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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, 13 Dec 2007 07:43:30 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Dec/13/t1197556179yy96xmht41s57pc.htm/, Retrieved Sun, 05 May 2024 10:01:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3579, Retrieved Sun, 05 May 2024 10:01:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscentral tendancy
Estimated Impact159
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [paper] [2007-12-13 14:43:30] [8ce1ad2ac57e06e10fb37a1292ae8cb6] [Current]
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Dataseries X:
2.59938172072753e-06
-1.98124589452182e-05
9.03904019533454e-06
5.974689692847e-05
-0.000114153168333964
-1.16454302842665e-05
8.25491857171207e-05
-0.000130540730545100
0.000105660554293888
-5.98925115999448e-05
8.88698175348437e-05
1.23144658772834e-05
-8.98673305764362e-05
-0.000280048698227729
-0.000119627728663478
-6.75372320398912e-05
-5.38412109493011e-06
0.000199445906388824
-2.0046270725276e-05
-0.000156299795964434
-0.000144982756037757
-0.000194619427641021
5.41769707616213e-05
-5.18713127332003e-05
-0.000286830242259062
0.000370918394597008
5.22842311086383e-05
4.20581762978733e-06
-0.000167434731789327
-2.18453441691534e-05
-0.000205183647384550
-0.000101997961783984
-6.7968896103759e-05
3.76651753521485e-05
0.000234200060900207
-7.64547750049195e-05
-0.000223414016843751
-0.000203716715028846
8.71869856094325e-05
9.60718008341786e-05
-8.53519533296036e-07
-9.59663908169988e-05
5.95180164565832e-05
0.000307613554623039
-5.43966650096198e-05
-0.000129986451065416
8.88899614917256e-06
-8.87463588797454e-05
7.00835423537816e-05
1.97103930387834e-05
-0.000102232966669420
-0.000223490605733882
0.000107278243221417
-0.000198793872269956
-4.10723476605181e-08
1.50439084468808e-05
-6.85256818749045e-06
0.000113657724571234
-0.000112152424110303
-4.8941404075035e-05
4.09094742309553e-05
-0.000125967834427353
4.94525032591576e-05
2.95458917379868e-05
4.86273205095606e-05
-4.61792875866992e-05
4.78662470015082e-05
-0.000135506138234512
5.77855686636954e-06




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3579&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3579&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3579&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-2.56575913740789e-051.50142720844433e-05-1.70888013949497
Geometric MeanNaN
Harmonic Mean-2.77678163804097e-06
Quadratic Mean0.000126441452453166
Winsorized Mean ( 1 / 23 )-2.64767695761461e-051.46569497484740e-05-1.80643108085315
Winsorized Mean ( 2 / 23 )-2.69653319306094e-051.36142472086214e-05-1.98067006698198
Winsorized Mean ( 3 / 23 )-2.84730521750117e-051.32083478901412e-05-2.15568611697941
Winsorized Mean ( 4 / 23 )-3.23894470943386e-051.18909613503357e-05-2.72387119426841
Winsorized Mean ( 5 / 23 )-3.27454289055062e-051.17861272731246e-05-2.77830267285287
Winsorized Mean ( 6 / 23 )-3.24580242245183e-051.16710754082520e-05-2.78106541935020
Winsorized Mean ( 7 / 23 )-3.30073019319881e-051.14170573556340e-05-2.89105159971013
Winsorized Mean ( 8 / 23 )-3.06904656940334e-051.06520877999564e-05-2.88116905064932
Winsorized Mean ( 9 / 23 )-2.94575825767097e-051.03476900235552e-05-2.84677860562630
Winsorized Mean ( 10 / 23 )-2.84895767746278e-059.94760977036623e-06-2.86396204035846
Winsorized Mean ( 11 / 23 )-2.89660880958022e-059.37336760398126e-06-3.09025414553241
Winsorized Mean ( 12 / 23 )-2.99002163976978e-058.95770690955068e-06-3.33793198411284
Winsorized Mean ( 13 / 23 )-2.98389093382578e-058.93412790306679e-06-3.33987935498607
Winsorized Mean ( 14 / 23 )-3.01072282773387e-058.64297992344922e-06-3.48343147201522
Winsorized Mean ( 15 / 23 )-2.91404095575796e-058.36189816597222e-06-3.48490366411817
Winsorized Mean ( 16 / 23 )-2.85275788375718e-058.06810349015846e-06-3.53584691524719
Winsorized Mean ( 17 / 23 )-2.8237947749759e-057.96255801168567e-06-3.54634122706768
Winsorized Mean ( 18 / 23 )-2.58488041151075e-057.5407323138664e-06-3.42789042750862
Winsorized Mean ( 19 / 23 )-2.76997257066614e-057.26015298633872e-06-3.81530881770445
Winsorized Mean ( 20 / 23 )-2.68918207535663e-056.86892563595814e-06-3.9149966353967
Winsorized Mean ( 21 / 23 )-2.75066713455312e-056.25899704509585e-06-4.39474106591626
Winsorized Mean ( 22 / 23 )-3.02852161869120e-055.79683172832212e-06-5.22444286918745
Winsorized Mean ( 23 / 23 )-2.77435164259376e-055.00234037938627e-06-5.54610728615421
Trimmed Mean ( 1 / 23 )-2.76785366738715e-051.37163929610219e-05-2.01791657271164
Trimmed Mean ( 2 / 23 )-2.89542586699184e-051.25550261456950e-05-2.30618863982585
Trimmed Mean ( 3 / 23 )-3.00434328366829e-051.18508177870540e-05-2.53513583421244
Trimmed Mean ( 4 / 23 )-3.06355435779688e-051.11923943008376e-05-2.73717515256555
Trimmed Mean ( 5 / 23 )-3.01227497532675e-051.09082562178485e-05-2.76146334956631
Trimmed Mean ( 6 / 23 )-2.9487785326936e-051.05925194219096e-05-2.78383113142501
Trimmed Mean ( 7 / 23 )-2.88667353756233e-051.02362044217746e-05-2.82006241632081
Trimmed Mean ( 8 / 23 )-2.809665695948e-059.86264932928561e-06-2.84879407362192
Trimmed Mean ( 9 / 23 )-2.76579981293717e-059.59932911845087e-06-2.88124282312712
Trimmed Mean ( 10 / 23 )-2.73764304947542e-059.34125303895676e-06-2.93070216389424
Trimmed Mean ( 11 / 23 )-2.73764304947542e-059.10715944505264e-06-3.00603395163199
Trimmed Mean ( 12 / 23 )-2.69686428453687e-058.93637260644525e-06-3.01785120574738
Trimmed Mean ( 13 / 23 )-2.65766301029060e-058.80032484062985e-06-3.01996012467693
Trimmed Mean ( 14 / 23 )-2.61543087760031e-058.61626983548596e-06-3.03545609357393
Trimmed Mean ( 15 / 23 )-2.56547640038563e-058.43040041481775e-06-3.04312520657548
Trimmed Mean ( 16 / 23 )-2.52214134755555e-058.23891710004422e-06-3.06125345956208
Trimmed Mean ( 17 / 23 )-2.48140466720214e-058.04007685289712e-06-3.08629471160839
Trimmed Mean ( 18 / 23 )-2.43929251490911e-057.77875260734879e-06-3.13584020219983
Trimmed Mean ( 19 / 23 )-2.42128971049063e-057.52172702004833e-06-3.21906086732069
Trimmed Mean ( 20 / 23 )-2.37762525068643e-057.21921545725691e-06-3.29346764169006
Trimmed Mean ( 21 / 23 )-2.33781521197858e-056.8903001853317e-06-3.39290763696391
Trimmed Mean ( 22 / 23 )-2.33781521197858e-056.5953509306314e-06-3.54464112155253
Trimmed Mean ( 23 / 23 )-2.18196827197741e-056.27452731272472e-06-3.47750222961399
Median-1.16454302842665e-05
Midrange4.2044076168973e-05
Midmean - Weighted Average at Xnp-2.69740868832444e-05
Midmean - Weighted Average at X(n+1)p-2.48140466720214e-05
Midmean - Empirical Distribution Function-2.48140466720214e-05
Midmean - Empirical Distribution Function - Averaging-2.48140466720214e-05
Midmean - Empirical Distribution Function - Interpolation-2.48140466720214e-05
Midmean - Closest Observation-2.72956889404087e-05
Midmean - True Basic - Statistics Graphics Toolkit-2.48140466720214e-05
Midmean - MS Excel (old versions)-2.48140466720214e-05
Number of observations69

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -2.56575913740789e-05 & 1.50142720844433e-05 & -1.70888013949497 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -2.77678163804097e-06 &  &  \tabularnewline
Quadratic Mean & 0.000126441452453166 &  &  \tabularnewline
Winsorized Mean ( 1 / 23 ) & -2.64767695761461e-05 & 1.46569497484740e-05 & -1.80643108085315 \tabularnewline
Winsorized Mean ( 2 / 23 ) & -2.69653319306094e-05 & 1.36142472086214e-05 & -1.98067006698198 \tabularnewline
Winsorized Mean ( 3 / 23 ) & -2.84730521750117e-05 & 1.32083478901412e-05 & -2.15568611697941 \tabularnewline
Winsorized Mean ( 4 / 23 ) & -3.23894470943386e-05 & 1.18909613503357e-05 & -2.72387119426841 \tabularnewline
Winsorized Mean ( 5 / 23 ) & -3.27454289055062e-05 & 1.17861272731246e-05 & -2.77830267285287 \tabularnewline
Winsorized Mean ( 6 / 23 ) & -3.24580242245183e-05 & 1.16710754082520e-05 & -2.78106541935020 \tabularnewline
Winsorized Mean ( 7 / 23 ) & -3.30073019319881e-05 & 1.14170573556340e-05 & -2.89105159971013 \tabularnewline
Winsorized Mean ( 8 / 23 ) & -3.06904656940334e-05 & 1.06520877999564e-05 & -2.88116905064932 \tabularnewline
Winsorized Mean ( 9 / 23 ) & -2.94575825767097e-05 & 1.03476900235552e-05 & -2.84677860562630 \tabularnewline
Winsorized Mean ( 10 / 23 ) & -2.84895767746278e-05 & 9.94760977036623e-06 & -2.86396204035846 \tabularnewline
Winsorized Mean ( 11 / 23 ) & -2.89660880958022e-05 & 9.37336760398126e-06 & -3.09025414553241 \tabularnewline
Winsorized Mean ( 12 / 23 ) & -2.99002163976978e-05 & 8.95770690955068e-06 & -3.33793198411284 \tabularnewline
Winsorized Mean ( 13 / 23 ) & -2.98389093382578e-05 & 8.93412790306679e-06 & -3.33987935498607 \tabularnewline
Winsorized Mean ( 14 / 23 ) & -3.01072282773387e-05 & 8.64297992344922e-06 & -3.48343147201522 \tabularnewline
Winsorized Mean ( 15 / 23 ) & -2.91404095575796e-05 & 8.36189816597222e-06 & -3.48490366411817 \tabularnewline
Winsorized Mean ( 16 / 23 ) & -2.85275788375718e-05 & 8.06810349015846e-06 & -3.53584691524719 \tabularnewline
Winsorized Mean ( 17 / 23 ) & -2.8237947749759e-05 & 7.96255801168567e-06 & -3.54634122706768 \tabularnewline
Winsorized Mean ( 18 / 23 ) & -2.58488041151075e-05 & 7.5407323138664e-06 & -3.42789042750862 \tabularnewline
Winsorized Mean ( 19 / 23 ) & -2.76997257066614e-05 & 7.26015298633872e-06 & -3.81530881770445 \tabularnewline
Winsorized Mean ( 20 / 23 ) & -2.68918207535663e-05 & 6.86892563595814e-06 & -3.9149966353967 \tabularnewline
Winsorized Mean ( 21 / 23 ) & -2.75066713455312e-05 & 6.25899704509585e-06 & -4.39474106591626 \tabularnewline
Winsorized Mean ( 22 / 23 ) & -3.02852161869120e-05 & 5.79683172832212e-06 & -5.22444286918745 \tabularnewline
Winsorized Mean ( 23 / 23 ) & -2.77435164259376e-05 & 5.00234037938627e-06 & -5.54610728615421 \tabularnewline
Trimmed Mean ( 1 / 23 ) & -2.76785366738715e-05 & 1.37163929610219e-05 & -2.01791657271164 \tabularnewline
Trimmed Mean ( 2 / 23 ) & -2.89542586699184e-05 & 1.25550261456950e-05 & -2.30618863982585 \tabularnewline
Trimmed Mean ( 3 / 23 ) & -3.00434328366829e-05 & 1.18508177870540e-05 & -2.53513583421244 \tabularnewline
Trimmed Mean ( 4 / 23 ) & -3.06355435779688e-05 & 1.11923943008376e-05 & -2.73717515256555 \tabularnewline
Trimmed Mean ( 5 / 23 ) & -3.01227497532675e-05 & 1.09082562178485e-05 & -2.76146334956631 \tabularnewline
Trimmed Mean ( 6 / 23 ) & -2.9487785326936e-05 & 1.05925194219096e-05 & -2.78383113142501 \tabularnewline
Trimmed Mean ( 7 / 23 ) & -2.88667353756233e-05 & 1.02362044217746e-05 & -2.82006241632081 \tabularnewline
Trimmed Mean ( 8 / 23 ) & -2.809665695948e-05 & 9.86264932928561e-06 & -2.84879407362192 \tabularnewline
Trimmed Mean ( 9 / 23 ) & -2.76579981293717e-05 & 9.59932911845087e-06 & -2.88124282312712 \tabularnewline
Trimmed Mean ( 10 / 23 ) & -2.73764304947542e-05 & 9.34125303895676e-06 & -2.93070216389424 \tabularnewline
Trimmed Mean ( 11 / 23 ) & -2.73764304947542e-05 & 9.10715944505264e-06 & -3.00603395163199 \tabularnewline
Trimmed Mean ( 12 / 23 ) & -2.69686428453687e-05 & 8.93637260644525e-06 & -3.01785120574738 \tabularnewline
Trimmed Mean ( 13 / 23 ) & -2.65766301029060e-05 & 8.80032484062985e-06 & -3.01996012467693 \tabularnewline
Trimmed Mean ( 14 / 23 ) & -2.61543087760031e-05 & 8.61626983548596e-06 & -3.03545609357393 \tabularnewline
Trimmed Mean ( 15 / 23 ) & -2.56547640038563e-05 & 8.43040041481775e-06 & -3.04312520657548 \tabularnewline
Trimmed Mean ( 16 / 23 ) & -2.52214134755555e-05 & 8.23891710004422e-06 & -3.06125345956208 \tabularnewline
Trimmed Mean ( 17 / 23 ) & -2.48140466720214e-05 & 8.04007685289712e-06 & -3.08629471160839 \tabularnewline
Trimmed Mean ( 18 / 23 ) & -2.43929251490911e-05 & 7.77875260734879e-06 & -3.13584020219983 \tabularnewline
Trimmed Mean ( 19 / 23 ) & -2.42128971049063e-05 & 7.52172702004833e-06 & -3.21906086732069 \tabularnewline
Trimmed Mean ( 20 / 23 ) & -2.37762525068643e-05 & 7.21921545725691e-06 & -3.29346764169006 \tabularnewline
Trimmed Mean ( 21 / 23 ) & -2.33781521197858e-05 & 6.8903001853317e-06 & -3.39290763696391 \tabularnewline
Trimmed Mean ( 22 / 23 ) & -2.33781521197858e-05 & 6.5953509306314e-06 & -3.54464112155253 \tabularnewline
Trimmed Mean ( 23 / 23 ) & -2.18196827197741e-05 & 6.27452731272472e-06 & -3.47750222961399 \tabularnewline
Median & -1.16454302842665e-05 &  &  \tabularnewline
Midrange & 4.2044076168973e-05 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -2.69740868832444e-05 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -2.48140466720214e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -2.48140466720214e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -2.48140466720214e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -2.48140466720214e-05 &  &  \tabularnewline
Midmean - Closest Observation & -2.72956889404087e-05 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -2.48140466720214e-05 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -2.48140466720214e-05 &  &  \tabularnewline
Number of observations & 69 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3579&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]-2.56575913740789e-05[/C][C]1.50142720844433e-05[/C][C]-1.70888013949497[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-2.77678163804097e-06[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]0.000126441452453166[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 23 )[/C][C]-2.64767695761461e-05[/C][C]1.46569497484740e-05[/C][C]-1.80643108085315[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 23 )[/C][C]-2.69653319306094e-05[/C][C]1.36142472086214e-05[/C][C]-1.98067006698198[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 23 )[/C][C]-2.84730521750117e-05[/C][C]1.32083478901412e-05[/C][C]-2.15568611697941[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 23 )[/C][C]-3.23894470943386e-05[/C][C]1.18909613503357e-05[/C][C]-2.72387119426841[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 23 )[/C][C]-3.27454289055062e-05[/C][C]1.17861272731246e-05[/C][C]-2.77830267285287[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 23 )[/C][C]-3.24580242245183e-05[/C][C]1.16710754082520e-05[/C][C]-2.78106541935020[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 23 )[/C][C]-3.30073019319881e-05[/C][C]1.14170573556340e-05[/C][C]-2.89105159971013[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 23 )[/C][C]-3.06904656940334e-05[/C][C]1.06520877999564e-05[/C][C]-2.88116905064932[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 23 )[/C][C]-2.94575825767097e-05[/C][C]1.03476900235552e-05[/C][C]-2.84677860562630[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 23 )[/C][C]-2.84895767746278e-05[/C][C]9.94760977036623e-06[/C][C]-2.86396204035846[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 23 )[/C][C]-2.89660880958022e-05[/C][C]9.37336760398126e-06[/C][C]-3.09025414553241[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 23 )[/C][C]-2.99002163976978e-05[/C][C]8.95770690955068e-06[/C][C]-3.33793198411284[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 23 )[/C][C]-2.98389093382578e-05[/C][C]8.93412790306679e-06[/C][C]-3.33987935498607[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 23 )[/C][C]-3.01072282773387e-05[/C][C]8.64297992344922e-06[/C][C]-3.48343147201522[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 23 )[/C][C]-2.91404095575796e-05[/C][C]8.36189816597222e-06[/C][C]-3.48490366411817[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 23 )[/C][C]-2.85275788375718e-05[/C][C]8.06810349015846e-06[/C][C]-3.53584691524719[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 23 )[/C][C]-2.8237947749759e-05[/C][C]7.96255801168567e-06[/C][C]-3.54634122706768[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 23 )[/C][C]-2.58488041151075e-05[/C][C]7.5407323138664e-06[/C][C]-3.42789042750862[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 23 )[/C][C]-2.76997257066614e-05[/C][C]7.26015298633872e-06[/C][C]-3.81530881770445[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 23 )[/C][C]-2.68918207535663e-05[/C][C]6.86892563595814e-06[/C][C]-3.9149966353967[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 23 )[/C][C]-2.75066713455312e-05[/C][C]6.25899704509585e-06[/C][C]-4.39474106591626[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 23 )[/C][C]-3.02852161869120e-05[/C][C]5.79683172832212e-06[/C][C]-5.22444286918745[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 23 )[/C][C]-2.77435164259376e-05[/C][C]5.00234037938627e-06[/C][C]-5.54610728615421[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 23 )[/C][C]-2.76785366738715e-05[/C][C]1.37163929610219e-05[/C][C]-2.01791657271164[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 23 )[/C][C]-2.89542586699184e-05[/C][C]1.25550261456950e-05[/C][C]-2.30618863982585[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 23 )[/C][C]-3.00434328366829e-05[/C][C]1.18508177870540e-05[/C][C]-2.53513583421244[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 23 )[/C][C]-3.06355435779688e-05[/C][C]1.11923943008376e-05[/C][C]-2.73717515256555[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 23 )[/C][C]-3.01227497532675e-05[/C][C]1.09082562178485e-05[/C][C]-2.76146334956631[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 23 )[/C][C]-2.9487785326936e-05[/C][C]1.05925194219096e-05[/C][C]-2.78383113142501[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 23 )[/C][C]-2.88667353756233e-05[/C][C]1.02362044217746e-05[/C][C]-2.82006241632081[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 23 )[/C][C]-2.809665695948e-05[/C][C]9.86264932928561e-06[/C][C]-2.84879407362192[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 23 )[/C][C]-2.76579981293717e-05[/C][C]9.59932911845087e-06[/C][C]-2.88124282312712[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 23 )[/C][C]-2.73764304947542e-05[/C][C]9.34125303895676e-06[/C][C]-2.93070216389424[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 23 )[/C][C]-2.73764304947542e-05[/C][C]9.10715944505264e-06[/C][C]-3.00603395163199[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 23 )[/C][C]-2.69686428453687e-05[/C][C]8.93637260644525e-06[/C][C]-3.01785120574738[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 23 )[/C][C]-2.65766301029060e-05[/C][C]8.80032484062985e-06[/C][C]-3.01996012467693[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 23 )[/C][C]-2.61543087760031e-05[/C][C]8.61626983548596e-06[/C][C]-3.03545609357393[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 23 )[/C][C]-2.56547640038563e-05[/C][C]8.43040041481775e-06[/C][C]-3.04312520657548[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 23 )[/C][C]-2.52214134755555e-05[/C][C]8.23891710004422e-06[/C][C]-3.06125345956208[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 23 )[/C][C]-2.48140466720214e-05[/C][C]8.04007685289712e-06[/C][C]-3.08629471160839[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 23 )[/C][C]-2.43929251490911e-05[/C][C]7.77875260734879e-06[/C][C]-3.13584020219983[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 23 )[/C][C]-2.42128971049063e-05[/C][C]7.52172702004833e-06[/C][C]-3.21906086732069[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 23 )[/C][C]-2.37762525068643e-05[/C][C]7.21921545725691e-06[/C][C]-3.29346764169006[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 23 )[/C][C]-2.33781521197858e-05[/C][C]6.8903001853317e-06[/C][C]-3.39290763696391[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 23 )[/C][C]-2.33781521197858e-05[/C][C]6.5953509306314e-06[/C][C]-3.54464112155253[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 23 )[/C][C]-2.18196827197741e-05[/C][C]6.27452731272472e-06[/C][C]-3.47750222961399[/C][/ROW]
[ROW][C]Median[/C][C]-1.16454302842665e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4.2044076168973e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-2.69740868832444e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-2.48140466720214e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-2.48140466720214e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-2.48140466720214e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-2.48140466720214e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-2.72956889404087e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-2.48140466720214e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-2.48140466720214e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]69[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3579&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3579&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 Mean-2.56575913740789e-051.50142720844433e-05-1.70888013949497
Geometric MeanNaN
Harmonic Mean-2.77678163804097e-06
Quadratic Mean0.000126441452453166
Winsorized Mean ( 1 / 23 )-2.64767695761461e-051.46569497484740e-05-1.80643108085315
Winsorized Mean ( 2 / 23 )-2.69653319306094e-051.36142472086214e-05-1.98067006698198
Winsorized Mean ( 3 / 23 )-2.84730521750117e-051.32083478901412e-05-2.15568611697941
Winsorized Mean ( 4 / 23 )-3.23894470943386e-051.18909613503357e-05-2.72387119426841
Winsorized Mean ( 5 / 23 )-3.27454289055062e-051.17861272731246e-05-2.77830267285287
Winsorized Mean ( 6 / 23 )-3.24580242245183e-051.16710754082520e-05-2.78106541935020
Winsorized Mean ( 7 / 23 )-3.30073019319881e-051.14170573556340e-05-2.89105159971013
Winsorized Mean ( 8 / 23 )-3.06904656940334e-051.06520877999564e-05-2.88116905064932
Winsorized Mean ( 9 / 23 )-2.94575825767097e-051.03476900235552e-05-2.84677860562630
Winsorized Mean ( 10 / 23 )-2.84895767746278e-059.94760977036623e-06-2.86396204035846
Winsorized Mean ( 11 / 23 )-2.89660880958022e-059.37336760398126e-06-3.09025414553241
Winsorized Mean ( 12 / 23 )-2.99002163976978e-058.95770690955068e-06-3.33793198411284
Winsorized Mean ( 13 / 23 )-2.98389093382578e-058.93412790306679e-06-3.33987935498607
Winsorized Mean ( 14 / 23 )-3.01072282773387e-058.64297992344922e-06-3.48343147201522
Winsorized Mean ( 15 / 23 )-2.91404095575796e-058.36189816597222e-06-3.48490366411817
Winsorized Mean ( 16 / 23 )-2.85275788375718e-058.06810349015846e-06-3.53584691524719
Winsorized Mean ( 17 / 23 )-2.8237947749759e-057.96255801168567e-06-3.54634122706768
Winsorized Mean ( 18 / 23 )-2.58488041151075e-057.5407323138664e-06-3.42789042750862
Winsorized Mean ( 19 / 23 )-2.76997257066614e-057.26015298633872e-06-3.81530881770445
Winsorized Mean ( 20 / 23 )-2.68918207535663e-056.86892563595814e-06-3.9149966353967
Winsorized Mean ( 21 / 23 )-2.75066713455312e-056.25899704509585e-06-4.39474106591626
Winsorized Mean ( 22 / 23 )-3.02852161869120e-055.79683172832212e-06-5.22444286918745
Winsorized Mean ( 23 / 23 )-2.77435164259376e-055.00234037938627e-06-5.54610728615421
Trimmed Mean ( 1 / 23 )-2.76785366738715e-051.37163929610219e-05-2.01791657271164
Trimmed Mean ( 2 / 23 )-2.89542586699184e-051.25550261456950e-05-2.30618863982585
Trimmed Mean ( 3 / 23 )-3.00434328366829e-051.18508177870540e-05-2.53513583421244
Trimmed Mean ( 4 / 23 )-3.06355435779688e-051.11923943008376e-05-2.73717515256555
Trimmed Mean ( 5 / 23 )-3.01227497532675e-051.09082562178485e-05-2.76146334956631
Trimmed Mean ( 6 / 23 )-2.9487785326936e-051.05925194219096e-05-2.78383113142501
Trimmed Mean ( 7 / 23 )-2.88667353756233e-051.02362044217746e-05-2.82006241632081
Trimmed Mean ( 8 / 23 )-2.809665695948e-059.86264932928561e-06-2.84879407362192
Trimmed Mean ( 9 / 23 )-2.76579981293717e-059.59932911845087e-06-2.88124282312712
Trimmed Mean ( 10 / 23 )-2.73764304947542e-059.34125303895676e-06-2.93070216389424
Trimmed Mean ( 11 / 23 )-2.73764304947542e-059.10715944505264e-06-3.00603395163199
Trimmed Mean ( 12 / 23 )-2.69686428453687e-058.93637260644525e-06-3.01785120574738
Trimmed Mean ( 13 / 23 )-2.65766301029060e-058.80032484062985e-06-3.01996012467693
Trimmed Mean ( 14 / 23 )-2.61543087760031e-058.61626983548596e-06-3.03545609357393
Trimmed Mean ( 15 / 23 )-2.56547640038563e-058.43040041481775e-06-3.04312520657548
Trimmed Mean ( 16 / 23 )-2.52214134755555e-058.23891710004422e-06-3.06125345956208
Trimmed Mean ( 17 / 23 )-2.48140466720214e-058.04007685289712e-06-3.08629471160839
Trimmed Mean ( 18 / 23 )-2.43929251490911e-057.77875260734879e-06-3.13584020219983
Trimmed Mean ( 19 / 23 )-2.42128971049063e-057.52172702004833e-06-3.21906086732069
Trimmed Mean ( 20 / 23 )-2.37762525068643e-057.21921545725691e-06-3.29346764169006
Trimmed Mean ( 21 / 23 )-2.33781521197858e-056.8903001853317e-06-3.39290763696391
Trimmed Mean ( 22 / 23 )-2.33781521197858e-056.5953509306314e-06-3.54464112155253
Trimmed Mean ( 23 / 23 )-2.18196827197741e-056.27452731272472e-06-3.47750222961399
Median-1.16454302842665e-05
Midrange4.2044076168973e-05
Midmean - Weighted Average at Xnp-2.69740868832444e-05
Midmean - Weighted Average at X(n+1)p-2.48140466720214e-05
Midmean - Empirical Distribution Function-2.48140466720214e-05
Midmean - Empirical Distribution Function - Averaging-2.48140466720214e-05
Midmean - Empirical Distribution Function - Interpolation-2.48140466720214e-05
Midmean - Closest Observation-2.72956889404087e-05
Midmean - True Basic - Statistics Graphics Toolkit-2.48140466720214e-05
Midmean - MS Excel (old versions)-2.48140466720214e-05
Number of observations69



Parameters (Session):
par1 = FALSE ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 0 ; par8 = 2 ; par9 = 0 ;
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')