[/C][C]0.016489509436646[/C][C]142.486246235151[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 27 )[/C][C]2.34941176470588[/C][C]0.0162255711152535[/C][C]144.796860955928[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 27 )[/C][C]2.34930612244898[/C][C]0.0158878992823731[/C][C]147.867636916319[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 27 )[/C][C]2.34917021276596[/C][C]0.0154791291896799[/C][C]151.763719003791[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 27 )[/C][C]2.34875555555556[/C][C]0.0151913769917214[/C][C]154.611103182781[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 27 )[/C][C]2.34827906976744[/C][C]0.0148238578460936[/C][C]158.412141707515[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 27 )[/C][C]2.3480487804878[/C][C]0.0144345432235515[/C][C]162.668727657188[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 27 )[/C][C]2.34758974358974[/C][C]0.0140724325386773[/C][C]166.821886488887[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 27 )[/C][C]2.34705405405405[/C][C]0.0136110131363362[/C][C]172.43786561254[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 27 )[/C][C]2.34725714285714[/C][C]0.0133018822739044[/C][C]176.460526001045[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 27 )[/C][C]2.34706060606061[/C][C]0.0130024720401618[/C][C]180.508798543158[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 27 )[/C][C]2.34677419354839[/C][C]0.0126144404090376[/C][C]186.038707818307[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 27 )[/C][C]2.34624137931034[/C][C]0.0121451256386809[/C][C]193.183788221821[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 27 )[/C][C]2.34525925925926[/C][C]0.0117373430154153[/C][C]199.811767976714[/C][/ROW]
[ROW][C]Median[/C][C]2.333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]2.376[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2.34395[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2.3480487804878[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2.3480487804878[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2.3480487804878[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2.3480487804878[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2.34421428571428[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2.3480487804878[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2.3480487804878[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]81[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163719&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 Mean2.353740740740740.02523850904511493.2598964753985
Geometric Mean2.34290463747359
Harmonic Mean2.33205509908655
Quadratic Mean2.36454098330488
Winsorized Mean ( 1 / 27 )2.353629629629630.024583125827400795.7416744377657
Winsorized Mean ( 2 / 27 )2.354172839506170.024430840849344696.3606964665453
Winsorized Mean ( 3 / 27 )2.352506172839510.024010974364981597.9762893866768
Winsorized Mean ( 4 / 27 )2.35309876543210.023739771058694399.1205332020384
Winsorized Mean ( 5 / 27 )2.35260493827160.0231451917453655101.645515152955
Winsorized Mean ( 6 / 27 )2.353938271604940.0228251022314521103.129363791471
Winsorized Mean ( 7 / 27 )2.351691358024690.022371565133794105.119661675896
Winsorized Mean ( 8 / 27 )2.352283950617280.0219529395270652107.151206229909
Winsorized Mean ( 9 / 27 )2.350506172839510.0214821424795423109.416748123607
Winsorized Mean ( 10 / 27 )2.347790123456790.0206851449355062113.501265317547
Winsorized Mean ( 11 / 27 )2.352271604938270.0194565360209327120.898787040382
Winsorized Mean ( 12 / 27 )2.34960493827160.0189311836857749124.112943874562
Winsorized Mean ( 13 / 27 )2.350728395061730.0170877366714008137.568154300743
Winsorized Mean ( 14 / 27 )2.350555555555560.0168586351833983139.427393142138
Winsorized Mean ( 15 / 27 )2.350370370370370.016831283744351139.642965211089
Winsorized Mean ( 16 / 27 )2.350567901234570.0166873477083873140.85928706652
Winsorized Mean ( 17 / 27 )2.353086419753090.0154911782694601151.898479174567
Winsorized Mean ( 18 / 27 )2.353308641975310.0153984290722662152.827839186128
Winsorized Mean ( 19 / 27 )2.350493827160490.0149300852479601157.433382872455
Winsorized Mean ( 20 / 27 )2.352469135802470.0141874910824985165.812906744622
Winsorized Mean ( 21 / 27 )2.352728395061730.0140118667998879167.909703158222
Winsorized Mean ( 22 / 27 )2.345123456790120.0126868185545399184.847244934463
Winsorized Mean ( 23 / 27 )2.34909876543210.012088097463604194.33155403528
Winsorized Mean ( 24 / 27 )2.349691358024690.0118570789656356198.167808853649
Winsorized Mean ( 25 / 27 )2.351543209876540.0114614228075071205.170269814697
Winsorized Mean ( 26 / 27 )2.354753086419750.0104884052805208224.510116022408
Winsorized Mean ( 27 / 27 )2.355753086419750.010114979889647232.897456259992
Trimmed Mean ( 1 / 27 )2.353177215189870.024001959237172198.0410470635863
Trimmed Mean ( 2 / 27 )2.35270129870130.0233245480193272100.868033830786
Trimmed Mean ( 3 / 27 )2.351906666666670.0226272352304512103.941407012975
Trimmed Mean ( 4 / 27 )2.351684931506850.0219979405836314106.904776952472
Trimmed Mean ( 5 / 27 )2.351281690140850.0213537719077348110.110836638148
Trimmed Mean ( 6 / 27 )2.350971014492750.0207755837723118113.160286625782
Trimmed Mean ( 7 / 27 )2.350373134328360.0201751022702503116.49869739665
Trimmed Mean ( 8 / 27 )2.350138461538460.0195730004004127120.070424230355
Trimmed Mean ( 9 / 27 )2.349793650793650.0189489593726348124.006474687318
Trimmed Mean ( 10 / 27 )2.349688524590160.0183027147346427128.379235466242
Trimmed Mean ( 11 / 27 )2.349949152542370.0176941583595238132.809320725759
Trimmed Mean ( 12 / 27 )2.349649122807020.0172127242675097136.506521936342
Trimmed Mean ( 13 / 27 )2.349654545454550.0167271471961327140.469532425576
Trimmed Mean ( 14 / 27 )2.349528301886790.016489509436646142.486246235151
Trimmed Mean ( 15 / 27 )2.349411764705880.0162255711152535144.796860955928
Trimmed Mean ( 16 / 27 )2.349306122448980.0158878992823731147.867636916319
Trimmed Mean ( 17 / 27 )2.349170212765960.0154791291896799151.763719003791
Trimmed Mean ( 18 / 27 )2.348755555555560.0151913769917214154.611103182781
Trimmed Mean ( 19 / 27 )2.348279069767440.0148238578460936158.412141707515
Trimmed Mean ( 20 / 27 )2.34804878048780.0144345432235515162.668727657188
Trimmed Mean ( 21 / 27 )2.347589743589740.0140724325386773166.821886488887
Trimmed Mean ( 22 / 27 )2.347054054054050.0136110131363362172.43786561254
Trimmed Mean ( 23 / 27 )2.347257142857140.0133018822739044176.460526001045
Trimmed Mean ( 24 / 27 )2.347060606060610.0130024720401618180.508798543158
Trimmed Mean ( 25 / 27 )2.346774193548390.0126144404090376186.038707818307
Trimmed Mean ( 26 / 27 )2.346241379310340.0121451256386809193.183788221821
Trimmed Mean ( 27 / 27 )2.345259259259260.0117373430154153199.811767976714
Median2.333
Midrange2.376
Midmean - Weighted Average at Xnp2.34395
Midmean - Weighted Average at X(n+1)p2.3480487804878
Midmean - Empirical Distribution Function2.3480487804878
Midmean - Empirical Distribution Function - Averaging2.3480487804878
Midmean - Empirical Distribution Function - Interpolation2.3480487804878
Midmean - Closest Observation2.34421428571428
Midmean - True Basic - Statistics Graphics Toolkit2.3480487804878
Midmean - MS Excel (old versions)2.3480487804878
Number of observations81



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')