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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 computationThu, 08 Dec 2016 21:11:19 +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/08/t1481227944usp9teabynlvwdm.htm/, Retrieved Sun, 28 Apr 2024 12:40:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298383, Retrieved Sun, 28 Apr 2024 12:40:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central tendency ...] [2016-12-08 20:11:19] [c0b73e623858a81821526bb2f691ccd9] [Current]
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Dataseries X:
3300
4100
3550
3650
3400
4050
2950
3300
3950
3950
3900
3700
3850
4350
4350
3550
3800
4150
3500
3850
4250
4150
4200
4100
4200
4350
4150
4200
3850
4100
3800
4250
4400
4400
4450
4050
4100
4450
4600
4100
4300
4850
3800
4450
4800
4900
4900
4350
4500
5050
5150
4450
4900
5450
4100
5050
5550
5450
5500
4950
5400
5750
5950
5950
5750
6450
5000
5950
6250
6300
6400
5700
5750
6450
6500
5950
6200
6750
5300
6450
6900
6800
6750
6050
6100
7400
7300
6200
6550
7500
5400
6750
7400
7450
7200
6500
7150
8000
7000
7600
7100
8050
5700
7550
7800
7800
8250
7150
7350
7800
8250
7500
8150
8550




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=298383&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=298383&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298383&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 Mean5447.37135.71840.1373
Geometric Mean5259.76
Harmonic Mean5079.96
Quadratic Mean5635.18
Winsorized Mean ( 1 / 38 )5447.81134.74340.431
Winsorized Mean ( 2 / 38 )5447.81134.74340.431
Winsorized Mean ( 3 / 38 )5447.81133.90240.6849
Winsorized Mean ( 4 / 38 )5447.81132.8241.0166
Winsorized Mean ( 5 / 38 )5447.81132.1641.2212
Winsorized Mean ( 6 / 38 )5437.28130.41741.6916
Winsorized Mean ( 7 / 38 )5443.42129.64841.9862
Winsorized Mean ( 8 / 38 )5446.93129.22342.1514
Winsorized Mean ( 9 / 38 )5439.04125.82243.2278
Winsorized Mean ( 10 / 38 )5434.65125.16143.4212
Winsorized Mean ( 11 / 38 )5429.82124.44543.6322
Winsorized Mean ( 12 / 38 )5435.09123.84243.8872
Winsorized Mean ( 13 / 38 )5429.39123.00744.1388
Winsorized Mean ( 14 / 38 )5423.25122.12144.4088
Winsorized Mean ( 15 / 38 )5429.82121.37944.7345
Winsorized Mean ( 16 / 38 )5429.82119.60145.3996
Winsorized Mean ( 17 / 38 )5422.37118.54945.7397
Winsorized Mean ( 18 / 38 )5422.37114.65447.2934
Winsorized Mean ( 19 / 38 )5414.04113.51847.6931
Winsorized Mean ( 20 / 38 )5422.81112.59648.1617
Winsorized Mean ( 21 / 38 )5413.6111.35348.6163
Winsorized Mean ( 22 / 38 )5394.3108.849.5801
Winsorized Mean ( 23 / 38 )5374.12106.19950.6043
Winsorized Mean ( 24 / 38 )5353.07103.55951.6912
Winsorized Mean ( 25 / 38 )5342.11102.21252.2648
Winsorized Mean ( 26 / 38 )5353.51100.99853.0062
Winsorized Mean ( 27 / 38 )5353.51100.99853.0062
Winsorized Mean ( 28 / 38 )5304.3995.14255.7523
Winsorized Mean ( 29 / 38 )5304.3992.319957.4566
Winsorized Mean ( 30 / 38 )5304.3992.319957.4566
Winsorized Mean ( 31 / 38 )5290.7990.772458.2863
Winsorized Mean ( 32 / 38 )5304.8289.292459.4096
Winsorized Mean ( 33 / 38 )5304.8289.292459.4096
Winsorized Mean ( 34 / 38 )5304.8286.056261.6437
Winsorized Mean ( 35 / 38 )5289.4781.05265.2602
Winsorized Mean ( 36 / 38 )5273.6879.320966.4854
Winsorized Mean ( 37 / 38 )5257.4677.564467.7818
Winsorized Mean ( 38 / 38 )5257.4677.564467.7818
Trimmed Mean ( 1 / 38 )5441.96133.45440.7779
Trimmed Mean ( 2 / 38 )5435.91132.00741.179
Trimmed Mean ( 3 / 38 )5429.63130.38341.6436
Trimmed Mean ( 4 / 38 )5423.11128.942.0724
Trimmed Mean ( 5 / 38 )5416.35127.56842.4586
Trimmed Mean ( 6 / 38 )5409.31126.23242.852
Trimmed Mean ( 7 / 38 )5404125.11943.1907
Trimmed Mean ( 8 / 38 )5397.45123.99943.5282
Trimmed Mean ( 9 / 38 )5390.1122.78943.8974
Trimmed Mean ( 10 / 38 )5383.51121.98644.1321
Trimmed Mean ( 11 / 38 )5377.17121.15244.3838
Trimmed Mean ( 12 / 38 )5371.11120.28144.6547
Trimmed Mean ( 13 / 38 )5364.2119.33944.9494
Trimmed Mean ( 14 / 38 )5357.56118.34945.2691
Trimmed Mean ( 15 / 38 )5351.19117.30645.6173
Trimmed Mean ( 16 / 38 )5343.9116.16746.002
Trimmed Mean ( 17 / 38 )5336.25115.05446.3806
Trimmed Mean ( 18 / 38 )5328.85113.87146.7972
Trimmed Mean ( 19 / 38 )5321.05112.96447.1042
Trimmed Mean ( 20 / 38 )5313.51112.00747.439
Trimmed Mean ( 21 / 38 )5304.86110.94347.8159
Trimmed Mean ( 22 / 38 )5296.43109.8148.2325
Trimmed Mean ( 23 / 38 )5288.97108.77348.6241
Trimmed Mean ( 24 / 38 )5282.58107.84248.9843
Trimmed Mean ( 25 / 38 )5277.34107.03249.3064
Trimmed Mean ( 26 / 38 )5272.58106.17349.6603
Trimmed Mean ( 27 / 38 )5266.67105.21550.0563
Trimmed Mean ( 28 / 38 )5260.34103.97350.5936
Trimmed Mean ( 29 / 38 )5257.14103.26250.9107
Trimmed Mean ( 30 / 38 )5253.7102.68851.1618
Trimmed Mean ( 31 / 38 )5250101.85951.542
Trimmed Mean ( 32 / 38 )5247100.95951.9717
Trimmed Mean ( 33 / 38 )5242.7199.933452.462
Trimmed Mean ( 34 / 38 )5238.0498.505653.1751
Trimmed Mean ( 35 / 38 )5232.9597.14453.868
Trimmed Mean ( 36 / 38 )5228.5796.198754.3518
Trimmed Mean ( 37 / 38 )522595.138254.9201
Trimmed Mean ( 38 / 38 )5222.3793.924655.6017
Median5225
Midrange5750
Midmean - Weighted Average at Xnp5200.85
Midmean - Weighted Average at X(n+1)p5223.33
Midmean - Empirical Distribution Function5223.33
Midmean - Empirical Distribution Function - Averaging5223.33
Midmean - Empirical Distribution Function - Interpolation5257.14
Midmean - Closest Observation5223.33
Midmean - True Basic - Statistics Graphics Toolkit5223.33
Midmean - MS Excel (old versions)5223.33
Number of observations114

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5447.37 & 135.718 & 40.1373 \tabularnewline
Geometric Mean & 5259.76 &  &  \tabularnewline
Harmonic Mean & 5079.96 &  &  \tabularnewline
Quadratic Mean & 5635.18 &  &  \tabularnewline
Winsorized Mean ( 1 / 38 ) & 5447.81 & 134.743 & 40.431 \tabularnewline
Winsorized Mean ( 2 / 38 ) & 5447.81 & 134.743 & 40.431 \tabularnewline
Winsorized Mean ( 3 / 38 ) & 5447.81 & 133.902 & 40.6849 \tabularnewline
Winsorized Mean ( 4 / 38 ) & 5447.81 & 132.82 & 41.0166 \tabularnewline
Winsorized Mean ( 5 / 38 ) & 5447.81 & 132.16 & 41.2212 \tabularnewline
Winsorized Mean ( 6 / 38 ) & 5437.28 & 130.417 & 41.6916 \tabularnewline
Winsorized Mean ( 7 / 38 ) & 5443.42 & 129.648 & 41.9862 \tabularnewline
Winsorized Mean ( 8 / 38 ) & 5446.93 & 129.223 & 42.1514 \tabularnewline
Winsorized Mean ( 9 / 38 ) & 5439.04 & 125.822 & 43.2278 \tabularnewline
Winsorized Mean ( 10 / 38 ) & 5434.65 & 125.161 & 43.4212 \tabularnewline
Winsorized Mean ( 11 / 38 ) & 5429.82 & 124.445 & 43.6322 \tabularnewline
Winsorized Mean ( 12 / 38 ) & 5435.09 & 123.842 & 43.8872 \tabularnewline
Winsorized Mean ( 13 / 38 ) & 5429.39 & 123.007 & 44.1388 \tabularnewline
Winsorized Mean ( 14 / 38 ) & 5423.25 & 122.121 & 44.4088 \tabularnewline
Winsorized Mean ( 15 / 38 ) & 5429.82 & 121.379 & 44.7345 \tabularnewline
Winsorized Mean ( 16 / 38 ) & 5429.82 & 119.601 & 45.3996 \tabularnewline
Winsorized Mean ( 17 / 38 ) & 5422.37 & 118.549 & 45.7397 \tabularnewline
Winsorized Mean ( 18 / 38 ) & 5422.37 & 114.654 & 47.2934 \tabularnewline
Winsorized Mean ( 19 / 38 ) & 5414.04 & 113.518 & 47.6931 \tabularnewline
Winsorized Mean ( 20 / 38 ) & 5422.81 & 112.596 & 48.1617 \tabularnewline
Winsorized Mean ( 21 / 38 ) & 5413.6 & 111.353 & 48.6163 \tabularnewline
Winsorized Mean ( 22 / 38 ) & 5394.3 & 108.8 & 49.5801 \tabularnewline
Winsorized Mean ( 23 / 38 ) & 5374.12 & 106.199 & 50.6043 \tabularnewline
Winsorized Mean ( 24 / 38 ) & 5353.07 & 103.559 & 51.6912 \tabularnewline
Winsorized Mean ( 25 / 38 ) & 5342.11 & 102.212 & 52.2648 \tabularnewline
Winsorized Mean ( 26 / 38 ) & 5353.51 & 100.998 & 53.0062 \tabularnewline
Winsorized Mean ( 27 / 38 ) & 5353.51 & 100.998 & 53.0062 \tabularnewline
Winsorized Mean ( 28 / 38 ) & 5304.39 & 95.142 & 55.7523 \tabularnewline
Winsorized Mean ( 29 / 38 ) & 5304.39 & 92.3199 & 57.4566 \tabularnewline
Winsorized Mean ( 30 / 38 ) & 5304.39 & 92.3199 & 57.4566 \tabularnewline
Winsorized Mean ( 31 / 38 ) & 5290.79 & 90.7724 & 58.2863 \tabularnewline
Winsorized Mean ( 32 / 38 ) & 5304.82 & 89.2924 & 59.4096 \tabularnewline
Winsorized Mean ( 33 / 38 ) & 5304.82 & 89.2924 & 59.4096 \tabularnewline
Winsorized Mean ( 34 / 38 ) & 5304.82 & 86.0562 & 61.6437 \tabularnewline
Winsorized Mean ( 35 / 38 ) & 5289.47 & 81.052 & 65.2602 \tabularnewline
Winsorized Mean ( 36 / 38 ) & 5273.68 & 79.3209 & 66.4854 \tabularnewline
Winsorized Mean ( 37 / 38 ) & 5257.46 & 77.5644 & 67.7818 \tabularnewline
Winsorized Mean ( 38 / 38 ) & 5257.46 & 77.5644 & 67.7818 \tabularnewline
Trimmed Mean ( 1 / 38 ) & 5441.96 & 133.454 & 40.7779 \tabularnewline
Trimmed Mean ( 2 / 38 ) & 5435.91 & 132.007 & 41.179 \tabularnewline
Trimmed Mean ( 3 / 38 ) & 5429.63 & 130.383 & 41.6436 \tabularnewline
Trimmed Mean ( 4 / 38 ) & 5423.11 & 128.9 & 42.0724 \tabularnewline
Trimmed Mean ( 5 / 38 ) & 5416.35 & 127.568 & 42.4586 \tabularnewline
Trimmed Mean ( 6 / 38 ) & 5409.31 & 126.232 & 42.852 \tabularnewline
Trimmed Mean ( 7 / 38 ) & 5404 & 125.119 & 43.1907 \tabularnewline
Trimmed Mean ( 8 / 38 ) & 5397.45 & 123.999 & 43.5282 \tabularnewline
Trimmed Mean ( 9 / 38 ) & 5390.1 & 122.789 & 43.8974 \tabularnewline
Trimmed Mean ( 10 / 38 ) & 5383.51 & 121.986 & 44.1321 \tabularnewline
Trimmed Mean ( 11 / 38 ) & 5377.17 & 121.152 & 44.3838 \tabularnewline
Trimmed Mean ( 12 / 38 ) & 5371.11 & 120.281 & 44.6547 \tabularnewline
Trimmed Mean ( 13 / 38 ) & 5364.2 & 119.339 & 44.9494 \tabularnewline
Trimmed Mean ( 14 / 38 ) & 5357.56 & 118.349 & 45.2691 \tabularnewline
Trimmed Mean ( 15 / 38 ) & 5351.19 & 117.306 & 45.6173 \tabularnewline
Trimmed Mean ( 16 / 38 ) & 5343.9 & 116.167 & 46.002 \tabularnewline
Trimmed Mean ( 17 / 38 ) & 5336.25 & 115.054 & 46.3806 \tabularnewline
Trimmed Mean ( 18 / 38 ) & 5328.85 & 113.871 & 46.7972 \tabularnewline
Trimmed Mean ( 19 / 38 ) & 5321.05 & 112.964 & 47.1042 \tabularnewline
Trimmed Mean ( 20 / 38 ) & 5313.51 & 112.007 & 47.439 \tabularnewline
Trimmed Mean ( 21 / 38 ) & 5304.86 & 110.943 & 47.8159 \tabularnewline
Trimmed Mean ( 22 / 38 ) & 5296.43 & 109.81 & 48.2325 \tabularnewline
Trimmed Mean ( 23 / 38 ) & 5288.97 & 108.773 & 48.6241 \tabularnewline
Trimmed Mean ( 24 / 38 ) & 5282.58 & 107.842 & 48.9843 \tabularnewline
Trimmed Mean ( 25 / 38 ) & 5277.34 & 107.032 & 49.3064 \tabularnewline
Trimmed Mean ( 26 / 38 ) & 5272.58 & 106.173 & 49.6603 \tabularnewline
Trimmed Mean ( 27 / 38 ) & 5266.67 & 105.215 & 50.0563 \tabularnewline
Trimmed Mean ( 28 / 38 ) & 5260.34 & 103.973 & 50.5936 \tabularnewline
Trimmed Mean ( 29 / 38 ) & 5257.14 & 103.262 & 50.9107 \tabularnewline
Trimmed Mean ( 30 / 38 ) & 5253.7 & 102.688 & 51.1618 \tabularnewline
Trimmed Mean ( 31 / 38 ) & 5250 & 101.859 & 51.542 \tabularnewline
Trimmed Mean ( 32 / 38 ) & 5247 & 100.959 & 51.9717 \tabularnewline
Trimmed Mean ( 33 / 38 ) & 5242.71 & 99.9334 & 52.462 \tabularnewline
Trimmed Mean ( 34 / 38 ) & 5238.04 & 98.5056 & 53.1751 \tabularnewline
Trimmed Mean ( 35 / 38 ) & 5232.95 & 97.144 & 53.868 \tabularnewline
Trimmed Mean ( 36 / 38 ) & 5228.57 & 96.1987 & 54.3518 \tabularnewline
Trimmed Mean ( 37 / 38 ) & 5225 & 95.1382 & 54.9201 \tabularnewline
Trimmed Mean ( 38 / 38 ) & 5222.37 & 93.9246 & 55.6017 \tabularnewline
Median & 5225 &  &  \tabularnewline
Midrange & 5750 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5200.85 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5223.33 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5223.33 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5223.33 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5257.14 &  &  \tabularnewline
Midmean - Closest Observation & 5223.33 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5223.33 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5223.33 &  &  \tabularnewline
Number of observations & 114 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298383&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]5447.37[/C][C]135.718[/C][C]40.1373[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5259.76[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5079.96[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5635.18[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 38 )[/C][C]5447.81[/C][C]134.743[/C][C]40.431[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 38 )[/C][C]5447.81[/C][C]134.743[/C][C]40.431[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 38 )[/C][C]5447.81[/C][C]133.902[/C][C]40.6849[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 38 )[/C][C]5447.81[/C][C]132.82[/C][C]41.0166[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 38 )[/C][C]5447.81[/C][C]132.16[/C][C]41.2212[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 38 )[/C][C]5437.28[/C][C]130.417[/C][C]41.6916[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 38 )[/C][C]5443.42[/C][C]129.648[/C][C]41.9862[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 38 )[/C][C]5446.93[/C][C]129.223[/C][C]42.1514[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 38 )[/C][C]5439.04[/C][C]125.822[/C][C]43.2278[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 38 )[/C][C]5434.65[/C][C]125.161[/C][C]43.4212[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 38 )[/C][C]5429.82[/C][C]124.445[/C][C]43.6322[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 38 )[/C][C]5435.09[/C][C]123.842[/C][C]43.8872[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 38 )[/C][C]5429.39[/C][C]123.007[/C][C]44.1388[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 38 )[/C][C]5423.25[/C][C]122.121[/C][C]44.4088[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 38 )[/C][C]5429.82[/C][C]121.379[/C][C]44.7345[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 38 )[/C][C]5429.82[/C][C]119.601[/C][C]45.3996[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 38 )[/C][C]5422.37[/C][C]118.549[/C][C]45.7397[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 38 )[/C][C]5422.37[/C][C]114.654[/C][C]47.2934[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 38 )[/C][C]5414.04[/C][C]113.518[/C][C]47.6931[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 38 )[/C][C]5422.81[/C][C]112.596[/C][C]48.1617[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 38 )[/C][C]5413.6[/C][C]111.353[/C][C]48.6163[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 38 )[/C][C]5394.3[/C][C]108.8[/C][C]49.5801[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 38 )[/C][C]5374.12[/C][C]106.199[/C][C]50.6043[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 38 )[/C][C]5353.07[/C][C]103.559[/C][C]51.6912[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 38 )[/C][C]5342.11[/C][C]102.212[/C][C]52.2648[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 38 )[/C][C]5353.51[/C][C]100.998[/C][C]53.0062[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 38 )[/C][C]5353.51[/C][C]100.998[/C][C]53.0062[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 38 )[/C][C]5304.39[/C][C]95.142[/C][C]55.7523[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 38 )[/C][C]5304.39[/C][C]92.3199[/C][C]57.4566[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 38 )[/C][C]5304.39[/C][C]92.3199[/C][C]57.4566[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 38 )[/C][C]5290.79[/C][C]90.7724[/C][C]58.2863[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 38 )[/C][C]5304.82[/C][C]89.2924[/C][C]59.4096[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 38 )[/C][C]5304.82[/C][C]89.2924[/C][C]59.4096[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 38 )[/C][C]5304.82[/C][C]86.0562[/C][C]61.6437[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 38 )[/C][C]5289.47[/C][C]81.052[/C][C]65.2602[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 38 )[/C][C]5273.68[/C][C]79.3209[/C][C]66.4854[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 38 )[/C][C]5257.46[/C][C]77.5644[/C][C]67.7818[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 38 )[/C][C]5257.46[/C][C]77.5644[/C][C]67.7818[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 38 )[/C][C]5441.96[/C][C]133.454[/C][C]40.7779[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 38 )[/C][C]5435.91[/C][C]132.007[/C][C]41.179[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 38 )[/C][C]5429.63[/C][C]130.383[/C][C]41.6436[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 38 )[/C][C]5423.11[/C][C]128.9[/C][C]42.0724[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 38 )[/C][C]5416.35[/C][C]127.568[/C][C]42.4586[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 38 )[/C][C]5409.31[/C][C]126.232[/C][C]42.852[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 38 )[/C][C]5404[/C][C]125.119[/C][C]43.1907[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 38 )[/C][C]5397.45[/C][C]123.999[/C][C]43.5282[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 38 )[/C][C]5390.1[/C][C]122.789[/C][C]43.8974[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 38 )[/C][C]5383.51[/C][C]121.986[/C][C]44.1321[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 38 )[/C][C]5377.17[/C][C]121.152[/C][C]44.3838[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 38 )[/C][C]5371.11[/C][C]120.281[/C][C]44.6547[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 38 )[/C][C]5364.2[/C][C]119.339[/C][C]44.9494[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 38 )[/C][C]5357.56[/C][C]118.349[/C][C]45.2691[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 38 )[/C][C]5351.19[/C][C]117.306[/C][C]45.6173[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 38 )[/C][C]5343.9[/C][C]116.167[/C][C]46.002[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 38 )[/C][C]5336.25[/C][C]115.054[/C][C]46.3806[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 38 )[/C][C]5328.85[/C][C]113.871[/C][C]46.7972[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 38 )[/C][C]5321.05[/C][C]112.964[/C][C]47.1042[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 38 )[/C][C]5313.51[/C][C]112.007[/C][C]47.439[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 38 )[/C][C]5304.86[/C][C]110.943[/C][C]47.8159[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 38 )[/C][C]5296.43[/C][C]109.81[/C][C]48.2325[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 38 )[/C][C]5288.97[/C][C]108.773[/C][C]48.6241[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 38 )[/C][C]5282.58[/C][C]107.842[/C][C]48.9843[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 38 )[/C][C]5277.34[/C][C]107.032[/C][C]49.3064[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 38 )[/C][C]5272.58[/C][C]106.173[/C][C]49.6603[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 38 )[/C][C]5266.67[/C][C]105.215[/C][C]50.0563[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 38 )[/C][C]5260.34[/C][C]103.973[/C][C]50.5936[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 38 )[/C][C]5257.14[/C][C]103.262[/C][C]50.9107[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 38 )[/C][C]5253.7[/C][C]102.688[/C][C]51.1618[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 38 )[/C][C]5250[/C][C]101.859[/C][C]51.542[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 38 )[/C][C]5247[/C][C]100.959[/C][C]51.9717[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 38 )[/C][C]5242.71[/C][C]99.9334[/C][C]52.462[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 38 )[/C][C]5238.04[/C][C]98.5056[/C][C]53.1751[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 38 )[/C][C]5232.95[/C][C]97.144[/C][C]53.868[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 38 )[/C][C]5228.57[/C][C]96.1987[/C][C]54.3518[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 38 )[/C][C]5225[/C][C]95.1382[/C][C]54.9201[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 38 )[/C][C]5222.37[/C][C]93.9246[/C][C]55.6017[/C][/ROW]
[ROW][C]Median[/C][C]5225[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5750[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5200.85[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5223.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5223.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5223.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5257.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5223.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5223.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5223.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]114[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298383&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298383&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 Mean5447.37135.71840.1373
Geometric Mean5259.76
Harmonic Mean5079.96
Quadratic Mean5635.18
Winsorized Mean ( 1 / 38 )5447.81134.74340.431
Winsorized Mean ( 2 / 38 )5447.81134.74340.431
Winsorized Mean ( 3 / 38 )5447.81133.90240.6849
Winsorized Mean ( 4 / 38 )5447.81132.8241.0166
Winsorized Mean ( 5 / 38 )5447.81132.1641.2212
Winsorized Mean ( 6 / 38 )5437.28130.41741.6916
Winsorized Mean ( 7 / 38 )5443.42129.64841.9862
Winsorized Mean ( 8 / 38 )5446.93129.22342.1514
Winsorized Mean ( 9 / 38 )5439.04125.82243.2278
Winsorized Mean ( 10 / 38 )5434.65125.16143.4212
Winsorized Mean ( 11 / 38 )5429.82124.44543.6322
Winsorized Mean ( 12 / 38 )5435.09123.84243.8872
Winsorized Mean ( 13 / 38 )5429.39123.00744.1388
Winsorized Mean ( 14 / 38 )5423.25122.12144.4088
Winsorized Mean ( 15 / 38 )5429.82121.37944.7345
Winsorized Mean ( 16 / 38 )5429.82119.60145.3996
Winsorized Mean ( 17 / 38 )5422.37118.54945.7397
Winsorized Mean ( 18 / 38 )5422.37114.65447.2934
Winsorized Mean ( 19 / 38 )5414.04113.51847.6931
Winsorized Mean ( 20 / 38 )5422.81112.59648.1617
Winsorized Mean ( 21 / 38 )5413.6111.35348.6163
Winsorized Mean ( 22 / 38 )5394.3108.849.5801
Winsorized Mean ( 23 / 38 )5374.12106.19950.6043
Winsorized Mean ( 24 / 38 )5353.07103.55951.6912
Winsorized Mean ( 25 / 38 )5342.11102.21252.2648
Winsorized Mean ( 26 / 38 )5353.51100.99853.0062
Winsorized Mean ( 27 / 38 )5353.51100.99853.0062
Winsorized Mean ( 28 / 38 )5304.3995.14255.7523
Winsorized Mean ( 29 / 38 )5304.3992.319957.4566
Winsorized Mean ( 30 / 38 )5304.3992.319957.4566
Winsorized Mean ( 31 / 38 )5290.7990.772458.2863
Winsorized Mean ( 32 / 38 )5304.8289.292459.4096
Winsorized Mean ( 33 / 38 )5304.8289.292459.4096
Winsorized Mean ( 34 / 38 )5304.8286.056261.6437
Winsorized Mean ( 35 / 38 )5289.4781.05265.2602
Winsorized Mean ( 36 / 38 )5273.6879.320966.4854
Winsorized Mean ( 37 / 38 )5257.4677.564467.7818
Winsorized Mean ( 38 / 38 )5257.4677.564467.7818
Trimmed Mean ( 1 / 38 )5441.96133.45440.7779
Trimmed Mean ( 2 / 38 )5435.91132.00741.179
Trimmed Mean ( 3 / 38 )5429.63130.38341.6436
Trimmed Mean ( 4 / 38 )5423.11128.942.0724
Trimmed Mean ( 5 / 38 )5416.35127.56842.4586
Trimmed Mean ( 6 / 38 )5409.31126.23242.852
Trimmed Mean ( 7 / 38 )5404125.11943.1907
Trimmed Mean ( 8 / 38 )5397.45123.99943.5282
Trimmed Mean ( 9 / 38 )5390.1122.78943.8974
Trimmed Mean ( 10 / 38 )5383.51121.98644.1321
Trimmed Mean ( 11 / 38 )5377.17121.15244.3838
Trimmed Mean ( 12 / 38 )5371.11120.28144.6547
Trimmed Mean ( 13 / 38 )5364.2119.33944.9494
Trimmed Mean ( 14 / 38 )5357.56118.34945.2691
Trimmed Mean ( 15 / 38 )5351.19117.30645.6173
Trimmed Mean ( 16 / 38 )5343.9116.16746.002
Trimmed Mean ( 17 / 38 )5336.25115.05446.3806
Trimmed Mean ( 18 / 38 )5328.85113.87146.7972
Trimmed Mean ( 19 / 38 )5321.05112.96447.1042
Trimmed Mean ( 20 / 38 )5313.51112.00747.439
Trimmed Mean ( 21 / 38 )5304.86110.94347.8159
Trimmed Mean ( 22 / 38 )5296.43109.8148.2325
Trimmed Mean ( 23 / 38 )5288.97108.77348.6241
Trimmed Mean ( 24 / 38 )5282.58107.84248.9843
Trimmed Mean ( 25 / 38 )5277.34107.03249.3064
Trimmed Mean ( 26 / 38 )5272.58106.17349.6603
Trimmed Mean ( 27 / 38 )5266.67105.21550.0563
Trimmed Mean ( 28 / 38 )5260.34103.97350.5936
Trimmed Mean ( 29 / 38 )5257.14103.26250.9107
Trimmed Mean ( 30 / 38 )5253.7102.68851.1618
Trimmed Mean ( 31 / 38 )5250101.85951.542
Trimmed Mean ( 32 / 38 )5247100.95951.9717
Trimmed Mean ( 33 / 38 )5242.7199.933452.462
Trimmed Mean ( 34 / 38 )5238.0498.505653.1751
Trimmed Mean ( 35 / 38 )5232.9597.14453.868
Trimmed Mean ( 36 / 38 )5228.5796.198754.3518
Trimmed Mean ( 37 / 38 )522595.138254.9201
Trimmed Mean ( 38 / 38 )5222.3793.924655.6017
Median5225
Midrange5750
Midmean - Weighted Average at Xnp5200.85
Midmean - Weighted Average at X(n+1)p5223.33
Midmean - Empirical Distribution Function5223.33
Midmean - Empirical Distribution Function - Averaging5223.33
Midmean - Empirical Distribution Function - Interpolation5257.14
Midmean - Closest Observation5223.33
Midmean - True Basic - Statistics Graphics Toolkit5223.33
Midmean - MS Excel (old versions)5223.33
Number of observations114



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')