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*The author of this computation has been verified*

R Software Module

rwasp_centraltendency.wasp

Title produced by software

Central Tendency

Date of computation

Tue, 20 Oct 2009 14:31:10 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/20/t1256070799ft4w8ai6bh9b95e.htm/, Retrieved Thu, 02 May 2024 21:14:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49138, Retrieved Thu, 02 May 2024 21:14:44 +0000

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Original text written by user:

De berekening om de extremen weg te werken

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

100

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Central Tendency] [Workshop 3 part 2...] [2009-10-20 20:31:10] [852eae237d08746109043531619a60c9] [Current]

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0,2
0,4
0,4
0,3
0,2
0
-0,2
-0,2
-0,5
-0,5
0,1
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0,1
0
0,1
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0,3
0
-0,3
-0,6
-0,6
0,2
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0,1
-0,1
0
0,2
0,2
0
-0,2
-0,5
-0,6
0,1
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0,2
0
-0,1
0
0,2
0,2
0,1
0
-0,3
-0,4
0,1
0,1
0,1
0
-0,1
0
0,2
0,2
0
-0,1
-0,3
-0,4
0,2
0,3
0,2
0
-0,1
0
0,2
0,2
0,1
-0,3
-0,5
-0,4
0,4
0,4
0,2
-0,2
-0,3
-0,2
0,2
0,3
0,2
-0,1
-0,4
-0,3
0,3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49138&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49138&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49138&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	0.00602409638554217	0.029609536430608	0.203451222536363
Geometric Mean	NaN
Harmonic Mean	0
Quadratic Mean	0.268193420581814
Winsorized Mean ( 1 / 27 )	0.00602409638554217	0.029609536430608	0.203451222536363
Winsorized Mean ( 2 / 27 )	0.00602409638554217	0.029609536430608	0.203451222536363
Winsorized Mean ( 3 / 27 )	0.00963855421686747	0.0287671275602443	0.335054453965984
Winsorized Mean ( 4 / 27 )	0.00963855421686747	0.0287671275602443	0.335054453965984
Winsorized Mean ( 5 / 27 )	0.00963855421686747	0.0287671275602443	0.335054453965984
Winsorized Mean ( 6 / 27 )	0.00240963855421687	0.0276929505662032	0.0870127055784954
Winsorized Mean ( 7 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767034
Winsorized Mean ( 8 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767034
Winsorized Mean ( 9 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767034
Winsorized Mean ( 10 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767035
Winsorized Mean ( 11 / 27 )	0.0240963855421687	0.0235412094798144	1.02358315798644
Winsorized Mean ( 12 / 27 )	0.0240963855421687	0.0235412094798144	1.02358315798644
Winsorized Mean ( 13 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 14 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 15 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 16 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 17 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 18 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 19 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 20 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 21 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 22 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Winsorized Mean ( 23 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Winsorized Mean ( 24 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Winsorized Mean ( 25 / 27 )	0.0554216867469879	0.0143681713953220	3.8572540111146
Winsorized Mean ( 26 / 27 )	0.0554216867469879	0.0143681713953220	3.8572540111146
Winsorized Mean ( 27 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Trimmed Mean ( 1 / 27 )	0.00864197530864198	0.0289847517843540	0.298155919116994
Trimmed Mean ( 2 / 27 )	0.0113924050632911	0.0282559901518547	0.403185483929799
Trimmed Mean ( 3 / 27 )	0.0142857142857143	0.0274026135999149	0.521326706068602
Trimmed Mean ( 4 / 27 )	0.016	0.0267817337239631	0.597422114823131
Trimmed Mean ( 5 / 27 )	0.0178082191780822	0.0260504184018133	0.6836058793145
Trimmed Mean ( 6 / 27 )	0.0197183098591549	0.0251850070622142	0.78293842882176
Trimmed Mean ( 7 / 27 )	0.0197183098591549	0.0244413217265725	0.806761192366994
Trimmed Mean ( 8 / 27 )	0.0253731343283582	0.0239990279071647	1.05725675333638
Trimmed Mean ( 9 / 27 )	0.0276923076923077	0.0234631147011493	1.18024857505177
Trimmed Mean ( 10 / 27 )	0.0301587301587302	0.0228123672492173	1.3220342207039
Trimmed Mean ( 11 / 27 )	0.0327868852459016	0.0220185355939421	1.48905839382535
Trimmed Mean ( 12 / 27 )	0.0338983050847458	0.0215704531840234	1.57151566522734
Trimmed Mean ( 13 / 27 )	0.0350877192982456	0.0210160500889666	1.66956774225936
Trimmed Mean ( 14 / 27 )	0.0350877192982456	0.0206772389202812	1.69692478930685
Trimmed Mean ( 15 / 27 )	0.0415094339622642	0.0202369781572196	2.05116760218746
Trimmed Mean ( 16 / 27 )	0.0450980392156863	0.0196665786950899	2.29313089556069
Trimmed Mean ( 17 / 27 )	0.0489795918367347	0.0189257520316239	2.58798655688252
Trimmed Mean ( 18 / 27 )	0.0510638297872340	0.0187175165244493	2.72813061073210
Trimmed Mean ( 19 / 27 )	0.0533333333333333	0.0184226474588735	2.89498745782298
Trimmed Mean ( 20 / 27 )	0.0558139534883721	0.0180138760288717	3.09838667696593
Trimmed Mean ( 21 / 27 )	0.0585365853658537	0.0174522378731691	3.35410196624968
Trimmed Mean ( 22 / 27 )	0.0615384615384615	0.0166796378466725	3.68943631175651
Trimmed Mean ( 23 / 27 )	0.0621621621621622	0.0165995727681876	3.74480494349187
Trimmed Mean ( 24 / 27 )	0.0628571428571429	0.0164422668527093	3.82290005509706
Trimmed Mean ( 25 / 27 )	0.0636363636363636	0.0161773912909565	3.93366040864312
Trimmed Mean ( 26 / 27 )	0.064516129032258	0.0157592008262893	4.09387060571201
Trimmed Mean ( 27 / 27 )	0.0655172413793104	0.0151152078744495	4.33452466704474
Median	0.1
Midrange	-0.1
Midmean - Weighted Average at Xnp	0.060377358490566
Midmean - Weighted Average at X(n+1)p	0.060377358490566
Midmean - Empirical Distribution Function	0.060377358490566
Midmean - Empirical Distribution Function - Averaging	0.060377358490566
Midmean - Empirical Distribution Function - Interpolation	0.060377358490566
Midmean - Closest Observation	0.060377358490566
Midmean - True Basic - Statistics Graphics Toolkit	0.060377358490566
Midmean - MS Excel (old versions)	0.060377358490566
Number of observations	83

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.00602409638554217 & 0.029609536430608 & 0.203451222536363 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 0.268193420581814 &  &  \tabularnewline
Winsorized Mean ( 1 / 27 ) & 0.00602409638554217 & 0.029609536430608 & 0.203451222536363 \tabularnewline
Winsorized Mean ( 2 / 27 ) & 0.00602409638554217 & 0.029609536430608 & 0.203451222536363 \tabularnewline
Winsorized Mean ( 3 / 27 ) & 0.00963855421686747 & 0.0287671275602443 & 0.335054453965984 \tabularnewline
Winsorized Mean ( 4 / 27 ) & 0.00963855421686747 & 0.0287671275602443 & 0.335054453965984 \tabularnewline
Winsorized Mean ( 5 / 27 ) & 0.00963855421686747 & 0.0287671275602443 & 0.335054453965984 \tabularnewline
Winsorized Mean ( 6 / 27 ) & 0.00240963855421687 & 0.0276929505662032 & 0.0870127055784954 \tabularnewline
Winsorized Mean ( 7 / 27 ) & 0.0108433734939759 & 0.0259416855589767 & 0.417990321767034 \tabularnewline
Winsorized Mean ( 8 / 27 ) & 0.0108433734939759 & 0.0259416855589767 & 0.417990321767034 \tabularnewline
Winsorized Mean ( 9 / 27 ) & 0.0108433734939759 & 0.0259416855589767 & 0.417990321767034 \tabularnewline
Winsorized Mean ( 10 / 27 ) & 0.0108433734939759 & 0.0259416855589767 & 0.417990321767035 \tabularnewline
Winsorized Mean ( 11 / 27 ) & 0.0240963855421687 & 0.0235412094798144 & 1.02358315798644 \tabularnewline
Winsorized Mean ( 12 / 27 ) & 0.0240963855421687 & 0.0235412094798144 & 1.02358315798644 \tabularnewline
Winsorized Mean ( 13 / 27 ) & 0.00843373493975904 & 0.0215614954907210 & 0.391147958331022 \tabularnewline
Winsorized Mean ( 14 / 27 ) & 0.00843373493975904 & 0.0215614954907210 & 0.391147958331022 \tabularnewline
Winsorized Mean ( 15 / 27 ) & 0.00843373493975904 & 0.0215614954907210 & 0.391147958331022 \tabularnewline
Winsorized Mean ( 16 / 27 ) & 0.00843373493975904 & 0.0215614954907210 & 0.391147958331022 \tabularnewline
Winsorized Mean ( 17 / 27 ) & 0.0289156626506024 & 0.0181845859688485 & 1.59011938463361 \tabularnewline
Winsorized Mean ( 18 / 27 ) & 0.0289156626506024 & 0.0181845859688485 & 1.59011938463361 \tabularnewline
Winsorized Mean ( 19 / 27 ) & 0.0289156626506024 & 0.0181845859688485 & 1.59011938463361 \tabularnewline
Winsorized Mean ( 20 / 27 ) & 0.0289156626506024 & 0.0181845859688485 & 1.59011938463361 \tabularnewline
Winsorized Mean ( 21 / 27 ) & 0.0289156626506024 & 0.0181845859688485 & 1.59011938463361 \tabularnewline
Winsorized Mean ( 22 / 27 ) & 0.055421686746988 & 0.0143681713953220 & 3.8572540111146 \tabularnewline
Winsorized Mean ( 23 / 27 ) & 0.055421686746988 & 0.0143681713953220 & 3.8572540111146 \tabularnewline
Winsorized Mean ( 24 / 27 ) & 0.055421686746988 & 0.0143681713953220 & 3.8572540111146 \tabularnewline
Winsorized Mean ( 25 / 27 ) & 0.0554216867469879 & 0.0143681713953220 & 3.8572540111146 \tabularnewline
Winsorized Mean ( 26 / 27 ) & 0.0554216867469879 & 0.0143681713953220 & 3.8572540111146 \tabularnewline
Winsorized Mean ( 27 / 27 ) & 0.055421686746988 & 0.0143681713953220 & 3.8572540111146 \tabularnewline
Trimmed Mean ( 1 / 27 ) & 0.00864197530864198 & 0.0289847517843540 & 0.298155919116994 \tabularnewline
Trimmed Mean ( 2 / 27 ) & 0.0113924050632911 & 0.0282559901518547 & 0.403185483929799 \tabularnewline
Trimmed Mean ( 3 / 27 ) & 0.0142857142857143 & 0.0274026135999149 & 0.521326706068602 \tabularnewline
Trimmed Mean ( 4 / 27 ) & 0.016 & 0.0267817337239631 & 0.597422114823131 \tabularnewline
Trimmed Mean ( 5 / 27 ) & 0.0178082191780822 & 0.0260504184018133 & 0.6836058793145 \tabularnewline
Trimmed Mean ( 6 / 27 ) & 0.0197183098591549 & 0.0251850070622142 & 0.78293842882176 \tabularnewline
Trimmed Mean ( 7 / 27 ) & 0.0197183098591549 & 0.0244413217265725 & 0.806761192366994 \tabularnewline
Trimmed Mean ( 8 / 27 ) & 0.0253731343283582 & 0.0239990279071647 & 1.05725675333638 \tabularnewline
Trimmed Mean ( 9 / 27 ) & 0.0276923076923077 & 0.0234631147011493 & 1.18024857505177 \tabularnewline
Trimmed Mean ( 10 / 27 ) & 0.0301587301587302 & 0.0228123672492173 & 1.3220342207039 \tabularnewline
Trimmed Mean ( 11 / 27 ) & 0.0327868852459016 & 0.0220185355939421 & 1.48905839382535 \tabularnewline
Trimmed Mean ( 12 / 27 ) & 0.0338983050847458 & 0.0215704531840234 & 1.57151566522734 \tabularnewline
Trimmed Mean ( 13 / 27 ) & 0.0350877192982456 & 0.0210160500889666 & 1.66956774225936 \tabularnewline
Trimmed Mean ( 14 / 27 ) & 0.0350877192982456 & 0.0206772389202812 & 1.69692478930685 \tabularnewline
Trimmed Mean ( 15 / 27 ) & 0.0415094339622642 & 0.0202369781572196 & 2.05116760218746 \tabularnewline
Trimmed Mean ( 16 / 27 ) & 0.0450980392156863 & 0.0196665786950899 & 2.29313089556069 \tabularnewline
Trimmed Mean ( 17 / 27 ) & 0.0489795918367347 & 0.0189257520316239 & 2.58798655688252 \tabularnewline
Trimmed Mean ( 18 / 27 ) & 0.0510638297872340 & 0.0187175165244493 & 2.72813061073210 \tabularnewline
Trimmed Mean ( 19 / 27 ) & 0.0533333333333333 & 0.0184226474588735 & 2.89498745782298 \tabularnewline
Trimmed Mean ( 20 / 27 ) & 0.0558139534883721 & 0.0180138760288717 & 3.09838667696593 \tabularnewline
Trimmed Mean ( 21 / 27 ) & 0.0585365853658537 & 0.0174522378731691 & 3.35410196624968 \tabularnewline
Trimmed Mean ( 22 / 27 ) & 0.0615384615384615 & 0.0166796378466725 & 3.68943631175651 \tabularnewline
Trimmed Mean ( 23 / 27 ) & 0.0621621621621622 & 0.0165995727681876 & 3.74480494349187 \tabularnewline
Trimmed Mean ( 24 / 27 ) & 0.0628571428571429 & 0.0164422668527093 & 3.82290005509706 \tabularnewline
Trimmed Mean ( 25 / 27 ) & 0.0636363636363636 & 0.0161773912909565 & 3.93366040864312 \tabularnewline
Trimmed Mean ( 26 / 27 ) & 0.064516129032258 & 0.0157592008262893 & 4.09387060571201 \tabularnewline
Trimmed Mean ( 27 / 27 ) & 0.0655172413793104 & 0.0151152078744495 & 4.33452466704474 \tabularnewline
Median & 0.1 &  &  \tabularnewline
Midrange & -0.1 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.060377358490566 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.060377358490566 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.060377358490566 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.060377358490566 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.060377358490566 &  &  \tabularnewline
Midmean - Closest Observation & 0.060377358490566 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.060377358490566 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.060377358490566 &  &  \tabularnewline
Number of observations & 83 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49138&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]0.00602409638554217[/C][C]0.029609536430608[/C][C]0.203451222536363[/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]0.268193420581814[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 27 )[/C][C]0.00602409638554217[/C][C]0.029609536430608[/C][C]0.203451222536363[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 27 )[/C][C]0.00602409638554217[/C][C]0.029609536430608[/C][C]0.203451222536363[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 27 )[/C][C]0.00963855421686747[/C][C]0.0287671275602443[/C][C]0.335054453965984[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 27 )[/C][C]0.00963855421686747[/C][C]0.0287671275602443[/C][C]0.335054453965984[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 27 )[/C][C]0.00963855421686747[/C][C]0.0287671275602443[/C][C]0.335054453965984[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 27 )[/C][C]0.00240963855421687[/C][C]0.0276929505662032[/C][C]0.0870127055784954[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 27 )[/C][C]0.0108433734939759[/C][C]0.0259416855589767[/C][C]0.417990321767034[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 27 )[/C][C]0.0108433734939759[/C][C]0.0259416855589767[/C][C]0.417990321767034[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 27 )[/C][C]0.0108433734939759[/C][C]0.0259416855589767[/C][C]0.417990321767034[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 27 )[/C][C]0.0108433734939759[/C][C]0.0259416855589767[/C][C]0.417990321767035[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 27 )[/C][C]0.0240963855421687[/C][C]0.0235412094798144[/C][C]1.02358315798644[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 27 )[/C][C]0.0240963855421687[/C][C]0.0235412094798144[/C][C]1.02358315798644[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 27 )[/C][C]0.00843373493975904[/C][C]0.0215614954907210[/C][C]0.391147958331022[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 27 )[/C][C]0.00843373493975904[/C][C]0.0215614954907210[/C][C]0.391147958331022[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 27 )[/C][C]0.00843373493975904[/C][C]0.0215614954907210[/C][C]0.391147958331022[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 27 )[/C][C]0.00843373493975904[/C][C]0.0215614954907210[/C][C]0.391147958331022[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 27 )[/C][C]0.0289156626506024[/C][C]0.0181845859688485[/C][C]1.59011938463361[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 27 )[/C][C]0.0289156626506024[/C][C]0.0181845859688485[/C][C]1.59011938463361[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 27 )[/C][C]0.0289156626506024[/C][C]0.0181845859688485[/C][C]1.59011938463361[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 27 )[/C][C]0.0289156626506024[/C][C]0.0181845859688485[/C][C]1.59011938463361[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 27 )[/C][C]0.0289156626506024[/C][C]0.0181845859688485[/C][C]1.59011938463361[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 27 )[/C][C]0.055421686746988[/C][C]0.0143681713953220[/C][C]3.8572540111146[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 27 )[/C][C]0.055421686746988[/C][C]0.0143681713953220[/C][C]3.8572540111146[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 27 )[/C][C]0.055421686746988[/C][C]0.0143681713953220[/C][C]3.8572540111146[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 27 )[/C][C]0.0554216867469879[/C][C]0.0143681713953220[/C][C]3.8572540111146[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 27 )[/C][C]0.0554216867469879[/C][C]0.0143681713953220[/C][C]3.8572540111146[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 27 )[/C][C]0.055421686746988[/C][C]0.0143681713953220[/C][C]3.8572540111146[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 27 )[/C][C]0.00864197530864198[/C][C]0.0289847517843540[/C][C]0.298155919116994[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 27 )[/C][C]0.0113924050632911[/C][C]0.0282559901518547[/C][C]0.403185483929799[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 27 )[/C][C]0.0142857142857143[/C][C]0.0274026135999149[/C][C]0.521326706068602[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 27 )[/C][C]0.016[/C][C]0.0267817337239631[/C][C]0.597422114823131[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 27 )[/C][C]0.0178082191780822[/C][C]0.0260504184018133[/C][C]0.6836058793145[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 27 )[/C][C]0.0197183098591549[/C][C]0.0251850070622142[/C][C]0.78293842882176[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 27 )[/C][C]0.0197183098591549[/C][C]0.0244413217265725[/C][C]0.806761192366994[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 27 )[/C][C]0.0253731343283582[/C][C]0.0239990279071647[/C][C]1.05725675333638[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 27 )[/C][C]0.0276923076923077[/C][C]0.0234631147011493[/C][C]1.18024857505177[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 27 )[/C][C]0.0301587301587302[/C][C]0.0228123672492173[/C][C]1.3220342207039[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 27 )[/C][C]0.0327868852459016[/C][C]0.0220185355939421[/C][C]1.48905839382535[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 27 )[/C][C]0.0338983050847458[/C][C]0.0215704531840234[/C][C]1.57151566522734[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 27 )[/C][C]0.0350877192982456[/C][C]0.0210160500889666[/C][C]1.66956774225936[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 27 )[/C][C]0.0350877192982456[/C][C]0.0206772389202812[/C][C]1.69692478930685[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 27 )[/C][C]0.0415094339622642[/C][C]0.0202369781572196[/C][C]2.05116760218746[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 27 )[/C][C]0.0450980392156863[/C][C]0.0196665786950899[/C][C]2.29313089556069[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 27 )[/C][C]0.0489795918367347[/C][C]0.0189257520316239[/C][C]2.58798655688252[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 27 )[/C][C]0.0510638297872340[/C][C]0.0187175165244493[/C][C]2.72813061073210[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 27 )[/C][C]0.0533333333333333[/C][C]0.0184226474588735[/C][C]2.89498745782298[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 27 )[/C][C]0.0558139534883721[/C][C]0.0180138760288717[/C][C]3.09838667696593[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 27 )[/C][C]0.0585365853658537[/C][C]0.0174522378731691[/C][C]3.35410196624968[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 27 )[/C][C]0.0615384615384615[/C][C]0.0166796378466725[/C][C]3.68943631175651[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 27 )[/C][C]0.0621621621621622[/C][C]0.0165995727681876[/C][C]3.74480494349187[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 27 )[/C][C]0.0628571428571429[/C][C]0.0164422668527093[/C][C]3.82290005509706[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 27 )[/C][C]0.0636363636363636[/C][C]0.0161773912909565[/C][C]3.93366040864312[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 27 )[/C][C]0.064516129032258[/C][C]0.0157592008262893[/C][C]4.09387060571201[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 27 )[/C][C]0.0655172413793104[/C][C]0.0151152078744495[/C][C]4.33452466704474[/C][/ROW]
[ROW][C]Median[/C][C]0.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-0.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.060377358490566[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]83[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49138&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49138&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
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	0.00602409638554217	0.029609536430608	0.203451222536363
Geometric Mean	NaN
Harmonic Mean	0
Quadratic Mean	0.268193420581814
Winsorized Mean ( 1 / 27 )	0.00602409638554217	0.029609536430608	0.203451222536363
Winsorized Mean ( 2 / 27 )	0.00602409638554217	0.029609536430608	0.203451222536363
Winsorized Mean ( 3 / 27 )	0.00963855421686747	0.0287671275602443	0.335054453965984
Winsorized Mean ( 4 / 27 )	0.00963855421686747	0.0287671275602443	0.335054453965984
Winsorized Mean ( 5 / 27 )	0.00963855421686747	0.0287671275602443	0.335054453965984
Winsorized Mean ( 6 / 27 )	0.00240963855421687	0.0276929505662032	0.0870127055784954
Winsorized Mean ( 7 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767034
Winsorized Mean ( 8 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767034
Winsorized Mean ( 9 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767034
Winsorized Mean ( 10 / 27 )	0.0108433734939759	0.0259416855589767	0.417990321767035
Winsorized Mean ( 11 / 27 )	0.0240963855421687	0.0235412094798144	1.02358315798644
Winsorized Mean ( 12 / 27 )	0.0240963855421687	0.0235412094798144	1.02358315798644
Winsorized Mean ( 13 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 14 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 15 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 16 / 27 )	0.00843373493975904	0.0215614954907210	0.391147958331022
Winsorized Mean ( 17 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 18 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 19 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 20 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 21 / 27 )	0.0289156626506024	0.0181845859688485	1.59011938463361
Winsorized Mean ( 22 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Winsorized Mean ( 23 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Winsorized Mean ( 24 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Winsorized Mean ( 25 / 27 )	0.0554216867469879	0.0143681713953220	3.8572540111146
Winsorized Mean ( 26 / 27 )	0.0554216867469879	0.0143681713953220	3.8572540111146
Winsorized Mean ( 27 / 27 )	0.055421686746988	0.0143681713953220	3.8572540111146
Trimmed Mean ( 1 / 27 )	0.00864197530864198	0.0289847517843540	0.298155919116994
Trimmed Mean ( 2 / 27 )	0.0113924050632911	0.0282559901518547	0.403185483929799
Trimmed Mean ( 3 / 27 )	0.0142857142857143	0.0274026135999149	0.521326706068602
Trimmed Mean ( 4 / 27 )	0.016	0.0267817337239631	0.597422114823131
Trimmed Mean ( 5 / 27 )	0.0178082191780822	0.0260504184018133	0.6836058793145
Trimmed Mean ( 6 / 27 )	0.0197183098591549	0.0251850070622142	0.78293842882176
Trimmed Mean ( 7 / 27 )	0.0197183098591549	0.0244413217265725	0.806761192366994
Trimmed Mean ( 8 / 27 )	0.0253731343283582	0.0239990279071647	1.05725675333638
Trimmed Mean ( 9 / 27 )	0.0276923076923077	0.0234631147011493	1.18024857505177
Trimmed Mean ( 10 / 27 )	0.0301587301587302	0.0228123672492173	1.3220342207039
Trimmed Mean ( 11 / 27 )	0.0327868852459016	0.0220185355939421	1.48905839382535
Trimmed Mean ( 12 / 27 )	0.0338983050847458	0.0215704531840234	1.57151566522734
Trimmed Mean ( 13 / 27 )	0.0350877192982456	0.0210160500889666	1.66956774225936
Trimmed Mean ( 14 / 27 )	0.0350877192982456	0.0206772389202812	1.69692478930685
Trimmed Mean ( 15 / 27 )	0.0415094339622642	0.0202369781572196	2.05116760218746
Trimmed Mean ( 16 / 27 )	0.0450980392156863	0.0196665786950899	2.29313089556069
Trimmed Mean ( 17 / 27 )	0.0489795918367347	0.0189257520316239	2.58798655688252
Trimmed Mean ( 18 / 27 )	0.0510638297872340	0.0187175165244493	2.72813061073210
Trimmed Mean ( 19 / 27 )	0.0533333333333333	0.0184226474588735	2.89498745782298
Trimmed Mean ( 20 / 27 )	0.0558139534883721	0.0180138760288717	3.09838667696593
Trimmed Mean ( 21 / 27 )	0.0585365853658537	0.0174522378731691	3.35410196624968
Trimmed Mean ( 22 / 27 )	0.0615384615384615	0.0166796378466725	3.68943631175651
Trimmed Mean ( 23 / 27 )	0.0621621621621622	0.0165995727681876	3.74480494349187
Trimmed Mean ( 24 / 27 )	0.0628571428571429	0.0164422668527093	3.82290005509706
Trimmed Mean ( 25 / 27 )	0.0636363636363636	0.0161773912909565	3.93366040864312
Trimmed Mean ( 26 / 27 )	0.064516129032258	0.0157592008262893	4.09387060571201
Trimmed Mean ( 27 / 27 )	0.0655172413793104	0.0151152078744495	4.33452466704474
Median	0.1
Midrange	-0.1
Midmean - Weighted Average at Xnp	0.060377358490566
Midmean - Weighted Average at X(n+1)p	0.060377358490566
Midmean - Empirical Distribution Function	0.060377358490566
Midmean - Empirical Distribution Function - Averaging	0.060377358490566
Midmean - Empirical Distribution Function - Interpolation	0.060377358490566
Midmean - Closest Observation	0.060377358490566
Midmean - True Basic - Statistics Graphics Toolkit	0.060377358490566
Midmean - MS Excel (old versions)	0.060377358490566
Number of observations	83

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code