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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 16 Aug 2017 15:36:42 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/16/t1502890630tvhjoyypvb3wvbf.htm/, Retrieved Sun, 12 May 2024 10:47:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307395, Retrieved Sun, 12 May 2024 10:47:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-16 13:36:42] [888a13d027786d499af5f5e6685ea85b] [Current]
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Dataseries X:
5400
5200
5500
4400
5700
5600
6000
6200
6900
6000
5700
7100
6000
4500
5300
4000
5600
4600
6100
5500
5800
6500
6400
7600
5500
4600
5100
3700
5300
4100
5800
5500
4900
7000
6300
7200
5400
5000
4500
3700
4900
4400
6000
5800
5000
6700
6200
8000
6400
3900
3900
3900
4600
4600
6200
5700
5100
6400
5900
8500
6700
3900
4100
3400
4700
5400
6800
6700
5400
6300
5600
8000
6100
4900
4400
3300
4900
5900
6900
6500
4800
6900
5400
8300
6900
5000
4600
3100
4900
4700
7100
7100
5400
7000
5200
8100
6900
5100
3900
2700
5300
5100
6700
7700
5700
6400
4800
8300




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307395&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307395&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307395&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean5613.89117.07447.9518
Geometric Mean5479
Harmonic Mean5338.27
Quadratic Mean5743.02
Winsorized Mean ( 1 / 36 )5615.74115.85348.4731
Winsorized Mean ( 2 / 36 )5619.44115.12848.8103
Winsorized Mean ( 3 / 36 )5616.67113.4449.5122
Winsorized Mean ( 4 / 36 )5624.07110.77250.7716
Winsorized Mean ( 5 / 36 )5624.07110.77250.7716
Winsorized Mean ( 6 / 36 )5618.52105.8253.095
Winsorized Mean ( 7 / 36 )5612.04104.64953.6273
Winsorized Mean ( 8 / 36 )5582.4199.764655.9558
Winsorized Mean ( 9 / 36 )5574.0798.5356.5724
Winsorized Mean ( 10 / 36 )5574.0798.5356.5724
Winsorized Mean ( 11 / 36 )5584.2696.943357.6034
Winsorized Mean ( 12 / 36 )5584.2693.674759.6133
Winsorized Mean ( 13 / 36 )5584.2693.674759.6133
Winsorized Mean ( 14 / 36 )5610.1986.416964.92
Winsorized Mean ( 15 / 36 )5610.1986.416964.92
Winsorized Mean ( 16 / 36 )5610.1986.416964.92
Winsorized Mean ( 17 / 36 )5625.9384.405166.6539
Winsorized Mean ( 18 / 36 )5625.9384.405166.6539
Winsorized Mean ( 19 / 36 )5625.9379.799170.5011
Winsorized Mean ( 20 / 36 )5607.4177.30272.5389
Winsorized Mean ( 21 / 36 )5607.4177.30272.5389
Winsorized Mean ( 22 / 36 )5607.4177.30272.5389
Winsorized Mean ( 23 / 36 )5607.4177.30272.5389
Winsorized Mean ( 24 / 36 )5585.1968.91181.0492
Winsorized Mean ( 25 / 36 )5585.1968.91181.0492
Winsorized Mean ( 26 / 36 )5585.1963.11788.4894
Winsorized Mean ( 27 / 36 )5585.1963.11788.4894
Winsorized Mean ( 28 / 36 )5611.1160.176593.2443
Winsorized Mean ( 29 / 36 )5611.1160.176593.2443
Winsorized Mean ( 30 / 36 )5583.3356.836298.2355
Winsorized Mean ( 31 / 36 )5583.3356.836298.2355
Winsorized Mean ( 32 / 36 )5553.753.4129103.977
Winsorized Mean ( 33 / 36 )5584.2649.9942111.698
Winsorized Mean ( 34 / 36 )5584.2649.9942111.698
Winsorized Mean ( 35 / 36 )5551.8546.3347119.821
Winsorized Mean ( 36 / 36 )5585.1942.7064130.781
Trimmed Mean ( 1 / 36 )5614.15112.78149.7792
Trimmed Mean ( 2 / 36 )5612.5109.32751.3369
Trimmed Mean ( 3 / 36 )5608.82105.86752.9801
Trimmed Mean ( 4 / 36 )5606102.67954.5971
Trimmed Mean ( 5 / 36 )5601.0299.973656.025
Trimmed Mean ( 6 / 36 )5595.8396.902957.7468
Trimmed Mean ( 7 / 36 )5591.4994.660259.0691
Trimmed Mean ( 8 / 36 )5588.0492.373360.4941
Trimmed Mean ( 9 / 36 )5588.8990.765261.5753
Trimmed Mean ( 10 / 36 )5590.9189.153662.7109
Trimmed Mean ( 11 / 36 )5593.0287.303364.0643
Trimmed Mean ( 12 / 36 )5594.0585.449665.466
Trimmed Mean ( 13 / 36 )5595.1283.849466.7282
Trimmed Mean ( 14 / 36 )5596.2581.993468.2524
Trimmed Mean ( 15 / 36 )5594.8780.951369.1141
Trimmed Mean ( 16 / 36 )5593.4279.721870.1618
Trimmed Mean ( 17 / 36 )5591.8978.271771.4421
Trimmed Mean ( 18 / 36 )5588.8976.8572.7246
Trimmed Mean ( 19 / 36 )5585.7175.161374.3164
Trimmed Mean ( 20 / 36 )5582.3573.836975.6038
Trimmed Mean ( 21 / 36 )5580.372.620676.8419
Trimmed Mean ( 22 / 36 )5578.1271.146778.4032
Trimmed Mean ( 23 / 36 )5575.8169.358580.3911
Trimmed Mean ( 24 / 36 )5573.3367.181682.9592
Trimmed Mean ( 25 / 36 )5572.4165.896684.563
Trimmed Mean ( 26 / 36 )5571.4364.300186.6472
Trimmed Mean ( 27 / 36 )5570.3763.258288.0576
Trimmed Mean ( 28 / 36 )5569.2361.928489.9301
Trimmed Mean ( 29 / 36 )556660.717591.6705
Trimmed Mean ( 30 / 36 )5562.559.147794.0443
Trimmed Mean ( 31 / 36 )5560.8757.77596.2504
Trimmed Mean ( 32 / 36 )5559.0955.967299.3277
Trimmed Mean ( 33 / 36 )5559.5254.3208102.346
Trimmed Mean ( 34 / 36 )5557.552.8529105.15
Trimmed Mean ( 35 / 36 )5555.2650.839109.272
Trimmed Mean ( 36 / 36 )5555.5649.0294113.311
Median5500
Midrange5600
Midmean - Weighted Average at Xnp5571.43
Midmean - Weighted Average at X(n+1)p5571.43
Midmean - Empirical Distribution Function5571.43
Midmean - Empirical Distribution Function - Averaging5571.43
Midmean - Empirical Distribution Function - Interpolation5571.43
Midmean - Closest Observation5571.43
Midmean - True Basic - Statistics Graphics Toolkit5571.43
Midmean - MS Excel (old versions)5571.43
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5613.89 & 117.074 & 47.9518 \tabularnewline
Geometric Mean & 5479 &  &  \tabularnewline
Harmonic Mean & 5338.27 &  &  \tabularnewline
Quadratic Mean & 5743.02 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 5615.74 & 115.853 & 48.4731 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 5619.44 & 115.128 & 48.8103 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 5616.67 & 113.44 & 49.5122 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 5624.07 & 110.772 & 50.7716 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 5624.07 & 110.772 & 50.7716 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 5618.52 & 105.82 & 53.095 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 5612.04 & 104.649 & 53.6273 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 5582.41 & 99.7646 & 55.9558 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 5574.07 & 98.53 & 56.5724 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 5574.07 & 98.53 & 56.5724 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 5584.26 & 96.9433 & 57.6034 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 5584.26 & 93.6747 & 59.6133 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 5584.26 & 93.6747 & 59.6133 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 5610.19 & 86.4169 & 64.92 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 5610.19 & 86.4169 & 64.92 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 5610.19 & 86.4169 & 64.92 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 5625.93 & 84.4051 & 66.6539 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 5625.93 & 84.4051 & 66.6539 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 5625.93 & 79.7991 & 70.5011 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 5607.41 & 77.302 & 72.5389 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 5607.41 & 77.302 & 72.5389 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 5607.41 & 77.302 & 72.5389 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 5607.41 & 77.302 & 72.5389 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 5585.19 & 68.911 & 81.0492 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 5585.19 & 68.911 & 81.0492 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 5585.19 & 63.117 & 88.4894 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 5585.19 & 63.117 & 88.4894 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 5611.11 & 60.1765 & 93.2443 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 5611.11 & 60.1765 & 93.2443 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 5583.33 & 56.8362 & 98.2355 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 5583.33 & 56.8362 & 98.2355 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 5553.7 & 53.4129 & 103.977 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 5584.26 & 49.9942 & 111.698 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 5584.26 & 49.9942 & 111.698 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 5551.85 & 46.3347 & 119.821 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 5585.19 & 42.7064 & 130.781 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 5614.15 & 112.781 & 49.7792 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 5612.5 & 109.327 & 51.3369 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 5608.82 & 105.867 & 52.9801 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 5606 & 102.679 & 54.5971 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 5601.02 & 99.9736 & 56.025 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 5595.83 & 96.9029 & 57.7468 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 5591.49 & 94.6602 & 59.0691 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 5588.04 & 92.3733 & 60.4941 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 5588.89 & 90.7652 & 61.5753 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 5590.91 & 89.1536 & 62.7109 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 5593.02 & 87.3033 & 64.0643 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 5594.05 & 85.4496 & 65.466 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 5595.12 & 83.8494 & 66.7282 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 5596.25 & 81.9934 & 68.2524 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 5594.87 & 80.9513 & 69.1141 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 5593.42 & 79.7218 & 70.1618 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 5591.89 & 78.2717 & 71.4421 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 5588.89 & 76.85 & 72.7246 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 5585.71 & 75.1613 & 74.3164 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 5582.35 & 73.8369 & 75.6038 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 5580.3 & 72.6206 & 76.8419 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 5578.12 & 71.1467 & 78.4032 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 5575.81 & 69.3585 & 80.3911 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 5573.33 & 67.1816 & 82.9592 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 5572.41 & 65.8966 & 84.563 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 5571.43 & 64.3001 & 86.6472 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 5570.37 & 63.2582 & 88.0576 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 5569.23 & 61.9284 & 89.9301 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 5566 & 60.7175 & 91.6705 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 5562.5 & 59.1477 & 94.0443 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 5560.87 & 57.775 & 96.2504 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 5559.09 & 55.9672 & 99.3277 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 5559.52 & 54.3208 & 102.346 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 5557.5 & 52.8529 & 105.15 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 5555.26 & 50.839 & 109.272 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 5555.56 & 49.0294 & 113.311 \tabularnewline
Median & 5500 &  &  \tabularnewline
Midrange & 5600 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5571.43 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5571.43 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5571.43 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5571.43 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5571.43 &  &  \tabularnewline
Midmean - Closest Observation & 5571.43 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5571.43 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5571.43 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307395&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]5613.89[/C][C]117.074[/C][C]47.9518[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5479[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5338.27[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5743.02[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]5615.74[/C][C]115.853[/C][C]48.4731[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]5619.44[/C][C]115.128[/C][C]48.8103[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]5616.67[/C][C]113.44[/C][C]49.5122[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]5624.07[/C][C]110.772[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]5624.07[/C][C]110.772[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]5618.52[/C][C]105.82[/C][C]53.095[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]5612.04[/C][C]104.649[/C][C]53.6273[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]5582.41[/C][C]99.7646[/C][C]55.9558[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]5574.07[/C][C]98.53[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]5574.07[/C][C]98.53[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]5584.26[/C][C]96.9433[/C][C]57.6034[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]5584.26[/C][C]93.6747[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]5584.26[/C][C]93.6747[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]5610.19[/C][C]86.4169[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]5610.19[/C][C]86.4169[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]5610.19[/C][C]86.4169[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]5625.93[/C][C]84.4051[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]5625.93[/C][C]84.4051[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]5625.93[/C][C]79.7991[/C][C]70.5011[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]5607.41[/C][C]77.302[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]5607.41[/C][C]77.302[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]5607.41[/C][C]77.302[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]5607.41[/C][C]77.302[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]5585.19[/C][C]68.911[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]5585.19[/C][C]68.911[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]5585.19[/C][C]63.117[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]5585.19[/C][C]63.117[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]5611.11[/C][C]60.1765[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]5611.11[/C][C]60.1765[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]5583.33[/C][C]56.8362[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]5583.33[/C][C]56.8362[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]5553.7[/C][C]53.4129[/C][C]103.977[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]5584.26[/C][C]49.9942[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]5584.26[/C][C]49.9942[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]5551.85[/C][C]46.3347[/C][C]119.821[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]5585.19[/C][C]42.7064[/C][C]130.781[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]5614.15[/C][C]112.781[/C][C]49.7792[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]5612.5[/C][C]109.327[/C][C]51.3369[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]5608.82[/C][C]105.867[/C][C]52.9801[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]5606[/C][C]102.679[/C][C]54.5971[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]5601.02[/C][C]99.9736[/C][C]56.025[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]5595.83[/C][C]96.9029[/C][C]57.7468[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]5591.49[/C][C]94.6602[/C][C]59.0691[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]5588.04[/C][C]92.3733[/C][C]60.4941[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]5588.89[/C][C]90.7652[/C][C]61.5753[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]5590.91[/C][C]89.1536[/C][C]62.7109[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]5593.02[/C][C]87.3033[/C][C]64.0643[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]5594.05[/C][C]85.4496[/C][C]65.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]5595.12[/C][C]83.8494[/C][C]66.7282[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]5596.25[/C][C]81.9934[/C][C]68.2524[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]5594.87[/C][C]80.9513[/C][C]69.1141[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]5593.42[/C][C]79.7218[/C][C]70.1618[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]5591.89[/C][C]78.2717[/C][C]71.4421[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]5588.89[/C][C]76.85[/C][C]72.7246[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]5585.71[/C][C]75.1613[/C][C]74.3164[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]5582.35[/C][C]73.8369[/C][C]75.6038[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]5580.3[/C][C]72.6206[/C][C]76.8419[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]5578.12[/C][C]71.1467[/C][C]78.4032[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]5575.81[/C][C]69.3585[/C][C]80.3911[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]5573.33[/C][C]67.1816[/C][C]82.9592[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]5572.41[/C][C]65.8966[/C][C]84.563[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]5571.43[/C][C]64.3001[/C][C]86.6472[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]5570.37[/C][C]63.2582[/C][C]88.0576[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]5569.23[/C][C]61.9284[/C][C]89.9301[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]5566[/C][C]60.7175[/C][C]91.6705[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]5562.5[/C][C]59.1477[/C][C]94.0443[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]5560.87[/C][C]57.775[/C][C]96.2504[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]5559.09[/C][C]55.9672[/C][C]99.3277[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]5559.52[/C][C]54.3208[/C][C]102.346[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]5557.5[/C][C]52.8529[/C][C]105.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]5555.26[/C][C]50.839[/C][C]109.272[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]5555.56[/C][C]49.0294[/C][C]113.311[/C][/ROW]
[ROW][C]Median[/C][C]5500[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5600[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5571.43[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307395&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307395&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 Mean5613.89117.07447.9518
Geometric Mean5479
Harmonic Mean5338.27
Quadratic Mean5743.02
Winsorized Mean ( 1 / 36 )5615.74115.85348.4731
Winsorized Mean ( 2 / 36 )5619.44115.12848.8103
Winsorized Mean ( 3 / 36 )5616.67113.4449.5122
Winsorized Mean ( 4 / 36 )5624.07110.77250.7716
Winsorized Mean ( 5 / 36 )5624.07110.77250.7716
Winsorized Mean ( 6 / 36 )5618.52105.8253.095
Winsorized Mean ( 7 / 36 )5612.04104.64953.6273
Winsorized Mean ( 8 / 36 )5582.4199.764655.9558
Winsorized Mean ( 9 / 36 )5574.0798.5356.5724
Winsorized Mean ( 10 / 36 )5574.0798.5356.5724
Winsorized Mean ( 11 / 36 )5584.2696.943357.6034
Winsorized Mean ( 12 / 36 )5584.2693.674759.6133
Winsorized Mean ( 13 / 36 )5584.2693.674759.6133
Winsorized Mean ( 14 / 36 )5610.1986.416964.92
Winsorized Mean ( 15 / 36 )5610.1986.416964.92
Winsorized Mean ( 16 / 36 )5610.1986.416964.92
Winsorized Mean ( 17 / 36 )5625.9384.405166.6539
Winsorized Mean ( 18 / 36 )5625.9384.405166.6539
Winsorized Mean ( 19 / 36 )5625.9379.799170.5011
Winsorized Mean ( 20 / 36 )5607.4177.30272.5389
Winsorized Mean ( 21 / 36 )5607.4177.30272.5389
Winsorized Mean ( 22 / 36 )5607.4177.30272.5389
Winsorized Mean ( 23 / 36 )5607.4177.30272.5389
Winsorized Mean ( 24 / 36 )5585.1968.91181.0492
Winsorized Mean ( 25 / 36 )5585.1968.91181.0492
Winsorized Mean ( 26 / 36 )5585.1963.11788.4894
Winsorized Mean ( 27 / 36 )5585.1963.11788.4894
Winsorized Mean ( 28 / 36 )5611.1160.176593.2443
Winsorized Mean ( 29 / 36 )5611.1160.176593.2443
Winsorized Mean ( 30 / 36 )5583.3356.836298.2355
Winsorized Mean ( 31 / 36 )5583.3356.836298.2355
Winsorized Mean ( 32 / 36 )5553.753.4129103.977
Winsorized Mean ( 33 / 36 )5584.2649.9942111.698
Winsorized Mean ( 34 / 36 )5584.2649.9942111.698
Winsorized Mean ( 35 / 36 )5551.8546.3347119.821
Winsorized Mean ( 36 / 36 )5585.1942.7064130.781
Trimmed Mean ( 1 / 36 )5614.15112.78149.7792
Trimmed Mean ( 2 / 36 )5612.5109.32751.3369
Trimmed Mean ( 3 / 36 )5608.82105.86752.9801
Trimmed Mean ( 4 / 36 )5606102.67954.5971
Trimmed Mean ( 5 / 36 )5601.0299.973656.025
Trimmed Mean ( 6 / 36 )5595.8396.902957.7468
Trimmed Mean ( 7 / 36 )5591.4994.660259.0691
Trimmed Mean ( 8 / 36 )5588.0492.373360.4941
Trimmed Mean ( 9 / 36 )5588.8990.765261.5753
Trimmed Mean ( 10 / 36 )5590.9189.153662.7109
Trimmed Mean ( 11 / 36 )5593.0287.303364.0643
Trimmed Mean ( 12 / 36 )5594.0585.449665.466
Trimmed Mean ( 13 / 36 )5595.1283.849466.7282
Trimmed Mean ( 14 / 36 )5596.2581.993468.2524
Trimmed Mean ( 15 / 36 )5594.8780.951369.1141
Trimmed Mean ( 16 / 36 )5593.4279.721870.1618
Trimmed Mean ( 17 / 36 )5591.8978.271771.4421
Trimmed Mean ( 18 / 36 )5588.8976.8572.7246
Trimmed Mean ( 19 / 36 )5585.7175.161374.3164
Trimmed Mean ( 20 / 36 )5582.3573.836975.6038
Trimmed Mean ( 21 / 36 )5580.372.620676.8419
Trimmed Mean ( 22 / 36 )5578.1271.146778.4032
Trimmed Mean ( 23 / 36 )5575.8169.358580.3911
Trimmed Mean ( 24 / 36 )5573.3367.181682.9592
Trimmed Mean ( 25 / 36 )5572.4165.896684.563
Trimmed Mean ( 26 / 36 )5571.4364.300186.6472
Trimmed Mean ( 27 / 36 )5570.3763.258288.0576
Trimmed Mean ( 28 / 36 )5569.2361.928489.9301
Trimmed Mean ( 29 / 36 )556660.717591.6705
Trimmed Mean ( 30 / 36 )5562.559.147794.0443
Trimmed Mean ( 31 / 36 )5560.8757.77596.2504
Trimmed Mean ( 32 / 36 )5559.0955.967299.3277
Trimmed Mean ( 33 / 36 )5559.5254.3208102.346
Trimmed Mean ( 34 / 36 )5557.552.8529105.15
Trimmed Mean ( 35 / 36 )5555.2650.839109.272
Trimmed Mean ( 36 / 36 )5555.5649.0294113.311
Median5500
Midrange5600
Midmean - Weighted Average at Xnp5571.43
Midmean - Weighted Average at X(n+1)p5571.43
Midmean - Empirical Distribution Function5571.43
Midmean - Empirical Distribution Function - Averaging5571.43
Midmean - Empirical Distribution Function - Interpolation5571.43
Midmean - Closest Observation5571.43
Midmean - True Basic - Statistics Graphics Toolkit5571.43
Midmean - MS Excel (old versions)5571.43
Number of observations108



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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')