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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, 10 Oct 2013 08:50:35 -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/10/t1381409707izl2z34wjgls7mw.htm/, Retrieved Thu, 02 May 2024 17:52:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=214558, Retrieved Thu, 02 May 2024 17:52:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2013-10-10 12:50:35] [d7aee701571668449ffc3c4d70a8a545] [Current]
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Dataseries X:
6
6
5
5
3
5
5
5
3
6
6
4
6
5
4
5
5
4
3
2
3
2
-1
0
-2
1
-2
-2
-2
-6
-4
-2
0
-5
-4
-5
-1
-2
-4
-1
1
1
-2
1
1
3
3
1
1
0
2
2
-1
1
0
1
1
3
2
0
0
3
-2
0
1
-1
-2
-1
-1
1
-2
-5
-5
-6
-4
-3
-3
-1
-2
-3
-3
-3
-5
-5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214558&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=214558&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214558&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.2976190476190480.3607936373318890.824901042656892
Geometric MeanNaN
Harmonic Mean0
Quadratic Mean3.30043287204226
Winsorized Mean ( 1 / 28 )0.2976190476190480.3607936373318890.824901042656892
Winsorized Mean ( 2 / 28 )0.3214285714285710.3561446175467080.902522614669071
Winsorized Mean ( 3 / 28 )0.3214285714285710.3561446175467080.902522614669071
Winsorized Mean ( 4 / 28 )0.3214285714285710.3561446175467080.902522614669071
Winsorized Mean ( 5 / 28 )0.2619047619047620.3454976569913770.758050761285766
Winsorized Mean ( 6 / 28 )0.2619047619047620.3454976569913770.758050761285766
Winsorized Mean ( 7 / 28 )0.2619047619047620.3454976569913770.758050761285766
Winsorized Mean ( 8 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 9 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 10 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 11 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 12 / 28 )0.50.3079087570029931.62385768065421
Winsorized Mean ( 13 / 28 )0.3452380952380950.2821390141377771.2236453589843
Winsorized Mean ( 14 / 28 )0.3452380952380950.2821390141377771.2236453589843
Winsorized Mean ( 15 / 28 )0.3452380952380950.2821390141377771.2236453589843
Winsorized Mean ( 16 / 28 )0.1547619047619050.2543336650958810.608499487095274
Winsorized Mean ( 17 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 18 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 19 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 20 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 21 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 22 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 23 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 24 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 25 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 26 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 27 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 28 / 28 )0.4047619047619050.1467950276904232.75732707796826
Trimmed Mean ( 1 / 28 )0.3048780487804880.3546435731177170.859674534914775
Trimmed Mean ( 2 / 28 )0.31250.3475018213229750.899275862239457
Trimmed Mean ( 3 / 28 )0.3076923076923080.342031546094860.899602130871788
Trimmed Mean ( 4 / 28 )0.3026315789473680.335616602919350.90171814002924
Trimmed Mean ( 5 / 28 )0.2972972972972970.328082019960630.906167602031263
Trimmed Mean ( 6 / 28 )0.3055555555555560.3223780045421130.947817627910283
Trimmed Mean ( 7 / 28 )0.3142857142857140.3156004872524410.995834059135419
Trimmed Mean ( 8 / 28 )0.3235294117647060.3075300055815791.05202551260931
Trimmed Mean ( 9 / 28 )0.3181818181818180.3016343136400061.05485948976469
Trimmed Mean ( 10 / 28 )0.31250.294522582474251.06103918203733
Trimmed Mean ( 11 / 28 )0.3064516129032260.2859190694343741.07181243108223
Trimmed Mean ( 12 / 28 )0.30.2754554523234011.08910532526974
Trimmed Mean ( 13 / 28 )0.2758620689655170.2669460538638621.03340006331842
Trimmed Mean ( 14 / 28 )0.2678571428571430.261726375691941.02342433829603
Trimmed Mean ( 15 / 28 )0.2592592592592590.255184105016281.01596946738795
Trimmed Mean ( 16 / 28 )0.250.2469649861297291.01228924762912
Trimmed Mean ( 17 / 28 )0.260.242116517741491.07386312352966
Trimmed Mean ( 18 / 28 )0.250.2409717325466311.03746608516259
Trimmed Mean ( 19 / 28 )0.2391304347826090.2391304347826091
Trimmed Mean ( 20 / 28 )0.2272727272727270.2363920945626330.961422706174765
Trimmed Mean ( 21 / 28 )0.2142857142857140.2324832222930330.921725499897013
Trimmed Mean ( 22 / 28 )0.20.2270208394365190.880976391843207
Trimmed Mean ( 23 / 28 )0.1842105263157890.2194499238377550.839419413296224
Trimmed Mean ( 24 / 28 )0.1666666666666670.2089277235093360.797724035217466
Trimmed Mean ( 25 / 28 )0.1764705882352940.2045410855497890.862763526266404
Trimmed Mean ( 26 / 28 )0.18750.1979608750852450.947156855713329
Trimmed Mean ( 27 / 28 )0.20.1881549862495671.06295349374755
Trimmed Mean ( 28 / 28 )0.2142857142857140.1733359497447741.2362450755382
Median0
Midrange0
Midmean - Weighted Average at Xnp0.313725490196078
Midmean - Weighted Average at X(n+1)p0.313725490196078
Midmean - Empirical Distribution Function0.313725490196078
Midmean - Empirical Distribution Function - Averaging0.313725490196078
Midmean - Empirical Distribution Function - Interpolation0.313725490196078
Midmean - Closest Observation0.313725490196078
Midmean - True Basic - Statistics Graphics Toolkit0.313725490196078
Midmean - MS Excel (old versions)0.313725490196078
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.297619047619048 & 0.360793637331889 & 0.824901042656892 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 3.30043287204226 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 0.297619047619048 & 0.360793637331889 & 0.824901042656892 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 0.321428571428571 & 0.356144617546708 & 0.902522614669071 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 0.321428571428571 & 0.356144617546708 & 0.902522614669071 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 0.321428571428571 & 0.356144617546708 & 0.902522614669071 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 0.261904761904762 & 0.345497656991377 & 0.758050761285766 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 0.261904761904762 & 0.345497656991377 & 0.758050761285766 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 0.261904761904762 & 0.345497656991377 & 0.758050761285766 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 0.357142857142857 & 0.329137181614228 & 1.08508815500964 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 0.357142857142857 & 0.329137181614228 & 1.08508815500964 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 0.357142857142857 & 0.329137181614228 & 1.08508815500964 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 0.357142857142857 & 0.329137181614228 & 1.08508815500964 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 0.5 & 0.307908757002993 & 1.62385768065421 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 0.345238095238095 & 0.282139014137777 & 1.2236453589843 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 0.345238095238095 & 0.282139014137777 & 1.2236453589843 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 0.345238095238095 & 0.282139014137777 & 1.2236453589843 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 0.154761904761905 & 0.254333665095881 & 0.608499487095274 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 0.357142857142857 & 0.226375350965226 & 1.57765788377604 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 0.0714285714285714 & 0.188439338983882 & 0.379053396248016 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 0.0714285714285714 & 0.188439338983882 & 0.379053396248016 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 0.0714285714285714 & 0.188439338983882 & 0.379053396248016 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 0.0714285714285714 & 0.188439338983882 & 0.379053396248016 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 0.404761904761905 & 0.146795027690423 & 2.75732707796826 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 0.304878048780488 & 0.354643573117717 & 0.859674534914775 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 0.3125 & 0.347501821322975 & 0.899275862239457 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 0.307692307692308 & 0.34203154609486 & 0.899602130871788 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 0.302631578947368 & 0.33561660291935 & 0.90171814002924 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 0.297297297297297 & 0.32808201996063 & 0.906167602031263 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 0.305555555555556 & 0.322378004542113 & 0.947817627910283 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 0.314285714285714 & 0.315600487252441 & 0.995834059135419 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 0.323529411764706 & 0.307530005581579 & 1.05202551260931 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 0.318181818181818 & 0.301634313640006 & 1.05485948976469 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 0.3125 & 0.29452258247425 & 1.06103918203733 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 0.306451612903226 & 0.285919069434374 & 1.07181243108223 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 0.3 & 0.275455452323401 & 1.08910532526974 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 0.275862068965517 & 0.266946053863862 & 1.03340006331842 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 0.267857142857143 & 0.26172637569194 & 1.02342433829603 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 0.259259259259259 & 0.25518410501628 & 1.01596946738795 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 0.25 & 0.246964986129729 & 1.01228924762912 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 0.26 & 0.24211651774149 & 1.07386312352966 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 0.25 & 0.240971732546631 & 1.03746608516259 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 0.239130434782609 & 0.239130434782609 & 1 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 0.227272727272727 & 0.236392094562633 & 0.961422706174765 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 0.214285714285714 & 0.232483222293033 & 0.921725499897013 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 0.2 & 0.227020839436519 & 0.880976391843207 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 0.184210526315789 & 0.219449923837755 & 0.839419413296224 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 0.166666666666667 & 0.208927723509336 & 0.797724035217466 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 0.176470588235294 & 0.204541085549789 & 0.862763526266404 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 0.1875 & 0.197960875085245 & 0.947156855713329 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 0.2 & 0.188154986249567 & 1.06295349374755 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 0.214285714285714 & 0.173335949744774 & 1.2362450755382 \tabularnewline
Median & 0 &  &  \tabularnewline
Midrange & 0 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.313725490196078 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.313725490196078 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.313725490196078 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.313725490196078 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.313725490196078 &  &  \tabularnewline
Midmean - Closest Observation & 0.313725490196078 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.313725490196078 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.313725490196078 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214558&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]0.297619047619048[/C][C]0.360793637331889[/C][C]0.824901042656892[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]3.30043287204226[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]0.297619047619048[/C][C]0.360793637331889[/C][C]0.824901042656892[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]0.321428571428571[/C][C]0.356144617546708[/C][C]0.902522614669071[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]0.321428571428571[/C][C]0.356144617546708[/C][C]0.902522614669071[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]0.321428571428571[/C][C]0.356144617546708[/C][C]0.902522614669071[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]0.261904761904762[/C][C]0.345497656991377[/C][C]0.758050761285766[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]0.261904761904762[/C][C]0.345497656991377[/C][C]0.758050761285766[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]0.261904761904762[/C][C]0.345497656991377[/C][C]0.758050761285766[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]0.357142857142857[/C][C]0.329137181614228[/C][C]1.08508815500964[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]0.357142857142857[/C][C]0.329137181614228[/C][C]1.08508815500964[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]0.357142857142857[/C][C]0.329137181614228[/C][C]1.08508815500964[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]0.357142857142857[/C][C]0.329137181614228[/C][C]1.08508815500964[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]0.5[/C][C]0.307908757002993[/C][C]1.62385768065421[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]0.345238095238095[/C][C]0.282139014137777[/C][C]1.2236453589843[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]0.345238095238095[/C][C]0.282139014137777[/C][C]1.2236453589843[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]0.345238095238095[/C][C]0.282139014137777[/C][C]1.2236453589843[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]0.154761904761905[/C][C]0.254333665095881[/C][C]0.608499487095274[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]0.357142857142857[/C][C]0.226375350965226[/C][C]1.57765788377604[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]0.0714285714285714[/C][C]0.188439338983882[/C][C]0.379053396248016[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]0.0714285714285714[/C][C]0.188439338983882[/C][C]0.379053396248016[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]0.0714285714285714[/C][C]0.188439338983882[/C][C]0.379053396248016[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]0.0714285714285714[/C][C]0.188439338983882[/C][C]0.379053396248016[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]0.404761904761905[/C][C]0.146795027690423[/C][C]2.75732707796826[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]0.304878048780488[/C][C]0.354643573117717[/C][C]0.859674534914775[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]0.3125[/C][C]0.347501821322975[/C][C]0.899275862239457[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]0.307692307692308[/C][C]0.34203154609486[/C][C]0.899602130871788[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]0.302631578947368[/C][C]0.33561660291935[/C][C]0.90171814002924[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]0.297297297297297[/C][C]0.32808201996063[/C][C]0.906167602031263[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]0.305555555555556[/C][C]0.322378004542113[/C][C]0.947817627910283[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]0.314285714285714[/C][C]0.315600487252441[/C][C]0.995834059135419[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]0.323529411764706[/C][C]0.307530005581579[/C][C]1.05202551260931[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]0.318181818181818[/C][C]0.301634313640006[/C][C]1.05485948976469[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]0.3125[/C][C]0.29452258247425[/C][C]1.06103918203733[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]0.306451612903226[/C][C]0.285919069434374[/C][C]1.07181243108223[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]0.3[/C][C]0.275455452323401[/C][C]1.08910532526974[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]0.275862068965517[/C][C]0.266946053863862[/C][C]1.03340006331842[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]0.267857142857143[/C][C]0.26172637569194[/C][C]1.02342433829603[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]0.259259259259259[/C][C]0.25518410501628[/C][C]1.01596946738795[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]0.25[/C][C]0.246964986129729[/C][C]1.01228924762912[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]0.26[/C][C]0.24211651774149[/C][C]1.07386312352966[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]0.25[/C][C]0.240971732546631[/C][C]1.03746608516259[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]0.239130434782609[/C][C]0.239130434782609[/C][C]1[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]0.227272727272727[/C][C]0.236392094562633[/C][C]0.961422706174765[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]0.214285714285714[/C][C]0.232483222293033[/C][C]0.921725499897013[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]0.2[/C][C]0.227020839436519[/C][C]0.880976391843207[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]0.184210526315789[/C][C]0.219449923837755[/C][C]0.839419413296224[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]0.166666666666667[/C][C]0.208927723509336[/C][C]0.797724035217466[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]0.176470588235294[/C][C]0.204541085549789[/C][C]0.862763526266404[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]0.1875[/C][C]0.197960875085245[/C][C]0.947156855713329[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]0.2[/C][C]0.188154986249567[/C][C]1.06295349374755[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]0.214285714285714[/C][C]0.173335949744774[/C][C]1.2362450755382[/C][/ROW]
[ROW][C]Median[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.313725490196078[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.313725490196078[/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=214558&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214558&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 Mean0.2976190476190480.3607936373318890.824901042656892
Geometric MeanNaN
Harmonic Mean0
Quadratic Mean3.30043287204226
Winsorized Mean ( 1 / 28 )0.2976190476190480.3607936373318890.824901042656892
Winsorized Mean ( 2 / 28 )0.3214285714285710.3561446175467080.902522614669071
Winsorized Mean ( 3 / 28 )0.3214285714285710.3561446175467080.902522614669071
Winsorized Mean ( 4 / 28 )0.3214285714285710.3561446175467080.902522614669071
Winsorized Mean ( 5 / 28 )0.2619047619047620.3454976569913770.758050761285766
Winsorized Mean ( 6 / 28 )0.2619047619047620.3454976569913770.758050761285766
Winsorized Mean ( 7 / 28 )0.2619047619047620.3454976569913770.758050761285766
Winsorized Mean ( 8 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 9 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 10 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 11 / 28 )0.3571428571428570.3291371816142281.08508815500964
Winsorized Mean ( 12 / 28 )0.50.3079087570029931.62385768065421
Winsorized Mean ( 13 / 28 )0.3452380952380950.2821390141377771.2236453589843
Winsorized Mean ( 14 / 28 )0.3452380952380950.2821390141377771.2236453589843
Winsorized Mean ( 15 / 28 )0.3452380952380950.2821390141377771.2236453589843
Winsorized Mean ( 16 / 28 )0.1547619047619050.2543336650958810.608499487095274
Winsorized Mean ( 17 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 18 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 19 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 20 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 21 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 22 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 23 / 28 )0.3571428571428570.2263753509652261.57765788377604
Winsorized Mean ( 24 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 25 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 26 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 27 / 28 )0.07142857142857140.1884393389838820.379053396248016
Winsorized Mean ( 28 / 28 )0.4047619047619050.1467950276904232.75732707796826
Trimmed Mean ( 1 / 28 )0.3048780487804880.3546435731177170.859674534914775
Trimmed Mean ( 2 / 28 )0.31250.3475018213229750.899275862239457
Trimmed Mean ( 3 / 28 )0.3076923076923080.342031546094860.899602130871788
Trimmed Mean ( 4 / 28 )0.3026315789473680.335616602919350.90171814002924
Trimmed Mean ( 5 / 28 )0.2972972972972970.328082019960630.906167602031263
Trimmed Mean ( 6 / 28 )0.3055555555555560.3223780045421130.947817627910283
Trimmed Mean ( 7 / 28 )0.3142857142857140.3156004872524410.995834059135419
Trimmed Mean ( 8 / 28 )0.3235294117647060.3075300055815791.05202551260931
Trimmed Mean ( 9 / 28 )0.3181818181818180.3016343136400061.05485948976469
Trimmed Mean ( 10 / 28 )0.31250.294522582474251.06103918203733
Trimmed Mean ( 11 / 28 )0.3064516129032260.2859190694343741.07181243108223
Trimmed Mean ( 12 / 28 )0.30.2754554523234011.08910532526974
Trimmed Mean ( 13 / 28 )0.2758620689655170.2669460538638621.03340006331842
Trimmed Mean ( 14 / 28 )0.2678571428571430.261726375691941.02342433829603
Trimmed Mean ( 15 / 28 )0.2592592592592590.255184105016281.01596946738795
Trimmed Mean ( 16 / 28 )0.250.2469649861297291.01228924762912
Trimmed Mean ( 17 / 28 )0.260.242116517741491.07386312352966
Trimmed Mean ( 18 / 28 )0.250.2409717325466311.03746608516259
Trimmed Mean ( 19 / 28 )0.2391304347826090.2391304347826091
Trimmed Mean ( 20 / 28 )0.2272727272727270.2363920945626330.961422706174765
Trimmed Mean ( 21 / 28 )0.2142857142857140.2324832222930330.921725499897013
Trimmed Mean ( 22 / 28 )0.20.2270208394365190.880976391843207
Trimmed Mean ( 23 / 28 )0.1842105263157890.2194499238377550.839419413296224
Trimmed Mean ( 24 / 28 )0.1666666666666670.2089277235093360.797724035217466
Trimmed Mean ( 25 / 28 )0.1764705882352940.2045410855497890.862763526266404
Trimmed Mean ( 26 / 28 )0.18750.1979608750852450.947156855713329
Trimmed Mean ( 27 / 28 )0.20.1881549862495671.06295349374755
Trimmed Mean ( 28 / 28 )0.2142857142857140.1733359497447741.2362450755382
Median0
Midrange0
Midmean - Weighted Average at Xnp0.313725490196078
Midmean - Weighted Average at X(n+1)p0.313725490196078
Midmean - Empirical Distribution Function0.313725490196078
Midmean - Empirical Distribution Function - Averaging0.313725490196078
Midmean - Empirical Distribution Function - Interpolation0.313725490196078
Midmean - Closest Observation0.313725490196078
Midmean - True Basic - Statistics Graphics Toolkit0.313725490196078
Midmean - MS Excel (old versions)0.313725490196078
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')