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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 07 Mar 2012 10:49:51 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Mar/07/t1331135760g89rvb4eaemb1s9.htm/, Retrieved Sun, 28 Apr 2024 19:58:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=163639, Retrieved Sun, 28 Apr 2024 19:58:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2012-03-07 15:49:51] [0557341c9fb01f967ad344d41189c66a] [Current]
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Dataseries X:
12 693,7
13154
15405,1
13869,4
12827,7
15716,7
13012,5
12837,6
15052,7
15002,6
14839,6
15022,6
14097,8
14776,8
16833,3
15385,5
15172,6
16858,9
14143,5
14731,8
16471,6
15214
17637,4
17972,4
16896,2
16698
19691,6
15930,7
17444,6
17699,4
15189,8
15672,7
17180,8
17664,9
17862,9
16162,3
17463,6
16772,1
19106,9
16721,3
18161,3
18509,9
17802,7
16409,9
17967,7
20286,6
19537,3
18021,9
20194,3
19049,6
20244,7
21473,3
19673,6
21053,2
20159,5
18203,6
21289,5
20432,3
17180,4
15816,8
15076,6
14531,6
15761,3
14345,5
13916,8
15496,8
14285,6
13597,3
16263,1
16773,3
15986,9
16842,6
15911,9
15782,9
18622,8
17422,5
16989,8
18990,5
16849,3
16511,3
18704,5
19111,1
19420,7
18985,1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163639&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163639&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163639&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'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean16792.0892857143234.10225428623871.7297205740808
Geometric Mean16656.4401155816
Harmonic Mean16520.7413753382
Quadratic Mean16926.9897918306
Winsorized Mean ( 1 / 28 )16791.4964285714233.2529195697271.9883655027624
Winsorized Mean ( 2 / 28 )16786.105952381231.92737700679772.3765610124112
Winsorized Mean ( 3 / 28 )16770.1773809524226.03521097127274.1927654054032
Winsorized Mean ( 4 / 28 )16769.9773809524223.36791928926775.0778242207414
Winsorized Mean ( 5 / 28 )16793.8702380952217.98636710663477.0409198566077
Winsorized Mean ( 6 / 28 )16809.705952381213.97321559444778.5598604277701
Winsorized Mean ( 7 / 28 )16810.755952381212.77128835548879.0085733949889
Winsorized Mean ( 8 / 28 )16783.4321428571201.87504103302383.1377274623647
Winsorized Mean ( 9 / 28 )16786.4200.75987016944783.6143198629876
Winsorized Mean ( 10 / 28 )16787.0904761905195.33030395658685.942069080697
Winsorized Mean ( 11 / 28 )16779.6654761905191.56116114207887.5942982186523
Winsorized Mean ( 12 / 28 )16762.0226190476180.39529502738892.9182915580075
Winsorized Mean ( 13 / 28 )16792.355952381175.79575400632795.5219655178738
Winsorized Mean ( 14 / 28 )16790.305952381173.23320146369496.9231406596144
Winsorized Mean ( 15 / 28 )16790.9666666667170.02086426868598.7582714562128
Winsorized Mean ( 16 / 28 )16820.9857142857165.65891313907101.539877302977
Winsorized Mean ( 17 / 28 )16768.2452380952156.408512045506107.208009454221
Winsorized Mean ( 18 / 28 )16757.1880952381152.949613574578109.560185891332
Winsorized Mean ( 19 / 28 )16737.0571428571148.509132810314112.700524379432
Winsorized Mean ( 20 / 28 )16686.9857142857135.241802321154123.386300891345
Winsorized Mean ( 21 / 28 )16680.7107142857133.239545148318125.193392815303
Winsorized Mean ( 22 / 28 )16650.5392857143127.572452702452130.518297116618
Winsorized Mean ( 23 / 28 )16683.944047619119.55350533481139.552111005826
Winsorized Mean ( 24 / 28 )16688.2011904762118.647870386042140.653187757843
Winsorized Mean ( 25 / 28 )16684.3023809524111.09104243908150.185847703264
Winsorized Mean ( 26 / 28 )16720.1142857143101.821204216329164.210533693855
Winsorized Mean ( 27 / 28 )16701.053571428695.8587000743184174.225746421351
Winsorized Mean ( 28 / 28 )16704.420238095292.5864161436814180.419773589381
Trimmed Mean ( 1 / 28 )16784.9817073171227.37186353503773.8217185114929
Trimmed Mean ( 2 / 28 )16778.14125220.55144214432776.0735957419882
Trimmed Mean ( 3 / 28 )16773.8525641026213.44187352931878.5874500009883
Trimmed Mean ( 4 / 28 )16775.2065789474207.78100599020180.7350339796625
Trimmed Mean ( 5 / 28 )16776.6905405405202.10050750990383.0116200461221
Trimmed Mean ( 6 / 28 )16772.6819444444197.05670729356985.116016474674
Trimmed Mean ( 7 / 28 )16765.2771428571192.16834291129587.2426586443326
Trimmed Mean ( 8 / 28 )16757.2514705882186.65211276752989.7779897699794
Trimmed Mean ( 9 / 28 )16753.0863636364182.60119118025891.7468624128428
Trimmed Mean ( 10 / 28 )16748.228125177.96625493106994.1090103373082
Trimmed Mean ( 11 / 28 )16742.9629032258173.50729032232896.4971723788784
Trimmed Mean ( 12 / 28 )16738.2916666667168.85863410670699.1260633796751
Trimmed Mean ( 13 / 28 )16735.4275862069165.394430716385101.184952321064
Trimmed Mean ( 14 / 28 )16728.8589285714161.964260924231103.28734767232
Trimmed Mean ( 15 / 28 )16722.0314814815158.165771267766105.724717474883
Trimmed Mean ( 16 / 28 )16714.6076923077154.011964649666108.527981772901
Trimmed Mean ( 17 / 28 )16703.438149.573900290397111.673480250033
Trimmed Mean ( 18 / 28 )16696.7666666667145.835602373432114.4903329155
Trimmed Mean ( 19 / 28 )16690.6369565217141.705232137208117.784196848574
Trimmed Mean ( 20 / 28 )16685.9727272727137.269085725889121.556668342592
Trimmed Mean ( 21 / 28 )16685.8714285714134.296228132657124.2467615106
Trimmed Mean ( 22 / 28 )16686.3875130.683512201724127.685483951814
Trimmed Mean ( 23 / 28 )16689.9894736842127.035209094877131.380816331157
Trimmed Mean ( 24 / 28 )16690.6027777778123.903657752874134.706295846949
Trimmed Mean ( 25 / 28 )16690.85119.640615607126139.508225658159
Trimmed Mean ( 26 / 28 )16691.5375115.618507468109144.367349704838
Trimmed Mean ( 27 / 28 )16688.46112.38123780905148.498631313848
Trimmed Mean ( 28 / 28 )16687.0607142857109.238163106202152.758525407119
Median16772.7
Midrange17083.5
Midmean - Weighted Average at Xnp16650.6790697674
Midmean - Weighted Average at X(n+1)p16685.8714285714
Midmean - Empirical Distribution Function16650.6790697674
Midmean - Empirical Distribution Function - Averaging16685.8714285714
Midmean - Empirical Distribution Function - Interpolation16685.8714285714
Midmean - Closest Observation16650.6790697674
Midmean - True Basic - Statistics Graphics Toolkit16685.8714285714
Midmean - MS Excel (old versions)16685.9727272727
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 16792.0892857143 & 234.102254286238 & 71.7297205740808 \tabularnewline
Geometric Mean & 16656.4401155816 &  &  \tabularnewline
Harmonic Mean & 16520.7413753382 &  &  \tabularnewline
Quadratic Mean & 16926.9897918306 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 16791.4964285714 & 233.25291956972 & 71.9883655027624 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 16786.105952381 & 231.927377006797 & 72.3765610124112 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 16770.1773809524 & 226.035210971272 & 74.1927654054032 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 16769.9773809524 & 223.367919289267 & 75.0778242207414 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 16793.8702380952 & 217.986367106634 & 77.0409198566077 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 16809.705952381 & 213.973215594447 & 78.5598604277701 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 16810.755952381 & 212.771288355488 & 79.0085733949889 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 16783.4321428571 & 201.875041033023 & 83.1377274623647 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 16786.4 & 200.759870169447 & 83.6143198629876 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 16787.0904761905 & 195.330303956586 & 85.942069080697 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 16779.6654761905 & 191.561161142078 & 87.5942982186523 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 16762.0226190476 & 180.395295027388 & 92.9182915580075 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 16792.355952381 & 175.795754006327 & 95.5219655178738 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 16790.305952381 & 173.233201463694 & 96.9231406596144 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 16790.9666666667 & 170.020864268685 & 98.7582714562128 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 16820.9857142857 & 165.65891313907 & 101.539877302977 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 16768.2452380952 & 156.408512045506 & 107.208009454221 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 16757.1880952381 & 152.949613574578 & 109.560185891332 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 16737.0571428571 & 148.509132810314 & 112.700524379432 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 16686.9857142857 & 135.241802321154 & 123.386300891345 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 16680.7107142857 & 133.239545148318 & 125.193392815303 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 16650.5392857143 & 127.572452702452 & 130.518297116618 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 16683.944047619 & 119.55350533481 & 139.552111005826 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 16688.2011904762 & 118.647870386042 & 140.653187757843 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 16684.3023809524 & 111.09104243908 & 150.185847703264 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 16720.1142857143 & 101.821204216329 & 164.210533693855 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 16701.0535714286 & 95.8587000743184 & 174.225746421351 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 16704.4202380952 & 92.5864161436814 & 180.419773589381 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 16784.9817073171 & 227.371863535037 & 73.8217185114929 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 16778.14125 & 220.551442144327 & 76.0735957419882 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 16773.8525641026 & 213.441873529318 & 78.5874500009883 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 16775.2065789474 & 207.781005990201 & 80.7350339796625 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 16776.6905405405 & 202.100507509903 & 83.0116200461221 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 16772.6819444444 & 197.056707293569 & 85.116016474674 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 16765.2771428571 & 192.168342911295 & 87.2426586443326 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 16757.2514705882 & 186.652112767529 & 89.7779897699794 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 16753.0863636364 & 182.601191180258 & 91.7468624128428 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 16748.228125 & 177.966254931069 & 94.1090103373082 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 16742.9629032258 & 173.507290322328 & 96.4971723788784 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 16738.2916666667 & 168.858634106706 & 99.1260633796751 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 16735.4275862069 & 165.394430716385 & 101.184952321064 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 16728.8589285714 & 161.964260924231 & 103.28734767232 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 16722.0314814815 & 158.165771267766 & 105.724717474883 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 16714.6076923077 & 154.011964649666 & 108.527981772901 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 16703.438 & 149.573900290397 & 111.673480250033 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 16696.7666666667 & 145.835602373432 & 114.4903329155 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 16690.6369565217 & 141.705232137208 & 117.784196848574 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 16685.9727272727 & 137.269085725889 & 121.556668342592 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 16685.8714285714 & 134.296228132657 & 124.2467615106 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 16686.3875 & 130.683512201724 & 127.685483951814 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 16689.9894736842 & 127.035209094877 & 131.380816331157 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 16690.6027777778 & 123.903657752874 & 134.706295846949 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 16690.85 & 119.640615607126 & 139.508225658159 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 16691.5375 & 115.618507468109 & 144.367349704838 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 16688.46 & 112.38123780905 & 148.498631313848 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 16687.0607142857 & 109.238163106202 & 152.758525407119 \tabularnewline
Median & 16772.7 &  &  \tabularnewline
Midrange & 17083.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 16650.6790697674 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 16685.8714285714 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 16650.6790697674 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 16685.8714285714 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 16685.8714285714 &  &  \tabularnewline
Midmean - Closest Observation & 16650.6790697674 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 16685.8714285714 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 16685.9727272727 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=163639&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]16792.0892857143[/C][C]234.102254286238[/C][C]71.7297205740808[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]16656.4401155816[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]16520.7413753382[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]16926.9897918306[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]16791.4964285714[/C][C]233.25291956972[/C][C]71.9883655027624[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]16786.105952381[/C][C]231.927377006797[/C][C]72.3765610124112[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]16770.1773809524[/C][C]226.035210971272[/C][C]74.1927654054032[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]16769.9773809524[/C][C]223.367919289267[/C][C]75.0778242207414[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]16793.8702380952[/C][C]217.986367106634[/C][C]77.0409198566077[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]16809.705952381[/C][C]213.973215594447[/C][C]78.5598604277701[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]16810.755952381[/C][C]212.771288355488[/C][C]79.0085733949889[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]16783.4321428571[/C][C]201.875041033023[/C][C]83.1377274623647[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]16786.4[/C][C]200.759870169447[/C][C]83.6143198629876[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]16787.0904761905[/C][C]195.330303956586[/C][C]85.942069080697[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]16779.6654761905[/C][C]191.561161142078[/C][C]87.5942982186523[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]16762.0226190476[/C][C]180.395295027388[/C][C]92.9182915580075[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]16792.355952381[/C][C]175.795754006327[/C][C]95.5219655178738[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]16790.305952381[/C][C]173.233201463694[/C][C]96.9231406596144[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]16790.9666666667[/C][C]170.020864268685[/C][C]98.7582714562128[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]16820.9857142857[/C][C]165.65891313907[/C][C]101.539877302977[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]16768.2452380952[/C][C]156.408512045506[/C][C]107.208009454221[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]16757.1880952381[/C][C]152.949613574578[/C][C]109.560185891332[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]16737.0571428571[/C][C]148.509132810314[/C][C]112.700524379432[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]16686.9857142857[/C][C]135.241802321154[/C][C]123.386300891345[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]16680.7107142857[/C][C]133.239545148318[/C][C]125.193392815303[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]16650.5392857143[/C][C]127.572452702452[/C][C]130.518297116618[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]16683.944047619[/C][C]119.55350533481[/C][C]139.552111005826[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]16688.2011904762[/C][C]118.647870386042[/C][C]140.653187757843[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]16684.3023809524[/C][C]111.09104243908[/C][C]150.185847703264[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]16720.1142857143[/C][C]101.821204216329[/C][C]164.210533693855[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]16701.0535714286[/C][C]95.8587000743184[/C][C]174.225746421351[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]16704.4202380952[/C][C]92.5864161436814[/C][C]180.419773589381[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]16784.9817073171[/C][C]227.371863535037[/C][C]73.8217185114929[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]16778.14125[/C][C]220.551442144327[/C][C]76.0735957419882[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]16773.8525641026[/C][C]213.441873529318[/C][C]78.5874500009883[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]16775.2065789474[/C][C]207.781005990201[/C][C]80.7350339796625[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]16776.6905405405[/C][C]202.100507509903[/C][C]83.0116200461221[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]16772.6819444444[/C][C]197.056707293569[/C][C]85.116016474674[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]16765.2771428571[/C][C]192.168342911295[/C][C]87.2426586443326[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]16757.2514705882[/C][C]186.652112767529[/C][C]89.7779897699794[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]16753.0863636364[/C][C]182.601191180258[/C][C]91.7468624128428[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]16748.228125[/C][C]177.966254931069[/C][C]94.1090103373082[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]16742.9629032258[/C][C]173.507290322328[/C][C]96.4971723788784[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]16738.2916666667[/C][C]168.858634106706[/C][C]99.1260633796751[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]16735.4275862069[/C][C]165.394430716385[/C][C]101.184952321064[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]16728.8589285714[/C][C]161.964260924231[/C][C]103.28734767232[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]16722.0314814815[/C][C]158.165771267766[/C][C]105.724717474883[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]16714.6076923077[/C][C]154.011964649666[/C][C]108.527981772901[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]16703.438[/C][C]149.573900290397[/C][C]111.673480250033[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]16696.7666666667[/C][C]145.835602373432[/C][C]114.4903329155[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]16690.6369565217[/C][C]141.705232137208[/C][C]117.784196848574[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]16685.9727272727[/C][C]137.269085725889[/C][C]121.556668342592[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]16685.8714285714[/C][C]134.296228132657[/C][C]124.2467615106[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]16686.3875[/C][C]130.683512201724[/C][C]127.685483951814[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]16689.9894736842[/C][C]127.035209094877[/C][C]131.380816331157[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]16690.6027777778[/C][C]123.903657752874[/C][C]134.706295846949[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]16690.85[/C][C]119.640615607126[/C][C]139.508225658159[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]16691.5375[/C][C]115.618507468109[/C][C]144.367349704838[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]16688.46[/C][C]112.38123780905[/C][C]148.498631313848[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]16687.0607142857[/C][C]109.238163106202[/C][C]152.758525407119[/C][/ROW]
[ROW][C]Median[/C][C]16772.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]17083.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]16650.6790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]16685.8714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]16650.6790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]16685.8714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]16685.8714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]16650.6790697674[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]16685.8714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]16685.9727272727[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=163639&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=163639&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 Mean16792.0892857143234.10225428623871.7297205740808
Geometric Mean16656.4401155816
Harmonic Mean16520.7413753382
Quadratic Mean16926.9897918306
Winsorized Mean ( 1 / 28 )16791.4964285714233.2529195697271.9883655027624
Winsorized Mean ( 2 / 28 )16786.105952381231.92737700679772.3765610124112
Winsorized Mean ( 3 / 28 )16770.1773809524226.03521097127274.1927654054032
Winsorized Mean ( 4 / 28 )16769.9773809524223.36791928926775.0778242207414
Winsorized Mean ( 5 / 28 )16793.8702380952217.98636710663477.0409198566077
Winsorized Mean ( 6 / 28 )16809.705952381213.97321559444778.5598604277701
Winsorized Mean ( 7 / 28 )16810.755952381212.77128835548879.0085733949889
Winsorized Mean ( 8 / 28 )16783.4321428571201.87504103302383.1377274623647
Winsorized Mean ( 9 / 28 )16786.4200.75987016944783.6143198629876
Winsorized Mean ( 10 / 28 )16787.0904761905195.33030395658685.942069080697
Winsorized Mean ( 11 / 28 )16779.6654761905191.56116114207887.5942982186523
Winsorized Mean ( 12 / 28 )16762.0226190476180.39529502738892.9182915580075
Winsorized Mean ( 13 / 28 )16792.355952381175.79575400632795.5219655178738
Winsorized Mean ( 14 / 28 )16790.305952381173.23320146369496.9231406596144
Winsorized Mean ( 15 / 28 )16790.9666666667170.02086426868598.7582714562128
Winsorized Mean ( 16 / 28 )16820.9857142857165.65891313907101.539877302977
Winsorized Mean ( 17 / 28 )16768.2452380952156.408512045506107.208009454221
Winsorized Mean ( 18 / 28 )16757.1880952381152.949613574578109.560185891332
Winsorized Mean ( 19 / 28 )16737.0571428571148.509132810314112.700524379432
Winsorized Mean ( 20 / 28 )16686.9857142857135.241802321154123.386300891345
Winsorized Mean ( 21 / 28 )16680.7107142857133.239545148318125.193392815303
Winsorized Mean ( 22 / 28 )16650.5392857143127.572452702452130.518297116618
Winsorized Mean ( 23 / 28 )16683.944047619119.55350533481139.552111005826
Winsorized Mean ( 24 / 28 )16688.2011904762118.647870386042140.653187757843
Winsorized Mean ( 25 / 28 )16684.3023809524111.09104243908150.185847703264
Winsorized Mean ( 26 / 28 )16720.1142857143101.821204216329164.210533693855
Winsorized Mean ( 27 / 28 )16701.053571428695.8587000743184174.225746421351
Winsorized Mean ( 28 / 28 )16704.420238095292.5864161436814180.419773589381
Trimmed Mean ( 1 / 28 )16784.9817073171227.37186353503773.8217185114929
Trimmed Mean ( 2 / 28 )16778.14125220.55144214432776.0735957419882
Trimmed Mean ( 3 / 28 )16773.8525641026213.44187352931878.5874500009883
Trimmed Mean ( 4 / 28 )16775.2065789474207.78100599020180.7350339796625
Trimmed Mean ( 5 / 28 )16776.6905405405202.10050750990383.0116200461221
Trimmed Mean ( 6 / 28 )16772.6819444444197.05670729356985.116016474674
Trimmed Mean ( 7 / 28 )16765.2771428571192.16834291129587.2426586443326
Trimmed Mean ( 8 / 28 )16757.2514705882186.65211276752989.7779897699794
Trimmed Mean ( 9 / 28 )16753.0863636364182.60119118025891.7468624128428
Trimmed Mean ( 10 / 28 )16748.228125177.96625493106994.1090103373082
Trimmed Mean ( 11 / 28 )16742.9629032258173.50729032232896.4971723788784
Trimmed Mean ( 12 / 28 )16738.2916666667168.85863410670699.1260633796751
Trimmed Mean ( 13 / 28 )16735.4275862069165.394430716385101.184952321064
Trimmed Mean ( 14 / 28 )16728.8589285714161.964260924231103.28734767232
Trimmed Mean ( 15 / 28 )16722.0314814815158.165771267766105.724717474883
Trimmed Mean ( 16 / 28 )16714.6076923077154.011964649666108.527981772901
Trimmed Mean ( 17 / 28 )16703.438149.573900290397111.673480250033
Trimmed Mean ( 18 / 28 )16696.7666666667145.835602373432114.4903329155
Trimmed Mean ( 19 / 28 )16690.6369565217141.705232137208117.784196848574
Trimmed Mean ( 20 / 28 )16685.9727272727137.269085725889121.556668342592
Trimmed Mean ( 21 / 28 )16685.8714285714134.296228132657124.2467615106
Trimmed Mean ( 22 / 28 )16686.3875130.683512201724127.685483951814
Trimmed Mean ( 23 / 28 )16689.9894736842127.035209094877131.380816331157
Trimmed Mean ( 24 / 28 )16690.6027777778123.903657752874134.706295846949
Trimmed Mean ( 25 / 28 )16690.85119.640615607126139.508225658159
Trimmed Mean ( 26 / 28 )16691.5375115.618507468109144.367349704838
Trimmed Mean ( 27 / 28 )16688.46112.38123780905148.498631313848
Trimmed Mean ( 28 / 28 )16687.0607142857109.238163106202152.758525407119
Median16772.7
Midrange17083.5
Midmean - Weighted Average at Xnp16650.6790697674
Midmean - Weighted Average at X(n+1)p16685.8714285714
Midmean - Empirical Distribution Function16650.6790697674
Midmean - Empirical Distribution Function - Averaging16685.8714285714
Midmean - Empirical Distribution Function - Interpolation16685.8714285714
Midmean - Closest Observation16650.6790697674
Midmean - True Basic - Statistics Graphics Toolkit16685.8714285714
Midmean - MS Excel (old versions)16685.9727272727
Number of observations84



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')