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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 05 Aug 2010 13:28:20 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Aug/05/t12810148997qcf2e4vp5y208j.htm/, Retrieved Sun, 05 May 2024 20:31:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78407, Retrieved Sun, 05 May 2024 20:31:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [TDEown] [2010-08-05 13:28:20] [0abb2f32ac9a4f8da344b8b91382021c] [Current]
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Dataseries X:
3552000
2368000
1184000
1184000
0
0
3552000
4736000
1184000
4736000
3552000
0
0
4736000
7104000
5920000
2368000
2368000
5920000
0
1184000
5920000
0
3552000
3552000
4736000
3552000
1184000
1184000
3552000
1184000
3552000
4736000
2368000
3552000
4736000
3552000
4736000
5920000
2368000
2368000
3552000
0
1184000
1184000
0
1184000
3552000
3552000
7104000
2368000
2368000
2368000
4736000
5920000
2368000
3552000
2368000
2368000
5920000
3552000
0
3552000
4736000
2368000
3552000
4736000
2368000
2368000
7104000
3552000
3552000
3552000
4736000
1184000
2368000
3552000
0
1184000
1184000
2368000
3552000
2368000
2368000
1184000
2368000
1184000
3552000
5920000
1184000
2368000
2368000
3552000
2368000
5920000
0
2368000
4736000
1184000
4736000




Summary of computational 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 computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78407&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78407&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78407&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean2924480182383.21099411916.0348092571651
Geometric Mean0
Harmonic Mean0
Quadratic Mean3441755.83096768
Winsorized Mean ( 1 / 33 )2924480182383.21099411916.0348092571651
Winsorized Mean ( 2 / 33 )2924480182383.21099411916.0348092571651
Winsorized Mean ( 3 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 4 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 5 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 6 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 7 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 8 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 9 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 10 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 11 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 12 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 13 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 14 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 15 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 16 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 17 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 18 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 19 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 20 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 21 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 22 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 23 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 24 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 25 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 26 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 27 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 28 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 29 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 30 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 31 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 32 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 33 / 33 )293632059450.621017731549.3909054225729
Trimmed Mean ( 1 / 33 )2911673.46938776178615.00191534116.301393713658
Trimmed Mean ( 2 / 33 )2898333.33333333174341.6253772516.6244482754005
Trimmed Mean ( 3 / 33 )2884425.53191489169478.54640472317.0194139205487
Trimmed Mean ( 4 / 33 )2882782.60869565167026.70924743617.2594109150834
Trimmed Mean ( 5 / 33 )2881066.66666667164224.05206273917.5435122351384
Trimmed Mean ( 6 / 33 )2879272.72727273161015.77439749717.8819295068862
Trimmed Mean ( 7 / 33 )2877395.34883721157334.81710287818.288357286841
Trimmed Mean ( 8 / 33 )2875428.57142857153097.84320589118.7816399709929
Trimmed Mean ( 9 / 33 )2873365.85365854148199.32083797419.3885224130006
Trimmed Mean ( 10 / 33 )2871200142502.45212191820.1484252182801
Trimmed Mean ( 11 / 33 )2868923.07692308135824.55085315921.1222717756283
Trimmed Mean ( 12 / 33 )2866526.31578947135384.54843769521.1732162116614
Trimmed Mean ( 13 / 33 )2864000134792.38220823121.247491535357
Trimmed Mean ( 14 / 33 )2861333.33333333134022.25774551421.3496875926872
Trimmed Mean ( 15 / 33 )2858514.28571429133043.05058766421.4856339589926
Trimmed Mean ( 16 / 33 )2855529.41176471131816.87165043421.6628522283347
Trimmed Mean ( 17 / 33 )2852363.63636364130297.12438505121.891224766668
Trimmed Mean ( 18 / 33 )2849000128425.81701585722.1840130450423
Trimmed Mean ( 19 / 33 )2845419.35483871126129.74934234622.5594625350089
Trimmed Mean ( 20 / 33 )2841600123314.93648103623.0434372436058
Trimmed Mean ( 21 / 33 )2837517.24137931119858.14675122123.6739622486313
Trimmed Mean ( 22 / 33 )2833142.85714286115593.45302476824.5095442951757
Trimmed Mean ( 23 / 33 )2828444.44444444110289.55811588325.6456231465952
Trimmed Mean ( 24 / 33 )2823384.61538462103608.4626845427.2505212627375
Trimmed Mean ( 25 / 33 )2841600101485.71428571428
Trimmed Mean ( 26 / 33 )2861333.3333333398666.666666666729
Trimmed Mean ( 27 / 33 )2882782.6086956594921.222934215530.3702640946119
Trimmed Mean ( 28 / 33 )2906181.8181818289905.325308010532.3249129929223
Trimmed Mean ( 29 / 33 )2906181.8181818292034.615466750431.5770517803896
Trimmed Mean ( 30 / 33 )290080094320.696806977930.7546498085815
Trimmed Mean ( 31 / 33 )2897684.2105263296783.506298401629.9398556773942
Trimmed Mean ( 32 / 33 )2894222.2222222299446.652453983329.1032644217105
Trimmed Mean ( 33 / 33 )2890352.94117647102338.31108176328.2431174662169
Median2368000
Midrange3552000
Midmean - Weighted Average at Xnp2495507.69230769
Midmean - Weighted Average at X(n+1)p2495507.69230769
Midmean - Empirical Distribution Function2495507.69230769
Midmean - Empirical Distribution Function - Averaging2495507.69230769
Midmean - Empirical Distribution Function - Interpolation2495507.69230769
Midmean - Closest Observation2495507.69230769
Midmean - True Basic - Statistics Graphics Toolkit2495507.69230769
Midmean - MS Excel (old versions)2495507.69230769
Number of observations100

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 2924480 & 182383.210994119 & 16.0348092571651 \tabularnewline
Geometric Mean & 0 &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 3441755.83096768 &  &  \tabularnewline
Winsorized Mean ( 1 / 33 ) & 2924480 & 182383.210994119 & 16.0348092571651 \tabularnewline
Winsorized Mean ( 2 / 33 ) & 2924480 & 182383.210994119 & 16.0348092571651 \tabularnewline
Winsorized Mean ( 3 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 4 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 5 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 6 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 7 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 8 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 9 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 10 / 33 ) & 2888960 & 175147.292657502 & 16.4944599266477 \tabularnewline
Winsorized Mean ( 11 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 12 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 13 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 14 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 15 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 16 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 17 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 18 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 19 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 20 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 21 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 22 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 23 / 33 ) & 2888960 & 134965.298884677 & 21.4052058112249 \tabularnewline
Winsorized Mean ( 24 / 33 ) & 2604800 & 100971.859266017 & 25.7972866790289 \tabularnewline
Winsorized Mean ( 25 / 33 ) & 2604800 & 100971.859266017 & 25.7972866790289 \tabularnewline
Winsorized Mean ( 26 / 33 ) & 2604800 & 100971.859266017 & 25.7972866790289 \tabularnewline
Winsorized Mean ( 27 / 33 ) & 2604800 & 100971.859266017 & 25.7972866790289 \tabularnewline
Winsorized Mean ( 28 / 33 ) & 2936320 & 59450.6210177315 & 49.3909054225729 \tabularnewline
Winsorized Mean ( 29 / 33 ) & 2936320 & 59450.6210177315 & 49.3909054225729 \tabularnewline
Winsorized Mean ( 30 / 33 ) & 2936320 & 59450.6210177315 & 49.3909054225729 \tabularnewline
Winsorized Mean ( 31 / 33 ) & 2936320 & 59450.6210177315 & 49.3909054225729 \tabularnewline
Winsorized Mean ( 32 / 33 ) & 2936320 & 59450.6210177315 & 49.3909054225729 \tabularnewline
Winsorized Mean ( 33 / 33 ) & 2936320 & 59450.6210177315 & 49.3909054225729 \tabularnewline
Trimmed Mean ( 1 / 33 ) & 2911673.46938776 & 178615.001915341 & 16.301393713658 \tabularnewline
Trimmed Mean ( 2 / 33 ) & 2898333.33333333 & 174341.62537725 & 16.6244482754005 \tabularnewline
Trimmed Mean ( 3 / 33 ) & 2884425.53191489 & 169478.546404723 & 17.0194139205487 \tabularnewline
Trimmed Mean ( 4 / 33 ) & 2882782.60869565 & 167026.709247436 & 17.2594109150834 \tabularnewline
Trimmed Mean ( 5 / 33 ) & 2881066.66666667 & 164224.052062739 & 17.5435122351384 \tabularnewline
Trimmed Mean ( 6 / 33 ) & 2879272.72727273 & 161015.774397497 & 17.8819295068862 \tabularnewline
Trimmed Mean ( 7 / 33 ) & 2877395.34883721 & 157334.817102878 & 18.288357286841 \tabularnewline
Trimmed Mean ( 8 / 33 ) & 2875428.57142857 & 153097.843205891 & 18.7816399709929 \tabularnewline
Trimmed Mean ( 9 / 33 ) & 2873365.85365854 & 148199.320837974 & 19.3885224130006 \tabularnewline
Trimmed Mean ( 10 / 33 ) & 2871200 & 142502.452121918 & 20.1484252182801 \tabularnewline
Trimmed Mean ( 11 / 33 ) & 2868923.07692308 & 135824.550853159 & 21.1222717756283 \tabularnewline
Trimmed Mean ( 12 / 33 ) & 2866526.31578947 & 135384.548437695 & 21.1732162116614 \tabularnewline
Trimmed Mean ( 13 / 33 ) & 2864000 & 134792.382208231 & 21.247491535357 \tabularnewline
Trimmed Mean ( 14 / 33 ) & 2861333.33333333 & 134022.257745514 & 21.3496875926872 \tabularnewline
Trimmed Mean ( 15 / 33 ) & 2858514.28571429 & 133043.050587664 & 21.4856339589926 \tabularnewline
Trimmed Mean ( 16 / 33 ) & 2855529.41176471 & 131816.871650434 & 21.6628522283347 \tabularnewline
Trimmed Mean ( 17 / 33 ) & 2852363.63636364 & 130297.124385051 & 21.891224766668 \tabularnewline
Trimmed Mean ( 18 / 33 ) & 2849000 & 128425.817015857 & 22.1840130450423 \tabularnewline
Trimmed Mean ( 19 / 33 ) & 2845419.35483871 & 126129.749342346 & 22.5594625350089 \tabularnewline
Trimmed Mean ( 20 / 33 ) & 2841600 & 123314.936481036 & 23.0434372436058 \tabularnewline
Trimmed Mean ( 21 / 33 ) & 2837517.24137931 & 119858.146751221 & 23.6739622486313 \tabularnewline
Trimmed Mean ( 22 / 33 ) & 2833142.85714286 & 115593.453024768 & 24.5095442951757 \tabularnewline
Trimmed Mean ( 23 / 33 ) & 2828444.44444444 & 110289.558115883 & 25.6456231465952 \tabularnewline
Trimmed Mean ( 24 / 33 ) & 2823384.61538462 & 103608.46268454 & 27.2505212627375 \tabularnewline
Trimmed Mean ( 25 / 33 ) & 2841600 & 101485.714285714 & 28 \tabularnewline
Trimmed Mean ( 26 / 33 ) & 2861333.33333333 & 98666.6666666667 & 29 \tabularnewline
Trimmed Mean ( 27 / 33 ) & 2882782.60869565 & 94921.2229342155 & 30.3702640946119 \tabularnewline
Trimmed Mean ( 28 / 33 ) & 2906181.81818182 & 89905.3253080105 & 32.3249129929223 \tabularnewline
Trimmed Mean ( 29 / 33 ) & 2906181.81818182 & 92034.6154667504 & 31.5770517803896 \tabularnewline
Trimmed Mean ( 30 / 33 ) & 2900800 & 94320.6968069779 & 30.7546498085815 \tabularnewline
Trimmed Mean ( 31 / 33 ) & 2897684.21052632 & 96783.5062984016 & 29.9398556773942 \tabularnewline
Trimmed Mean ( 32 / 33 ) & 2894222.22222222 & 99446.6524539833 & 29.1032644217105 \tabularnewline
Trimmed Mean ( 33 / 33 ) & 2890352.94117647 & 102338.311081763 & 28.2431174662169 \tabularnewline
Median & 2368000 &  &  \tabularnewline
Midrange & 3552000 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2495507.69230769 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2495507.69230769 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2495507.69230769 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2495507.69230769 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2495507.69230769 &  &  \tabularnewline
Midmean - Closest Observation & 2495507.69230769 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2495507.69230769 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2495507.69230769 &  &  \tabularnewline
Number of observations & 100 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78407&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]2924480[/C][C]182383.210994119[/C][C]16.0348092571651[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]0[/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]3441755.83096768[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 33 )[/C][C]2924480[/C][C]182383.210994119[/C][C]16.0348092571651[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 33 )[/C][C]2924480[/C][C]182383.210994119[/C][C]16.0348092571651[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 33 )[/C][C]2888960[/C][C]175147.292657502[/C][C]16.4944599266477[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 33 )[/C][C]2888960[/C][C]134965.298884677[/C][C]21.4052058112249[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 33 )[/C][C]2604800[/C][C]100971.859266017[/C][C]25.7972866790289[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 33 )[/C][C]2604800[/C][C]100971.859266017[/C][C]25.7972866790289[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 33 )[/C][C]2604800[/C][C]100971.859266017[/C][C]25.7972866790289[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 33 )[/C][C]2604800[/C][C]100971.859266017[/C][C]25.7972866790289[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 33 )[/C][C]2936320[/C][C]59450.6210177315[/C][C]49.3909054225729[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 33 )[/C][C]2936320[/C][C]59450.6210177315[/C][C]49.3909054225729[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 33 )[/C][C]2936320[/C][C]59450.6210177315[/C][C]49.3909054225729[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 33 )[/C][C]2936320[/C][C]59450.6210177315[/C][C]49.3909054225729[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 33 )[/C][C]2936320[/C][C]59450.6210177315[/C][C]49.3909054225729[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 33 )[/C][C]2936320[/C][C]59450.6210177315[/C][C]49.3909054225729[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 33 )[/C][C]2911673.46938776[/C][C]178615.001915341[/C][C]16.301393713658[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 33 )[/C][C]2898333.33333333[/C][C]174341.62537725[/C][C]16.6244482754005[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 33 )[/C][C]2884425.53191489[/C][C]169478.546404723[/C][C]17.0194139205487[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 33 )[/C][C]2882782.60869565[/C][C]167026.709247436[/C][C]17.2594109150834[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 33 )[/C][C]2881066.66666667[/C][C]164224.052062739[/C][C]17.5435122351384[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 33 )[/C][C]2879272.72727273[/C][C]161015.774397497[/C][C]17.8819295068862[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 33 )[/C][C]2877395.34883721[/C][C]157334.817102878[/C][C]18.288357286841[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 33 )[/C][C]2875428.57142857[/C][C]153097.843205891[/C][C]18.7816399709929[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 33 )[/C][C]2873365.85365854[/C][C]148199.320837974[/C][C]19.3885224130006[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 33 )[/C][C]2871200[/C][C]142502.452121918[/C][C]20.1484252182801[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 33 )[/C][C]2868923.07692308[/C][C]135824.550853159[/C][C]21.1222717756283[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 33 )[/C][C]2866526.31578947[/C][C]135384.548437695[/C][C]21.1732162116614[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 33 )[/C][C]2864000[/C][C]134792.382208231[/C][C]21.247491535357[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 33 )[/C][C]2861333.33333333[/C][C]134022.257745514[/C][C]21.3496875926872[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 33 )[/C][C]2858514.28571429[/C][C]133043.050587664[/C][C]21.4856339589926[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 33 )[/C][C]2855529.41176471[/C][C]131816.871650434[/C][C]21.6628522283347[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 33 )[/C][C]2852363.63636364[/C][C]130297.124385051[/C][C]21.891224766668[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 33 )[/C][C]2849000[/C][C]128425.817015857[/C][C]22.1840130450423[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 33 )[/C][C]2845419.35483871[/C][C]126129.749342346[/C][C]22.5594625350089[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 33 )[/C][C]2841600[/C][C]123314.936481036[/C][C]23.0434372436058[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 33 )[/C][C]2837517.24137931[/C][C]119858.146751221[/C][C]23.6739622486313[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 33 )[/C][C]2833142.85714286[/C][C]115593.453024768[/C][C]24.5095442951757[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 33 )[/C][C]2828444.44444444[/C][C]110289.558115883[/C][C]25.6456231465952[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 33 )[/C][C]2823384.61538462[/C][C]103608.46268454[/C][C]27.2505212627375[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 33 )[/C][C]2841600[/C][C]101485.714285714[/C][C]28[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 33 )[/C][C]2861333.33333333[/C][C]98666.6666666667[/C][C]29[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 33 )[/C][C]2882782.60869565[/C][C]94921.2229342155[/C][C]30.3702640946119[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 33 )[/C][C]2906181.81818182[/C][C]89905.3253080105[/C][C]32.3249129929223[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 33 )[/C][C]2906181.81818182[/C][C]92034.6154667504[/C][C]31.5770517803896[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 33 )[/C][C]2900800[/C][C]94320.6968069779[/C][C]30.7546498085815[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 33 )[/C][C]2897684.21052632[/C][C]96783.5062984016[/C][C]29.9398556773942[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 33 )[/C][C]2894222.22222222[/C][C]99446.6524539833[/C][C]29.1032644217105[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 33 )[/C][C]2890352.94117647[/C][C]102338.311081763[/C][C]28.2431174662169[/C][/ROW]
[ROW][C]Median[/C][C]2368000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3552000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2495507.69230769[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]100[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78407&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78407&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 Mean2924480182383.21099411916.0348092571651
Geometric Mean0
Harmonic Mean0
Quadratic Mean3441755.83096768
Winsorized Mean ( 1 / 33 )2924480182383.21099411916.0348092571651
Winsorized Mean ( 2 / 33 )2924480182383.21099411916.0348092571651
Winsorized Mean ( 3 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 4 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 5 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 6 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 7 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 8 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 9 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 10 / 33 )2888960175147.29265750216.4944599266477
Winsorized Mean ( 11 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 12 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 13 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 14 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 15 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 16 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 17 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 18 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 19 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 20 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 21 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 22 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 23 / 33 )2888960134965.29888467721.4052058112249
Winsorized Mean ( 24 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 25 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 26 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 27 / 33 )2604800100971.85926601725.7972866790289
Winsorized Mean ( 28 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 29 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 30 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 31 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 32 / 33 )293632059450.621017731549.3909054225729
Winsorized Mean ( 33 / 33 )293632059450.621017731549.3909054225729
Trimmed Mean ( 1 / 33 )2911673.46938776178615.00191534116.301393713658
Trimmed Mean ( 2 / 33 )2898333.33333333174341.6253772516.6244482754005
Trimmed Mean ( 3 / 33 )2884425.53191489169478.54640472317.0194139205487
Trimmed Mean ( 4 / 33 )2882782.60869565167026.70924743617.2594109150834
Trimmed Mean ( 5 / 33 )2881066.66666667164224.05206273917.5435122351384
Trimmed Mean ( 6 / 33 )2879272.72727273161015.77439749717.8819295068862
Trimmed Mean ( 7 / 33 )2877395.34883721157334.81710287818.288357286841
Trimmed Mean ( 8 / 33 )2875428.57142857153097.84320589118.7816399709929
Trimmed Mean ( 9 / 33 )2873365.85365854148199.32083797419.3885224130006
Trimmed Mean ( 10 / 33 )2871200142502.45212191820.1484252182801
Trimmed Mean ( 11 / 33 )2868923.07692308135824.55085315921.1222717756283
Trimmed Mean ( 12 / 33 )2866526.31578947135384.54843769521.1732162116614
Trimmed Mean ( 13 / 33 )2864000134792.38220823121.247491535357
Trimmed Mean ( 14 / 33 )2861333.33333333134022.25774551421.3496875926872
Trimmed Mean ( 15 / 33 )2858514.28571429133043.05058766421.4856339589926
Trimmed Mean ( 16 / 33 )2855529.41176471131816.87165043421.6628522283347
Trimmed Mean ( 17 / 33 )2852363.63636364130297.12438505121.891224766668
Trimmed Mean ( 18 / 33 )2849000128425.81701585722.1840130450423
Trimmed Mean ( 19 / 33 )2845419.35483871126129.74934234622.5594625350089
Trimmed Mean ( 20 / 33 )2841600123314.93648103623.0434372436058
Trimmed Mean ( 21 / 33 )2837517.24137931119858.14675122123.6739622486313
Trimmed Mean ( 22 / 33 )2833142.85714286115593.45302476824.5095442951757
Trimmed Mean ( 23 / 33 )2828444.44444444110289.55811588325.6456231465952
Trimmed Mean ( 24 / 33 )2823384.61538462103608.4626845427.2505212627375
Trimmed Mean ( 25 / 33 )2841600101485.71428571428
Trimmed Mean ( 26 / 33 )2861333.3333333398666.666666666729
Trimmed Mean ( 27 / 33 )2882782.6086956594921.222934215530.3702640946119
Trimmed Mean ( 28 / 33 )2906181.8181818289905.325308010532.3249129929223
Trimmed Mean ( 29 / 33 )2906181.8181818292034.615466750431.5770517803896
Trimmed Mean ( 30 / 33 )290080094320.696806977930.7546498085815
Trimmed Mean ( 31 / 33 )2897684.2105263296783.506298401629.9398556773942
Trimmed Mean ( 32 / 33 )2894222.2222222299446.652453983329.1032644217105
Trimmed Mean ( 33 / 33 )2890352.94117647102338.31108176328.2431174662169
Median2368000
Midrange3552000
Midmean - Weighted Average at Xnp2495507.69230769
Midmean - Weighted Average at X(n+1)p2495507.69230769
Midmean - Empirical Distribution Function2495507.69230769
Midmean - Empirical Distribution Function - Averaging2495507.69230769
Midmean - Empirical Distribution Function - Interpolation2495507.69230769
Midmean - Closest Observation2495507.69230769
Midmean - True Basic - Statistics Graphics Toolkit2495507.69230769
Midmean - MS Excel (old versions)2495507.69230769
Number of observations100



Parameters (Session):
par1 = 24 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 0 ; par9 = 0 ; par10 = TRUE ;
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')