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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, 10 Dec 2008 07:45:06 -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/10/t1228920364miurpfq5xir1tzq.htm/, Retrieved Fri, 17 May 2024 03:20:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31981, Retrieved Fri, 17 May 2024 03:20:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190
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] [732c025e7dfb439ac3d0c7b7e70fa7a1] [Current]
-    D      [Central Tendency] [Central Tendency ...] [2008-12-18 13:16:50] [7506b5e9e41ec66c6657f4234f97306e]
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Dataseries X:
18 562,2 
23 184,8 
22 925,8 
21 490,2 
23 243,2 
21 688,7 
21 423,1 
21 211,2 
17 877,4  
20 664,3  
22 160,0  
19 813,6  
17 735,4  
19 640,2  
20 844,4  
19 823,1  
18 594,6  
21 350,6  
18 574,1  
18 924,2  
17 343,4  
19 961,2  
19 932,1  
19 464,6  
16 165,4  
17 574,9  
19 795,4  
19 439,5  
17 170,0  
21 072,4  
17 751,8  
17 515,5  
18 040,3  
19 090,1  
17 746,5  
19 202,1  
15 141,6  
16 258,1  
18 586,5  
17 209,4  
17 838,7  
19 123,5  
16 583,6  
15 991,2  
16 704,4  
17 420,4  
17 872,0  
17 823,2  
13 866,5  
15 912,8  
17 870,5  
15 420,3  
16 379,4  
17 903,9  
15 305,8  
14 583,3  
14 861,0  
14 968,9  
16 726,5  
16 283,6  
11 703,7  
15 101,8  
15 469,7  
14 956,9  
15 370,6  
15 998,1  
14 725,1  
14 768,9  
13 659,6  
15 070,3  
16 943,0  
15 761,3  
12 083,0  
15 023,6  
15 106,5  
15 498,6  
15 258,9  
15 859,4  
14 205,3  
14 291,1  
12 875,1  
14 755,3  
15 873,2  
14 803,0  
12 520,2  
14 568,3  
15 644,8  
15 454,9  
14 254,0  
16 754,8  
14 944,2  
15 044,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31981&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31981&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31981&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







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 )17152.8043478261218.7217435161678.422949964089
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 )16918.5597826087164.17381935013103.052726979122
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 )16720.8804347826115.427780045399144.860105844590
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 )16895.3185.76341014662890.950634393846
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 & 78.422949964089 \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 & 164.17381935013 & 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 & 144.860105844590 \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 & 90.950634393846 \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=31981&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]78.422949964089[/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]164.17381935013[/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]144.860105844590[/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]90.950634393846[/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=31981&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31981&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 )17152.8043478261218.7217435161678.422949964089
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 )16918.5597826087164.17381935013103.052726979122
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 )16720.8804347826115.427780045399144.860105844590
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 )16895.3185.76341014662890.950634393846
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')