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Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 14 Dec 2016 19:29:17 +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/14/t1481741014fpcfnfel8l68i19.htm/, Retrieved Sat, 04 May 2024 01:58:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299688, Retrieved Sat, 04 May 2024 01:58:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central Tendency ...] [2016-12-14 18:29:17] [153c3207812fd13fe5ceee3276565119] [Current]
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Dataseries X:
4070
4229.2
3775.2
3584.2
5248
4182.4
4119
4082.4
3639.8
4020.6
4089.6
4373.6
4143.2
4604
4336.4
3953.6
4591.6
4272.4
3911.2
3911.2
4306.2
4280.2
4270.6
4387.8
4282.8
4534
4400.6
4282.8
5135.8
4524
4875.6
4593.8
4447.8
4406.6
5148.2
6357.6
4503.2
4688.2
4682.2
5012.6
5505.4
4871.8
4909.6
5025.6
4946.8
4943.6
5712.4
6932.4
5201.8
5247
4873.6
4854.8
5626.4
4769.4
4713.2
4762.4
5333.2
4960.8
4708.8
5490
4650.4
4376
4397.2
4318.6
4207.4
4488.6
4520
4358.8
4142.4
4052.8
4413.4
4837.4
3882.6
4672
3790
3713.4
5199.2
4016.2
3849.2
3903.4
3901.2
3943.2
4209.8
4850.2
4256.6
4479.6
3914
3849.4
4768
3944
4002.2
3768
4330.8
4109
3983
5666.8
3783
3599
3796.8
3663.8
4572.8
3914.6
3604
3777.4
3848.6
4110.6
4500.6
4701.6
4026
4415.4
4200.8
4325.8
4991.8
4244.2
4146.2
4109.2




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=299688&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=299688&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299688&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 Mean4446.0753.255583.4857
Geometric Mean4412.14
Harmonic Mean4380.53
Quadratic Mean4482.6
Winsorized Mean ( 1 / 38 )4441.2451.425286.3632
Winsorized Mean ( 2 / 38 )4430.2148.310491.7029
Winsorized Mean ( 3 / 38 )4429.9547.906792.4704
Winsorized Mean ( 4 / 38 )4429.3947.480293.2891
Winsorized Mean ( 5 / 38 )4426.3146.083296.0504
Winsorized Mean ( 6 / 38 )4428.3445.553397.2121
Winsorized Mean ( 7 / 38 )4419.3143.6764101.183
Winsorized Mean ( 8 / 38 )4413.5842.6218103.552
Winsorized Mean ( 9 / 38 )4413.9442.5523103.73
Winsorized Mean ( 10 / 38 )4410.6541.8223105.462
Winsorized Mean ( 11 / 38 )4411.0541.6988105.784
Winsorized Mean ( 12 / 38 )4411.1340.1744109.799
Winsorized Mean ( 13 / 38 )4409.8139.9456110.395
Winsorized Mean ( 14 / 38 )4396.5337.9302115.911
Winsorized Mean ( 15 / 38 )4399.1437.1595118.385
Winsorized Mean ( 16 / 38 )4398.8436.4432120.704
Winsorized Mean ( 17 / 38 )4394.6235.7707122.855
Winsorized Mean ( 18 / 38 )4393.6635.3291124.364
Winsorized Mean ( 19 / 38 )4393.1335.2579124.6
Winsorized Mean ( 20 / 38 )4387.7534.4158127.492
Winsorized Mean ( 21 / 38 )4381.7133.6034130.395
Winsorized Mean ( 22 / 38 )4386.7532.909133.299
Winsorized Mean ( 23 / 38 )4386.5532.8446133.555
Winsorized Mean ( 24 / 38 )4385.0232.163136.337
Winsorized Mean ( 25 / 38 )4390.3731.3087140.229
Winsorized Mean ( 26 / 38 )4391.830.4601144.182
Winsorized Mean ( 27 / 38 )4379.2328.133155.662
Winsorized Mean ( 28 / 38 )4379.9627.9733156.576
Winsorized Mean ( 29 / 38 )4379.9127.6542158.381
Winsorized Mean ( 30 / 38 )4374.1125.3815172.335
Winsorized Mean ( 31 / 38 )4377.5324.7433176.918
Winsorized Mean ( 32 / 38 )4378.9724.1447181.363
Winsorized Mean ( 33 / 38 )4377.2123.4853186.381
Winsorized Mean ( 34 / 38 )4381.1322.6831193.145
Winsorized Mean ( 35 / 38 )4378.1222.323196.126
Winsorized Mean ( 36 / 38 )4371.8521.5162203.189
Winsorized Mean ( 37 / 38 )4359.7319.5951222.491
Winsorized Mean ( 38 / 38 )4364.0518.4221236.893
Trimmed Mean ( 1 / 38 )4431.8248.965790.5087
Trimmed Mean ( 2 / 38 )4422.0646.146195.8274
Trimmed Mean ( 3 / 38 )4417.7744.867798.462
Trimmed Mean ( 4 / 38 )4413.4143.6024101.219
Trimmed Mean ( 5 / 38 )4409.0442.321104.181
Trimmed Mean ( 6 / 38 )4405.1841.2726106.734
Trimmed Mean ( 7 / 38 )4400.7940.2168109.427
Trimmed Mean ( 8 / 38 )4397.7339.4413111.5
Trimmed Mean ( 9 / 38 )4395.3838.7751113.356
Trimmed Mean ( 10 / 38 )4392.8938.032115.505
Trimmed Mean ( 11 / 38 )4390.737.3162117.662
Trimmed Mean ( 12 / 38 )4388.3636.5208120.161
Trimmed Mean ( 13 / 38 )4385.9235.8543122.326
Trimmed Mean ( 14 / 38 )4383.535.1259124.794
Trimmed Mean ( 15 / 38 )4382.2434.5945126.674
Trimmed Mean ( 16 / 38 )4380.6834.0877128.512
Trimmed Mean ( 17 / 38 )4379.0833.5981130.337
Trimmed Mean ( 18 / 38 )4377.7533.1206132.176
Trimmed Mean ( 19 / 38 )4376.4432.6213134.159
Trimmed Mean ( 20 / 38 )4375.132.0444136.532
Trimmed Mean ( 21 / 38 )4374.1131.4838138.932
Trimmed Mean ( 22 / 38 )4373.5230.9347141.379
Trimmed Mean ( 23 / 38 )4372.5330.376143.947
Trimmed Mean ( 24 / 38 )4371.4929.718147.099
Trimmed Mean ( 25 / 38 )4370.4929.0301150.551
Trimmed Mean ( 26 / 38 )4369.0528.3253154.245
Trimmed Mean ( 27 / 38 )4367.4227.5995158.242
Trimmed Mean ( 28 / 38 )4366.5727.0796161.25
Trimmed Mean ( 29 / 38 )4365.6126.4621164.976
Trimmed Mean ( 30 / 38 )4364.5925.7496169.502
Trimmed Mean ( 31 / 38 )4364.5925.241172.917
Trimmed Mean ( 32 / 38 )4362.9324.7004176.634
Trimmed Mean ( 33 / 38 )4361.7724.1133180.887
Trimmed Mean ( 34 / 38 )4360.6423.481185.71
Trimmed Mean ( 35 / 38 )4359.1222.8102191.104
Trimmed Mean ( 36 / 38 )4357.6922.0103197.984
Trimmed Mean ( 37 / 38 )4356.621.1433206.051
Trimmed Mean ( 38 / 38 )4356.3620.446213.067
Median4347.6
Midrange5258.3
Midmean - Weighted Average at Xnp4359.77
Midmean - Weighted Average at X(n+1)p4365.61
Midmean - Empirical Distribution Function4359.77
Midmean - Empirical Distribution Function - Averaging4365.61
Midmean - Empirical Distribution Function - Interpolation4365.61
Midmean - Closest Observation4359.77
Midmean - True Basic - Statistics Graphics Toolkit4365.61
Midmean - MS Excel (old versions)4366.57
Number of observations116

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4446.07 & 53.2555 & 83.4857 \tabularnewline
Geometric Mean & 4412.14 &  &  \tabularnewline
Harmonic Mean & 4380.53 &  &  \tabularnewline
Quadratic Mean & 4482.6 &  &  \tabularnewline
Winsorized Mean ( 1 / 38 ) & 4441.24 & 51.4252 & 86.3632 \tabularnewline
Winsorized Mean ( 2 / 38 ) & 4430.21 & 48.3104 & 91.7029 \tabularnewline
Winsorized Mean ( 3 / 38 ) & 4429.95 & 47.9067 & 92.4704 \tabularnewline
Winsorized Mean ( 4 / 38 ) & 4429.39 & 47.4802 & 93.2891 \tabularnewline
Winsorized Mean ( 5 / 38 ) & 4426.31 & 46.0832 & 96.0504 \tabularnewline
Winsorized Mean ( 6 / 38 ) & 4428.34 & 45.5533 & 97.2121 \tabularnewline
Winsorized Mean ( 7 / 38 ) & 4419.31 & 43.6764 & 101.183 \tabularnewline
Winsorized Mean ( 8 / 38 ) & 4413.58 & 42.6218 & 103.552 \tabularnewline
Winsorized Mean ( 9 / 38 ) & 4413.94 & 42.5523 & 103.73 \tabularnewline
Winsorized Mean ( 10 / 38 ) & 4410.65 & 41.8223 & 105.462 \tabularnewline
Winsorized Mean ( 11 / 38 ) & 4411.05 & 41.6988 & 105.784 \tabularnewline
Winsorized Mean ( 12 / 38 ) & 4411.13 & 40.1744 & 109.799 \tabularnewline
Winsorized Mean ( 13 / 38 ) & 4409.81 & 39.9456 & 110.395 \tabularnewline
Winsorized Mean ( 14 / 38 ) & 4396.53 & 37.9302 & 115.911 \tabularnewline
Winsorized Mean ( 15 / 38 ) & 4399.14 & 37.1595 & 118.385 \tabularnewline
Winsorized Mean ( 16 / 38 ) & 4398.84 & 36.4432 & 120.704 \tabularnewline
Winsorized Mean ( 17 / 38 ) & 4394.62 & 35.7707 & 122.855 \tabularnewline
Winsorized Mean ( 18 / 38 ) & 4393.66 & 35.3291 & 124.364 \tabularnewline
Winsorized Mean ( 19 / 38 ) & 4393.13 & 35.2579 & 124.6 \tabularnewline
Winsorized Mean ( 20 / 38 ) & 4387.75 & 34.4158 & 127.492 \tabularnewline
Winsorized Mean ( 21 / 38 ) & 4381.71 & 33.6034 & 130.395 \tabularnewline
Winsorized Mean ( 22 / 38 ) & 4386.75 & 32.909 & 133.299 \tabularnewline
Winsorized Mean ( 23 / 38 ) & 4386.55 & 32.8446 & 133.555 \tabularnewline
Winsorized Mean ( 24 / 38 ) & 4385.02 & 32.163 & 136.337 \tabularnewline
Winsorized Mean ( 25 / 38 ) & 4390.37 & 31.3087 & 140.229 \tabularnewline
Winsorized Mean ( 26 / 38 ) & 4391.8 & 30.4601 & 144.182 \tabularnewline
Winsorized Mean ( 27 / 38 ) & 4379.23 & 28.133 & 155.662 \tabularnewline
Winsorized Mean ( 28 / 38 ) & 4379.96 & 27.9733 & 156.576 \tabularnewline
Winsorized Mean ( 29 / 38 ) & 4379.91 & 27.6542 & 158.381 \tabularnewline
Winsorized Mean ( 30 / 38 ) & 4374.11 & 25.3815 & 172.335 \tabularnewline
Winsorized Mean ( 31 / 38 ) & 4377.53 & 24.7433 & 176.918 \tabularnewline
Winsorized Mean ( 32 / 38 ) & 4378.97 & 24.1447 & 181.363 \tabularnewline
Winsorized Mean ( 33 / 38 ) & 4377.21 & 23.4853 & 186.381 \tabularnewline
Winsorized Mean ( 34 / 38 ) & 4381.13 & 22.6831 & 193.145 \tabularnewline
Winsorized Mean ( 35 / 38 ) & 4378.12 & 22.323 & 196.126 \tabularnewline
Winsorized Mean ( 36 / 38 ) & 4371.85 & 21.5162 & 203.189 \tabularnewline
Winsorized Mean ( 37 / 38 ) & 4359.73 & 19.5951 & 222.491 \tabularnewline
Winsorized Mean ( 38 / 38 ) & 4364.05 & 18.4221 & 236.893 \tabularnewline
Trimmed Mean ( 1 / 38 ) & 4431.82 & 48.9657 & 90.5087 \tabularnewline
Trimmed Mean ( 2 / 38 ) & 4422.06 & 46.1461 & 95.8274 \tabularnewline
Trimmed Mean ( 3 / 38 ) & 4417.77 & 44.8677 & 98.462 \tabularnewline
Trimmed Mean ( 4 / 38 ) & 4413.41 & 43.6024 & 101.219 \tabularnewline
Trimmed Mean ( 5 / 38 ) & 4409.04 & 42.321 & 104.181 \tabularnewline
Trimmed Mean ( 6 / 38 ) & 4405.18 & 41.2726 & 106.734 \tabularnewline
Trimmed Mean ( 7 / 38 ) & 4400.79 & 40.2168 & 109.427 \tabularnewline
Trimmed Mean ( 8 / 38 ) & 4397.73 & 39.4413 & 111.5 \tabularnewline
Trimmed Mean ( 9 / 38 ) & 4395.38 & 38.7751 & 113.356 \tabularnewline
Trimmed Mean ( 10 / 38 ) & 4392.89 & 38.032 & 115.505 \tabularnewline
Trimmed Mean ( 11 / 38 ) & 4390.7 & 37.3162 & 117.662 \tabularnewline
Trimmed Mean ( 12 / 38 ) & 4388.36 & 36.5208 & 120.161 \tabularnewline
Trimmed Mean ( 13 / 38 ) & 4385.92 & 35.8543 & 122.326 \tabularnewline
Trimmed Mean ( 14 / 38 ) & 4383.5 & 35.1259 & 124.794 \tabularnewline
Trimmed Mean ( 15 / 38 ) & 4382.24 & 34.5945 & 126.674 \tabularnewline
Trimmed Mean ( 16 / 38 ) & 4380.68 & 34.0877 & 128.512 \tabularnewline
Trimmed Mean ( 17 / 38 ) & 4379.08 & 33.5981 & 130.337 \tabularnewline
Trimmed Mean ( 18 / 38 ) & 4377.75 & 33.1206 & 132.176 \tabularnewline
Trimmed Mean ( 19 / 38 ) & 4376.44 & 32.6213 & 134.159 \tabularnewline
Trimmed Mean ( 20 / 38 ) & 4375.1 & 32.0444 & 136.532 \tabularnewline
Trimmed Mean ( 21 / 38 ) & 4374.11 & 31.4838 & 138.932 \tabularnewline
Trimmed Mean ( 22 / 38 ) & 4373.52 & 30.9347 & 141.379 \tabularnewline
Trimmed Mean ( 23 / 38 ) & 4372.53 & 30.376 & 143.947 \tabularnewline
Trimmed Mean ( 24 / 38 ) & 4371.49 & 29.718 & 147.099 \tabularnewline
Trimmed Mean ( 25 / 38 ) & 4370.49 & 29.0301 & 150.551 \tabularnewline
Trimmed Mean ( 26 / 38 ) & 4369.05 & 28.3253 & 154.245 \tabularnewline
Trimmed Mean ( 27 / 38 ) & 4367.42 & 27.5995 & 158.242 \tabularnewline
Trimmed Mean ( 28 / 38 ) & 4366.57 & 27.0796 & 161.25 \tabularnewline
Trimmed Mean ( 29 / 38 ) & 4365.61 & 26.4621 & 164.976 \tabularnewline
Trimmed Mean ( 30 / 38 ) & 4364.59 & 25.7496 & 169.502 \tabularnewline
Trimmed Mean ( 31 / 38 ) & 4364.59 & 25.241 & 172.917 \tabularnewline
Trimmed Mean ( 32 / 38 ) & 4362.93 & 24.7004 & 176.634 \tabularnewline
Trimmed Mean ( 33 / 38 ) & 4361.77 & 24.1133 & 180.887 \tabularnewline
Trimmed Mean ( 34 / 38 ) & 4360.64 & 23.481 & 185.71 \tabularnewline
Trimmed Mean ( 35 / 38 ) & 4359.12 & 22.8102 & 191.104 \tabularnewline
Trimmed Mean ( 36 / 38 ) & 4357.69 & 22.0103 & 197.984 \tabularnewline
Trimmed Mean ( 37 / 38 ) & 4356.6 & 21.1433 & 206.051 \tabularnewline
Trimmed Mean ( 38 / 38 ) & 4356.36 & 20.446 & 213.067 \tabularnewline
Median & 4347.6 &  &  \tabularnewline
Midrange & 5258.3 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4359.77 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4365.61 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4359.77 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4365.61 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4365.61 &  &  \tabularnewline
Midmean - Closest Observation & 4359.77 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4365.61 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4366.57 &  &  \tabularnewline
Number of observations & 116 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299688&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]4446.07[/C][C]53.2555[/C][C]83.4857[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4412.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]4380.53[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4482.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 38 )[/C][C]4441.24[/C][C]51.4252[/C][C]86.3632[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 38 )[/C][C]4430.21[/C][C]48.3104[/C][C]91.7029[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 38 )[/C][C]4429.95[/C][C]47.9067[/C][C]92.4704[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 38 )[/C][C]4429.39[/C][C]47.4802[/C][C]93.2891[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 38 )[/C][C]4426.31[/C][C]46.0832[/C][C]96.0504[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 38 )[/C][C]4428.34[/C][C]45.5533[/C][C]97.2121[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 38 )[/C][C]4419.31[/C][C]43.6764[/C][C]101.183[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 38 )[/C][C]4413.58[/C][C]42.6218[/C][C]103.552[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 38 )[/C][C]4413.94[/C][C]42.5523[/C][C]103.73[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 38 )[/C][C]4410.65[/C][C]41.8223[/C][C]105.462[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 38 )[/C][C]4411.05[/C][C]41.6988[/C][C]105.784[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 38 )[/C][C]4411.13[/C][C]40.1744[/C][C]109.799[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 38 )[/C][C]4409.81[/C][C]39.9456[/C][C]110.395[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 38 )[/C][C]4396.53[/C][C]37.9302[/C][C]115.911[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 38 )[/C][C]4399.14[/C][C]37.1595[/C][C]118.385[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 38 )[/C][C]4398.84[/C][C]36.4432[/C][C]120.704[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 38 )[/C][C]4394.62[/C][C]35.7707[/C][C]122.855[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 38 )[/C][C]4393.66[/C][C]35.3291[/C][C]124.364[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 38 )[/C][C]4393.13[/C][C]35.2579[/C][C]124.6[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 38 )[/C][C]4387.75[/C][C]34.4158[/C][C]127.492[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 38 )[/C][C]4381.71[/C][C]33.6034[/C][C]130.395[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 38 )[/C][C]4386.75[/C][C]32.909[/C][C]133.299[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 38 )[/C][C]4386.55[/C][C]32.8446[/C][C]133.555[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 38 )[/C][C]4385.02[/C][C]32.163[/C][C]136.337[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 38 )[/C][C]4390.37[/C][C]31.3087[/C][C]140.229[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 38 )[/C][C]4391.8[/C][C]30.4601[/C][C]144.182[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 38 )[/C][C]4379.23[/C][C]28.133[/C][C]155.662[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 38 )[/C][C]4379.96[/C][C]27.9733[/C][C]156.576[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 38 )[/C][C]4379.91[/C][C]27.6542[/C][C]158.381[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 38 )[/C][C]4374.11[/C][C]25.3815[/C][C]172.335[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 38 )[/C][C]4377.53[/C][C]24.7433[/C][C]176.918[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 38 )[/C][C]4378.97[/C][C]24.1447[/C][C]181.363[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 38 )[/C][C]4377.21[/C][C]23.4853[/C][C]186.381[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 38 )[/C][C]4381.13[/C][C]22.6831[/C][C]193.145[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 38 )[/C][C]4378.12[/C][C]22.323[/C][C]196.126[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 38 )[/C][C]4371.85[/C][C]21.5162[/C][C]203.189[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 38 )[/C][C]4359.73[/C][C]19.5951[/C][C]222.491[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 38 )[/C][C]4364.05[/C][C]18.4221[/C][C]236.893[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 38 )[/C][C]4431.82[/C][C]48.9657[/C][C]90.5087[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 38 )[/C][C]4422.06[/C][C]46.1461[/C][C]95.8274[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 38 )[/C][C]4417.77[/C][C]44.8677[/C][C]98.462[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 38 )[/C][C]4413.41[/C][C]43.6024[/C][C]101.219[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 38 )[/C][C]4409.04[/C][C]42.321[/C][C]104.181[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 38 )[/C][C]4405.18[/C][C]41.2726[/C][C]106.734[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 38 )[/C][C]4400.79[/C][C]40.2168[/C][C]109.427[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 38 )[/C][C]4397.73[/C][C]39.4413[/C][C]111.5[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 38 )[/C][C]4395.38[/C][C]38.7751[/C][C]113.356[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 38 )[/C][C]4392.89[/C][C]38.032[/C][C]115.505[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 38 )[/C][C]4390.7[/C][C]37.3162[/C][C]117.662[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 38 )[/C][C]4388.36[/C][C]36.5208[/C][C]120.161[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 38 )[/C][C]4385.92[/C][C]35.8543[/C][C]122.326[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 38 )[/C][C]4383.5[/C][C]35.1259[/C][C]124.794[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 38 )[/C][C]4382.24[/C][C]34.5945[/C][C]126.674[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 38 )[/C][C]4380.68[/C][C]34.0877[/C][C]128.512[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 38 )[/C][C]4379.08[/C][C]33.5981[/C][C]130.337[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 38 )[/C][C]4377.75[/C][C]33.1206[/C][C]132.176[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 38 )[/C][C]4376.44[/C][C]32.6213[/C][C]134.159[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 38 )[/C][C]4375.1[/C][C]32.0444[/C][C]136.532[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 38 )[/C][C]4374.11[/C][C]31.4838[/C][C]138.932[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 38 )[/C][C]4373.52[/C][C]30.9347[/C][C]141.379[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 38 )[/C][C]4372.53[/C][C]30.376[/C][C]143.947[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 38 )[/C][C]4371.49[/C][C]29.718[/C][C]147.099[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 38 )[/C][C]4370.49[/C][C]29.0301[/C][C]150.551[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 38 )[/C][C]4369.05[/C][C]28.3253[/C][C]154.245[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 38 )[/C][C]4367.42[/C][C]27.5995[/C][C]158.242[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 38 )[/C][C]4366.57[/C][C]27.0796[/C][C]161.25[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 38 )[/C][C]4365.61[/C][C]26.4621[/C][C]164.976[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 38 )[/C][C]4364.59[/C][C]25.7496[/C][C]169.502[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 38 )[/C][C]4364.59[/C][C]25.241[/C][C]172.917[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 38 )[/C][C]4362.93[/C][C]24.7004[/C][C]176.634[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 38 )[/C][C]4361.77[/C][C]24.1133[/C][C]180.887[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 38 )[/C][C]4360.64[/C][C]23.481[/C][C]185.71[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 38 )[/C][C]4359.12[/C][C]22.8102[/C][C]191.104[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 38 )[/C][C]4357.69[/C][C]22.0103[/C][C]197.984[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 38 )[/C][C]4356.6[/C][C]21.1433[/C][C]206.051[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 38 )[/C][C]4356.36[/C][C]20.446[/C][C]213.067[/C][/ROW]
[ROW][C]Median[/C][C]4347.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5258.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4359.77[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4365.61[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4359.77[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4365.61[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4365.61[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4359.77[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4365.61[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4366.57[/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=299688&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299688&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 Mean4446.0753.255583.4857
Geometric Mean4412.14
Harmonic Mean4380.53
Quadratic Mean4482.6
Winsorized Mean ( 1 / 38 )4441.2451.425286.3632
Winsorized Mean ( 2 / 38 )4430.2148.310491.7029
Winsorized Mean ( 3 / 38 )4429.9547.906792.4704
Winsorized Mean ( 4 / 38 )4429.3947.480293.2891
Winsorized Mean ( 5 / 38 )4426.3146.083296.0504
Winsorized Mean ( 6 / 38 )4428.3445.553397.2121
Winsorized Mean ( 7 / 38 )4419.3143.6764101.183
Winsorized Mean ( 8 / 38 )4413.5842.6218103.552
Winsorized Mean ( 9 / 38 )4413.9442.5523103.73
Winsorized Mean ( 10 / 38 )4410.6541.8223105.462
Winsorized Mean ( 11 / 38 )4411.0541.6988105.784
Winsorized Mean ( 12 / 38 )4411.1340.1744109.799
Winsorized Mean ( 13 / 38 )4409.8139.9456110.395
Winsorized Mean ( 14 / 38 )4396.5337.9302115.911
Winsorized Mean ( 15 / 38 )4399.1437.1595118.385
Winsorized Mean ( 16 / 38 )4398.8436.4432120.704
Winsorized Mean ( 17 / 38 )4394.6235.7707122.855
Winsorized Mean ( 18 / 38 )4393.6635.3291124.364
Winsorized Mean ( 19 / 38 )4393.1335.2579124.6
Winsorized Mean ( 20 / 38 )4387.7534.4158127.492
Winsorized Mean ( 21 / 38 )4381.7133.6034130.395
Winsorized Mean ( 22 / 38 )4386.7532.909133.299
Winsorized Mean ( 23 / 38 )4386.5532.8446133.555
Winsorized Mean ( 24 / 38 )4385.0232.163136.337
Winsorized Mean ( 25 / 38 )4390.3731.3087140.229
Winsorized Mean ( 26 / 38 )4391.830.4601144.182
Winsorized Mean ( 27 / 38 )4379.2328.133155.662
Winsorized Mean ( 28 / 38 )4379.9627.9733156.576
Winsorized Mean ( 29 / 38 )4379.9127.6542158.381
Winsorized Mean ( 30 / 38 )4374.1125.3815172.335
Winsorized Mean ( 31 / 38 )4377.5324.7433176.918
Winsorized Mean ( 32 / 38 )4378.9724.1447181.363
Winsorized Mean ( 33 / 38 )4377.2123.4853186.381
Winsorized Mean ( 34 / 38 )4381.1322.6831193.145
Winsorized Mean ( 35 / 38 )4378.1222.323196.126
Winsorized Mean ( 36 / 38 )4371.8521.5162203.189
Winsorized Mean ( 37 / 38 )4359.7319.5951222.491
Winsorized Mean ( 38 / 38 )4364.0518.4221236.893
Trimmed Mean ( 1 / 38 )4431.8248.965790.5087
Trimmed Mean ( 2 / 38 )4422.0646.146195.8274
Trimmed Mean ( 3 / 38 )4417.7744.867798.462
Trimmed Mean ( 4 / 38 )4413.4143.6024101.219
Trimmed Mean ( 5 / 38 )4409.0442.321104.181
Trimmed Mean ( 6 / 38 )4405.1841.2726106.734
Trimmed Mean ( 7 / 38 )4400.7940.2168109.427
Trimmed Mean ( 8 / 38 )4397.7339.4413111.5
Trimmed Mean ( 9 / 38 )4395.3838.7751113.356
Trimmed Mean ( 10 / 38 )4392.8938.032115.505
Trimmed Mean ( 11 / 38 )4390.737.3162117.662
Trimmed Mean ( 12 / 38 )4388.3636.5208120.161
Trimmed Mean ( 13 / 38 )4385.9235.8543122.326
Trimmed Mean ( 14 / 38 )4383.535.1259124.794
Trimmed Mean ( 15 / 38 )4382.2434.5945126.674
Trimmed Mean ( 16 / 38 )4380.6834.0877128.512
Trimmed Mean ( 17 / 38 )4379.0833.5981130.337
Trimmed Mean ( 18 / 38 )4377.7533.1206132.176
Trimmed Mean ( 19 / 38 )4376.4432.6213134.159
Trimmed Mean ( 20 / 38 )4375.132.0444136.532
Trimmed Mean ( 21 / 38 )4374.1131.4838138.932
Trimmed Mean ( 22 / 38 )4373.5230.9347141.379
Trimmed Mean ( 23 / 38 )4372.5330.376143.947
Trimmed Mean ( 24 / 38 )4371.4929.718147.099
Trimmed Mean ( 25 / 38 )4370.4929.0301150.551
Trimmed Mean ( 26 / 38 )4369.0528.3253154.245
Trimmed Mean ( 27 / 38 )4367.4227.5995158.242
Trimmed Mean ( 28 / 38 )4366.5727.0796161.25
Trimmed Mean ( 29 / 38 )4365.6126.4621164.976
Trimmed Mean ( 30 / 38 )4364.5925.7496169.502
Trimmed Mean ( 31 / 38 )4364.5925.241172.917
Trimmed Mean ( 32 / 38 )4362.9324.7004176.634
Trimmed Mean ( 33 / 38 )4361.7724.1133180.887
Trimmed Mean ( 34 / 38 )4360.6423.481185.71
Trimmed Mean ( 35 / 38 )4359.1222.8102191.104
Trimmed Mean ( 36 / 38 )4357.6922.0103197.984
Trimmed Mean ( 37 / 38 )4356.621.1433206.051
Trimmed Mean ( 38 / 38 )4356.3620.446213.067
Median4347.6
Midrange5258.3
Midmean - Weighted Average at Xnp4359.77
Midmean - Weighted Average at X(n+1)p4365.61
Midmean - Empirical Distribution Function4359.77
Midmean - Empirical Distribution Function - Averaging4365.61
Midmean - Empirical Distribution Function - Interpolation4365.61
Midmean - Closest Observation4359.77
Midmean - True Basic - Statistics Graphics Toolkit4365.61
Midmean - MS Excel (old versions)4366.57
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')