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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 29 Jul 2010 12:32:48 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jul/29/t1280406760v2okhzvf8c32pbb.htm/, Retrieved Mon, 29 Apr 2024 07:31:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78173, Retrieved Mon, 29 Apr 2024 07:31:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVan de Walle Mathias
Estimated Impact162
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [tijdreeks 1 - stap 2] [2010-07-17 10:32:38] [2b5a188751227050025c4bb07404e527]
- RMPD  [Harrell-Davis Quantiles] [tijdreeks 2 - stap 6] [2010-07-29 11:37:00] [2b5a188751227050025c4bb07404e527]
- RMP       [Central Tendency] [tijdreeks 2 - stap 9] [2010-07-29 12:32:48] [589929edeb20bd59f78e9be1ffd92c80] [Current]
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Dataseries X:
239
238
237
235
233
232
233
235
236
236
237
239
238
237
244
230
237
244
239
240
230
228
231
228
225
227
238
214
222
233
228
218
203
209
207
203
195
199
207
182
181
189
186
174
153
158
153
147
143
156
168
142
146
150
145
133
111
115
109
105
96
112
127
107
116
125
120
107
86
87
79
83
75
89
104
86
98
98
85
74
49
54
47
56




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78173&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78173&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78173&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean168.9285714285716.8179504248759324.7770313512723
Geometric Mean155.03448878726
Harmonic Mean138.971428473394
Quadratic Mean179.986309003133
Winsorized Mean ( 1 / 28 )168.9523809523816.8128600166869824.7990389555282
Winsorized Mean ( 2 / 28 )168.976190476196.7757281755818424.9384547457411
Winsorized Mean ( 3 / 28 )169.0119047619056.7567457218931225.0138027562995
Winsorized Mean ( 4 / 28 )169.8690476190486.5951872210974225.7565163693385
Winsorized Mean ( 5 / 28 )169.9285714285716.5848054749070125.8061642179295
Winsorized Mean ( 6 / 28 )170.1428571428576.5269673794091526.0676738908812
Winsorized Mean ( 7 / 28 )170.476190476196.4717816402520826.3414620505568
Winsorized Mean ( 8 / 28 )170.6666666666676.4410102560967326.4968785766367
Winsorized Mean ( 9 / 28 )170.6666666666676.4104747303834726.6230932722915
Winsorized Mean ( 10 / 28 )170.6666666666676.4104747303834726.6230932722915
Winsorized Mean ( 11 / 28 )170.7976190476196.3897099704131226.7301050968635
Winsorized Mean ( 12 / 28 )171.0833333333336.3448699543050926.9640409599334
Winsorized Mean ( 13 / 28 )172.0119047619056.1604920331527927.9217802468082
Winsorized Mean ( 14 / 28 )172.3452380952386.1112861284120528.2011403939976
Winsorized Mean ( 15 / 28 )172.1666666666676.0889805129536628.2751219683493
Winsorized Mean ( 16 / 28 )173.3095238095245.924534404883829.2528512732847
Winsorized Mean ( 17 / 28 )173.1071428571435.845692616116429.6127686187076
Winsorized Mean ( 18 / 28 )173.5357142857145.7859219025950629.9927508886494
Winsorized Mean ( 19 / 28 )173.5357142857145.7859219025950629.9927508886494
Winsorized Mean ( 20 / 28 )173.773809523815.6908637106783630.5355774375232
Winsorized Mean ( 21 / 28 )174.023809523815.5918753093376131.1208315452269
Winsorized Mean ( 22 / 28 )174.023809523815.524315836292831.5014229238189
Winsorized Mean ( 23 / 28 )174.8452380952385.4140521263413232.2947090303311
Winsorized Mean ( 24 / 28 )174.5595238095245.3062912895102732.8967096387266
Winsorized Mean ( 25 / 28 )175.755.149483065924434.1296393735107
Winsorized Mean ( 26 / 28 )177.2976190476194.9500018765362335.817687239279
Winsorized Mean ( 27 / 28 )177.6190476190484.828852397786236.782869507562
Winsorized Mean ( 28 / 28 )178.9523809523814.4971433771632539.7924562203445
Trimmed Mean ( 1 / 28 )169.56.7604124692203325.0724346734347
Trimmed Mean ( 2 / 28 )170.0756.6971507024738225.395128100847
Trimmed Mean ( 3 / 28 )170.6666666666676.6433992906308225.6896596456813
Trimmed Mean ( 4 / 28 )171.2763157894746.5858327127839826.0067820212019
Trimmed Mean ( 5 / 28 )171.6756756756766.5698510374187326.1308322970937
Trimmed Mean ( 6 / 28 )172.0833333333336.5493716025361126.2747853957008
Trimmed Mean ( 7 / 28 )172.4714285714296.5347525002538626.392954984099
Trimmed Mean ( 8 / 28 )172.8235294117656.524551497692126.4881853523413
Trimmed Mean ( 9 / 28 )173.1666666666676.5130166719720726.587781881761
Trimmed Mean ( 10 / 28 )173.531256.4989685059911726.7013526592763
Trimmed Mean ( 11 / 28 )173.919354838716.4757326105638626.8570932893361
Trimmed Mean ( 12 / 28 )174.3166666666676.4452273616901627.045852207292
Trimmed Mean ( 13 / 28 )174.7068965517246.4100178996709127.2552899673952
Trimmed Mean ( 14 / 28 )175.0178571428576.3929999802659927.3764832915853
Trimmed Mean ( 15 / 28 )175.3148148148156.3725928752690727.5107508429075
Trimmed Mean ( 16 / 28 )175.6538461538466.34240942598627.6951288313493
Trimmed Mean ( 17 / 28 )175.96.3252167826042727.8093235450464
Trimmed Mean ( 18 / 28 )176.18756.3066339220938627.9368522378899
Trimmed Mean ( 19 / 28 )176.456521739136.2828427149969728.085459041961
Trimmed Mean ( 20 / 28 )176.756.24069074143528.3221853674739
Trimmed Mean ( 21 / 28 )177.0476190476196.1927941697948728.589294943979
Trimmed Mean ( 22 / 28 )177.356.137479437534128.8962271572604
Trimmed Mean ( 23 / 28 )177.6842105263166.0648586993349529.2973372233388
Trimmed Mean ( 24 / 28 )177.9722222222225.9792612633779429.7649181701216
Trimmed Mean ( 25 / 28 )178.3235294117655.8729447936651930.3635630295916
Trimmed Mean ( 26 / 28 )178.593755.7526044899105231.0457203016886
Trimmed Mean ( 27 / 28 )178.7333333333335.6236228624985931.7825959712244
Trimmed Mean ( 28 / 28 )178.8571428571435.4563477633475732.7796450326345
Median181.5
Midrange145.5
Midmean - Weighted Average at Xnp175.46511627907
Midmean - Weighted Average at X(n+1)p177.047619047619
Midmean - Empirical Distribution Function175.46511627907
Midmean - Empirical Distribution Function - Averaging177.047619047619
Midmean - Empirical Distribution Function - Interpolation177.047619047619
Midmean - Closest Observation175.46511627907
Midmean - True Basic - Statistics Graphics Toolkit177.047619047619
Midmean - MS Excel (old versions)176.75
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 168.928571428571 & 6.81795042487593 & 24.7770313512723 \tabularnewline
Geometric Mean & 155.03448878726 &  &  \tabularnewline
Harmonic Mean & 138.971428473394 &  &  \tabularnewline
Quadratic Mean & 179.986309003133 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 168.952380952381 & 6.81286001668698 & 24.7990389555282 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 168.97619047619 & 6.77572817558184 & 24.9384547457411 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 169.011904761905 & 6.75674572189312 & 25.0138027562995 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 169.869047619048 & 6.59518722109742 & 25.7565163693385 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 169.928571428571 & 6.58480547490701 & 25.8061642179295 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 170.142857142857 & 6.52696737940915 & 26.0676738908812 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 170.47619047619 & 6.47178164025208 & 26.3414620505568 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 170.666666666667 & 6.44101025609673 & 26.4968785766367 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 170.666666666667 & 6.41047473038347 & 26.6230932722915 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 170.666666666667 & 6.41047473038347 & 26.6230932722915 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 170.797619047619 & 6.38970997041312 & 26.7301050968635 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 171.083333333333 & 6.34486995430509 & 26.9640409599334 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 172.011904761905 & 6.16049203315279 & 27.9217802468082 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 172.345238095238 & 6.11128612841205 & 28.2011403939976 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 172.166666666667 & 6.08898051295366 & 28.2751219683493 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 173.309523809524 & 5.9245344048838 & 29.2528512732847 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 173.107142857143 & 5.8456926161164 & 29.6127686187076 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 173.535714285714 & 5.78592190259506 & 29.9927508886494 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 173.535714285714 & 5.78592190259506 & 29.9927508886494 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 173.77380952381 & 5.69086371067836 & 30.5355774375232 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 174.02380952381 & 5.59187530933761 & 31.1208315452269 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 174.02380952381 & 5.5243158362928 & 31.5014229238189 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 174.845238095238 & 5.41405212634132 & 32.2947090303311 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 174.559523809524 & 5.30629128951027 & 32.8967096387266 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 175.75 & 5.1494830659244 & 34.1296393735107 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 177.297619047619 & 4.95000187653623 & 35.817687239279 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 177.619047619048 & 4.8288523977862 & 36.782869507562 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 178.952380952381 & 4.49714337716325 & 39.7924562203445 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 169.5 & 6.76041246922033 & 25.0724346734347 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 170.075 & 6.69715070247382 & 25.395128100847 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 170.666666666667 & 6.64339929063082 & 25.6896596456813 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 171.276315789474 & 6.58583271278398 & 26.0067820212019 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 171.675675675676 & 6.56985103741873 & 26.1308322970937 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 172.083333333333 & 6.54937160253611 & 26.2747853957008 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 172.471428571429 & 6.53475250025386 & 26.392954984099 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 172.823529411765 & 6.5245514976921 & 26.4881853523413 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 173.166666666667 & 6.51301667197207 & 26.587781881761 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 173.53125 & 6.49896850599117 & 26.7013526592763 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 173.91935483871 & 6.47573261056386 & 26.8570932893361 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 174.316666666667 & 6.44522736169016 & 27.045852207292 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 174.706896551724 & 6.41001789967091 & 27.2552899673952 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 175.017857142857 & 6.39299998026599 & 27.3764832915853 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 175.314814814815 & 6.37259287526907 & 27.5107508429075 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 175.653846153846 & 6.342409425986 & 27.6951288313493 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 175.9 & 6.32521678260427 & 27.8093235450464 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 176.1875 & 6.30663392209386 & 27.9368522378899 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 176.45652173913 & 6.28284271499697 & 28.085459041961 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 176.75 & 6.240690741435 & 28.3221853674739 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 177.047619047619 & 6.19279416979487 & 28.589294943979 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 177.35 & 6.1374794375341 & 28.8962271572604 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 177.684210526316 & 6.06485869933495 & 29.2973372233388 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 177.972222222222 & 5.97926126337794 & 29.7649181701216 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 178.323529411765 & 5.87294479366519 & 30.3635630295916 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 178.59375 & 5.75260448991052 & 31.0457203016886 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 178.733333333333 & 5.62362286249859 & 31.7825959712244 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 178.857142857143 & 5.45634776334757 & 32.7796450326345 \tabularnewline
Median & 181.5 &  &  \tabularnewline
Midrange & 145.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 175.46511627907 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 177.047619047619 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 175.46511627907 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 177.047619047619 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 177.047619047619 &  &  \tabularnewline
Midmean - Closest Observation & 175.46511627907 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 177.047619047619 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 176.75 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78173&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]168.928571428571[/C][C]6.81795042487593[/C][C]24.7770313512723[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]155.03448878726[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]138.971428473394[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]179.986309003133[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]168.952380952381[/C][C]6.81286001668698[/C][C]24.7990389555282[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]168.97619047619[/C][C]6.77572817558184[/C][C]24.9384547457411[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]169.011904761905[/C][C]6.75674572189312[/C][C]25.0138027562995[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]169.869047619048[/C][C]6.59518722109742[/C][C]25.7565163693385[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]169.928571428571[/C][C]6.58480547490701[/C][C]25.8061642179295[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]170.142857142857[/C][C]6.52696737940915[/C][C]26.0676738908812[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]170.47619047619[/C][C]6.47178164025208[/C][C]26.3414620505568[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]170.666666666667[/C][C]6.44101025609673[/C][C]26.4968785766367[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]170.666666666667[/C][C]6.41047473038347[/C][C]26.6230932722915[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]170.666666666667[/C][C]6.41047473038347[/C][C]26.6230932722915[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]170.797619047619[/C][C]6.38970997041312[/C][C]26.7301050968635[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]171.083333333333[/C][C]6.34486995430509[/C][C]26.9640409599334[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]172.011904761905[/C][C]6.16049203315279[/C][C]27.9217802468082[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]172.345238095238[/C][C]6.11128612841205[/C][C]28.2011403939976[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]172.166666666667[/C][C]6.08898051295366[/C][C]28.2751219683493[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]173.309523809524[/C][C]5.9245344048838[/C][C]29.2528512732847[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]173.107142857143[/C][C]5.8456926161164[/C][C]29.6127686187076[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]173.535714285714[/C][C]5.78592190259506[/C][C]29.9927508886494[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]173.535714285714[/C][C]5.78592190259506[/C][C]29.9927508886494[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]173.77380952381[/C][C]5.69086371067836[/C][C]30.5355774375232[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]174.02380952381[/C][C]5.59187530933761[/C][C]31.1208315452269[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]174.02380952381[/C][C]5.5243158362928[/C][C]31.5014229238189[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]174.845238095238[/C][C]5.41405212634132[/C][C]32.2947090303311[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]174.559523809524[/C][C]5.30629128951027[/C][C]32.8967096387266[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]175.75[/C][C]5.1494830659244[/C][C]34.1296393735107[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]177.297619047619[/C][C]4.95000187653623[/C][C]35.817687239279[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]177.619047619048[/C][C]4.8288523977862[/C][C]36.782869507562[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]178.952380952381[/C][C]4.49714337716325[/C][C]39.7924562203445[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]169.5[/C][C]6.76041246922033[/C][C]25.0724346734347[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]170.075[/C][C]6.69715070247382[/C][C]25.395128100847[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]170.666666666667[/C][C]6.64339929063082[/C][C]25.6896596456813[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]171.276315789474[/C][C]6.58583271278398[/C][C]26.0067820212019[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]171.675675675676[/C][C]6.56985103741873[/C][C]26.1308322970937[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]172.083333333333[/C][C]6.54937160253611[/C][C]26.2747853957008[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]172.471428571429[/C][C]6.53475250025386[/C][C]26.392954984099[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]172.823529411765[/C][C]6.5245514976921[/C][C]26.4881853523413[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]173.166666666667[/C][C]6.51301667197207[/C][C]26.587781881761[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]173.53125[/C][C]6.49896850599117[/C][C]26.7013526592763[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]173.91935483871[/C][C]6.47573261056386[/C][C]26.8570932893361[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]174.316666666667[/C][C]6.44522736169016[/C][C]27.045852207292[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]174.706896551724[/C][C]6.41001789967091[/C][C]27.2552899673952[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]175.017857142857[/C][C]6.39299998026599[/C][C]27.3764832915853[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]175.314814814815[/C][C]6.37259287526907[/C][C]27.5107508429075[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]175.653846153846[/C][C]6.342409425986[/C][C]27.6951288313493[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]175.9[/C][C]6.32521678260427[/C][C]27.8093235450464[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]176.1875[/C][C]6.30663392209386[/C][C]27.9368522378899[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]176.45652173913[/C][C]6.28284271499697[/C][C]28.085459041961[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]176.75[/C][C]6.240690741435[/C][C]28.3221853674739[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]177.047619047619[/C][C]6.19279416979487[/C][C]28.589294943979[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]177.35[/C][C]6.1374794375341[/C][C]28.8962271572604[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]177.684210526316[/C][C]6.06485869933495[/C][C]29.2973372233388[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]177.972222222222[/C][C]5.97926126337794[/C][C]29.7649181701216[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]178.323529411765[/C][C]5.87294479366519[/C][C]30.3635630295916[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]178.59375[/C][C]5.75260448991052[/C][C]31.0457203016886[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]178.733333333333[/C][C]5.62362286249859[/C][C]31.7825959712244[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]178.857142857143[/C][C]5.45634776334757[/C][C]32.7796450326345[/C][/ROW]
[ROW][C]Median[/C][C]181.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]145.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]175.46511627907[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]177.047619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]175.46511627907[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]177.047619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]177.047619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]175.46511627907[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]177.047619047619[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]176.75[/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=78173&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78173&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 Mean168.9285714285716.8179504248759324.7770313512723
Geometric Mean155.03448878726
Harmonic Mean138.971428473394
Quadratic Mean179.986309003133
Winsorized Mean ( 1 / 28 )168.9523809523816.8128600166869824.7990389555282
Winsorized Mean ( 2 / 28 )168.976190476196.7757281755818424.9384547457411
Winsorized Mean ( 3 / 28 )169.0119047619056.7567457218931225.0138027562995
Winsorized Mean ( 4 / 28 )169.8690476190486.5951872210974225.7565163693385
Winsorized Mean ( 5 / 28 )169.9285714285716.5848054749070125.8061642179295
Winsorized Mean ( 6 / 28 )170.1428571428576.5269673794091526.0676738908812
Winsorized Mean ( 7 / 28 )170.476190476196.4717816402520826.3414620505568
Winsorized Mean ( 8 / 28 )170.6666666666676.4410102560967326.4968785766367
Winsorized Mean ( 9 / 28 )170.6666666666676.4104747303834726.6230932722915
Winsorized Mean ( 10 / 28 )170.6666666666676.4104747303834726.6230932722915
Winsorized Mean ( 11 / 28 )170.7976190476196.3897099704131226.7301050968635
Winsorized Mean ( 12 / 28 )171.0833333333336.3448699543050926.9640409599334
Winsorized Mean ( 13 / 28 )172.0119047619056.1604920331527927.9217802468082
Winsorized Mean ( 14 / 28 )172.3452380952386.1112861284120528.2011403939976
Winsorized Mean ( 15 / 28 )172.1666666666676.0889805129536628.2751219683493
Winsorized Mean ( 16 / 28 )173.3095238095245.924534404883829.2528512732847
Winsorized Mean ( 17 / 28 )173.1071428571435.845692616116429.6127686187076
Winsorized Mean ( 18 / 28 )173.5357142857145.7859219025950629.9927508886494
Winsorized Mean ( 19 / 28 )173.5357142857145.7859219025950629.9927508886494
Winsorized Mean ( 20 / 28 )173.773809523815.6908637106783630.5355774375232
Winsorized Mean ( 21 / 28 )174.023809523815.5918753093376131.1208315452269
Winsorized Mean ( 22 / 28 )174.023809523815.524315836292831.5014229238189
Winsorized Mean ( 23 / 28 )174.8452380952385.4140521263413232.2947090303311
Winsorized Mean ( 24 / 28 )174.5595238095245.3062912895102732.8967096387266
Winsorized Mean ( 25 / 28 )175.755.149483065924434.1296393735107
Winsorized Mean ( 26 / 28 )177.2976190476194.9500018765362335.817687239279
Winsorized Mean ( 27 / 28 )177.6190476190484.828852397786236.782869507562
Winsorized Mean ( 28 / 28 )178.9523809523814.4971433771632539.7924562203445
Trimmed Mean ( 1 / 28 )169.56.7604124692203325.0724346734347
Trimmed Mean ( 2 / 28 )170.0756.6971507024738225.395128100847
Trimmed Mean ( 3 / 28 )170.6666666666676.6433992906308225.6896596456813
Trimmed Mean ( 4 / 28 )171.2763157894746.5858327127839826.0067820212019
Trimmed Mean ( 5 / 28 )171.6756756756766.5698510374187326.1308322970937
Trimmed Mean ( 6 / 28 )172.0833333333336.5493716025361126.2747853957008
Trimmed Mean ( 7 / 28 )172.4714285714296.5347525002538626.392954984099
Trimmed Mean ( 8 / 28 )172.8235294117656.524551497692126.4881853523413
Trimmed Mean ( 9 / 28 )173.1666666666676.5130166719720726.587781881761
Trimmed Mean ( 10 / 28 )173.531256.4989685059911726.7013526592763
Trimmed Mean ( 11 / 28 )173.919354838716.4757326105638626.8570932893361
Trimmed Mean ( 12 / 28 )174.3166666666676.4452273616901627.045852207292
Trimmed Mean ( 13 / 28 )174.7068965517246.4100178996709127.2552899673952
Trimmed Mean ( 14 / 28 )175.0178571428576.3929999802659927.3764832915853
Trimmed Mean ( 15 / 28 )175.3148148148156.3725928752690727.5107508429075
Trimmed Mean ( 16 / 28 )175.6538461538466.34240942598627.6951288313493
Trimmed Mean ( 17 / 28 )175.96.3252167826042727.8093235450464
Trimmed Mean ( 18 / 28 )176.18756.3066339220938627.9368522378899
Trimmed Mean ( 19 / 28 )176.456521739136.2828427149969728.085459041961
Trimmed Mean ( 20 / 28 )176.756.24069074143528.3221853674739
Trimmed Mean ( 21 / 28 )177.0476190476196.1927941697948728.589294943979
Trimmed Mean ( 22 / 28 )177.356.137479437534128.8962271572604
Trimmed Mean ( 23 / 28 )177.6842105263166.0648586993349529.2973372233388
Trimmed Mean ( 24 / 28 )177.9722222222225.9792612633779429.7649181701216
Trimmed Mean ( 25 / 28 )178.3235294117655.8729447936651930.3635630295916
Trimmed Mean ( 26 / 28 )178.593755.7526044899105231.0457203016886
Trimmed Mean ( 27 / 28 )178.7333333333335.6236228624985931.7825959712244
Trimmed Mean ( 28 / 28 )178.8571428571435.4563477633475732.7796450326345
Median181.5
Midrange145.5
Midmean - Weighted Average at Xnp175.46511627907
Midmean - Weighted Average at X(n+1)p177.047619047619
Midmean - Empirical Distribution Function175.46511627907
Midmean - Empirical Distribution Function - Averaging177.047619047619
Midmean - Empirical Distribution Function - Interpolation177.047619047619
Midmean - Closest Observation175.46511627907
Midmean - True Basic - Statistics Graphics Toolkit177.047619047619
Midmean - MS Excel (old versions)176.75
Number of observations84



Parameters (Session):
par1 = 0.1 ; par2 = 0.99 ; par3 = 0.1 ;
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')