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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 14 Oct 2013 06:06:38 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/14/t1381745485hvnnho89cnz1h4i.htm/, Retrieved Sun, 28 Apr 2024 17:50:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=215455, Retrieved Sun, 28 Apr 2024 17:50:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2013-10-14 10:06:38] [edfef9daf94f6afee2f7e041aec7fc2a] [Current]
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Dataseries X:
93,61
93,17
91,60
90,30
90,88
91,06
92,05
95,29
96,44
96,49
96,52
96,09
99,16
98,09
99,41
99,87
100,06
99,65
99,92
98,44
102,64
112,33
115,63
118,29
121,43
129,96
147,73
154,10
150,09
144,14
141,54
136,68
129,32
118,99
109,61
106,22
104,97
102,45
101,91
101,77
102,67
103,45
101,41
102,45
102,17
101,40
101,68
100,61
97,93
98,30
99,79
101,62
101,55
102,43
102,09
102,01
102,26
101,24
100,91
100,67
100,33
99,99
99,23
98,17
97,38
96,70
98,65
100,68
101,07
101,12
101,13
99,88
99,20
99,91
103,62
108,05
113,96
117,39
126,04
139,67
145,04
142,37
137,72
132,46




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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 & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=215455&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]8 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=215455&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=215455&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 time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean107.7892857142861.7317028038472462.2446793265077
Geometric Mean106.768365518563
Harmonic Mean105.86958275777
Quadratic Mean108.937734815199
Winsorized Mean ( 1 / 28 )107.7484523809521.7160848890303262.7873673789155
Winsorized Mean ( 2 / 28 )107.6965476190481.699249821774363.3788782785303
Winsorized Mean ( 3 / 28 )107.6197619047621.6703922757919964.4278373795375
Winsorized Mean ( 4 / 28 )107.5983333333331.656463079005864.9566746745197
Winsorized Mean ( 5 / 28 )107.5596428571431.6214967573130566.3335540894809
Winsorized Mean ( 6 / 28 )107.5317857142861.6029270966356967.0846390581201
Winsorized Mean ( 7 / 28 )107.5159523809521.5495322996469369.3860672703955
Winsorized Mean ( 8 / 28 )107.4064285714291.4965516362132271.7692767642839
Winsorized Mean ( 9 / 28 )107.33251.4661299010773473.2080424259338
Winsorized Mean ( 10 / 28 )106.8360714285711.3473246265816979.2949741441498
Winsorized Mean ( 11 / 28 )106.5126190476191.2730933244304483.6644234979955
Winsorized Mean ( 12 / 28 )106.4469047619051.2504506471224785.1268340792657
Winsorized Mean ( 13 / 28 )106.0445238095241.1305321225990993.8005401967067
Winsorized Mean ( 14 / 28 )105.3678571428570.962565703197817109.465625871362
Winsorized Mean ( 15 / 28 )104.9607142857140.873865082939985120.110891640836
Winsorized Mean ( 16 / 28 )104.8426190476190.846767098214552123.815178068072
Winsorized Mean ( 17 / 28 )104.6867857142860.809621912295857129.303300867221
Winsorized Mean ( 18 / 28 )104.3396428571430.736221853459173141.723099317004
Winsorized Mean ( 19 / 28 )104.0094047619050.66250306294425156.994602107458
Winsorized Mean ( 20 / 28 )103.7427380952380.581106560872147178.526186211935
Winsorized Mean ( 21 / 28 )103.0727380952380.461253012658426223.462471282691
Winsorized Mean ( 22 / 28 )102.6720238095240.391674062005665262.136387801035
Winsorized Mean ( 23 / 28 )102.2202380952380.305094248964651335.044788428908
Winsorized Mean ( 24 / 28 )101.9316666666670.24205652373117421.106876590002
Winsorized Mean ( 25 / 28 )101.5715476190480.178682747383446568.446305569051
Winsorized Mean ( 26 / 28 )101.543690476190.168491908497026602.662118210754
Winsorized Mean ( 27 / 28 )101.296190476190.135505566671713747.542650565782
Winsorized Mean ( 28 / 28 )101.296190476190.133028938047547761.459814405083
Trimmed Mean ( 1 / 28 )107.4378048780491.6665270223737864.4680844868723
Trimmed Mean ( 2 / 28 )107.1116251.6081785774059866.6043103078594
Trimmed Mean ( 3 / 28 )106.7966666666671.5500196970235868.9001997018121
Trimmed Mean ( 4 / 28 )106.4934210526321.4943931298049171.2619851688784
Trimmed Mean ( 5 / 28 )106.1798648648651.4332067602649474.0855177415131
Trimmed Mean ( 6 / 28 )105.8579166666671.3710698268754377.2082607257932
Trimmed Mean ( 7 / 28 )105.5231428571431.3012683658464481.0925291252297
Trimmed Mean ( 8 / 28 )105.1714705882351.2306002101786585.4635564973348
Trimmed Mean ( 9 / 28 )104.8159090909091.1576518709950490.5418215243039
Trimmed Mean ( 10 / 28 )104.448906251.0745039487929397.2066285725009
Trimmed Mean ( 11 / 28 )104.1254838709681.00247313633613103.868602655558
Trimmed Mean ( 12 / 28 )103.8216666666670.931241506742194111.487370263242
Trimmed Mean ( 13 / 28 )103.5048275862070.845474849892965122.422124796865
Trimmed Mean ( 14 / 28 )103.2117857142860.76723995582508134.523475909558
Trimmed Mean ( 15 / 28 )102.9722222222220.711825914982138144.659277015513
Trimmed Mean ( 16 / 28 )102.7580769230770.663465468762267154.880821627052
Trimmed Mean ( 17 / 28 )102.53920.606995937854141168.92897234617
Trimmed Mean ( 18 / 28 )102.3181250.541629130416543188.908090894801
Trimmed Mean ( 19 / 28 )102.1130434782610.475305329740506214.836731441681
Trimmed Mean ( 20 / 28 )101.92250.407192097582993250.305692583404
Trimmed Mean ( 21 / 28 )101.7404761904760.337687695023982301.285707740256
Trimmed Mean ( 22 / 28 )101.607250.285629531328024355.730899139108
Trimmed Mean ( 23 / 28 )101.5002631578950.238051743434531426.378995144009
Trimmed Mean ( 24 / 28 )101.4272222222220.204781963457037495.293728558773
Trimmed Mean ( 25 / 28 )101.3752941176470.181687100174223557.966382976208
Trimmed Mean ( 26 / 28 )101.35468750.172364945012474588.023785768416
Trimmed Mean ( 27 / 28 )101.3343333333330.162115811685559625.07371908844
Trimmed Mean ( 28 / 28 )101.3385714285710.158386970268132639.816338787314
Median101.405
Midrange122.2
Midmean - Weighted Average at Xnp101.680465116279
Midmean - Weighted Average at X(n+1)p101.740476190476
Midmean - Empirical Distribution Function101.680465116279
Midmean - Empirical Distribution Function - Averaging101.740476190476
Midmean - Empirical Distribution Function - Interpolation101.740476190476
Midmean - Closest Observation101.680465116279
Midmean - True Basic - Statistics Graphics Toolkit101.740476190476
Midmean - MS Excel (old versions)101.9225
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 107.789285714286 & 1.73170280384724 & 62.2446793265077 \tabularnewline
Geometric Mean & 106.768365518563 &  &  \tabularnewline
Harmonic Mean & 105.86958275777 &  &  \tabularnewline
Quadratic Mean & 108.937734815199 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 107.748452380952 & 1.71608488903032 & 62.7873673789155 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 107.696547619048 & 1.6992498217743 & 63.3788782785303 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 107.619761904762 & 1.67039227579199 & 64.4278373795375 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 107.598333333333 & 1.6564630790058 & 64.9566746745197 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 107.559642857143 & 1.62149675731305 & 66.3335540894809 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 107.531785714286 & 1.60292709663569 & 67.0846390581201 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 107.515952380952 & 1.54953229964693 & 69.3860672703955 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 107.406428571429 & 1.49655163621322 & 71.7692767642839 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 107.3325 & 1.46612990107734 & 73.2080424259338 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 106.836071428571 & 1.34732462658169 & 79.2949741441498 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 106.512619047619 & 1.27309332443044 & 83.6644234979955 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 106.446904761905 & 1.25045064712247 & 85.1268340792657 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 106.044523809524 & 1.13053212259909 & 93.8005401967067 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 105.367857142857 & 0.962565703197817 & 109.465625871362 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 104.960714285714 & 0.873865082939985 & 120.110891640836 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 104.842619047619 & 0.846767098214552 & 123.815178068072 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 104.686785714286 & 0.809621912295857 & 129.303300867221 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 104.339642857143 & 0.736221853459173 & 141.723099317004 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 104.009404761905 & 0.66250306294425 & 156.994602107458 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 103.742738095238 & 0.581106560872147 & 178.526186211935 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 103.072738095238 & 0.461253012658426 & 223.462471282691 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 102.672023809524 & 0.391674062005665 & 262.136387801035 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 102.220238095238 & 0.305094248964651 & 335.044788428908 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 101.931666666667 & 0.24205652373117 & 421.106876590002 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 101.571547619048 & 0.178682747383446 & 568.446305569051 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 101.54369047619 & 0.168491908497026 & 602.662118210754 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 101.29619047619 & 0.135505566671713 & 747.542650565782 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 101.29619047619 & 0.133028938047547 & 761.459814405083 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 107.437804878049 & 1.66652702237378 & 64.4680844868723 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 107.111625 & 1.60817857740598 & 66.6043103078594 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 106.796666666667 & 1.55001969702358 & 68.9001997018121 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 106.493421052632 & 1.49439312980491 & 71.2619851688784 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 106.179864864865 & 1.43320676026494 & 74.0855177415131 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 105.857916666667 & 1.37106982687543 & 77.2082607257932 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 105.523142857143 & 1.30126836584644 & 81.0925291252297 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 105.171470588235 & 1.23060021017865 & 85.4635564973348 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 104.815909090909 & 1.15765187099504 & 90.5418215243039 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 104.44890625 & 1.07450394879293 & 97.2066285725009 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 104.125483870968 & 1.00247313633613 & 103.868602655558 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 103.821666666667 & 0.931241506742194 & 111.487370263242 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 103.504827586207 & 0.845474849892965 & 122.422124796865 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 103.211785714286 & 0.76723995582508 & 134.523475909558 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 102.972222222222 & 0.711825914982138 & 144.659277015513 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 102.758076923077 & 0.663465468762267 & 154.880821627052 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 102.5392 & 0.606995937854141 & 168.92897234617 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 102.318125 & 0.541629130416543 & 188.908090894801 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 102.113043478261 & 0.475305329740506 & 214.836731441681 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 101.9225 & 0.407192097582993 & 250.305692583404 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 101.740476190476 & 0.337687695023982 & 301.285707740256 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 101.60725 & 0.285629531328024 & 355.730899139108 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 101.500263157895 & 0.238051743434531 & 426.378995144009 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 101.427222222222 & 0.204781963457037 & 495.293728558773 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 101.375294117647 & 0.181687100174223 & 557.966382976208 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 101.3546875 & 0.172364945012474 & 588.023785768416 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 101.334333333333 & 0.162115811685559 & 625.07371908844 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 101.338571428571 & 0.158386970268132 & 639.816338787314 \tabularnewline
Median & 101.405 &  &  \tabularnewline
Midrange & 122.2 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 101.680465116279 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 101.740476190476 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 101.680465116279 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 101.740476190476 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 101.740476190476 &  &  \tabularnewline
Midmean - Closest Observation & 101.680465116279 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 101.740476190476 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 101.9225 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=215455&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]107.789285714286[/C][C]1.73170280384724[/C][C]62.2446793265077[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]106.768365518563[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]105.86958275777[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]108.937734815199[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]107.748452380952[/C][C]1.71608488903032[/C][C]62.7873673789155[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]107.696547619048[/C][C]1.6992498217743[/C][C]63.3788782785303[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]107.619761904762[/C][C]1.67039227579199[/C][C]64.4278373795375[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]107.598333333333[/C][C]1.6564630790058[/C][C]64.9566746745197[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]107.559642857143[/C][C]1.62149675731305[/C][C]66.3335540894809[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]107.531785714286[/C][C]1.60292709663569[/C][C]67.0846390581201[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]107.515952380952[/C][C]1.54953229964693[/C][C]69.3860672703955[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]107.406428571429[/C][C]1.49655163621322[/C][C]71.7692767642839[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]107.3325[/C][C]1.46612990107734[/C][C]73.2080424259338[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]106.836071428571[/C][C]1.34732462658169[/C][C]79.2949741441498[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]106.512619047619[/C][C]1.27309332443044[/C][C]83.6644234979955[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]106.446904761905[/C][C]1.25045064712247[/C][C]85.1268340792657[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]106.044523809524[/C][C]1.13053212259909[/C][C]93.8005401967067[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]105.367857142857[/C][C]0.962565703197817[/C][C]109.465625871362[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]104.960714285714[/C][C]0.873865082939985[/C][C]120.110891640836[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]104.842619047619[/C][C]0.846767098214552[/C][C]123.815178068072[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]104.686785714286[/C][C]0.809621912295857[/C][C]129.303300867221[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]104.339642857143[/C][C]0.736221853459173[/C][C]141.723099317004[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]104.009404761905[/C][C]0.66250306294425[/C][C]156.994602107458[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]103.742738095238[/C][C]0.581106560872147[/C][C]178.526186211935[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]103.072738095238[/C][C]0.461253012658426[/C][C]223.462471282691[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]102.672023809524[/C][C]0.391674062005665[/C][C]262.136387801035[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]102.220238095238[/C][C]0.305094248964651[/C][C]335.044788428908[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]101.931666666667[/C][C]0.24205652373117[/C][C]421.106876590002[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]101.571547619048[/C][C]0.178682747383446[/C][C]568.446305569051[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]101.54369047619[/C][C]0.168491908497026[/C][C]602.662118210754[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]101.29619047619[/C][C]0.135505566671713[/C][C]747.542650565782[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]101.29619047619[/C][C]0.133028938047547[/C][C]761.459814405083[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]107.437804878049[/C][C]1.66652702237378[/C][C]64.4680844868723[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]107.111625[/C][C]1.60817857740598[/C][C]66.6043103078594[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]106.796666666667[/C][C]1.55001969702358[/C][C]68.9001997018121[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]106.493421052632[/C][C]1.49439312980491[/C][C]71.2619851688784[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]106.179864864865[/C][C]1.43320676026494[/C][C]74.0855177415131[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]105.857916666667[/C][C]1.37106982687543[/C][C]77.2082607257932[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]105.523142857143[/C][C]1.30126836584644[/C][C]81.0925291252297[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]105.171470588235[/C][C]1.23060021017865[/C][C]85.4635564973348[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]104.815909090909[/C][C]1.15765187099504[/C][C]90.5418215243039[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]104.44890625[/C][C]1.07450394879293[/C][C]97.2066285725009[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]104.125483870968[/C][C]1.00247313633613[/C][C]103.868602655558[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]103.821666666667[/C][C]0.931241506742194[/C][C]111.487370263242[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]103.504827586207[/C][C]0.845474849892965[/C][C]122.422124796865[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]103.211785714286[/C][C]0.76723995582508[/C][C]134.523475909558[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]102.972222222222[/C][C]0.711825914982138[/C][C]144.659277015513[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]102.758076923077[/C][C]0.663465468762267[/C][C]154.880821627052[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]102.5392[/C][C]0.606995937854141[/C][C]168.92897234617[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]102.318125[/C][C]0.541629130416543[/C][C]188.908090894801[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]102.113043478261[/C][C]0.475305329740506[/C][C]214.836731441681[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]101.9225[/C][C]0.407192097582993[/C][C]250.305692583404[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]101.740476190476[/C][C]0.337687695023982[/C][C]301.285707740256[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]101.60725[/C][C]0.285629531328024[/C][C]355.730899139108[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]101.500263157895[/C][C]0.238051743434531[/C][C]426.378995144009[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]101.427222222222[/C][C]0.204781963457037[/C][C]495.293728558773[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]101.375294117647[/C][C]0.181687100174223[/C][C]557.966382976208[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]101.3546875[/C][C]0.172364945012474[/C][C]588.023785768416[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]101.334333333333[/C][C]0.162115811685559[/C][C]625.07371908844[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]101.338571428571[/C][C]0.158386970268132[/C][C]639.816338787314[/C][/ROW]
[ROW][C]Median[/C][C]101.405[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]122.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]101.680465116279[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]101.740476190476[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]101.680465116279[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]101.740476190476[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]101.740476190476[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]101.680465116279[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]101.740476190476[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]101.9225[/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=215455&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=215455&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 Mean107.7892857142861.7317028038472462.2446793265077
Geometric Mean106.768365518563
Harmonic Mean105.86958275777
Quadratic Mean108.937734815199
Winsorized Mean ( 1 / 28 )107.7484523809521.7160848890303262.7873673789155
Winsorized Mean ( 2 / 28 )107.6965476190481.699249821774363.3788782785303
Winsorized Mean ( 3 / 28 )107.6197619047621.6703922757919964.4278373795375
Winsorized Mean ( 4 / 28 )107.5983333333331.656463079005864.9566746745197
Winsorized Mean ( 5 / 28 )107.5596428571431.6214967573130566.3335540894809
Winsorized Mean ( 6 / 28 )107.5317857142861.6029270966356967.0846390581201
Winsorized Mean ( 7 / 28 )107.5159523809521.5495322996469369.3860672703955
Winsorized Mean ( 8 / 28 )107.4064285714291.4965516362132271.7692767642839
Winsorized Mean ( 9 / 28 )107.33251.4661299010773473.2080424259338
Winsorized Mean ( 10 / 28 )106.8360714285711.3473246265816979.2949741441498
Winsorized Mean ( 11 / 28 )106.5126190476191.2730933244304483.6644234979955
Winsorized Mean ( 12 / 28 )106.4469047619051.2504506471224785.1268340792657
Winsorized Mean ( 13 / 28 )106.0445238095241.1305321225990993.8005401967067
Winsorized Mean ( 14 / 28 )105.3678571428570.962565703197817109.465625871362
Winsorized Mean ( 15 / 28 )104.9607142857140.873865082939985120.110891640836
Winsorized Mean ( 16 / 28 )104.8426190476190.846767098214552123.815178068072
Winsorized Mean ( 17 / 28 )104.6867857142860.809621912295857129.303300867221
Winsorized Mean ( 18 / 28 )104.3396428571430.736221853459173141.723099317004
Winsorized Mean ( 19 / 28 )104.0094047619050.66250306294425156.994602107458
Winsorized Mean ( 20 / 28 )103.7427380952380.581106560872147178.526186211935
Winsorized Mean ( 21 / 28 )103.0727380952380.461253012658426223.462471282691
Winsorized Mean ( 22 / 28 )102.6720238095240.391674062005665262.136387801035
Winsorized Mean ( 23 / 28 )102.2202380952380.305094248964651335.044788428908
Winsorized Mean ( 24 / 28 )101.9316666666670.24205652373117421.106876590002
Winsorized Mean ( 25 / 28 )101.5715476190480.178682747383446568.446305569051
Winsorized Mean ( 26 / 28 )101.543690476190.168491908497026602.662118210754
Winsorized Mean ( 27 / 28 )101.296190476190.135505566671713747.542650565782
Winsorized Mean ( 28 / 28 )101.296190476190.133028938047547761.459814405083
Trimmed Mean ( 1 / 28 )107.4378048780491.6665270223737864.4680844868723
Trimmed Mean ( 2 / 28 )107.1116251.6081785774059866.6043103078594
Trimmed Mean ( 3 / 28 )106.7966666666671.5500196970235868.9001997018121
Trimmed Mean ( 4 / 28 )106.4934210526321.4943931298049171.2619851688784
Trimmed Mean ( 5 / 28 )106.1798648648651.4332067602649474.0855177415131
Trimmed Mean ( 6 / 28 )105.8579166666671.3710698268754377.2082607257932
Trimmed Mean ( 7 / 28 )105.5231428571431.3012683658464481.0925291252297
Trimmed Mean ( 8 / 28 )105.1714705882351.2306002101786585.4635564973348
Trimmed Mean ( 9 / 28 )104.8159090909091.1576518709950490.5418215243039
Trimmed Mean ( 10 / 28 )104.448906251.0745039487929397.2066285725009
Trimmed Mean ( 11 / 28 )104.1254838709681.00247313633613103.868602655558
Trimmed Mean ( 12 / 28 )103.8216666666670.931241506742194111.487370263242
Trimmed Mean ( 13 / 28 )103.5048275862070.845474849892965122.422124796865
Trimmed Mean ( 14 / 28 )103.2117857142860.76723995582508134.523475909558
Trimmed Mean ( 15 / 28 )102.9722222222220.711825914982138144.659277015513
Trimmed Mean ( 16 / 28 )102.7580769230770.663465468762267154.880821627052
Trimmed Mean ( 17 / 28 )102.53920.606995937854141168.92897234617
Trimmed Mean ( 18 / 28 )102.3181250.541629130416543188.908090894801
Trimmed Mean ( 19 / 28 )102.1130434782610.475305329740506214.836731441681
Trimmed Mean ( 20 / 28 )101.92250.407192097582993250.305692583404
Trimmed Mean ( 21 / 28 )101.7404761904760.337687695023982301.285707740256
Trimmed Mean ( 22 / 28 )101.607250.285629531328024355.730899139108
Trimmed Mean ( 23 / 28 )101.5002631578950.238051743434531426.378995144009
Trimmed Mean ( 24 / 28 )101.4272222222220.204781963457037495.293728558773
Trimmed Mean ( 25 / 28 )101.3752941176470.181687100174223557.966382976208
Trimmed Mean ( 26 / 28 )101.35468750.172364945012474588.023785768416
Trimmed Mean ( 27 / 28 )101.3343333333330.162115811685559625.07371908844
Trimmed Mean ( 28 / 28 )101.3385714285710.158386970268132639.816338787314
Median101.405
Midrange122.2
Midmean - Weighted Average at Xnp101.680465116279
Midmean - Weighted Average at X(n+1)p101.740476190476
Midmean - Empirical Distribution Function101.680465116279
Midmean - Empirical Distribution Function - Averaging101.740476190476
Midmean - Empirical Distribution Function - Interpolation101.740476190476
Midmean - Closest Observation101.680465116279
Midmean - True Basic - Statistics Graphics Toolkit101.740476190476
Midmean - MS Excel (old versions)101.9225
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')