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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 13 Dec 2016 12:26:22 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/13/t14816284419s6cxpa1n9ls4cp.htm/, Retrieved Sat, 04 May 2024 20:51:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299068, Retrieved Sat, 04 May 2024 20:51:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendency] [2016-12-13 11:26:22] [afe7f6443461a2cd6ee0b843643e84a9] [Current]
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Dataseries X:
4028.8
4076.6
4125.8
4177.2
4183
4222.6
4255.8
4260.8
4279.2
4328.8
4356.6
4393
4419.4
4426.2
4467.2
4517.4
4517
4560.4
4589
4596
4621.2
4654.6
4708.6
4774.4
4824.8
4839
4869.8
4895.8
4895.8
4968.8
5010
5032.4
5054
5083.8
5117.4
5170.8
5182.2
5163.6
5212.6
5288
5303.4
5367.6
5433.8
5465.8
5493.8
5549.4
5590.2
5661.2
5699
5654.2
5671.8
5730.8
5693
5720.4
5747.8
5764.2
5783
5822.4
5836.2
5864.6
5913.4
5906.8
5954
6031.2
6011.2
6059.8
6091.6
6088
6082.2
6108
6151.4
6187
6190
6152.2
6183.8
6222.8
6165.8
6223.4
6292.8
6320.6
6344
6391.2
6443.4
6504
6520.2
6518.8
6563.8
6614
6555.6
6601.8
6632.4
6657.8
6674.4
6687
6697.6
6732
6736.4
6745.8
6805.2
6850.4
6807.2
6844.6
6850.8
6848.2
6837.8
6857.6
6900.8
6940.8
6937.4
6950.4
6978.8
6997.8
6934.8
6946.8
6956.2
6968.2




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299068&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299068&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299068&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean5725.6183.832668.2981
Geometric Mean5651.74
Harmonic Mean5575.18
Quadratic Mean5795.76
Winsorized Mean ( 1 / 38 )5725.8683.739668.377
Winsorized Mean ( 2 / 38 )5726.5383.572668.5215
Winsorized Mean ( 3 / 38 )5727.5483.314468.7461
Winsorized Mean ( 4 / 38 )5727.5483.256568.7939
Winsorized Mean ( 5 / 38 )5729.182.964369.055
Winsorized Mean ( 6 / 38 )5730.582.655969.3296
Winsorized Mean ( 7 / 38 )5730.682.583169.3919
Winsorized Mean ( 8 / 38 )5731.6982.364869.5891
Winsorized Mean ( 9 / 38 )5732.981.449370.3861
Winsorized Mean ( 10 / 38 )5731.5780.633671.0817
Winsorized Mean ( 11 / 38 )5734.3880.04871.6368
Winsorized Mean ( 12 / 38 )5737.0779.647572.0307
Winsorized Mean ( 13 / 38 )5737.5879.508172.1635
Winsorized Mean ( 14 / 38 )5742.178.752172.9136
Winsorized Mean ( 15 / 38 )5747.6677.748573.9263
Winsorized Mean ( 16 / 38 )5743.4977.230874.3679
Winsorized Mean ( 17 / 38 )5749.576.333875.3205
Winsorized Mean ( 18 / 38 )5744.7274.642576.9631
Winsorized Mean ( 19 / 38 )5744.3374.309277.3031
Winsorized Mean ( 20 / 38 )5747.9273.640178.0542
Winsorized Mean ( 21 / 38 )5747.7372.120879.6959
Winsorized Mean ( 22 / 38 )5755.9770.554381.582
Winsorized Mean ( 23 / 38 )5766.5168.604684.0544
Winsorized Mean ( 24 / 38 )5773.5166.91186.2864
Winsorized Mean ( 25 / 38 )5771.0965.908687.5621
Winsorized Mean ( 26 / 38 )5773.8764.596489.3838
Winsorized Mean ( 27 / 38 )5777.0863.542490.917
Winsorized Mean ( 28 / 38 )5767.9162.51792.2615
Winsorized Mean ( 29 / 38 )5784.1160.105396.233
Winsorized Mean ( 30 / 38 )5785.6157.8389100.03
Winsorized Mean ( 31 / 38 )5791.2257.1026101.418
Winsorized Mean ( 32 / 38 )5793.155.9645103.514
Winsorized Mean ( 33 / 38 )5784.3453.1087108.915
Winsorized Mean ( 34 / 38 )5778.8950.3462114.783
Winsorized Mean ( 35 / 38 )5778.5847.267122.254
Winsorized Mean ( 36 / 38 )5773.5646.2629124.799
Winsorized Mean ( 37 / 38 )5768.3344.9449128.342
Winsorized Mean ( 38 / 38 )5755.5541.5463138.533
Trimmed Mean ( 1 / 38 )5729.3483.237768.831
Trimmed Mean ( 2 / 38 )5732.9482.667469.3495
Trimmed Mean ( 3 / 38 )5736.3282.11669.8563
Trimmed Mean ( 4 / 38 )5739.4681.590870.3445
Trimmed Mean ( 5 / 38 )5742.7281.008370.8905
Trimmed Mean ( 6 / 38 )5745.7680.419371.4475
Trimmed Mean ( 7 / 38 )5748.6579.815172.0246
Trimmed Mean ( 8 / 38 )5751.6479.137272.6794
Trimmed Mean ( 9 / 38 )5754.5978.401873.3987
Trimmed Mean ( 10 / 38 )5757.577.717174.0828
Trimmed Mean ( 11 / 38 )5760.777.058974.7572
Trimmed Mean ( 12 / 38 )5763.7276.387475.4538
Trimmed Mean ( 13 / 38 )5766.5875.667776.2093
Trimmed Mean ( 14 / 38 )5769.5274.851677.0795
Trimmed Mean ( 15 / 38 )5772.1774.011877.9898
Trimmed Mean ( 16 / 38 )5774.4273.173878.9138
Trimmed Mean ( 17 / 38 )5777.1672.262479.9469
Trimmed Mean ( 18 / 38 )5779.5271.318781.0379
Trimmed Mean ( 19 / 38 )5782.3970.432482.0985
Trimmed Mean ( 20 / 38 )5785.4569.428483.3298
Trimmed Mean ( 21 / 38 )5788.3968.332484.7094
Trimmed Mean ( 22 / 38 )5791.5167.237686.1351
Trimmed Mean ( 23 / 38 )5794.1966.150787.5907
Trimmed Mean ( 24 / 38 )5796.2465.120789.0077
Trimmed Mean ( 25 / 38 )5797.9164.11490.4312
Trimmed Mean ( 26 / 38 )5799.8563.030292.017
Trimmed Mean ( 27 / 38 )5801.7261.898293.73
Trimmed Mean ( 28 / 38 )5803.4860.667995.6598
Trimmed Mean ( 29 / 38 )5806.0259.303797.9032
Trimmed Mean ( 30 / 38 )5807.5958.0081100.117
Trimmed Mean ( 31 / 38 )5807.5956.7582102.322
Trimmed Mean ( 32 / 38 )5810.4555.3097105.053
Trimmed Mean ( 33 / 38 )5811.7153.6793108.267
Trimmed Mean ( 34 / 38 )5813.7252.1289111.526
Trimmed Mean ( 35 / 38 )5816.350.6568114.818
Trimmed Mean ( 36 / 38 )5819.1449.3457117.926
Trimmed Mean ( 37 / 38 )5822.6447.8012121.809
Trimmed Mean ( 38 / 38 )5826.946.0125126.637
Median5829.3
Midrange5513.3
Midmean - Weighted Average at Xnp5775.68
Midmean - Weighted Average at X(n+1)p5806.02
Midmean - Empirical Distribution Function5775.68
Midmean - Empirical Distribution Function - Averaging5806.02
Midmean - Empirical Distribution Function - Interpolation5806.02
Midmean - Closest Observation5775.68
Midmean - True Basic - Statistics Graphics Toolkit5806.02
Midmean - MS Excel (old versions)5788.6
Number of observations116

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5725.61 & 83.8326 & 68.2981 \tabularnewline
Geometric Mean & 5651.74 &  &  \tabularnewline
Harmonic Mean & 5575.18 &  &  \tabularnewline
Quadratic Mean & 5795.76 &  &  \tabularnewline
Winsorized Mean ( 1 / 38 ) & 5725.86 & 83.7396 & 68.377 \tabularnewline
Winsorized Mean ( 2 / 38 ) & 5726.53 & 83.5726 & 68.5215 \tabularnewline
Winsorized Mean ( 3 / 38 ) & 5727.54 & 83.3144 & 68.7461 \tabularnewline
Winsorized Mean ( 4 / 38 ) & 5727.54 & 83.2565 & 68.7939 \tabularnewline
Winsorized Mean ( 5 / 38 ) & 5729.1 & 82.9643 & 69.055 \tabularnewline
Winsorized Mean ( 6 / 38 ) & 5730.5 & 82.6559 & 69.3296 \tabularnewline
Winsorized Mean ( 7 / 38 ) & 5730.6 & 82.5831 & 69.3919 \tabularnewline
Winsorized Mean ( 8 / 38 ) & 5731.69 & 82.3648 & 69.5891 \tabularnewline
Winsorized Mean ( 9 / 38 ) & 5732.9 & 81.4493 & 70.3861 \tabularnewline
Winsorized Mean ( 10 / 38 ) & 5731.57 & 80.6336 & 71.0817 \tabularnewline
Winsorized Mean ( 11 / 38 ) & 5734.38 & 80.048 & 71.6368 \tabularnewline
Winsorized Mean ( 12 / 38 ) & 5737.07 & 79.6475 & 72.0307 \tabularnewline
Winsorized Mean ( 13 / 38 ) & 5737.58 & 79.5081 & 72.1635 \tabularnewline
Winsorized Mean ( 14 / 38 ) & 5742.1 & 78.7521 & 72.9136 \tabularnewline
Winsorized Mean ( 15 / 38 ) & 5747.66 & 77.7485 & 73.9263 \tabularnewline
Winsorized Mean ( 16 / 38 ) & 5743.49 & 77.2308 & 74.3679 \tabularnewline
Winsorized Mean ( 17 / 38 ) & 5749.5 & 76.3338 & 75.3205 \tabularnewline
Winsorized Mean ( 18 / 38 ) & 5744.72 & 74.6425 & 76.9631 \tabularnewline
Winsorized Mean ( 19 / 38 ) & 5744.33 & 74.3092 & 77.3031 \tabularnewline
Winsorized Mean ( 20 / 38 ) & 5747.92 & 73.6401 & 78.0542 \tabularnewline
Winsorized Mean ( 21 / 38 ) & 5747.73 & 72.1208 & 79.6959 \tabularnewline
Winsorized Mean ( 22 / 38 ) & 5755.97 & 70.5543 & 81.582 \tabularnewline
Winsorized Mean ( 23 / 38 ) & 5766.51 & 68.6046 & 84.0544 \tabularnewline
Winsorized Mean ( 24 / 38 ) & 5773.51 & 66.911 & 86.2864 \tabularnewline
Winsorized Mean ( 25 / 38 ) & 5771.09 & 65.9086 & 87.5621 \tabularnewline
Winsorized Mean ( 26 / 38 ) & 5773.87 & 64.5964 & 89.3838 \tabularnewline
Winsorized Mean ( 27 / 38 ) & 5777.08 & 63.5424 & 90.917 \tabularnewline
Winsorized Mean ( 28 / 38 ) & 5767.91 & 62.517 & 92.2615 \tabularnewline
Winsorized Mean ( 29 / 38 ) & 5784.11 & 60.1053 & 96.233 \tabularnewline
Winsorized Mean ( 30 / 38 ) & 5785.61 & 57.8389 & 100.03 \tabularnewline
Winsorized Mean ( 31 / 38 ) & 5791.22 & 57.1026 & 101.418 \tabularnewline
Winsorized Mean ( 32 / 38 ) & 5793.1 & 55.9645 & 103.514 \tabularnewline
Winsorized Mean ( 33 / 38 ) & 5784.34 & 53.1087 & 108.915 \tabularnewline
Winsorized Mean ( 34 / 38 ) & 5778.89 & 50.3462 & 114.783 \tabularnewline
Winsorized Mean ( 35 / 38 ) & 5778.58 & 47.267 & 122.254 \tabularnewline
Winsorized Mean ( 36 / 38 ) & 5773.56 & 46.2629 & 124.799 \tabularnewline
Winsorized Mean ( 37 / 38 ) & 5768.33 & 44.9449 & 128.342 \tabularnewline
Winsorized Mean ( 38 / 38 ) & 5755.55 & 41.5463 & 138.533 \tabularnewline
Trimmed Mean ( 1 / 38 ) & 5729.34 & 83.2377 & 68.831 \tabularnewline
Trimmed Mean ( 2 / 38 ) & 5732.94 & 82.6674 & 69.3495 \tabularnewline
Trimmed Mean ( 3 / 38 ) & 5736.32 & 82.116 & 69.8563 \tabularnewline
Trimmed Mean ( 4 / 38 ) & 5739.46 & 81.5908 & 70.3445 \tabularnewline
Trimmed Mean ( 5 / 38 ) & 5742.72 & 81.0083 & 70.8905 \tabularnewline
Trimmed Mean ( 6 / 38 ) & 5745.76 & 80.4193 & 71.4475 \tabularnewline
Trimmed Mean ( 7 / 38 ) & 5748.65 & 79.8151 & 72.0246 \tabularnewline
Trimmed Mean ( 8 / 38 ) & 5751.64 & 79.1372 & 72.6794 \tabularnewline
Trimmed Mean ( 9 / 38 ) & 5754.59 & 78.4018 & 73.3987 \tabularnewline
Trimmed Mean ( 10 / 38 ) & 5757.5 & 77.7171 & 74.0828 \tabularnewline
Trimmed Mean ( 11 / 38 ) & 5760.7 & 77.0589 & 74.7572 \tabularnewline
Trimmed Mean ( 12 / 38 ) & 5763.72 & 76.3874 & 75.4538 \tabularnewline
Trimmed Mean ( 13 / 38 ) & 5766.58 & 75.6677 & 76.2093 \tabularnewline
Trimmed Mean ( 14 / 38 ) & 5769.52 & 74.8516 & 77.0795 \tabularnewline
Trimmed Mean ( 15 / 38 ) & 5772.17 & 74.0118 & 77.9898 \tabularnewline
Trimmed Mean ( 16 / 38 ) & 5774.42 & 73.1738 & 78.9138 \tabularnewline
Trimmed Mean ( 17 / 38 ) & 5777.16 & 72.2624 & 79.9469 \tabularnewline
Trimmed Mean ( 18 / 38 ) & 5779.52 & 71.3187 & 81.0379 \tabularnewline
Trimmed Mean ( 19 / 38 ) & 5782.39 & 70.4324 & 82.0985 \tabularnewline
Trimmed Mean ( 20 / 38 ) & 5785.45 & 69.4284 & 83.3298 \tabularnewline
Trimmed Mean ( 21 / 38 ) & 5788.39 & 68.3324 & 84.7094 \tabularnewline
Trimmed Mean ( 22 / 38 ) & 5791.51 & 67.2376 & 86.1351 \tabularnewline
Trimmed Mean ( 23 / 38 ) & 5794.19 & 66.1507 & 87.5907 \tabularnewline
Trimmed Mean ( 24 / 38 ) & 5796.24 & 65.1207 & 89.0077 \tabularnewline
Trimmed Mean ( 25 / 38 ) & 5797.91 & 64.114 & 90.4312 \tabularnewline
Trimmed Mean ( 26 / 38 ) & 5799.85 & 63.0302 & 92.017 \tabularnewline
Trimmed Mean ( 27 / 38 ) & 5801.72 & 61.8982 & 93.73 \tabularnewline
Trimmed Mean ( 28 / 38 ) & 5803.48 & 60.6679 & 95.6598 \tabularnewline
Trimmed Mean ( 29 / 38 ) & 5806.02 & 59.3037 & 97.9032 \tabularnewline
Trimmed Mean ( 30 / 38 ) & 5807.59 & 58.0081 & 100.117 \tabularnewline
Trimmed Mean ( 31 / 38 ) & 5807.59 & 56.7582 & 102.322 \tabularnewline
Trimmed Mean ( 32 / 38 ) & 5810.45 & 55.3097 & 105.053 \tabularnewline
Trimmed Mean ( 33 / 38 ) & 5811.71 & 53.6793 & 108.267 \tabularnewline
Trimmed Mean ( 34 / 38 ) & 5813.72 & 52.1289 & 111.526 \tabularnewline
Trimmed Mean ( 35 / 38 ) & 5816.3 & 50.6568 & 114.818 \tabularnewline
Trimmed Mean ( 36 / 38 ) & 5819.14 & 49.3457 & 117.926 \tabularnewline
Trimmed Mean ( 37 / 38 ) & 5822.64 & 47.8012 & 121.809 \tabularnewline
Trimmed Mean ( 38 / 38 ) & 5826.9 & 46.0125 & 126.637 \tabularnewline
Median & 5829.3 &  &  \tabularnewline
Midrange & 5513.3 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5775.68 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5806.02 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5775.68 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5806.02 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5806.02 &  &  \tabularnewline
Midmean - Closest Observation & 5775.68 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5806.02 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5788.6 &  &  \tabularnewline
Number of observations & 116 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299068&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]5725.61[/C][C]83.8326[/C][C]68.2981[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5651.74[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5575.18[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5795.76[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 38 )[/C][C]5725.86[/C][C]83.7396[/C][C]68.377[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 38 )[/C][C]5726.53[/C][C]83.5726[/C][C]68.5215[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 38 )[/C][C]5727.54[/C][C]83.3144[/C][C]68.7461[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 38 )[/C][C]5727.54[/C][C]83.2565[/C][C]68.7939[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 38 )[/C][C]5729.1[/C][C]82.9643[/C][C]69.055[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 38 )[/C][C]5730.5[/C][C]82.6559[/C][C]69.3296[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 38 )[/C][C]5730.6[/C][C]82.5831[/C][C]69.3919[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 38 )[/C][C]5731.69[/C][C]82.3648[/C][C]69.5891[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 38 )[/C][C]5732.9[/C][C]81.4493[/C][C]70.3861[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 38 )[/C][C]5731.57[/C][C]80.6336[/C][C]71.0817[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 38 )[/C][C]5734.38[/C][C]80.048[/C][C]71.6368[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 38 )[/C][C]5737.07[/C][C]79.6475[/C][C]72.0307[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 38 )[/C][C]5737.58[/C][C]79.5081[/C][C]72.1635[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 38 )[/C][C]5742.1[/C][C]78.7521[/C][C]72.9136[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 38 )[/C][C]5747.66[/C][C]77.7485[/C][C]73.9263[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 38 )[/C][C]5743.49[/C][C]77.2308[/C][C]74.3679[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 38 )[/C][C]5749.5[/C][C]76.3338[/C][C]75.3205[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 38 )[/C][C]5744.72[/C][C]74.6425[/C][C]76.9631[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 38 )[/C][C]5744.33[/C][C]74.3092[/C][C]77.3031[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 38 )[/C][C]5747.92[/C][C]73.6401[/C][C]78.0542[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 38 )[/C][C]5747.73[/C][C]72.1208[/C][C]79.6959[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 38 )[/C][C]5755.97[/C][C]70.5543[/C][C]81.582[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 38 )[/C][C]5766.51[/C][C]68.6046[/C][C]84.0544[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 38 )[/C][C]5773.51[/C][C]66.911[/C][C]86.2864[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 38 )[/C][C]5771.09[/C][C]65.9086[/C][C]87.5621[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 38 )[/C][C]5773.87[/C][C]64.5964[/C][C]89.3838[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 38 )[/C][C]5777.08[/C][C]63.5424[/C][C]90.917[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 38 )[/C][C]5767.91[/C][C]62.517[/C][C]92.2615[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 38 )[/C][C]5784.11[/C][C]60.1053[/C][C]96.233[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 38 )[/C][C]5785.61[/C][C]57.8389[/C][C]100.03[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 38 )[/C][C]5791.22[/C][C]57.1026[/C][C]101.418[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 38 )[/C][C]5793.1[/C][C]55.9645[/C][C]103.514[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 38 )[/C][C]5784.34[/C][C]53.1087[/C][C]108.915[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 38 )[/C][C]5778.89[/C][C]50.3462[/C][C]114.783[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 38 )[/C][C]5778.58[/C][C]47.267[/C][C]122.254[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 38 )[/C][C]5773.56[/C][C]46.2629[/C][C]124.799[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 38 )[/C][C]5768.33[/C][C]44.9449[/C][C]128.342[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 38 )[/C][C]5755.55[/C][C]41.5463[/C][C]138.533[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 38 )[/C][C]5729.34[/C][C]83.2377[/C][C]68.831[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 38 )[/C][C]5732.94[/C][C]82.6674[/C][C]69.3495[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 38 )[/C][C]5736.32[/C][C]82.116[/C][C]69.8563[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 38 )[/C][C]5739.46[/C][C]81.5908[/C][C]70.3445[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 38 )[/C][C]5742.72[/C][C]81.0083[/C][C]70.8905[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 38 )[/C][C]5745.76[/C][C]80.4193[/C][C]71.4475[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 38 )[/C][C]5748.65[/C][C]79.8151[/C][C]72.0246[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 38 )[/C][C]5751.64[/C][C]79.1372[/C][C]72.6794[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 38 )[/C][C]5754.59[/C][C]78.4018[/C][C]73.3987[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 38 )[/C][C]5757.5[/C][C]77.7171[/C][C]74.0828[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 38 )[/C][C]5760.7[/C][C]77.0589[/C][C]74.7572[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 38 )[/C][C]5763.72[/C][C]76.3874[/C][C]75.4538[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 38 )[/C][C]5766.58[/C][C]75.6677[/C][C]76.2093[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 38 )[/C][C]5769.52[/C][C]74.8516[/C][C]77.0795[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 38 )[/C][C]5772.17[/C][C]74.0118[/C][C]77.9898[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 38 )[/C][C]5774.42[/C][C]73.1738[/C][C]78.9138[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 38 )[/C][C]5777.16[/C][C]72.2624[/C][C]79.9469[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 38 )[/C][C]5779.52[/C][C]71.3187[/C][C]81.0379[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 38 )[/C][C]5782.39[/C][C]70.4324[/C][C]82.0985[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 38 )[/C][C]5785.45[/C][C]69.4284[/C][C]83.3298[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 38 )[/C][C]5788.39[/C][C]68.3324[/C][C]84.7094[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 38 )[/C][C]5791.51[/C][C]67.2376[/C][C]86.1351[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 38 )[/C][C]5794.19[/C][C]66.1507[/C][C]87.5907[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 38 )[/C][C]5796.24[/C][C]65.1207[/C][C]89.0077[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 38 )[/C][C]5797.91[/C][C]64.114[/C][C]90.4312[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 38 )[/C][C]5799.85[/C][C]63.0302[/C][C]92.017[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 38 )[/C][C]5801.72[/C][C]61.8982[/C][C]93.73[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 38 )[/C][C]5803.48[/C][C]60.6679[/C][C]95.6598[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 38 )[/C][C]5806.02[/C][C]59.3037[/C][C]97.9032[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 38 )[/C][C]5807.59[/C][C]58.0081[/C][C]100.117[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 38 )[/C][C]5807.59[/C][C]56.7582[/C][C]102.322[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 38 )[/C][C]5810.45[/C][C]55.3097[/C][C]105.053[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 38 )[/C][C]5811.71[/C][C]53.6793[/C][C]108.267[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 38 )[/C][C]5813.72[/C][C]52.1289[/C][C]111.526[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 38 )[/C][C]5816.3[/C][C]50.6568[/C][C]114.818[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 38 )[/C][C]5819.14[/C][C]49.3457[/C][C]117.926[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 38 )[/C][C]5822.64[/C][C]47.8012[/C][C]121.809[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 38 )[/C][C]5826.9[/C][C]46.0125[/C][C]126.637[/C][/ROW]
[ROW][C]Median[/C][C]5829.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5513.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5775.68[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5806.02[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5775.68[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5806.02[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5806.02[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5775.68[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5806.02[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5788.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]116[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299068&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299068&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 Mean5725.6183.832668.2981
Geometric Mean5651.74
Harmonic Mean5575.18
Quadratic Mean5795.76
Winsorized Mean ( 1 / 38 )5725.8683.739668.377
Winsorized Mean ( 2 / 38 )5726.5383.572668.5215
Winsorized Mean ( 3 / 38 )5727.5483.314468.7461
Winsorized Mean ( 4 / 38 )5727.5483.256568.7939
Winsorized Mean ( 5 / 38 )5729.182.964369.055
Winsorized Mean ( 6 / 38 )5730.582.655969.3296
Winsorized Mean ( 7 / 38 )5730.682.583169.3919
Winsorized Mean ( 8 / 38 )5731.6982.364869.5891
Winsorized Mean ( 9 / 38 )5732.981.449370.3861
Winsorized Mean ( 10 / 38 )5731.5780.633671.0817
Winsorized Mean ( 11 / 38 )5734.3880.04871.6368
Winsorized Mean ( 12 / 38 )5737.0779.647572.0307
Winsorized Mean ( 13 / 38 )5737.5879.508172.1635
Winsorized Mean ( 14 / 38 )5742.178.752172.9136
Winsorized Mean ( 15 / 38 )5747.6677.748573.9263
Winsorized Mean ( 16 / 38 )5743.4977.230874.3679
Winsorized Mean ( 17 / 38 )5749.576.333875.3205
Winsorized Mean ( 18 / 38 )5744.7274.642576.9631
Winsorized Mean ( 19 / 38 )5744.3374.309277.3031
Winsorized Mean ( 20 / 38 )5747.9273.640178.0542
Winsorized Mean ( 21 / 38 )5747.7372.120879.6959
Winsorized Mean ( 22 / 38 )5755.9770.554381.582
Winsorized Mean ( 23 / 38 )5766.5168.604684.0544
Winsorized Mean ( 24 / 38 )5773.5166.91186.2864
Winsorized Mean ( 25 / 38 )5771.0965.908687.5621
Winsorized Mean ( 26 / 38 )5773.8764.596489.3838
Winsorized Mean ( 27 / 38 )5777.0863.542490.917
Winsorized Mean ( 28 / 38 )5767.9162.51792.2615
Winsorized Mean ( 29 / 38 )5784.1160.105396.233
Winsorized Mean ( 30 / 38 )5785.6157.8389100.03
Winsorized Mean ( 31 / 38 )5791.2257.1026101.418
Winsorized Mean ( 32 / 38 )5793.155.9645103.514
Winsorized Mean ( 33 / 38 )5784.3453.1087108.915
Winsorized Mean ( 34 / 38 )5778.8950.3462114.783
Winsorized Mean ( 35 / 38 )5778.5847.267122.254
Winsorized Mean ( 36 / 38 )5773.5646.2629124.799
Winsorized Mean ( 37 / 38 )5768.3344.9449128.342
Winsorized Mean ( 38 / 38 )5755.5541.5463138.533
Trimmed Mean ( 1 / 38 )5729.3483.237768.831
Trimmed Mean ( 2 / 38 )5732.9482.667469.3495
Trimmed Mean ( 3 / 38 )5736.3282.11669.8563
Trimmed Mean ( 4 / 38 )5739.4681.590870.3445
Trimmed Mean ( 5 / 38 )5742.7281.008370.8905
Trimmed Mean ( 6 / 38 )5745.7680.419371.4475
Trimmed Mean ( 7 / 38 )5748.6579.815172.0246
Trimmed Mean ( 8 / 38 )5751.6479.137272.6794
Trimmed Mean ( 9 / 38 )5754.5978.401873.3987
Trimmed Mean ( 10 / 38 )5757.577.717174.0828
Trimmed Mean ( 11 / 38 )5760.777.058974.7572
Trimmed Mean ( 12 / 38 )5763.7276.387475.4538
Trimmed Mean ( 13 / 38 )5766.5875.667776.2093
Trimmed Mean ( 14 / 38 )5769.5274.851677.0795
Trimmed Mean ( 15 / 38 )5772.1774.011877.9898
Trimmed Mean ( 16 / 38 )5774.4273.173878.9138
Trimmed Mean ( 17 / 38 )5777.1672.262479.9469
Trimmed Mean ( 18 / 38 )5779.5271.318781.0379
Trimmed Mean ( 19 / 38 )5782.3970.432482.0985
Trimmed Mean ( 20 / 38 )5785.4569.428483.3298
Trimmed Mean ( 21 / 38 )5788.3968.332484.7094
Trimmed Mean ( 22 / 38 )5791.5167.237686.1351
Trimmed Mean ( 23 / 38 )5794.1966.150787.5907
Trimmed Mean ( 24 / 38 )5796.2465.120789.0077
Trimmed Mean ( 25 / 38 )5797.9164.11490.4312
Trimmed Mean ( 26 / 38 )5799.8563.030292.017
Trimmed Mean ( 27 / 38 )5801.7261.898293.73
Trimmed Mean ( 28 / 38 )5803.4860.667995.6598
Trimmed Mean ( 29 / 38 )5806.0259.303797.9032
Trimmed Mean ( 30 / 38 )5807.5958.0081100.117
Trimmed Mean ( 31 / 38 )5807.5956.7582102.322
Trimmed Mean ( 32 / 38 )5810.4555.3097105.053
Trimmed Mean ( 33 / 38 )5811.7153.6793108.267
Trimmed Mean ( 34 / 38 )5813.7252.1289111.526
Trimmed Mean ( 35 / 38 )5816.350.6568114.818
Trimmed Mean ( 36 / 38 )5819.1449.3457117.926
Trimmed Mean ( 37 / 38 )5822.6447.8012121.809
Trimmed Mean ( 38 / 38 )5826.946.0125126.637
Median5829.3
Midrange5513.3
Midmean - Weighted Average at Xnp5775.68
Midmean - Weighted Average at X(n+1)p5806.02
Midmean - Empirical Distribution Function5775.68
Midmean - Empirical Distribution Function - Averaging5806.02
Midmean - Empirical Distribution Function - Interpolation5806.02
Midmean - Closest Observation5775.68
Midmean - True Basic - Statistics Graphics Toolkit5806.02
Midmean - MS Excel (old versions)5788.6
Number of observations116



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')