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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 computationSat, 07 Aug 2010 11:50:12 +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/Aug/07/t1281181795ctznhvo2qvidkus.htm/, Retrieved Mon, 06 May 2024 16:29:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78493, Retrieved Mon, 06 May 2024 16:29:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsGosselin Claudia
Estimated Impact217
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Tijdsreeks B - st...] [2010-08-07 11:50:12] [f0cd0ad4d4cb2a25864ed1f6cd7bfd87] [Current]
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Dataseries X:
166
165
164
162
160
159
160
162
163
163
164
166
163
166
170
171
176
172
169
180
172
170
161
167
158
163
165
169
168
165
156
157
146
150
146
159
146
151
156
152
152
143
127
126
122
122
114
127
125
123
124
123
127
117
104
110
106
107
100
115
117
123
130
129
125
112
90
96
99
108
101
113
113
120
131
135
137
120
102
114
121
134
122
131




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78493&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78493&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78493&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean139.7023809523812.6519123401123052.6798638247842
Geometric Mean137.531037493646
Harmonic Mean135.300571763967
Quadratic Mean141.776106187588
Winsorized Mean ( 1 / 28 )139.7261904761902.6283654594942053.1608684673095
Winsorized Mean ( 2 / 28 )139.7023809523812.5994162680433153.7437511143765
Winsorized Mean ( 3 / 28 )139.7380952380952.5927498901756953.8957096353889
Winsorized Mean ( 4 / 28 )139.7380952380952.5769911255056554.2252916026927
Winsorized Mean ( 5 / 28 )139.7380952380952.5577169435206154.633917014191
Winsorized Mean ( 6 / 28 )139.8809523809522.5328255048144255.2272361894119
Winsorized Mean ( 7 / 28 )139.9642857142862.4931027304324656.1406010293074
Winsorized Mean ( 8 / 28 )140.0595238095242.4776309168187256.529615794979
Winsorized Mean ( 9 / 28 )140.0595238095242.4456426289942557.2690065789055
Winsorized Mean ( 10 / 28 )140.1785714285712.3925060325888658.590686718933
Winsorized Mean ( 11 / 28 )140.3095238095242.3359531348743660.0652135159681
Winsorized Mean ( 12 / 28 )140.4523809523812.3153188352008760.6622201733162
Winsorized Mean ( 13 / 28 )140.4523809523812.3153188352008760.6622201733162
Winsorized Mean ( 14 / 28 )140.4523809523812.2697722280595661.8795045670528
Winsorized Mean ( 15 / 28 )140.4523809523812.2697722280595661.8795045670528
Winsorized Mean ( 16 / 28 )140.6428571428572.2432817311185162.6951377492527
Winsorized Mean ( 17 / 28 )140.8452380952382.1622042873580165.1396535094915
Winsorized Mean ( 18 / 28 )140.8452380952382.1622042873580165.1396535094915
Winsorized Mean ( 19 / 28 )141.2976190476192.0454376531060069.0794064698372
Winsorized Mean ( 20 / 28 )141.2976190476192.0454376531060069.0794064698372
Winsorized Mean ( 21 / 28 )141.5476190476192.0143920469866270.2681582065239
Winsorized Mean ( 22 / 28 )141.8095238095241.9825310085323771.5295363347194
Winsorized Mean ( 23 / 28 )141.5357142857141.9475661458096672.6731231132966
Winsorized Mean ( 24 / 28 )141.5357142857141.9475661458096672.6731231132966
Winsorized Mean ( 25 / 28 )141.5357142857141.8743862203332575.5104325620525
Winsorized Mean ( 26 / 28 )141.2261904761901.8359537308128676.9225215788327
Winsorized Mean ( 27 / 28 )141.2261904761901.8359537308128676.9225215788327
Winsorized Mean ( 28 / 28 )141.2261904761901.7554399662704680.4505954004421
Trimmed Mean ( 1 / 28 )139.8170731707322.6010518364810853.754051038017
Trimmed Mean ( 2 / 28 )139.91252.5688736726827454.4645310852852
Trimmed Mean ( 3 / 28 )140.0256410256412.5482996204075854.9486567059352
Trimmed Mean ( 4 / 28 )140.1315789473682.5262372063801455.4704754539514
Trimmed Mean ( 5 / 28 )140.2432432432432.5047759497831255.9903344869574
Trimmed Mean ( 6 / 28 )140.3611111111112.4840103336850856.5058483081599
Trimmed Mean ( 7 / 28 )140.4571428571432.4647146084594756.987183171253
Trimmed Mean ( 8 / 28 )140.5441176470592.4496182196607157.373886477104
Trimmed Mean ( 9 / 28 )140.6212121212122.4334273844117957.787305683339
Trimmed Mean ( 10 / 28 )140.7031252.4187880352101558.1709198787959
Trimmed Mean ( 11 / 28 )140.7741935483872.4093747973791358.4276857637584
Trimmed Mean ( 12 / 28 )140.8333333333332.4058740106620158.5372852897567
Trimmed Mean ( 13 / 28 )140.8793103448282.4024938628778458.6387805278613
Trimmed Mean ( 14 / 28 )140.9285714285712.3954579779101158.8315773969547
Trimmed Mean ( 15 / 28 )140.9814814814812.3915309957561358.9503049434271
Trimmed Mean ( 16 / 28 )141.0384615384622.3833196012316659.1773178324784
Trimmed Mean ( 17 / 28 )141.082.3743252532379159.4189864289262
Trimmed Mean ( 18 / 28 )141.1041666666672.3732476893813059.456148339684
Trimmed Mean ( 19 / 28 )141.1304347826092.3673725617318359.6147970386908
Trimmed Mean ( 20 / 28 )141.1136363636362.3754861323084159.4041086766975
Trimmed Mean ( 21 / 28 )141.0952380952382.3796976949619359.2912445954592
Trimmed Mean ( 22 / 28 )141.052.3842297041290559.1595682898034
Trimmed Mean ( 23 / 28 )140.9736842105262.3887737803508559.015083542076
Trimmed Mean ( 24 / 28 )140.9166666666672.3938993229152258.8649093626303
Trimmed Mean ( 25 / 28 )140.8529411764712.3917312820929258.8916247536032
Trimmed Mean ( 26 / 28 )140.781252.3957011125272958.7641126281758
Trimmed Mean ( 27 / 28 )140.7333333333332.3992016552127358.6584012342452
Trimmed Mean ( 28 / 28 )140.6785714285712.3910401377407358.8357214118108
Median140
Midrange135
Midmean - Weighted Average at Xnp141.130434782609
Midmean - Weighted Average at X(n+1)p142.090909090909
Midmean - Empirical Distribution Function141.130434782609
Midmean - Empirical Distribution Function - Averaging142.090909090909
Midmean - Empirical Distribution Function - Interpolation142.090909090909
Midmean - Closest Observation141.130434782609
Midmean - True Basic - Statistics Graphics Toolkit142.090909090909
Midmean - MS Excel (old versions)141.130434782609
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 139.702380952381 & 2.65191234011230 & 52.6798638247842 \tabularnewline
Geometric Mean & 137.531037493646 &  &  \tabularnewline
Harmonic Mean & 135.300571763967 &  &  \tabularnewline
Quadratic Mean & 141.776106187588 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 139.726190476190 & 2.62836545949420 & 53.1608684673095 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 139.702380952381 & 2.59941626804331 & 53.7437511143765 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 139.738095238095 & 2.59274989017569 & 53.8957096353889 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 139.738095238095 & 2.57699112550565 & 54.2252916026927 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 139.738095238095 & 2.55771694352061 & 54.633917014191 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 139.880952380952 & 2.53282550481442 & 55.2272361894119 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 139.964285714286 & 2.49310273043246 & 56.1406010293074 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 140.059523809524 & 2.47763091681872 & 56.529615794979 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 140.059523809524 & 2.44564262899425 & 57.2690065789055 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 140.178571428571 & 2.39250603258886 & 58.590686718933 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 140.309523809524 & 2.33595313487436 & 60.0652135159681 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 140.452380952381 & 2.31531883520087 & 60.6622201733162 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 140.452380952381 & 2.31531883520087 & 60.6622201733162 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 140.452380952381 & 2.26977222805956 & 61.8795045670528 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 140.452380952381 & 2.26977222805956 & 61.8795045670528 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 140.642857142857 & 2.24328173111851 & 62.6951377492527 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 140.845238095238 & 2.16220428735801 & 65.1396535094915 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 140.845238095238 & 2.16220428735801 & 65.1396535094915 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 141.297619047619 & 2.04543765310600 & 69.0794064698372 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 141.297619047619 & 2.04543765310600 & 69.0794064698372 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 141.547619047619 & 2.01439204698662 & 70.2681582065239 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 141.809523809524 & 1.98253100853237 & 71.5295363347194 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 141.535714285714 & 1.94756614580966 & 72.6731231132966 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 141.535714285714 & 1.94756614580966 & 72.6731231132966 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 141.535714285714 & 1.87438622033325 & 75.5104325620525 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 141.226190476190 & 1.83595373081286 & 76.9225215788327 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 141.226190476190 & 1.83595373081286 & 76.9225215788327 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 141.226190476190 & 1.75543996627046 & 80.4505954004421 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 139.817073170732 & 2.60105183648108 & 53.754051038017 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 139.9125 & 2.56887367268274 & 54.4645310852852 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 140.025641025641 & 2.54829962040758 & 54.9486567059352 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 140.131578947368 & 2.52623720638014 & 55.4704754539514 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 140.243243243243 & 2.50477594978312 & 55.9903344869574 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 140.361111111111 & 2.48401033368508 & 56.5058483081599 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 140.457142857143 & 2.46471460845947 & 56.987183171253 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 140.544117647059 & 2.44961821966071 & 57.373886477104 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 140.621212121212 & 2.43342738441179 & 57.787305683339 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 140.703125 & 2.41878803521015 & 58.1709198787959 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 140.774193548387 & 2.40937479737913 & 58.4276857637584 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 140.833333333333 & 2.40587401066201 & 58.5372852897567 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 140.879310344828 & 2.40249386287784 & 58.6387805278613 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 140.928571428571 & 2.39545797791011 & 58.8315773969547 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 140.981481481481 & 2.39153099575613 & 58.9503049434271 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 141.038461538462 & 2.38331960123166 & 59.1773178324784 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 141.08 & 2.37432525323791 & 59.4189864289262 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 141.104166666667 & 2.37324768938130 & 59.456148339684 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 141.130434782609 & 2.36737256173183 & 59.6147970386908 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 141.113636363636 & 2.37548613230841 & 59.4041086766975 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 141.095238095238 & 2.37969769496193 & 59.2912445954592 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 141.05 & 2.38422970412905 & 59.1595682898034 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 140.973684210526 & 2.38877378035085 & 59.015083542076 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 140.916666666667 & 2.39389932291522 & 58.8649093626303 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 140.852941176471 & 2.39173128209292 & 58.8916247536032 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 140.78125 & 2.39570111252729 & 58.7641126281758 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 140.733333333333 & 2.39920165521273 & 58.6584012342452 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 140.678571428571 & 2.39104013774073 & 58.8357214118108 \tabularnewline
Median & 140 &  &  \tabularnewline
Midrange & 135 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 141.130434782609 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 142.090909090909 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 141.130434782609 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 142.090909090909 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 142.090909090909 &  &  \tabularnewline
Midmean - Closest Observation & 141.130434782609 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 142.090909090909 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 141.130434782609 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78493&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]139.702380952381[/C][C]2.65191234011230[/C][C]52.6798638247842[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]137.531037493646[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]135.300571763967[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]141.776106187588[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]139.726190476190[/C][C]2.62836545949420[/C][C]53.1608684673095[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]139.702380952381[/C][C]2.59941626804331[/C][C]53.7437511143765[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]139.738095238095[/C][C]2.59274989017569[/C][C]53.8957096353889[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]139.738095238095[/C][C]2.57699112550565[/C][C]54.2252916026927[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]139.738095238095[/C][C]2.55771694352061[/C][C]54.633917014191[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]139.880952380952[/C][C]2.53282550481442[/C][C]55.2272361894119[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]139.964285714286[/C][C]2.49310273043246[/C][C]56.1406010293074[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]140.059523809524[/C][C]2.47763091681872[/C][C]56.529615794979[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]140.059523809524[/C][C]2.44564262899425[/C][C]57.2690065789055[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]140.178571428571[/C][C]2.39250603258886[/C][C]58.590686718933[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]140.309523809524[/C][C]2.33595313487436[/C][C]60.0652135159681[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]140.452380952381[/C][C]2.31531883520087[/C][C]60.6622201733162[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]140.452380952381[/C][C]2.31531883520087[/C][C]60.6622201733162[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]140.452380952381[/C][C]2.26977222805956[/C][C]61.8795045670528[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]140.452380952381[/C][C]2.26977222805956[/C][C]61.8795045670528[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]140.642857142857[/C][C]2.24328173111851[/C][C]62.6951377492527[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]140.845238095238[/C][C]2.16220428735801[/C][C]65.1396535094915[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]140.845238095238[/C][C]2.16220428735801[/C][C]65.1396535094915[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]141.297619047619[/C][C]2.04543765310600[/C][C]69.0794064698372[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]141.297619047619[/C][C]2.04543765310600[/C][C]69.0794064698372[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]141.547619047619[/C][C]2.01439204698662[/C][C]70.2681582065239[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]141.809523809524[/C][C]1.98253100853237[/C][C]71.5295363347194[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]141.535714285714[/C][C]1.94756614580966[/C][C]72.6731231132966[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]141.535714285714[/C][C]1.94756614580966[/C][C]72.6731231132966[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]141.535714285714[/C][C]1.87438622033325[/C][C]75.5104325620525[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]141.226190476190[/C][C]1.83595373081286[/C][C]76.9225215788327[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]141.226190476190[/C][C]1.83595373081286[/C][C]76.9225215788327[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]141.226190476190[/C][C]1.75543996627046[/C][C]80.4505954004421[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]139.817073170732[/C][C]2.60105183648108[/C][C]53.754051038017[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]139.9125[/C][C]2.56887367268274[/C][C]54.4645310852852[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]140.025641025641[/C][C]2.54829962040758[/C][C]54.9486567059352[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]140.131578947368[/C][C]2.52623720638014[/C][C]55.4704754539514[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]140.243243243243[/C][C]2.50477594978312[/C][C]55.9903344869574[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]140.361111111111[/C][C]2.48401033368508[/C][C]56.5058483081599[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]140.457142857143[/C][C]2.46471460845947[/C][C]56.987183171253[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]140.544117647059[/C][C]2.44961821966071[/C][C]57.373886477104[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]140.621212121212[/C][C]2.43342738441179[/C][C]57.787305683339[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]140.703125[/C][C]2.41878803521015[/C][C]58.1709198787959[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]140.774193548387[/C][C]2.40937479737913[/C][C]58.4276857637584[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]140.833333333333[/C][C]2.40587401066201[/C][C]58.5372852897567[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]140.879310344828[/C][C]2.40249386287784[/C][C]58.6387805278613[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]140.928571428571[/C][C]2.39545797791011[/C][C]58.8315773969547[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]140.981481481481[/C][C]2.39153099575613[/C][C]58.9503049434271[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]141.038461538462[/C][C]2.38331960123166[/C][C]59.1773178324784[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]141.08[/C][C]2.37432525323791[/C][C]59.4189864289262[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]141.104166666667[/C][C]2.37324768938130[/C][C]59.456148339684[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]141.130434782609[/C][C]2.36737256173183[/C][C]59.6147970386908[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]141.113636363636[/C][C]2.37548613230841[/C][C]59.4041086766975[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]141.095238095238[/C][C]2.37969769496193[/C][C]59.2912445954592[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]141.05[/C][C]2.38422970412905[/C][C]59.1595682898034[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]140.973684210526[/C][C]2.38877378035085[/C][C]59.015083542076[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]140.916666666667[/C][C]2.39389932291522[/C][C]58.8649093626303[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]140.852941176471[/C][C]2.39173128209292[/C][C]58.8916247536032[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]140.78125[/C][C]2.39570111252729[/C][C]58.7641126281758[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]140.733333333333[/C][C]2.39920165521273[/C][C]58.6584012342452[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]140.678571428571[/C][C]2.39104013774073[/C][C]58.8357214118108[/C][/ROW]
[ROW][C]Median[/C][C]140[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]135[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]141.130434782609[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]142.090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]141.130434782609[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]142.090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]142.090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]141.130434782609[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]142.090909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]141.130434782609[/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=78493&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78493&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 Mean139.7023809523812.6519123401123052.6798638247842
Geometric Mean137.531037493646
Harmonic Mean135.300571763967
Quadratic Mean141.776106187588
Winsorized Mean ( 1 / 28 )139.7261904761902.6283654594942053.1608684673095
Winsorized Mean ( 2 / 28 )139.7023809523812.5994162680433153.7437511143765
Winsorized Mean ( 3 / 28 )139.7380952380952.5927498901756953.8957096353889
Winsorized Mean ( 4 / 28 )139.7380952380952.5769911255056554.2252916026927
Winsorized Mean ( 5 / 28 )139.7380952380952.5577169435206154.633917014191
Winsorized Mean ( 6 / 28 )139.8809523809522.5328255048144255.2272361894119
Winsorized Mean ( 7 / 28 )139.9642857142862.4931027304324656.1406010293074
Winsorized Mean ( 8 / 28 )140.0595238095242.4776309168187256.529615794979
Winsorized Mean ( 9 / 28 )140.0595238095242.4456426289942557.2690065789055
Winsorized Mean ( 10 / 28 )140.1785714285712.3925060325888658.590686718933
Winsorized Mean ( 11 / 28 )140.3095238095242.3359531348743660.0652135159681
Winsorized Mean ( 12 / 28 )140.4523809523812.3153188352008760.6622201733162
Winsorized Mean ( 13 / 28 )140.4523809523812.3153188352008760.6622201733162
Winsorized Mean ( 14 / 28 )140.4523809523812.2697722280595661.8795045670528
Winsorized Mean ( 15 / 28 )140.4523809523812.2697722280595661.8795045670528
Winsorized Mean ( 16 / 28 )140.6428571428572.2432817311185162.6951377492527
Winsorized Mean ( 17 / 28 )140.8452380952382.1622042873580165.1396535094915
Winsorized Mean ( 18 / 28 )140.8452380952382.1622042873580165.1396535094915
Winsorized Mean ( 19 / 28 )141.2976190476192.0454376531060069.0794064698372
Winsorized Mean ( 20 / 28 )141.2976190476192.0454376531060069.0794064698372
Winsorized Mean ( 21 / 28 )141.5476190476192.0143920469866270.2681582065239
Winsorized Mean ( 22 / 28 )141.8095238095241.9825310085323771.5295363347194
Winsorized Mean ( 23 / 28 )141.5357142857141.9475661458096672.6731231132966
Winsorized Mean ( 24 / 28 )141.5357142857141.9475661458096672.6731231132966
Winsorized Mean ( 25 / 28 )141.5357142857141.8743862203332575.5104325620525
Winsorized Mean ( 26 / 28 )141.2261904761901.8359537308128676.9225215788327
Winsorized Mean ( 27 / 28 )141.2261904761901.8359537308128676.9225215788327
Winsorized Mean ( 28 / 28 )141.2261904761901.7554399662704680.4505954004421
Trimmed Mean ( 1 / 28 )139.8170731707322.6010518364810853.754051038017
Trimmed Mean ( 2 / 28 )139.91252.5688736726827454.4645310852852
Trimmed Mean ( 3 / 28 )140.0256410256412.5482996204075854.9486567059352
Trimmed Mean ( 4 / 28 )140.1315789473682.5262372063801455.4704754539514
Trimmed Mean ( 5 / 28 )140.2432432432432.5047759497831255.9903344869574
Trimmed Mean ( 6 / 28 )140.3611111111112.4840103336850856.5058483081599
Trimmed Mean ( 7 / 28 )140.4571428571432.4647146084594756.987183171253
Trimmed Mean ( 8 / 28 )140.5441176470592.4496182196607157.373886477104
Trimmed Mean ( 9 / 28 )140.6212121212122.4334273844117957.787305683339
Trimmed Mean ( 10 / 28 )140.7031252.4187880352101558.1709198787959
Trimmed Mean ( 11 / 28 )140.7741935483872.4093747973791358.4276857637584
Trimmed Mean ( 12 / 28 )140.8333333333332.4058740106620158.5372852897567
Trimmed Mean ( 13 / 28 )140.8793103448282.4024938628778458.6387805278613
Trimmed Mean ( 14 / 28 )140.9285714285712.3954579779101158.8315773969547
Trimmed Mean ( 15 / 28 )140.9814814814812.3915309957561358.9503049434271
Trimmed Mean ( 16 / 28 )141.0384615384622.3833196012316659.1773178324784
Trimmed Mean ( 17 / 28 )141.082.3743252532379159.4189864289262
Trimmed Mean ( 18 / 28 )141.1041666666672.3732476893813059.456148339684
Trimmed Mean ( 19 / 28 )141.1304347826092.3673725617318359.6147970386908
Trimmed Mean ( 20 / 28 )141.1136363636362.3754861323084159.4041086766975
Trimmed Mean ( 21 / 28 )141.0952380952382.3796976949619359.2912445954592
Trimmed Mean ( 22 / 28 )141.052.3842297041290559.1595682898034
Trimmed Mean ( 23 / 28 )140.9736842105262.3887737803508559.015083542076
Trimmed Mean ( 24 / 28 )140.9166666666672.3938993229152258.8649093626303
Trimmed Mean ( 25 / 28 )140.8529411764712.3917312820929258.8916247536032
Trimmed Mean ( 26 / 28 )140.781252.3957011125272958.7641126281758
Trimmed Mean ( 27 / 28 )140.7333333333332.3992016552127358.6584012342452
Trimmed Mean ( 28 / 28 )140.6785714285712.3910401377407358.8357214118108
Median140
Midrange135
Midmean - Weighted Average at Xnp141.130434782609
Midmean - Weighted Average at X(n+1)p142.090909090909
Midmean - Empirical Distribution Function141.130434782609
Midmean - Empirical Distribution Function - Averaging142.090909090909
Midmean - Empirical Distribution Function - Interpolation142.090909090909
Midmean - Closest Observation141.130434782609
Midmean - True Basic - Statistics Graphics Toolkit142.090909090909
Midmean - MS Excel (old versions)141.130434782609
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')