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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, 18 Dec 2008 06:16:50 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/18/t1229606243wkufbsiarfj2b80.htm/, Retrieved Sat, 11 May 2024 17:04:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34733, Retrieved Sat, 11 May 2024 17:04:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Back to Back Histogram] [B-t-B-histogram p...] [2007-11-09 11:02:25] [d255a97fd5d03c71781b63d0b6fcea5d]
- RMPD  [Central Tendency] [Central Tendency ...] [2008-12-10 14:45:06] [7506b5e9e41ec66c6657f4234f97306e]
-    D      [Central Tendency] [Central Tendency ...] [2008-12-18 13:16:50] [732c025e7dfb439ac3d0c7b7e70fa7a1] [Current]
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Dataseries X:
15044,5
14944,2
16754,8
14254
15454,9
15644,8
14568,3
12520,2
14803
15873,2
14755,3
12875,1
14291,1
14205,3
15859,4
15258,9
15498,6
15106,5
15023,6
12083
15761,3
16943
15070,3
13659,6
14768,9
14725,1
15998,1
15370,6
14956,9
15469,7
15101,8
11703,7
16283,6
16726,5
14968,9
14861
14583,3
15305,8
17903,9
16379,4
15420,3
17870,5
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
21211,2
21423,1
21688,7
23243,2
21490,2
22925,8
23184,8
18562,2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34733&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34733&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34733&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean17151.9467391304269.78453965031363.5764627630712
Geometric Mean16962.3275394395
Harmonic Mean16776.011277075
Quadratic Mean17343.9497648284
Winsorized Mean ( 1 / 30 )17155.4347826087268.74244389842163.8359707300016
Winsorized Mean ( 2 / 30 )17159.3086956522265.47758989217064.6356202895387
Winsorized Mean ( 3 / 30 )17145.9097826087257.65653751380366.5456034923629
Winsorized Mean ( 4 / 30 )17159.5271739130247.63948231048469.2923721767391
Winsorized Mean ( 5 / 30 )17159.9836956522243.79416363864170.387180068376
Winsorized Mean ( 6 / 30 )17177.7032608696239.79530160809771.6348616744103
Winsorized Mean ( 7 / 30 )17175.8923913043238.22544039139672.0993205557097
Winsorized Mean ( 8 / 30 )17166.9967391304235.48038661082472.9020237575123
Winsorized Mean ( 9 / 30 )17180.5358695652229.41541338407974.8883242679172
Winsorized Mean ( 10 / 30 )17157.3836956522224.66531686424976.3686355113696
Winsorized Mean ( 11 / 30 )17152.8043478261218.7217435161678.4229499640889
Winsorized Mean ( 12 / 30 )17065.0347826087202.92010249538884.0973100878292
Winsorized Mean ( 13 / 30 )17062.8445652174202.03670262541484.4541825494586
Winsorized Mean ( 14 / 30 )17051.4467391304198.82558731743785.7608267084192
Winsorized Mean ( 15 / 30 )17059.3543478261197.42202471326586.4105936133673
Winsorized Mean ( 16 / 30 )17070.6586956522195.18506665834387.4588358008612
Winsorized Mean ( 17 / 30 )17044.3271739130190.55648066823089.4450144867455
Winsorized Mean ( 18 / 30 )17012.3184782609185.20068561829491.858830983617
Winsorized Mean ( 19 / 30 )17018.4315217391183.08572212434892.9533517101928
Winsorized Mean ( 20 / 30 )16971.3663043478175.17536388835996.8821524193543
Winsorized Mean ( 21 / 30 )16959.3141304348171.96793501311498.619048540308
Winsorized Mean ( 22 / 30 )16958.8597826087169.95847071546799.7823745484277
Winsorized Mean ( 23 / 30 )16918.5597826087164.173819350130103.052726979122
Winsorized Mean ( 24 / 30 )16841.7336956522151.816880653958110.934526009925
Winsorized Mean ( 25 / 30 )16871.4076086957147.662278682502114.2567198558
Winsorized Mean ( 26 / 30 )16881.1576086957145.631685960325115.916790342554
Winsorized Mean ( 27 / 30 )16896.6826086956142.938976682240118.209063761928
Winsorized Mean ( 28 / 30 )16752.9695652174121.664356841300137.698254444974
Winsorized Mean ( 29 / 30 )16720.8804347826115.427780045399144.86010584459
Winsorized Mean ( 30 / 30 )16717.0652173913113.876056884951146.800527474187
Trimmed Mean ( 1 / 30 )17144.8022222222260.25862616698565.8760190765854
Trimmed Mean ( 2 / 30 )17133.6863636364250.50614309904768.3962722497466
Trimmed Mean ( 3 / 30 )17119.9813953488241.28885778943270.9522252796651
Trimmed Mean ( 4 / 30 )17110.5154761905234.12357625858473.0832654687125
Trimmed Mean ( 5 / 30 )17096.7682926829229.31698429464974.5551767361257
Trimmed Mean ( 6 / 30 )17082.22875224.85025950614475.9715767618816
Trimmed Mean ( 7 / 30 )17063.4602564103220.63727271630177.3371608810208
Trimmed Mean ( 8 / 30 )17044.0171052632216.05536841028978.8872650129969
Trimmed Mean ( 9 / 30 )17024.9054054054211.26396374322180.5859414154425
Trimmed Mean ( 10 / 30 )17002.8097222222206.81478835649382.212736610082
Trimmed Mean ( 11 / 30 )16982.4942857143202.47513663669583.8744675904887
Trimmed Mean ( 12 / 30 )16961.5470588235198.39688623188785.4930104044013
Trimmed Mean ( 13 / 30 )16961.5470588235196.38647773072586.3682024079087
Trimmed Mean ( 14 / 30 )16936.9953125194.02935957767787.2908891178374
Trimmed Mean ( 15 / 30 )16924.8645161290191.64297442432388.3145576662524
Trimmed Mean ( 16 / 30 )16911.1166666667188.87561781921889.5357318320097
Trimmed Mean ( 17 / 30 )16895.3185.76341014662890.9506343938459
Trimmed Mean ( 18 / 30 )16880.8982142857182.67502696650992.4094469540197
Trimmed Mean ( 19 / 30 )16868.4592592593179.71996841655893.8596829716843
Trimmed Mean ( 20 / 30 )16854.4942307692176.2871271382995.6081961534694
Trimmed Mean ( 21 / 30 )16843.742173.35052666378797.1657965174137
Trimmed Mean ( 22 / 30 )16833.19375170.10082360109898.9600955106215
Trimmed Mean ( 23 / 30 )16821.7695652174166.19993340394101.214057194193
Trimmed Mean ( 24 / 30 )16812.9704545455162.259148052224103.618012644403
Trimmed Mean ( 25 / 30 )16810.3452380952159.566526643638105.350073049080
Trimmed Mean ( 26 / 30 )16810.3452380952156.651033002867107.310784460563
Trimmed Mean ( 27 / 30 )16797.6105263158152.975012918369109.806237017802
Trimmed Mean ( 28 / 30 )16788.2333333333148.401546487899113.127078057116
Trimmed Mean ( 29 / 30 )16791.6411764706147.195095724367114.077450025333
Trimmed Mean ( 30 / 30 )16798.65625146.477886689638114.683906421954
Median16740.65
Midrange17473.45
Midmean - Weighted Average at Xnp16785.1744680851
Midmean - Weighted Average at X(n+1)p16821.7695652174
Midmean - Empirical Distribution Function16785.1744680851
Midmean - Empirical Distribution Function - Averaging16821.7695652174
Midmean - Empirical Distribution Function - Interpolation16821.7695652174
Midmean - Closest Observation16785.1744680851
Midmean - True Basic - Statistics Graphics Toolkit16821.7695652174
Midmean - MS Excel (old versions)16833.19375
Number of observations92

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 17151.9467391304 & 269.784539650313 & 63.5764627630712 \tabularnewline
Geometric Mean & 16962.3275394395 &  &  \tabularnewline
Harmonic Mean & 16776.011277075 &  &  \tabularnewline
Quadratic Mean & 17343.9497648284 &  &  \tabularnewline
Winsorized Mean ( 1 / 30 ) & 17155.4347826087 & 268.742443898421 & 63.8359707300016 \tabularnewline
Winsorized Mean ( 2 / 30 ) & 17159.3086956522 & 265.477589892170 & 64.6356202895387 \tabularnewline
Winsorized Mean ( 3 / 30 ) & 17145.9097826087 & 257.656537513803 & 66.5456034923629 \tabularnewline
Winsorized Mean ( 4 / 30 ) & 17159.5271739130 & 247.639482310484 & 69.2923721767391 \tabularnewline
Winsorized Mean ( 5 / 30 ) & 17159.9836956522 & 243.794163638641 & 70.387180068376 \tabularnewline
Winsorized Mean ( 6 / 30 ) & 17177.7032608696 & 239.795301608097 & 71.6348616744103 \tabularnewline
Winsorized Mean ( 7 / 30 ) & 17175.8923913043 & 238.225440391396 & 72.0993205557097 \tabularnewline
Winsorized Mean ( 8 / 30 ) & 17166.9967391304 & 235.480386610824 & 72.9020237575123 \tabularnewline
Winsorized Mean ( 9 / 30 ) & 17180.5358695652 & 229.415413384079 & 74.8883242679172 \tabularnewline
Winsorized Mean ( 10 / 30 ) & 17157.3836956522 & 224.665316864249 & 76.3686355113696 \tabularnewline
Winsorized Mean ( 11 / 30 ) & 17152.8043478261 & 218.72174351616 & 78.4229499640889 \tabularnewline
Winsorized Mean ( 12 / 30 ) & 17065.0347826087 & 202.920102495388 & 84.0973100878292 \tabularnewline
Winsorized Mean ( 13 / 30 ) & 17062.8445652174 & 202.036702625414 & 84.4541825494586 \tabularnewline
Winsorized Mean ( 14 / 30 ) & 17051.4467391304 & 198.825587317437 & 85.7608267084192 \tabularnewline
Winsorized Mean ( 15 / 30 ) & 17059.3543478261 & 197.422024713265 & 86.4105936133673 \tabularnewline
Winsorized Mean ( 16 / 30 ) & 17070.6586956522 & 195.185066658343 & 87.4588358008612 \tabularnewline
Winsorized Mean ( 17 / 30 ) & 17044.3271739130 & 190.556480668230 & 89.4450144867455 \tabularnewline
Winsorized Mean ( 18 / 30 ) & 17012.3184782609 & 185.200685618294 & 91.858830983617 \tabularnewline
Winsorized Mean ( 19 / 30 ) & 17018.4315217391 & 183.085722124348 & 92.9533517101928 \tabularnewline
Winsorized Mean ( 20 / 30 ) & 16971.3663043478 & 175.175363888359 & 96.8821524193543 \tabularnewline
Winsorized Mean ( 21 / 30 ) & 16959.3141304348 & 171.967935013114 & 98.619048540308 \tabularnewline
Winsorized Mean ( 22 / 30 ) & 16958.8597826087 & 169.958470715467 & 99.7823745484277 \tabularnewline
Winsorized Mean ( 23 / 30 ) & 16918.5597826087 & 164.173819350130 & 103.052726979122 \tabularnewline
Winsorized Mean ( 24 / 30 ) & 16841.7336956522 & 151.816880653958 & 110.934526009925 \tabularnewline
Winsorized Mean ( 25 / 30 ) & 16871.4076086957 & 147.662278682502 & 114.2567198558 \tabularnewline
Winsorized Mean ( 26 / 30 ) & 16881.1576086957 & 145.631685960325 & 115.916790342554 \tabularnewline
Winsorized Mean ( 27 / 30 ) & 16896.6826086956 & 142.938976682240 & 118.209063761928 \tabularnewline
Winsorized Mean ( 28 / 30 ) & 16752.9695652174 & 121.664356841300 & 137.698254444974 \tabularnewline
Winsorized Mean ( 29 / 30 ) & 16720.8804347826 & 115.427780045399 & 144.86010584459 \tabularnewline
Winsorized Mean ( 30 / 30 ) & 16717.0652173913 & 113.876056884951 & 146.800527474187 \tabularnewline
Trimmed Mean ( 1 / 30 ) & 17144.8022222222 & 260.258626166985 & 65.8760190765854 \tabularnewline
Trimmed Mean ( 2 / 30 ) & 17133.6863636364 & 250.506143099047 & 68.3962722497466 \tabularnewline
Trimmed Mean ( 3 / 30 ) & 17119.9813953488 & 241.288857789432 & 70.9522252796651 \tabularnewline
Trimmed Mean ( 4 / 30 ) & 17110.5154761905 & 234.123576258584 & 73.0832654687125 \tabularnewline
Trimmed Mean ( 5 / 30 ) & 17096.7682926829 & 229.316984294649 & 74.5551767361257 \tabularnewline
Trimmed Mean ( 6 / 30 ) & 17082.22875 & 224.850259506144 & 75.9715767618816 \tabularnewline
Trimmed Mean ( 7 / 30 ) & 17063.4602564103 & 220.637272716301 & 77.3371608810208 \tabularnewline
Trimmed Mean ( 8 / 30 ) & 17044.0171052632 & 216.055368410289 & 78.8872650129969 \tabularnewline
Trimmed Mean ( 9 / 30 ) & 17024.9054054054 & 211.263963743221 & 80.5859414154425 \tabularnewline
Trimmed Mean ( 10 / 30 ) & 17002.8097222222 & 206.814788356493 & 82.212736610082 \tabularnewline
Trimmed Mean ( 11 / 30 ) & 16982.4942857143 & 202.475136636695 & 83.8744675904887 \tabularnewline
Trimmed Mean ( 12 / 30 ) & 16961.5470588235 & 198.396886231887 & 85.4930104044013 \tabularnewline
Trimmed Mean ( 13 / 30 ) & 16961.5470588235 & 196.386477730725 & 86.3682024079087 \tabularnewline
Trimmed Mean ( 14 / 30 ) & 16936.9953125 & 194.029359577677 & 87.2908891178374 \tabularnewline
Trimmed Mean ( 15 / 30 ) & 16924.8645161290 & 191.642974424323 & 88.3145576662524 \tabularnewline
Trimmed Mean ( 16 / 30 ) & 16911.1166666667 & 188.875617819218 & 89.5357318320097 \tabularnewline
Trimmed Mean ( 17 / 30 ) & 16895.3 & 185.763410146628 & 90.9506343938459 \tabularnewline
Trimmed Mean ( 18 / 30 ) & 16880.8982142857 & 182.675026966509 & 92.4094469540197 \tabularnewline
Trimmed Mean ( 19 / 30 ) & 16868.4592592593 & 179.719968416558 & 93.8596829716843 \tabularnewline
Trimmed Mean ( 20 / 30 ) & 16854.4942307692 & 176.28712713829 & 95.6081961534694 \tabularnewline
Trimmed Mean ( 21 / 30 ) & 16843.742 & 173.350526663787 & 97.1657965174137 \tabularnewline
Trimmed Mean ( 22 / 30 ) & 16833.19375 & 170.100823601098 & 98.9600955106215 \tabularnewline
Trimmed Mean ( 23 / 30 ) & 16821.7695652174 & 166.19993340394 & 101.214057194193 \tabularnewline
Trimmed Mean ( 24 / 30 ) & 16812.9704545455 & 162.259148052224 & 103.618012644403 \tabularnewline
Trimmed Mean ( 25 / 30 ) & 16810.3452380952 & 159.566526643638 & 105.350073049080 \tabularnewline
Trimmed Mean ( 26 / 30 ) & 16810.3452380952 & 156.651033002867 & 107.310784460563 \tabularnewline
Trimmed Mean ( 27 / 30 ) & 16797.6105263158 & 152.975012918369 & 109.806237017802 \tabularnewline
Trimmed Mean ( 28 / 30 ) & 16788.2333333333 & 148.401546487899 & 113.127078057116 \tabularnewline
Trimmed Mean ( 29 / 30 ) & 16791.6411764706 & 147.195095724367 & 114.077450025333 \tabularnewline
Trimmed Mean ( 30 / 30 ) & 16798.65625 & 146.477886689638 & 114.683906421954 \tabularnewline
Median & 16740.65 &  &  \tabularnewline
Midrange & 17473.45 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 16785.1744680851 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 16821.7695652174 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 16785.1744680851 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 16821.7695652174 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 16821.7695652174 &  &  \tabularnewline
Midmean - Closest Observation & 16785.1744680851 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 16821.7695652174 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 16833.19375 &  &  \tabularnewline
Number of observations & 92 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34733&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]17151.9467391304[/C][C]269.784539650313[/C][C]63.5764627630712[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]16962.3275394395[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]16776.011277075[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]17343.9497648284[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 30 )[/C][C]17155.4347826087[/C][C]268.742443898421[/C][C]63.8359707300016[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 30 )[/C][C]17159.3086956522[/C][C]265.477589892170[/C][C]64.6356202895387[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 30 )[/C][C]17145.9097826087[/C][C]257.656537513803[/C][C]66.5456034923629[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 30 )[/C][C]17159.5271739130[/C][C]247.639482310484[/C][C]69.2923721767391[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 30 )[/C][C]17159.9836956522[/C][C]243.794163638641[/C][C]70.387180068376[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 30 )[/C][C]17177.7032608696[/C][C]239.795301608097[/C][C]71.6348616744103[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 30 )[/C][C]17175.8923913043[/C][C]238.225440391396[/C][C]72.0993205557097[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 30 )[/C][C]17166.9967391304[/C][C]235.480386610824[/C][C]72.9020237575123[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 30 )[/C][C]17180.5358695652[/C][C]229.415413384079[/C][C]74.8883242679172[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 30 )[/C][C]17157.3836956522[/C][C]224.665316864249[/C][C]76.3686355113696[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 30 )[/C][C]17152.8043478261[/C][C]218.72174351616[/C][C]78.4229499640889[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 30 )[/C][C]17065.0347826087[/C][C]202.920102495388[/C][C]84.0973100878292[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 30 )[/C][C]17062.8445652174[/C][C]202.036702625414[/C][C]84.4541825494586[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 30 )[/C][C]17051.4467391304[/C][C]198.825587317437[/C][C]85.7608267084192[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 30 )[/C][C]17059.3543478261[/C][C]197.422024713265[/C][C]86.4105936133673[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 30 )[/C][C]17070.6586956522[/C][C]195.185066658343[/C][C]87.4588358008612[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 30 )[/C][C]17044.3271739130[/C][C]190.556480668230[/C][C]89.4450144867455[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 30 )[/C][C]17012.3184782609[/C][C]185.200685618294[/C][C]91.858830983617[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 30 )[/C][C]17018.4315217391[/C][C]183.085722124348[/C][C]92.9533517101928[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 30 )[/C][C]16971.3663043478[/C][C]175.175363888359[/C][C]96.8821524193543[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 30 )[/C][C]16959.3141304348[/C][C]171.967935013114[/C][C]98.619048540308[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 30 )[/C][C]16958.8597826087[/C][C]169.958470715467[/C][C]99.7823745484277[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 30 )[/C][C]16918.5597826087[/C][C]164.173819350130[/C][C]103.052726979122[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 30 )[/C][C]16841.7336956522[/C][C]151.816880653958[/C][C]110.934526009925[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 30 )[/C][C]16871.4076086957[/C][C]147.662278682502[/C][C]114.2567198558[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 30 )[/C][C]16881.1576086957[/C][C]145.631685960325[/C][C]115.916790342554[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 30 )[/C][C]16896.6826086956[/C][C]142.938976682240[/C][C]118.209063761928[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 30 )[/C][C]16752.9695652174[/C][C]121.664356841300[/C][C]137.698254444974[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 30 )[/C][C]16720.8804347826[/C][C]115.427780045399[/C][C]144.86010584459[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 30 )[/C][C]16717.0652173913[/C][C]113.876056884951[/C][C]146.800527474187[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 30 )[/C][C]17144.8022222222[/C][C]260.258626166985[/C][C]65.8760190765854[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 30 )[/C][C]17133.6863636364[/C][C]250.506143099047[/C][C]68.3962722497466[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 30 )[/C][C]17119.9813953488[/C][C]241.288857789432[/C][C]70.9522252796651[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 30 )[/C][C]17110.5154761905[/C][C]234.123576258584[/C][C]73.0832654687125[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 30 )[/C][C]17096.7682926829[/C][C]229.316984294649[/C][C]74.5551767361257[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 30 )[/C][C]17082.22875[/C][C]224.850259506144[/C][C]75.9715767618816[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 30 )[/C][C]17063.4602564103[/C][C]220.637272716301[/C][C]77.3371608810208[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 30 )[/C][C]17044.0171052632[/C][C]216.055368410289[/C][C]78.8872650129969[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 30 )[/C][C]17024.9054054054[/C][C]211.263963743221[/C][C]80.5859414154425[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 30 )[/C][C]17002.8097222222[/C][C]206.814788356493[/C][C]82.212736610082[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 30 )[/C][C]16982.4942857143[/C][C]202.475136636695[/C][C]83.8744675904887[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 30 )[/C][C]16961.5470588235[/C][C]198.396886231887[/C][C]85.4930104044013[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 30 )[/C][C]16961.5470588235[/C][C]196.386477730725[/C][C]86.3682024079087[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 30 )[/C][C]16936.9953125[/C][C]194.029359577677[/C][C]87.2908891178374[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 30 )[/C][C]16924.8645161290[/C][C]191.642974424323[/C][C]88.3145576662524[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 30 )[/C][C]16911.1166666667[/C][C]188.875617819218[/C][C]89.5357318320097[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 30 )[/C][C]16895.3[/C][C]185.763410146628[/C][C]90.9506343938459[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 30 )[/C][C]16880.8982142857[/C][C]182.675026966509[/C][C]92.4094469540197[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 30 )[/C][C]16868.4592592593[/C][C]179.719968416558[/C][C]93.8596829716843[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 30 )[/C][C]16854.4942307692[/C][C]176.28712713829[/C][C]95.6081961534694[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 30 )[/C][C]16843.742[/C][C]173.350526663787[/C][C]97.1657965174137[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 30 )[/C][C]16833.19375[/C][C]170.100823601098[/C][C]98.9600955106215[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 30 )[/C][C]16821.7695652174[/C][C]166.19993340394[/C][C]101.214057194193[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 30 )[/C][C]16812.9704545455[/C][C]162.259148052224[/C][C]103.618012644403[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 30 )[/C][C]16810.3452380952[/C][C]159.566526643638[/C][C]105.350073049080[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 30 )[/C][C]16810.3452380952[/C][C]156.651033002867[/C][C]107.310784460563[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 30 )[/C][C]16797.6105263158[/C][C]152.975012918369[/C][C]109.806237017802[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 30 )[/C][C]16788.2333333333[/C][C]148.401546487899[/C][C]113.127078057116[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 30 )[/C][C]16791.6411764706[/C][C]147.195095724367[/C][C]114.077450025333[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 30 )[/C][C]16798.65625[/C][C]146.477886689638[/C][C]114.683906421954[/C][/ROW]
[ROW][C]Median[/C][C]16740.65[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]17473.45[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]16785.1744680851[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]16821.7695652174[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]16785.1744680851[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]16821.7695652174[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]16821.7695652174[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]16785.1744680851[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]16821.7695652174[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]16833.19375[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]92[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34733&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34733&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 Mean17151.9467391304269.78453965031363.5764627630712
Geometric Mean16962.3275394395
Harmonic Mean16776.011277075
Quadratic Mean17343.9497648284
Winsorized Mean ( 1 / 30 )17155.4347826087268.74244389842163.8359707300016
Winsorized Mean ( 2 / 30 )17159.3086956522265.47758989217064.6356202895387
Winsorized Mean ( 3 / 30 )17145.9097826087257.65653751380366.5456034923629
Winsorized Mean ( 4 / 30 )17159.5271739130247.63948231048469.2923721767391
Winsorized Mean ( 5 / 30 )17159.9836956522243.79416363864170.387180068376
Winsorized Mean ( 6 / 30 )17177.7032608696239.79530160809771.6348616744103
Winsorized Mean ( 7 / 30 )17175.8923913043238.22544039139672.0993205557097
Winsorized Mean ( 8 / 30 )17166.9967391304235.48038661082472.9020237575123
Winsorized Mean ( 9 / 30 )17180.5358695652229.41541338407974.8883242679172
Winsorized Mean ( 10 / 30 )17157.3836956522224.66531686424976.3686355113696
Winsorized Mean ( 11 / 30 )17152.8043478261218.7217435161678.4229499640889
Winsorized Mean ( 12 / 30 )17065.0347826087202.92010249538884.0973100878292
Winsorized Mean ( 13 / 30 )17062.8445652174202.03670262541484.4541825494586
Winsorized Mean ( 14 / 30 )17051.4467391304198.82558731743785.7608267084192
Winsorized Mean ( 15 / 30 )17059.3543478261197.42202471326586.4105936133673
Winsorized Mean ( 16 / 30 )17070.6586956522195.18506665834387.4588358008612
Winsorized Mean ( 17 / 30 )17044.3271739130190.55648066823089.4450144867455
Winsorized Mean ( 18 / 30 )17012.3184782609185.20068561829491.858830983617
Winsorized Mean ( 19 / 30 )17018.4315217391183.08572212434892.9533517101928
Winsorized Mean ( 20 / 30 )16971.3663043478175.17536388835996.8821524193543
Winsorized Mean ( 21 / 30 )16959.3141304348171.96793501311498.619048540308
Winsorized Mean ( 22 / 30 )16958.8597826087169.95847071546799.7823745484277
Winsorized Mean ( 23 / 30 )16918.5597826087164.173819350130103.052726979122
Winsorized Mean ( 24 / 30 )16841.7336956522151.816880653958110.934526009925
Winsorized Mean ( 25 / 30 )16871.4076086957147.662278682502114.2567198558
Winsorized Mean ( 26 / 30 )16881.1576086957145.631685960325115.916790342554
Winsorized Mean ( 27 / 30 )16896.6826086956142.938976682240118.209063761928
Winsorized Mean ( 28 / 30 )16752.9695652174121.664356841300137.698254444974
Winsorized Mean ( 29 / 30 )16720.8804347826115.427780045399144.86010584459
Winsorized Mean ( 30 / 30 )16717.0652173913113.876056884951146.800527474187
Trimmed Mean ( 1 / 30 )17144.8022222222260.25862616698565.8760190765854
Trimmed Mean ( 2 / 30 )17133.6863636364250.50614309904768.3962722497466
Trimmed Mean ( 3 / 30 )17119.9813953488241.28885778943270.9522252796651
Trimmed Mean ( 4 / 30 )17110.5154761905234.12357625858473.0832654687125
Trimmed Mean ( 5 / 30 )17096.7682926829229.31698429464974.5551767361257
Trimmed Mean ( 6 / 30 )17082.22875224.85025950614475.9715767618816
Trimmed Mean ( 7 / 30 )17063.4602564103220.63727271630177.3371608810208
Trimmed Mean ( 8 / 30 )17044.0171052632216.05536841028978.8872650129969
Trimmed Mean ( 9 / 30 )17024.9054054054211.26396374322180.5859414154425
Trimmed Mean ( 10 / 30 )17002.8097222222206.81478835649382.212736610082
Trimmed Mean ( 11 / 30 )16982.4942857143202.47513663669583.8744675904887
Trimmed Mean ( 12 / 30 )16961.5470588235198.39688623188785.4930104044013
Trimmed Mean ( 13 / 30 )16961.5470588235196.38647773072586.3682024079087
Trimmed Mean ( 14 / 30 )16936.9953125194.02935957767787.2908891178374
Trimmed Mean ( 15 / 30 )16924.8645161290191.64297442432388.3145576662524
Trimmed Mean ( 16 / 30 )16911.1166666667188.87561781921889.5357318320097
Trimmed Mean ( 17 / 30 )16895.3185.76341014662890.9506343938459
Trimmed Mean ( 18 / 30 )16880.8982142857182.67502696650992.4094469540197
Trimmed Mean ( 19 / 30 )16868.4592592593179.71996841655893.8596829716843
Trimmed Mean ( 20 / 30 )16854.4942307692176.2871271382995.6081961534694
Trimmed Mean ( 21 / 30 )16843.742173.35052666378797.1657965174137
Trimmed Mean ( 22 / 30 )16833.19375170.10082360109898.9600955106215
Trimmed Mean ( 23 / 30 )16821.7695652174166.19993340394101.214057194193
Trimmed Mean ( 24 / 30 )16812.9704545455162.259148052224103.618012644403
Trimmed Mean ( 25 / 30 )16810.3452380952159.566526643638105.350073049080
Trimmed Mean ( 26 / 30 )16810.3452380952156.651033002867107.310784460563
Trimmed Mean ( 27 / 30 )16797.6105263158152.975012918369109.806237017802
Trimmed Mean ( 28 / 30 )16788.2333333333148.401546487899113.127078057116
Trimmed Mean ( 29 / 30 )16791.6411764706147.195095724367114.077450025333
Trimmed Mean ( 30 / 30 )16798.65625146.477886689638114.683906421954
Median16740.65
Midrange17473.45
Midmean - Weighted Average at Xnp16785.1744680851
Midmean - Weighted Average at X(n+1)p16821.7695652174
Midmean - Empirical Distribution Function16785.1744680851
Midmean - Empirical Distribution Function - Averaging16821.7695652174
Midmean - Empirical Distribution Function - Interpolation16821.7695652174
Midmean - Closest Observation16785.1744680851
Midmean - True Basic - Statistics Graphics Toolkit16821.7695652174
Midmean - MS Excel (old versions)16833.19375
Number of observations92



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,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
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,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
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,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
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,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')