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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 computationSun, 06 Jun 2010 19:13:50 +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/Jun/06/t1275851748yau59tsej5s1igw.htm/, Retrieved Thu, 30 May 2024 15:17:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77770, Retrieved Thu, 30 May 2024 15:17:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W52
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [Opgave 3 - box pl...] [2010-03-03 16:55:40] [74be16979710d4c4e7c6647856088456]
- RM D    [Central Tendency] [Centrummaten mega...] [2010-06-06 19:13:50] [0291ee60c135beb64d296f3dc8feb2dc] [Current]
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Dataseries X:
93.2  
96
 95.2   
 77.1
 70.9
 64.8
 70.1
 77.3
 79.5
100.6
100.7
107.1
 95.9
 82.8
 83.3
80
 80.4
 67.5
 75.7
 71.1
 89.3
101.1
105.2
114.1
 96.3
 84.4
 91.2
 81.9
 80.5
 70.4
 74.8
 75.9
 86.3
 98.7
100.9
113.8
 89.8
 84.4
 87.2
 85.6
72
 69.2
 77.5
 78.1
 94.3
 97.7
100.2
116.4
 97.1
93
96
 80.5
 76.1
 69.9
 73.6
 92.6
 94.2
 93.5
108.5
109.4
105.1
 92.5
 97.1
 81.4
 79.1
 72.1
 78.7
 87.1
 91.4
109.9
116.3
113
100
 84.8
 94.3
 87.1
 90.3
 72.4
 84.9
 92.7
 92.2
114.9
112.5
118.3
106
 91.2
 96.6
 96.3
 88.2
 70.2
 86.5
 88.2
102.8
119.1
119.2
125.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77770&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77770&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77770&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean90.91979166666671.4478035540507862.7984310525305
Geometric Mean89.8366215158824
Harmonic Mean88.768613541631
Quadratic Mean92.0083765434793
Winsorized Mean ( 1 / 32 )90.88645833333331.4286530736348463.6168850301045
Winsorized Mean ( 2 / 32 )90.91979166666671.4223202101653863.9235743237419
Winsorized Mean ( 3 / 32 )90.91666666666671.4136945086342764.311395504039
Winsorized Mean ( 4 / 32 )90.84583333333331.3966940263409165.0434752494313
Winsorized Mean ( 5 / 32 )90.84583333333331.3948793545474465.1280937216305
Winsorized Mean ( 6 / 32 )90.77083333333331.3764529139309565.945469267165
Winsorized Mean ( 7 / 32 )90.74895833333331.3601591389668666.7193681485418
Winsorized Mean ( 8 / 32 )90.7406251.3531044374678567.0610652713614
Winsorized Mean ( 9 / 32 )90.751.3270358408147968.3854928471865
Winsorized Mean ( 10 / 32 )90.70833333333331.3163518388875768.9088818457454
Winsorized Mean ( 11 / 32 )90.44479166666671.2610197330283971.7235339763161
Winsorized Mean ( 12 / 32 )90.53229166666671.2287112550259173.6806888488686
Winsorized Mean ( 13 / 32 )90.57291666666671.1859951029146176.3687104981142
Winsorized Mean ( 14 / 32 )90.51.1358444188618779.6764050579061
Winsorized Mean ( 15 / 32 )90.3593751.1055259704442781.7342852322932
Winsorized Mean ( 16 / 32 )90.2593751.0813070572360683.4724737954757
Winsorized Mean ( 17 / 32 )90.418751.0547431637357885.7258459772774
Winsorized Mean ( 18 / 32 )90.0250.98871926727139591.052134797014
Winsorized Mean ( 19 / 32 )89.7281250.93896137927251995.561039016875
Winsorized Mean ( 20 / 32 )89.81145833333330.91667767512329397.97495976026
Winsorized Mean ( 21 / 32 )89.89895833333330.893624463385304100.600377470387
Winsorized Mean ( 22 / 32 )89.96770833333330.87869332662905102.388063738322
Winsorized Mean ( 23 / 32 )89.96770833333330.854126329546063105.333023021487
Winsorized Mean ( 24 / 32 )90.04270833333330.831816265759287108.248314008553
Winsorized Mean ( 25 / 32 )89.80833333333330.776801339878754115.613000033382
Winsorized Mean ( 26 / 32 )89.56458333333330.741358075708445120.811502926902
Winsorized Mean ( 27 / 32 )89.39583333333330.722132740183163123.794184031399
Winsorized Mean ( 28 / 32 )89.65833333333330.68853178822173130.216694228300
Winsorized Mean ( 29 / 32 )89.65833333333330.652489609157479137.409595608892
Winsorized Mean ( 30 / 32 )89.84583333333330.607202596083102147.966813569152
Winsorized Mean ( 31 / 32 )90.00729166666670.587639951213689153.167413959465
Winsorized Mean ( 32 / 32 )90.27395833333330.53301987387586169.363212814009
Trimmed Mean ( 1 / 32 )90.83404255319151.4053502314070364.6344523402178
Trimmed Mean ( 2 / 32 )90.7793478260871.3788099611067965.8389120957738
Trimmed Mean ( 3 / 32 )90.70444444444441.3522957878753467.0744117209405
Trimmed Mean ( 4 / 32 )90.62727272727271.3255908239660168.3674562985634
Trimmed Mean ( 5 / 32 )90.56627906976741.3006960258843569.629088785899
Trimmed Mean ( 6 / 32 )90.5023809523811.2725183133021271.1206903714668
Trimmed Mean ( 7 / 32 )90.451.2446939475974872.6684661515289
Trimmed Mean ( 8 / 32 )90.398751.2162188418869274.327700646168
Trimmed Mean ( 9 / 32 )90.34615384615381.1846078164018276.266721015378
Trimmed Mean ( 10 / 32 )90.28947368421051.1530411032483878.3055117721688
Trimmed Mean ( 11 / 32 )90.23513513513511.1181406665919580.7010583115349
Trimmed Mean ( 12 / 32 )90.20972222222221.0877881675697682.9294939140224
Trimmed Mean ( 13 / 32 )90.17285714285711.0578209592832185.2439690776777
Trimmed Mean ( 14 / 32 )90.12941176470591.0298828722571487.5142350577928
Trimmed Mean ( 15 / 32 )90.09090909090911.0053533335503489.6111904983286
Trimmed Mean ( 16 / 32 )90.06406250.98116277589151391.7931914183813
Trimmed Mean ( 17 / 32 )90.04516129032260.95612550321172994.1771357294112
Trimmed Mean ( 18 / 32 )90.010.93020774060312396.7633315345665
Trimmed Mean ( 19 / 32 )90.00862068965520.9100477124723598.9053864496033
Trimmed Mean ( 20 / 32 )90.03392857142860.893422126439194100.774231919089
Trimmed Mean ( 21 / 32 )90.05370370370370.876343783805269102.760703468075
Trimmed Mean ( 22 / 32 )90.06730769230770.858744045686406104.882599355103
Trimmed Mean ( 23 / 32 )90.0760.8389671006174107.365354295434
Trimmed Mean ( 24 / 32 )90.08541666666670.818156061077456110.107864443405
Trimmed Mean ( 25 / 32 )90.08913043478260.795550599361013113.241232559113
Trimmed Mean ( 26 / 32 )90.11363636363640.776930800254196115.986695770271
Trimmed Mean ( 27 / 32 )90.16190476190480.758987591929723118.792330362962
Trimmed Mean ( 28 / 32 )90.230.738286303995047122.215459655344
Trimmed Mean ( 29 / 32 )90.28157894736840.718104182434643125.722118260445
Trimmed Mean ( 30 / 32 )90.33888888888890.698493591996351129.333883551735
Trimmed Mean ( 31 / 32 )90.3852941176470.682283211447297132.474744506635
Trimmed Mean ( 32 / 32 )90.4218750.663776681849352136.223337565995
Median91.2
Midrange94.95
Midmean - Weighted Average at Xnp89.869387755102
Midmean - Weighted Average at X(n+1)p90.0854166666666
Midmean - Empirical Distribution Function89.869387755102
Midmean - Empirical Distribution Function - Averaging90.0854166666666
Midmean - Empirical Distribution Function - Interpolation90.0854166666666
Midmean - Closest Observation89.869387755102
Midmean - True Basic - Statistics Graphics Toolkit90.0854166666666
Midmean - MS Excel (old versions)90.076
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 90.9197916666667 & 1.44780355405078 & 62.7984310525305 \tabularnewline
Geometric Mean & 89.8366215158824 &  &  \tabularnewline
Harmonic Mean & 88.768613541631 &  &  \tabularnewline
Quadratic Mean & 92.0083765434793 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 90.8864583333333 & 1.42865307363484 & 63.6168850301045 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 90.9197916666667 & 1.42232021016538 & 63.9235743237419 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 90.9166666666667 & 1.41369450863427 & 64.311395504039 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 90.8458333333333 & 1.39669402634091 & 65.0434752494313 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 90.8458333333333 & 1.39487935454744 & 65.1280937216305 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 90.7708333333333 & 1.37645291393095 & 65.945469267165 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 90.7489583333333 & 1.36015913896686 & 66.7193681485418 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 90.740625 & 1.35310443746785 & 67.0610652713614 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 90.75 & 1.32703584081479 & 68.3854928471865 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 90.7083333333333 & 1.31635183888757 & 68.9088818457454 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 90.4447916666667 & 1.26101973302839 & 71.7235339763161 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 90.5322916666667 & 1.22871125502591 & 73.6806888488686 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 90.5729166666667 & 1.18599510291461 & 76.3687104981142 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 90.5 & 1.13584441886187 & 79.6764050579061 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 90.359375 & 1.10552597044427 & 81.7342852322932 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 90.259375 & 1.08130705723606 & 83.4724737954757 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 90.41875 & 1.05474316373578 & 85.7258459772774 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 90.025 & 0.988719267271395 & 91.052134797014 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 89.728125 & 0.938961379272519 & 95.561039016875 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 89.8114583333333 & 0.916677675123293 & 97.97495976026 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 89.8989583333333 & 0.893624463385304 & 100.600377470387 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 89.9677083333333 & 0.87869332662905 & 102.388063738322 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 89.9677083333333 & 0.854126329546063 & 105.333023021487 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 90.0427083333333 & 0.831816265759287 & 108.248314008553 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 89.8083333333333 & 0.776801339878754 & 115.613000033382 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 89.5645833333333 & 0.741358075708445 & 120.811502926902 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 89.3958333333333 & 0.722132740183163 & 123.794184031399 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 89.6583333333333 & 0.68853178822173 & 130.216694228300 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 89.6583333333333 & 0.652489609157479 & 137.409595608892 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 89.8458333333333 & 0.607202596083102 & 147.966813569152 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 90.0072916666667 & 0.587639951213689 & 153.167413959465 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 90.2739583333333 & 0.53301987387586 & 169.363212814009 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 90.8340425531915 & 1.40535023140703 & 64.6344523402178 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 90.779347826087 & 1.37880996110679 & 65.8389120957738 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 90.7044444444444 & 1.35229578787534 & 67.0744117209405 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 90.6272727272727 & 1.32559082396601 & 68.3674562985634 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 90.5662790697674 & 1.30069602588435 & 69.629088785899 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 90.502380952381 & 1.27251831330212 & 71.1206903714668 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 90.45 & 1.24469394759748 & 72.6684661515289 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 90.39875 & 1.21621884188692 & 74.327700646168 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 90.3461538461538 & 1.18460781640182 & 76.266721015378 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 90.2894736842105 & 1.15304110324838 & 78.3055117721688 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 90.2351351351351 & 1.11814066659195 & 80.7010583115349 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 90.2097222222222 & 1.08778816756976 & 82.9294939140224 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 90.1728571428571 & 1.05782095928321 & 85.2439690776777 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 90.1294117647059 & 1.02988287225714 & 87.5142350577928 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 90.0909090909091 & 1.00535333355034 & 89.6111904983286 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 90.0640625 & 0.981162775891513 & 91.7931914183813 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 90.0451612903226 & 0.956125503211729 & 94.1771357294112 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 90.01 & 0.930207740603123 & 96.7633315345665 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 90.0086206896552 & 0.91004771247235 & 98.9053864496033 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 90.0339285714286 & 0.893422126439194 & 100.774231919089 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 90.0537037037037 & 0.876343783805269 & 102.760703468075 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 90.0673076923077 & 0.858744045686406 & 104.882599355103 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 90.076 & 0.8389671006174 & 107.365354295434 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 90.0854166666667 & 0.818156061077456 & 110.107864443405 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 90.0891304347826 & 0.795550599361013 & 113.241232559113 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 90.1136363636364 & 0.776930800254196 & 115.986695770271 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 90.1619047619048 & 0.758987591929723 & 118.792330362962 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 90.23 & 0.738286303995047 & 122.215459655344 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 90.2815789473684 & 0.718104182434643 & 125.722118260445 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 90.3388888888889 & 0.698493591996351 & 129.333883551735 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 90.385294117647 & 0.682283211447297 & 132.474744506635 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 90.421875 & 0.663776681849352 & 136.223337565995 \tabularnewline
Median & 91.2 &  &  \tabularnewline
Midrange & 94.95 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 89.869387755102 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 90.0854166666666 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 89.869387755102 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 90.0854166666666 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 90.0854166666666 &  &  \tabularnewline
Midmean - Closest Observation & 89.869387755102 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 90.0854166666666 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 90.076 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77770&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]90.9197916666667[/C][C]1.44780355405078[/C][C]62.7984310525305[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]89.8366215158824[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]88.768613541631[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]92.0083765434793[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]90.8864583333333[/C][C]1.42865307363484[/C][C]63.6168850301045[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]90.9197916666667[/C][C]1.42232021016538[/C][C]63.9235743237419[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]90.9166666666667[/C][C]1.41369450863427[/C][C]64.311395504039[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]90.8458333333333[/C][C]1.39669402634091[/C][C]65.0434752494313[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]90.8458333333333[/C][C]1.39487935454744[/C][C]65.1280937216305[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]90.7708333333333[/C][C]1.37645291393095[/C][C]65.945469267165[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]90.7489583333333[/C][C]1.36015913896686[/C][C]66.7193681485418[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]90.740625[/C][C]1.35310443746785[/C][C]67.0610652713614[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]90.75[/C][C]1.32703584081479[/C][C]68.3854928471865[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]90.7083333333333[/C][C]1.31635183888757[/C][C]68.9088818457454[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]90.4447916666667[/C][C]1.26101973302839[/C][C]71.7235339763161[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]90.5322916666667[/C][C]1.22871125502591[/C][C]73.6806888488686[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]90.5729166666667[/C][C]1.18599510291461[/C][C]76.3687104981142[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]90.5[/C][C]1.13584441886187[/C][C]79.6764050579061[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]90.359375[/C][C]1.10552597044427[/C][C]81.7342852322932[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]90.259375[/C][C]1.08130705723606[/C][C]83.4724737954757[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]90.41875[/C][C]1.05474316373578[/C][C]85.7258459772774[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]90.025[/C][C]0.988719267271395[/C][C]91.052134797014[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]89.728125[/C][C]0.938961379272519[/C][C]95.561039016875[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]89.8114583333333[/C][C]0.916677675123293[/C][C]97.97495976026[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]89.8989583333333[/C][C]0.893624463385304[/C][C]100.600377470387[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]89.9677083333333[/C][C]0.87869332662905[/C][C]102.388063738322[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]89.9677083333333[/C][C]0.854126329546063[/C][C]105.333023021487[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]90.0427083333333[/C][C]0.831816265759287[/C][C]108.248314008553[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]89.8083333333333[/C][C]0.776801339878754[/C][C]115.613000033382[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]89.5645833333333[/C][C]0.741358075708445[/C][C]120.811502926902[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]89.3958333333333[/C][C]0.722132740183163[/C][C]123.794184031399[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]89.6583333333333[/C][C]0.68853178822173[/C][C]130.216694228300[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]89.6583333333333[/C][C]0.652489609157479[/C][C]137.409595608892[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]89.8458333333333[/C][C]0.607202596083102[/C][C]147.966813569152[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]90.0072916666667[/C][C]0.587639951213689[/C][C]153.167413959465[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]90.2739583333333[/C][C]0.53301987387586[/C][C]169.363212814009[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]90.8340425531915[/C][C]1.40535023140703[/C][C]64.6344523402178[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]90.779347826087[/C][C]1.37880996110679[/C][C]65.8389120957738[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]90.7044444444444[/C][C]1.35229578787534[/C][C]67.0744117209405[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]90.6272727272727[/C][C]1.32559082396601[/C][C]68.3674562985634[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]90.5662790697674[/C][C]1.30069602588435[/C][C]69.629088785899[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]90.502380952381[/C][C]1.27251831330212[/C][C]71.1206903714668[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]90.45[/C][C]1.24469394759748[/C][C]72.6684661515289[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]90.39875[/C][C]1.21621884188692[/C][C]74.327700646168[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]90.3461538461538[/C][C]1.18460781640182[/C][C]76.266721015378[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]90.2894736842105[/C][C]1.15304110324838[/C][C]78.3055117721688[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]90.2351351351351[/C][C]1.11814066659195[/C][C]80.7010583115349[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]90.2097222222222[/C][C]1.08778816756976[/C][C]82.9294939140224[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]90.1728571428571[/C][C]1.05782095928321[/C][C]85.2439690776777[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]90.1294117647059[/C][C]1.02988287225714[/C][C]87.5142350577928[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]90.0909090909091[/C][C]1.00535333355034[/C][C]89.6111904983286[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]90.0640625[/C][C]0.981162775891513[/C][C]91.7931914183813[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]90.0451612903226[/C][C]0.956125503211729[/C][C]94.1771357294112[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]90.01[/C][C]0.930207740603123[/C][C]96.7633315345665[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]90.0086206896552[/C][C]0.91004771247235[/C][C]98.9053864496033[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]90.0339285714286[/C][C]0.893422126439194[/C][C]100.774231919089[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]90.0537037037037[/C][C]0.876343783805269[/C][C]102.760703468075[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]90.0673076923077[/C][C]0.858744045686406[/C][C]104.882599355103[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]90.076[/C][C]0.8389671006174[/C][C]107.365354295434[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]90.0854166666667[/C][C]0.818156061077456[/C][C]110.107864443405[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]90.0891304347826[/C][C]0.795550599361013[/C][C]113.241232559113[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]90.1136363636364[/C][C]0.776930800254196[/C][C]115.986695770271[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]90.1619047619048[/C][C]0.758987591929723[/C][C]118.792330362962[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]90.23[/C][C]0.738286303995047[/C][C]122.215459655344[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]90.2815789473684[/C][C]0.718104182434643[/C][C]125.722118260445[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]90.3388888888889[/C][C]0.698493591996351[/C][C]129.333883551735[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]90.385294117647[/C][C]0.682283211447297[/C][C]132.474744506635[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]90.421875[/C][C]0.663776681849352[/C][C]136.223337565995[/C][/ROW]
[ROW][C]Median[/C][C]91.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]94.95[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]89.869387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]90.0854166666666[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]89.869387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]90.0854166666666[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]90.0854166666666[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]89.869387755102[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]90.0854166666666[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]90.076[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]96[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77770&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77770&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 Mean90.91979166666671.4478035540507862.7984310525305
Geometric Mean89.8366215158824
Harmonic Mean88.768613541631
Quadratic Mean92.0083765434793
Winsorized Mean ( 1 / 32 )90.88645833333331.4286530736348463.6168850301045
Winsorized Mean ( 2 / 32 )90.91979166666671.4223202101653863.9235743237419
Winsorized Mean ( 3 / 32 )90.91666666666671.4136945086342764.311395504039
Winsorized Mean ( 4 / 32 )90.84583333333331.3966940263409165.0434752494313
Winsorized Mean ( 5 / 32 )90.84583333333331.3948793545474465.1280937216305
Winsorized Mean ( 6 / 32 )90.77083333333331.3764529139309565.945469267165
Winsorized Mean ( 7 / 32 )90.74895833333331.3601591389668666.7193681485418
Winsorized Mean ( 8 / 32 )90.7406251.3531044374678567.0610652713614
Winsorized Mean ( 9 / 32 )90.751.3270358408147968.3854928471865
Winsorized Mean ( 10 / 32 )90.70833333333331.3163518388875768.9088818457454
Winsorized Mean ( 11 / 32 )90.44479166666671.2610197330283971.7235339763161
Winsorized Mean ( 12 / 32 )90.53229166666671.2287112550259173.6806888488686
Winsorized Mean ( 13 / 32 )90.57291666666671.1859951029146176.3687104981142
Winsorized Mean ( 14 / 32 )90.51.1358444188618779.6764050579061
Winsorized Mean ( 15 / 32 )90.3593751.1055259704442781.7342852322932
Winsorized Mean ( 16 / 32 )90.2593751.0813070572360683.4724737954757
Winsorized Mean ( 17 / 32 )90.418751.0547431637357885.7258459772774
Winsorized Mean ( 18 / 32 )90.0250.98871926727139591.052134797014
Winsorized Mean ( 19 / 32 )89.7281250.93896137927251995.561039016875
Winsorized Mean ( 20 / 32 )89.81145833333330.91667767512329397.97495976026
Winsorized Mean ( 21 / 32 )89.89895833333330.893624463385304100.600377470387
Winsorized Mean ( 22 / 32 )89.96770833333330.87869332662905102.388063738322
Winsorized Mean ( 23 / 32 )89.96770833333330.854126329546063105.333023021487
Winsorized Mean ( 24 / 32 )90.04270833333330.831816265759287108.248314008553
Winsorized Mean ( 25 / 32 )89.80833333333330.776801339878754115.613000033382
Winsorized Mean ( 26 / 32 )89.56458333333330.741358075708445120.811502926902
Winsorized Mean ( 27 / 32 )89.39583333333330.722132740183163123.794184031399
Winsorized Mean ( 28 / 32 )89.65833333333330.68853178822173130.216694228300
Winsorized Mean ( 29 / 32 )89.65833333333330.652489609157479137.409595608892
Winsorized Mean ( 30 / 32 )89.84583333333330.607202596083102147.966813569152
Winsorized Mean ( 31 / 32 )90.00729166666670.587639951213689153.167413959465
Winsorized Mean ( 32 / 32 )90.27395833333330.53301987387586169.363212814009
Trimmed Mean ( 1 / 32 )90.83404255319151.4053502314070364.6344523402178
Trimmed Mean ( 2 / 32 )90.7793478260871.3788099611067965.8389120957738
Trimmed Mean ( 3 / 32 )90.70444444444441.3522957878753467.0744117209405
Trimmed Mean ( 4 / 32 )90.62727272727271.3255908239660168.3674562985634
Trimmed Mean ( 5 / 32 )90.56627906976741.3006960258843569.629088785899
Trimmed Mean ( 6 / 32 )90.5023809523811.2725183133021271.1206903714668
Trimmed Mean ( 7 / 32 )90.451.2446939475974872.6684661515289
Trimmed Mean ( 8 / 32 )90.398751.2162188418869274.327700646168
Trimmed Mean ( 9 / 32 )90.34615384615381.1846078164018276.266721015378
Trimmed Mean ( 10 / 32 )90.28947368421051.1530411032483878.3055117721688
Trimmed Mean ( 11 / 32 )90.23513513513511.1181406665919580.7010583115349
Trimmed Mean ( 12 / 32 )90.20972222222221.0877881675697682.9294939140224
Trimmed Mean ( 13 / 32 )90.17285714285711.0578209592832185.2439690776777
Trimmed Mean ( 14 / 32 )90.12941176470591.0298828722571487.5142350577928
Trimmed Mean ( 15 / 32 )90.09090909090911.0053533335503489.6111904983286
Trimmed Mean ( 16 / 32 )90.06406250.98116277589151391.7931914183813
Trimmed Mean ( 17 / 32 )90.04516129032260.95612550321172994.1771357294112
Trimmed Mean ( 18 / 32 )90.010.93020774060312396.7633315345665
Trimmed Mean ( 19 / 32 )90.00862068965520.9100477124723598.9053864496033
Trimmed Mean ( 20 / 32 )90.03392857142860.893422126439194100.774231919089
Trimmed Mean ( 21 / 32 )90.05370370370370.876343783805269102.760703468075
Trimmed Mean ( 22 / 32 )90.06730769230770.858744045686406104.882599355103
Trimmed Mean ( 23 / 32 )90.0760.8389671006174107.365354295434
Trimmed Mean ( 24 / 32 )90.08541666666670.818156061077456110.107864443405
Trimmed Mean ( 25 / 32 )90.08913043478260.795550599361013113.241232559113
Trimmed Mean ( 26 / 32 )90.11363636363640.776930800254196115.986695770271
Trimmed Mean ( 27 / 32 )90.16190476190480.758987591929723118.792330362962
Trimmed Mean ( 28 / 32 )90.230.738286303995047122.215459655344
Trimmed Mean ( 29 / 32 )90.28157894736840.718104182434643125.722118260445
Trimmed Mean ( 30 / 32 )90.33888888888890.698493591996351129.333883551735
Trimmed Mean ( 31 / 32 )90.3852941176470.682283211447297132.474744506635
Trimmed Mean ( 32 / 32 )90.4218750.663776681849352136.223337565995
Median91.2
Midrange94.95
Midmean - Weighted Average at Xnp89.869387755102
Midmean - Weighted Average at X(n+1)p90.0854166666666
Midmean - Empirical Distribution Function89.869387755102
Midmean - Empirical Distribution Function - Averaging90.0854166666666
Midmean - Empirical Distribution Function - Interpolation90.0854166666666
Midmean - Closest Observation89.869387755102
Midmean - True Basic - Statistics Graphics Toolkit90.0854166666666
Midmean - MS Excel (old versions)90.076
Number of observations96



Parameters (Session):
par1 = grey ;
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')