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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 computationWed, 21 Dec 2016 19:16:45 +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/21/t1482344224p0vt7yer8dmyggj.htm/, Retrieved Tue, 07 May 2024 02:21:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302457, Retrieved Tue, 07 May 2024 02:21:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-12-21 18:16:45] [f20c721eaecf28dbff8d9b9768e8b0c7] [Current]
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Dataseries X:
3904,45
4137,2
4334,5
4188,6
4304,1
4570,45
4178,85
4515,15
4740,55
4582,2
4493,6
4437
4294
4581,35
4780,15
4632
4648,2
4834,85
4465,25
4671,65
4871,3
4707,8
4580,45
4562,25
4329,7
4646,1
4844,1
4623
4707,2
4844,9
4436,75
4680,85
4873,8
4735,15
4681,9
4607
4436,4
4614,1
4619,25
4507,1
4515,85
4725,4
4250,85
4591,6
4898,15
4675,45
4568,95
4531,05
4387,35
4826,1
4954,35
4814,85
4821,55
5148,05
4810,75
4988,05
5322,65
5157
5006,65
4910,2
4764,05
5093,7
5312,2
5157,6
5192,4
5546,6
5092,05
5423,25
5647,2
5450,05
5360,3
5309,25
5181
5488,6
5668,15
5560,8
5590,45
5850,7
5252,2
5626,1
5819,8
5676,35
5525,5
5359,55
5296,85
5623,75
5899,3
5672,6
5724,75
5995,1
5475,2
6143,95
6366,95
6306,1
6077
5672,4
5458,6
5716,9
5828,1
5706,85
5888,3
6007,7
5581,85
5970,95
6190,4
6079,15
5902,2
5554,4
5320,45
5683,1
5987,9
5843,7
5917,5
6299,45
5846,75
5998,1




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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302457&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302457&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302457&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean5130.1155.349292.6861
Geometric Mean5096
Harmonic Mean5062.25
Quadratic Mean5164.33
Winsorized Mean ( 1 / 38 )5131.5954.898193.4747
Winsorized Mean ( 2 / 38 )5132.1954.765993.7114
Winsorized Mean ( 3 / 38 )5129.6254.226594.5962
Winsorized Mean ( 4 / 38 )5130.1753.643795.6342
Winsorized Mean ( 5 / 38 )5129.2352.93696.895
Winsorized Mean ( 6 / 38 )5129.6552.847397.0654
Winsorized Mean ( 7 / 38 )5127.0152.005498.586
Winsorized Mean ( 8 / 38 )5126.6851.864398.848
Winsorized Mean ( 9 / 38 )5130.5451.2995100.012
Winsorized Mean ( 10 / 38 )5134.1550.6891101.287
Winsorized Mean ( 11 / 38 )5132.5850.4513101.733
Winsorized Mean ( 12 / 38 )5127.0849.666103.231
Winsorized Mean ( 13 / 38 )5128.5349.0523104.552
Winsorized Mean ( 14 / 38 )5131.648.6078105.571
Winsorized Mean ( 15 / 38 )5131.9248.2151106.438
Winsorized Mean ( 16 / 38 )5127.8547.3924108.2
Winsorized Mean ( 17 / 38 )5127.3747.3042108.391
Winsorized Mean ( 18 / 38 )5129.2546.9785109.183
Winsorized Mean ( 19 / 38 )5131.8146.0841111.358
Winsorized Mean ( 20 / 38 )5131.5345.7727112.109
Winsorized Mean ( 21 / 38 )5114.643.5689117.391
Winsorized Mean ( 22 / 38 )5115.0143.1829118.45
Winsorized Mean ( 23 / 38 )5113.1942.9231119.124
Winsorized Mean ( 24 / 38 )5108.4542.3185120.714
Winsorized Mean ( 25 / 38 )5109.0241.9288121.85
Winsorized Mean ( 26 / 38 )5111.6441.462123.285
Winsorized Mean ( 27 / 38 )5113.2441.2822123.861
Winsorized Mean ( 28 / 38 )5113.4641.0311124.624
Winsorized Mean ( 29 / 38 )5109.1640.3211126.712
Winsorized Mean ( 30 / 38 )5106.0339.448129.437
Winsorized Mean ( 31 / 38 )5109.1738.9845131.056
Winsorized Mean ( 32 / 38 )5100.5637.8806134.648
Winsorized Mean ( 33 / 38 )5104.7936.9189138.27
Winsorized Mean ( 34 / 38 )5099.7336.116141.204
Winsorized Mean ( 35 / 38 )5099.4335.7358142.698
Winsorized Mean ( 36 / 38 )5097.3335.4351143.85
Winsorized Mean ( 37 / 38 )5098.6733.8785150.499
Winsorized Mean ( 38 / 38 )5086.7832.5474156.288
Trimmed Mean ( 1 / 38 )5130.0154.194994.6584
Trimmed Mean ( 2 / 38 )5128.3753.411996.0155
Trimmed Mean ( 3 / 38 )5126.3652.615597.4306
Trimmed Mean ( 4 / 38 )5125.1951.944998.6658
Trimmed Mean ( 5 / 38 )5123.8251.37799.7299
Trimmed Mean ( 6 / 38 )5122.6250.9225100.596
Trimmed Mean ( 7 / 38 )5121.2950.4265101.559
Trimmed Mean ( 8 / 38 )5120.3450.0342102.337
Trimmed Mean ( 9 / 38 )5119.449.6101103.193
Trimmed Mean ( 10 / 38 )5117.949.2185103.983
Trimmed Mean ( 11 / 38 )5115.948.8616104.702
Trimmed Mean ( 12 / 38 )5113.9948.482105.482
Trimmed Mean ( 13 / 38 )5112.5848.1548106.17
Trimmed Mean ( 14 / 38 )5110.9647.853106.806
Trimmed Mean ( 15 / 38 )5108.9847.5509107.442
Trimmed Mean ( 16 / 38 )5106.8647.2396108.105
Trimmed Mean ( 17 / 38 )5105.0146.9723108.681
Trimmed Mean ( 18 / 38 )5103.146.6561109.377
Trimmed Mean ( 19 / 38 )5100.9446.3112110.145
Trimmed Mean ( 20 / 38 )5098.4646.0011110.833
Trimmed Mean ( 21 / 38 )5095.8745.6566111.613
Trimmed Mean ( 22 / 38 )5094.4345.5124111.935
Trimmed Mean ( 23 / 38 )5092.8845.3582112.281
Trimmed Mean ( 24 / 38 )5091.3745.1762112.7
Trimmed Mean ( 25 / 38 )5090.1245.004113.104
Trimmed Mean ( 26 / 38 )5088.7544.8114113.559
Trimmed Mean ( 27 / 38 )5087.1144.601114.058
Trimmed Mean ( 28 / 38 )5085.2344.3307114.711
Trimmed Mean ( 29 / 38 )5083.2243.9974115.534
Trimmed Mean ( 30 / 38 )5081.3743.6545116.4
Trimmed Mean ( 31 / 38 )5081.3743.3195117.3
Trimmed Mean ( 32 / 38 )5077.4742.9252118.286
Trimmed Mean ( 33 / 38 )5075.842.5654119.247
Trimmed Mean ( 34 / 38 )5073.6742.2091120.203
Trimmed Mean ( 35 / 38 )5071.7441.8374121.225
Trimmed Mean ( 36 / 38 )5069.6641.3649122.559
Trimmed Mean ( 37 / 38 )5067.5340.7487124.361
Trimmed Mean ( 38 / 38 )5065.0940.1878126.036
Median5049.35
Midrange5135.7
Midmean - Weighted Average at Xnp5075.35
Midmean - Weighted Average at X(n+1)p5083.22
Midmean - Empirical Distribution Function5075.35
Midmean - Empirical Distribution Function - Averaging5083.22
Midmean - Empirical Distribution Function - Interpolation5083.22
Midmean - Closest Observation5075.35
Midmean - True Basic - Statistics Graphics Toolkit5083.22
Midmean - MS Excel (old versions)5085.23
Number of observations116

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 5130.11 & 55.3492 & 92.6861 \tabularnewline
Geometric Mean & 5096 &  &  \tabularnewline
Harmonic Mean & 5062.25 &  &  \tabularnewline
Quadratic Mean & 5164.33 &  &  \tabularnewline
Winsorized Mean ( 1 / 38 ) & 5131.59 & 54.8981 & 93.4747 \tabularnewline
Winsorized Mean ( 2 / 38 ) & 5132.19 & 54.7659 & 93.7114 \tabularnewline
Winsorized Mean ( 3 / 38 ) & 5129.62 & 54.2265 & 94.5962 \tabularnewline
Winsorized Mean ( 4 / 38 ) & 5130.17 & 53.6437 & 95.6342 \tabularnewline
Winsorized Mean ( 5 / 38 ) & 5129.23 & 52.936 & 96.895 \tabularnewline
Winsorized Mean ( 6 / 38 ) & 5129.65 & 52.8473 & 97.0654 \tabularnewline
Winsorized Mean ( 7 / 38 ) & 5127.01 & 52.0054 & 98.586 \tabularnewline
Winsorized Mean ( 8 / 38 ) & 5126.68 & 51.8643 & 98.848 \tabularnewline
Winsorized Mean ( 9 / 38 ) & 5130.54 & 51.2995 & 100.012 \tabularnewline
Winsorized Mean ( 10 / 38 ) & 5134.15 & 50.6891 & 101.287 \tabularnewline
Winsorized Mean ( 11 / 38 ) & 5132.58 & 50.4513 & 101.733 \tabularnewline
Winsorized Mean ( 12 / 38 ) & 5127.08 & 49.666 & 103.231 \tabularnewline
Winsorized Mean ( 13 / 38 ) & 5128.53 & 49.0523 & 104.552 \tabularnewline
Winsorized Mean ( 14 / 38 ) & 5131.6 & 48.6078 & 105.571 \tabularnewline
Winsorized Mean ( 15 / 38 ) & 5131.92 & 48.2151 & 106.438 \tabularnewline
Winsorized Mean ( 16 / 38 ) & 5127.85 & 47.3924 & 108.2 \tabularnewline
Winsorized Mean ( 17 / 38 ) & 5127.37 & 47.3042 & 108.391 \tabularnewline
Winsorized Mean ( 18 / 38 ) & 5129.25 & 46.9785 & 109.183 \tabularnewline
Winsorized Mean ( 19 / 38 ) & 5131.81 & 46.0841 & 111.358 \tabularnewline
Winsorized Mean ( 20 / 38 ) & 5131.53 & 45.7727 & 112.109 \tabularnewline
Winsorized Mean ( 21 / 38 ) & 5114.6 & 43.5689 & 117.391 \tabularnewline
Winsorized Mean ( 22 / 38 ) & 5115.01 & 43.1829 & 118.45 \tabularnewline
Winsorized Mean ( 23 / 38 ) & 5113.19 & 42.9231 & 119.124 \tabularnewline
Winsorized Mean ( 24 / 38 ) & 5108.45 & 42.3185 & 120.714 \tabularnewline
Winsorized Mean ( 25 / 38 ) & 5109.02 & 41.9288 & 121.85 \tabularnewline
Winsorized Mean ( 26 / 38 ) & 5111.64 & 41.462 & 123.285 \tabularnewline
Winsorized Mean ( 27 / 38 ) & 5113.24 & 41.2822 & 123.861 \tabularnewline
Winsorized Mean ( 28 / 38 ) & 5113.46 & 41.0311 & 124.624 \tabularnewline
Winsorized Mean ( 29 / 38 ) & 5109.16 & 40.3211 & 126.712 \tabularnewline
Winsorized Mean ( 30 / 38 ) & 5106.03 & 39.448 & 129.437 \tabularnewline
Winsorized Mean ( 31 / 38 ) & 5109.17 & 38.9845 & 131.056 \tabularnewline
Winsorized Mean ( 32 / 38 ) & 5100.56 & 37.8806 & 134.648 \tabularnewline
Winsorized Mean ( 33 / 38 ) & 5104.79 & 36.9189 & 138.27 \tabularnewline
Winsorized Mean ( 34 / 38 ) & 5099.73 & 36.116 & 141.204 \tabularnewline
Winsorized Mean ( 35 / 38 ) & 5099.43 & 35.7358 & 142.698 \tabularnewline
Winsorized Mean ( 36 / 38 ) & 5097.33 & 35.4351 & 143.85 \tabularnewline
Winsorized Mean ( 37 / 38 ) & 5098.67 & 33.8785 & 150.499 \tabularnewline
Winsorized Mean ( 38 / 38 ) & 5086.78 & 32.5474 & 156.288 \tabularnewline
Trimmed Mean ( 1 / 38 ) & 5130.01 & 54.1949 & 94.6584 \tabularnewline
Trimmed Mean ( 2 / 38 ) & 5128.37 & 53.4119 & 96.0155 \tabularnewline
Trimmed Mean ( 3 / 38 ) & 5126.36 & 52.6155 & 97.4306 \tabularnewline
Trimmed Mean ( 4 / 38 ) & 5125.19 & 51.9449 & 98.6658 \tabularnewline
Trimmed Mean ( 5 / 38 ) & 5123.82 & 51.377 & 99.7299 \tabularnewline
Trimmed Mean ( 6 / 38 ) & 5122.62 & 50.9225 & 100.596 \tabularnewline
Trimmed Mean ( 7 / 38 ) & 5121.29 & 50.4265 & 101.559 \tabularnewline
Trimmed Mean ( 8 / 38 ) & 5120.34 & 50.0342 & 102.337 \tabularnewline
Trimmed Mean ( 9 / 38 ) & 5119.4 & 49.6101 & 103.193 \tabularnewline
Trimmed Mean ( 10 / 38 ) & 5117.9 & 49.2185 & 103.983 \tabularnewline
Trimmed Mean ( 11 / 38 ) & 5115.9 & 48.8616 & 104.702 \tabularnewline
Trimmed Mean ( 12 / 38 ) & 5113.99 & 48.482 & 105.482 \tabularnewline
Trimmed Mean ( 13 / 38 ) & 5112.58 & 48.1548 & 106.17 \tabularnewline
Trimmed Mean ( 14 / 38 ) & 5110.96 & 47.853 & 106.806 \tabularnewline
Trimmed Mean ( 15 / 38 ) & 5108.98 & 47.5509 & 107.442 \tabularnewline
Trimmed Mean ( 16 / 38 ) & 5106.86 & 47.2396 & 108.105 \tabularnewline
Trimmed Mean ( 17 / 38 ) & 5105.01 & 46.9723 & 108.681 \tabularnewline
Trimmed Mean ( 18 / 38 ) & 5103.1 & 46.6561 & 109.377 \tabularnewline
Trimmed Mean ( 19 / 38 ) & 5100.94 & 46.3112 & 110.145 \tabularnewline
Trimmed Mean ( 20 / 38 ) & 5098.46 & 46.0011 & 110.833 \tabularnewline
Trimmed Mean ( 21 / 38 ) & 5095.87 & 45.6566 & 111.613 \tabularnewline
Trimmed Mean ( 22 / 38 ) & 5094.43 & 45.5124 & 111.935 \tabularnewline
Trimmed Mean ( 23 / 38 ) & 5092.88 & 45.3582 & 112.281 \tabularnewline
Trimmed Mean ( 24 / 38 ) & 5091.37 & 45.1762 & 112.7 \tabularnewline
Trimmed Mean ( 25 / 38 ) & 5090.12 & 45.004 & 113.104 \tabularnewline
Trimmed Mean ( 26 / 38 ) & 5088.75 & 44.8114 & 113.559 \tabularnewline
Trimmed Mean ( 27 / 38 ) & 5087.11 & 44.601 & 114.058 \tabularnewline
Trimmed Mean ( 28 / 38 ) & 5085.23 & 44.3307 & 114.711 \tabularnewline
Trimmed Mean ( 29 / 38 ) & 5083.22 & 43.9974 & 115.534 \tabularnewline
Trimmed Mean ( 30 / 38 ) & 5081.37 & 43.6545 & 116.4 \tabularnewline
Trimmed Mean ( 31 / 38 ) & 5081.37 & 43.3195 & 117.3 \tabularnewline
Trimmed Mean ( 32 / 38 ) & 5077.47 & 42.9252 & 118.286 \tabularnewline
Trimmed Mean ( 33 / 38 ) & 5075.8 & 42.5654 & 119.247 \tabularnewline
Trimmed Mean ( 34 / 38 ) & 5073.67 & 42.2091 & 120.203 \tabularnewline
Trimmed Mean ( 35 / 38 ) & 5071.74 & 41.8374 & 121.225 \tabularnewline
Trimmed Mean ( 36 / 38 ) & 5069.66 & 41.3649 & 122.559 \tabularnewline
Trimmed Mean ( 37 / 38 ) & 5067.53 & 40.7487 & 124.361 \tabularnewline
Trimmed Mean ( 38 / 38 ) & 5065.09 & 40.1878 & 126.036 \tabularnewline
Median & 5049.35 &  &  \tabularnewline
Midrange & 5135.7 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 5075.35 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 5083.22 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 5075.35 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 5083.22 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 5083.22 &  &  \tabularnewline
Midmean - Closest Observation & 5075.35 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 5083.22 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 5085.23 &  &  \tabularnewline
Number of observations & 116 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302457&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]5130.11[/C][C]55.3492[/C][C]92.6861[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]5096[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5062.25[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5164.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 38 )[/C][C]5131.59[/C][C]54.8981[/C][C]93.4747[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 38 )[/C][C]5132.19[/C][C]54.7659[/C][C]93.7114[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 38 )[/C][C]5129.62[/C][C]54.2265[/C][C]94.5962[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 38 )[/C][C]5130.17[/C][C]53.6437[/C][C]95.6342[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 38 )[/C][C]5129.23[/C][C]52.936[/C][C]96.895[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 38 )[/C][C]5129.65[/C][C]52.8473[/C][C]97.0654[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 38 )[/C][C]5127.01[/C][C]52.0054[/C][C]98.586[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 38 )[/C][C]5126.68[/C][C]51.8643[/C][C]98.848[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 38 )[/C][C]5130.54[/C][C]51.2995[/C][C]100.012[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 38 )[/C][C]5134.15[/C][C]50.6891[/C][C]101.287[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 38 )[/C][C]5132.58[/C][C]50.4513[/C][C]101.733[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 38 )[/C][C]5127.08[/C][C]49.666[/C][C]103.231[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 38 )[/C][C]5128.53[/C][C]49.0523[/C][C]104.552[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 38 )[/C][C]5131.6[/C][C]48.6078[/C][C]105.571[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 38 )[/C][C]5131.92[/C][C]48.2151[/C][C]106.438[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 38 )[/C][C]5127.85[/C][C]47.3924[/C][C]108.2[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 38 )[/C][C]5127.37[/C][C]47.3042[/C][C]108.391[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 38 )[/C][C]5129.25[/C][C]46.9785[/C][C]109.183[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 38 )[/C][C]5131.81[/C][C]46.0841[/C][C]111.358[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 38 )[/C][C]5131.53[/C][C]45.7727[/C][C]112.109[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 38 )[/C][C]5114.6[/C][C]43.5689[/C][C]117.391[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 38 )[/C][C]5115.01[/C][C]43.1829[/C][C]118.45[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 38 )[/C][C]5113.19[/C][C]42.9231[/C][C]119.124[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 38 )[/C][C]5108.45[/C][C]42.3185[/C][C]120.714[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 38 )[/C][C]5109.02[/C][C]41.9288[/C][C]121.85[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 38 )[/C][C]5111.64[/C][C]41.462[/C][C]123.285[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 38 )[/C][C]5113.24[/C][C]41.2822[/C][C]123.861[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 38 )[/C][C]5113.46[/C][C]41.0311[/C][C]124.624[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 38 )[/C][C]5109.16[/C][C]40.3211[/C][C]126.712[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 38 )[/C][C]5106.03[/C][C]39.448[/C][C]129.437[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 38 )[/C][C]5109.17[/C][C]38.9845[/C][C]131.056[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 38 )[/C][C]5100.56[/C][C]37.8806[/C][C]134.648[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 38 )[/C][C]5104.79[/C][C]36.9189[/C][C]138.27[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 38 )[/C][C]5099.73[/C][C]36.116[/C][C]141.204[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 38 )[/C][C]5099.43[/C][C]35.7358[/C][C]142.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 38 )[/C][C]5097.33[/C][C]35.4351[/C][C]143.85[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 38 )[/C][C]5098.67[/C][C]33.8785[/C][C]150.499[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 38 )[/C][C]5086.78[/C][C]32.5474[/C][C]156.288[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 38 )[/C][C]5130.01[/C][C]54.1949[/C][C]94.6584[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 38 )[/C][C]5128.37[/C][C]53.4119[/C][C]96.0155[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 38 )[/C][C]5126.36[/C][C]52.6155[/C][C]97.4306[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 38 )[/C][C]5125.19[/C][C]51.9449[/C][C]98.6658[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 38 )[/C][C]5123.82[/C][C]51.377[/C][C]99.7299[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 38 )[/C][C]5122.62[/C][C]50.9225[/C][C]100.596[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 38 )[/C][C]5121.29[/C][C]50.4265[/C][C]101.559[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 38 )[/C][C]5120.34[/C][C]50.0342[/C][C]102.337[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 38 )[/C][C]5119.4[/C][C]49.6101[/C][C]103.193[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 38 )[/C][C]5117.9[/C][C]49.2185[/C][C]103.983[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 38 )[/C][C]5115.9[/C][C]48.8616[/C][C]104.702[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 38 )[/C][C]5113.99[/C][C]48.482[/C][C]105.482[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 38 )[/C][C]5112.58[/C][C]48.1548[/C][C]106.17[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 38 )[/C][C]5110.96[/C][C]47.853[/C][C]106.806[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 38 )[/C][C]5108.98[/C][C]47.5509[/C][C]107.442[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 38 )[/C][C]5106.86[/C][C]47.2396[/C][C]108.105[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 38 )[/C][C]5105.01[/C][C]46.9723[/C][C]108.681[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 38 )[/C][C]5103.1[/C][C]46.6561[/C][C]109.377[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 38 )[/C][C]5100.94[/C][C]46.3112[/C][C]110.145[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 38 )[/C][C]5098.46[/C][C]46.0011[/C][C]110.833[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 38 )[/C][C]5095.87[/C][C]45.6566[/C][C]111.613[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 38 )[/C][C]5094.43[/C][C]45.5124[/C][C]111.935[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 38 )[/C][C]5092.88[/C][C]45.3582[/C][C]112.281[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 38 )[/C][C]5091.37[/C][C]45.1762[/C][C]112.7[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 38 )[/C][C]5090.12[/C][C]45.004[/C][C]113.104[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 38 )[/C][C]5088.75[/C][C]44.8114[/C][C]113.559[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 38 )[/C][C]5087.11[/C][C]44.601[/C][C]114.058[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 38 )[/C][C]5085.23[/C][C]44.3307[/C][C]114.711[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 38 )[/C][C]5083.22[/C][C]43.9974[/C][C]115.534[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 38 )[/C][C]5081.37[/C][C]43.6545[/C][C]116.4[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 38 )[/C][C]5081.37[/C][C]43.3195[/C][C]117.3[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 38 )[/C][C]5077.47[/C][C]42.9252[/C][C]118.286[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 38 )[/C][C]5075.8[/C][C]42.5654[/C][C]119.247[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 38 )[/C][C]5073.67[/C][C]42.2091[/C][C]120.203[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 38 )[/C][C]5071.74[/C][C]41.8374[/C][C]121.225[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 38 )[/C][C]5069.66[/C][C]41.3649[/C][C]122.559[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 38 )[/C][C]5067.53[/C][C]40.7487[/C][C]124.361[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 38 )[/C][C]5065.09[/C][C]40.1878[/C][C]126.036[/C][/ROW]
[ROW][C]Median[/C][C]5049.35[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5135.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]5075.35[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]5083.22[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]5075.35[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]5083.22[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]5083.22[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]5075.35[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]5083.22[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]5085.23[/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=302457&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302457&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 Mean5130.1155.349292.6861
Geometric Mean5096
Harmonic Mean5062.25
Quadratic Mean5164.33
Winsorized Mean ( 1 / 38 )5131.5954.898193.4747
Winsorized Mean ( 2 / 38 )5132.1954.765993.7114
Winsorized Mean ( 3 / 38 )5129.6254.226594.5962
Winsorized Mean ( 4 / 38 )5130.1753.643795.6342
Winsorized Mean ( 5 / 38 )5129.2352.93696.895
Winsorized Mean ( 6 / 38 )5129.6552.847397.0654
Winsorized Mean ( 7 / 38 )5127.0152.005498.586
Winsorized Mean ( 8 / 38 )5126.6851.864398.848
Winsorized Mean ( 9 / 38 )5130.5451.2995100.012
Winsorized Mean ( 10 / 38 )5134.1550.6891101.287
Winsorized Mean ( 11 / 38 )5132.5850.4513101.733
Winsorized Mean ( 12 / 38 )5127.0849.666103.231
Winsorized Mean ( 13 / 38 )5128.5349.0523104.552
Winsorized Mean ( 14 / 38 )5131.648.6078105.571
Winsorized Mean ( 15 / 38 )5131.9248.2151106.438
Winsorized Mean ( 16 / 38 )5127.8547.3924108.2
Winsorized Mean ( 17 / 38 )5127.3747.3042108.391
Winsorized Mean ( 18 / 38 )5129.2546.9785109.183
Winsorized Mean ( 19 / 38 )5131.8146.0841111.358
Winsorized Mean ( 20 / 38 )5131.5345.7727112.109
Winsorized Mean ( 21 / 38 )5114.643.5689117.391
Winsorized Mean ( 22 / 38 )5115.0143.1829118.45
Winsorized Mean ( 23 / 38 )5113.1942.9231119.124
Winsorized Mean ( 24 / 38 )5108.4542.3185120.714
Winsorized Mean ( 25 / 38 )5109.0241.9288121.85
Winsorized Mean ( 26 / 38 )5111.6441.462123.285
Winsorized Mean ( 27 / 38 )5113.2441.2822123.861
Winsorized Mean ( 28 / 38 )5113.4641.0311124.624
Winsorized Mean ( 29 / 38 )5109.1640.3211126.712
Winsorized Mean ( 30 / 38 )5106.0339.448129.437
Winsorized Mean ( 31 / 38 )5109.1738.9845131.056
Winsorized Mean ( 32 / 38 )5100.5637.8806134.648
Winsorized Mean ( 33 / 38 )5104.7936.9189138.27
Winsorized Mean ( 34 / 38 )5099.7336.116141.204
Winsorized Mean ( 35 / 38 )5099.4335.7358142.698
Winsorized Mean ( 36 / 38 )5097.3335.4351143.85
Winsorized Mean ( 37 / 38 )5098.6733.8785150.499
Winsorized Mean ( 38 / 38 )5086.7832.5474156.288
Trimmed Mean ( 1 / 38 )5130.0154.194994.6584
Trimmed Mean ( 2 / 38 )5128.3753.411996.0155
Trimmed Mean ( 3 / 38 )5126.3652.615597.4306
Trimmed Mean ( 4 / 38 )5125.1951.944998.6658
Trimmed Mean ( 5 / 38 )5123.8251.37799.7299
Trimmed Mean ( 6 / 38 )5122.6250.9225100.596
Trimmed Mean ( 7 / 38 )5121.2950.4265101.559
Trimmed Mean ( 8 / 38 )5120.3450.0342102.337
Trimmed Mean ( 9 / 38 )5119.449.6101103.193
Trimmed Mean ( 10 / 38 )5117.949.2185103.983
Trimmed Mean ( 11 / 38 )5115.948.8616104.702
Trimmed Mean ( 12 / 38 )5113.9948.482105.482
Trimmed Mean ( 13 / 38 )5112.5848.1548106.17
Trimmed Mean ( 14 / 38 )5110.9647.853106.806
Trimmed Mean ( 15 / 38 )5108.9847.5509107.442
Trimmed Mean ( 16 / 38 )5106.8647.2396108.105
Trimmed Mean ( 17 / 38 )5105.0146.9723108.681
Trimmed Mean ( 18 / 38 )5103.146.6561109.377
Trimmed Mean ( 19 / 38 )5100.9446.3112110.145
Trimmed Mean ( 20 / 38 )5098.4646.0011110.833
Trimmed Mean ( 21 / 38 )5095.8745.6566111.613
Trimmed Mean ( 22 / 38 )5094.4345.5124111.935
Trimmed Mean ( 23 / 38 )5092.8845.3582112.281
Trimmed Mean ( 24 / 38 )5091.3745.1762112.7
Trimmed Mean ( 25 / 38 )5090.1245.004113.104
Trimmed Mean ( 26 / 38 )5088.7544.8114113.559
Trimmed Mean ( 27 / 38 )5087.1144.601114.058
Trimmed Mean ( 28 / 38 )5085.2344.3307114.711
Trimmed Mean ( 29 / 38 )5083.2243.9974115.534
Trimmed Mean ( 30 / 38 )5081.3743.6545116.4
Trimmed Mean ( 31 / 38 )5081.3743.3195117.3
Trimmed Mean ( 32 / 38 )5077.4742.9252118.286
Trimmed Mean ( 33 / 38 )5075.842.5654119.247
Trimmed Mean ( 34 / 38 )5073.6742.2091120.203
Trimmed Mean ( 35 / 38 )5071.7441.8374121.225
Trimmed Mean ( 36 / 38 )5069.6641.3649122.559
Trimmed Mean ( 37 / 38 )5067.5340.7487124.361
Trimmed Mean ( 38 / 38 )5065.0940.1878126.036
Median5049.35
Midrange5135.7
Midmean - Weighted Average at Xnp5075.35
Midmean - Weighted Average at X(n+1)p5083.22
Midmean - Empirical Distribution Function5075.35
Midmean - Empirical Distribution Function - Averaging5083.22
Midmean - Empirical Distribution Function - Interpolation5083.22
Midmean - Closest Observation5075.35
Midmean - True Basic - Statistics Graphics Toolkit5083.22
Midmean - MS Excel (old versions)5085.23
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')