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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 computationFri, 24 Dec 2010 16:08:45 +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/Dec/24/t1293206839tmpwovltng2jjt9.htm/, Retrieved Tue, 30 Apr 2024 06:29:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115173, Retrieved Tue, 30 Apr 2024 06:29:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [] [2009-12-20 16:30:59] [ebd107afac1bd6180acb277edd05815b]
-   PD    [Central Tendency] [] [2010-12-24 16:08:45] [817f44ab92560f82acbc5e6c80d9a294] [Current]
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Dataseries X:
-74.6915795638773 
212.254697730591 
-41.5511936661506 
471.993871206887 
-1356.78478851341 
438.316374572804 
293.380991648800 
-37.9117683928118 
1816.68987489069 
816.11038731021 
258.925702479984 
-45.6248826681828 
3960.39036987729 
1735.14809352634 
-1053.68791259641 
-762.10853490894 
-561.127620753853 
286.904192766769 
-44.3844668623980 
-2186.13468440731 
-482.002210181472 
25.8471194482117 
-1999.40184934386 
141.474729104310 
-2035.50278754068 
-2309.10340024142 
1021.93936558592 
114.540206908403 
1660.0702554509 
270.085163129050 
-1431.19472368068 
2909.99760759191 
-949.692196653628 
694.398240429993 
-342.623341162817 
852.663100685635 
-1709.35398897022 
869.163287612745 
-530.011730453785 
-275.645283448380 
78.1235588541858 
1308.86905563902 
-350.805682413949 
522.033502131831 
-494.184012644346 
-544.431527076918 
1090.47629136852 
-721.25486445932 
-1544.20677426309 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115173&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115173&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115173&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'George Udny Yule' @ 72.249.76.132







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-0.686240100345076176.339143701456-0.00389159256385460
Geometric MeanNaN
Harmonic Mean-1450.36012687447
Quadratic Mean1221.71361774799
Winsorized Mean ( 1 / 16 )-19.6132614564935166.685877180623-0.117666006192236
Winsorized Mean ( 2 / 16 )-58.0898261844359150.953070725013-0.384820433962927
Winsorized Mean ( 3 / 16 )-60.8719186232643149.079580926077-0.408318283732285
Winsorized Mean ( 4 / 16 )-43.3233453744316141.420831445892-0.306343449769685
Winsorized Mean ( 5 / 16 )-62.3084458953245128.837896943095-0.483618930250351
Winsorized Mean ( 6 / 16 )-75.2122067550906119.865357437020-0.627472427090613
Winsorized Mean ( 7 / 16 )-74.3732054144234115.421009652013-0.64436453673949
Winsorized Mean ( 8 / 16 )-49.83103432155499.5879140678894-0.500372307101282
Winsorized Mean ( 9 / 16 )-33.760426951328695.0778378752567-0.355081980257299
Winsorized Mean ( 10 / 16 )-2.937784426989286.2482958831174-0.0340619417103666
Winsorized Mean ( 11 / 16 )-21.08968729916479.2870108709672-0.265991706176005
Winsorized Mean ( 12 / 16 )-24.086624750436364.5460261991212-0.373169754496276
Winsorized Mean ( 13 / 16 )-32.932869326438761.4713687520877-0.535743224772756
Winsorized Mean ( 14 / 16 )-38.435069329567259.1256680100651-0.650057253019524
Winsorized Mean ( 15 / 16 )-71.83537497688350.0875287005826-1.43419683183626
Winsorized Mean ( 16 / 16 )-69.972516664771149.0693466300043-1.42599242644053
Trimmed Mean ( 1 / 16 )-0.686240100345075155.175247600179-0.00442235543978784
Trimmed Mean ( 2 / 16 )-35.8492071181442139.884087864894-0.256277948874134
Trimmed Mean ( 3 / 16 )-50.929366164823131.684578135093-0.386752700172494
Trimmed Mean ( 4 / 16 )-50.929366164823121.801204110864-0.418135161606998
Trimmed Mean ( 5 / 16 )-48.1134680961679112.188139333703-0.428864123978872
Trimmed Mean ( 6 / 16 )-44.3537172196346104.595951191178-0.424048127241236
Trimmed Mean ( 7 / 16 )-37.153402994694897.7026669319188-0.380270100718787
Trimmed Mean ( 8 / 16 )-37.153402994694889.6877673812539-0.414252735679765
Trimmed Mean ( 9 / 16 )-25.193517964618284.4795845805346-0.298220192366135
Trimmed Mean ( 10 / 16 )-23.58517106673078.5632932510545-0.300205987946075
Trimmed Mean ( 11 / 16 )-27.332289382831173.1946497102463-0.373419225189693
Trimmed Mean ( 12 / 16 )-28.444607572284667.8046238182154-0.419508375248047
Trimmed Mean ( 13 / 16 )-29.218307421091065.512408636933-0.445996537587521
Trimmed Mean ( 14 / 16 )-28.551591181669662.7736192009141-0.454834236819881
Trimmed Mean ( 15 / 16 )-26.730950470214758.8766801138016-0.454015926484764
Trimmed Mean ( 16 / 16 )-26.730950470214756.3363539460025-0.47448847143775
Median-37.9117683928118
Midrange825.643484817935
Midmean - Weighted Average at Xnp-51.3811954766227
Midmean - Weighted Average at X(n+1)p-28.4446075722845
Midmean - Empirical Distribution Function-28.4446075722845
Midmean - Empirical Distribution Function - Averaging-28.4446075722845
Midmean - Empirical Distribution Function - Interpolation-28.4446075722845
Midmean - Closest Observation-55.0911559140935
Midmean - True Basic - Statistics Graphics Toolkit-28.4446075722845
Midmean - MS Excel (old versions)-28.4446075722845
Number of observations49

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -0.686240100345076 & 176.339143701456 & -0.00389159256385460 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -1450.36012687447 &  &  \tabularnewline
Quadratic Mean & 1221.71361774799 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & -19.6132614564935 & 166.685877180623 & -0.117666006192236 \tabularnewline
Winsorized Mean ( 2 / 16 ) & -58.0898261844359 & 150.953070725013 & -0.384820433962927 \tabularnewline
Winsorized Mean ( 3 / 16 ) & -60.8719186232643 & 149.079580926077 & -0.408318283732285 \tabularnewline
Winsorized Mean ( 4 / 16 ) & -43.3233453744316 & 141.420831445892 & -0.306343449769685 \tabularnewline
Winsorized Mean ( 5 / 16 ) & -62.3084458953245 & 128.837896943095 & -0.483618930250351 \tabularnewline
Winsorized Mean ( 6 / 16 ) & -75.2122067550906 & 119.865357437020 & -0.627472427090613 \tabularnewline
Winsorized Mean ( 7 / 16 ) & -74.3732054144234 & 115.421009652013 & -0.64436453673949 \tabularnewline
Winsorized Mean ( 8 / 16 ) & -49.831034321554 & 99.5879140678894 & -0.500372307101282 \tabularnewline
Winsorized Mean ( 9 / 16 ) & -33.7604269513286 & 95.0778378752567 & -0.355081980257299 \tabularnewline
Winsorized Mean ( 10 / 16 ) & -2.9377844269892 & 86.2482958831174 & -0.0340619417103666 \tabularnewline
Winsorized Mean ( 11 / 16 ) & -21.089687299164 & 79.2870108709672 & -0.265991706176005 \tabularnewline
Winsorized Mean ( 12 / 16 ) & -24.0866247504363 & 64.5460261991212 & -0.373169754496276 \tabularnewline
Winsorized Mean ( 13 / 16 ) & -32.9328693264387 & 61.4713687520877 & -0.535743224772756 \tabularnewline
Winsorized Mean ( 14 / 16 ) & -38.4350693295672 & 59.1256680100651 & -0.650057253019524 \tabularnewline
Winsorized Mean ( 15 / 16 ) & -71.835374976883 & 50.0875287005826 & -1.43419683183626 \tabularnewline
Winsorized Mean ( 16 / 16 ) & -69.9725166647711 & 49.0693466300043 & -1.42599242644053 \tabularnewline
Trimmed Mean ( 1 / 16 ) & -0.686240100345075 & 155.175247600179 & -0.00442235543978784 \tabularnewline
Trimmed Mean ( 2 / 16 ) & -35.8492071181442 & 139.884087864894 & -0.256277948874134 \tabularnewline
Trimmed Mean ( 3 / 16 ) & -50.929366164823 & 131.684578135093 & -0.386752700172494 \tabularnewline
Trimmed Mean ( 4 / 16 ) & -50.929366164823 & 121.801204110864 & -0.418135161606998 \tabularnewline
Trimmed Mean ( 5 / 16 ) & -48.1134680961679 & 112.188139333703 & -0.428864123978872 \tabularnewline
Trimmed Mean ( 6 / 16 ) & -44.3537172196346 & 104.595951191178 & -0.424048127241236 \tabularnewline
Trimmed Mean ( 7 / 16 ) & -37.1534029946948 & 97.7026669319188 & -0.380270100718787 \tabularnewline
Trimmed Mean ( 8 / 16 ) & -37.1534029946948 & 89.6877673812539 & -0.414252735679765 \tabularnewline
Trimmed Mean ( 9 / 16 ) & -25.1935179646182 & 84.4795845805346 & -0.298220192366135 \tabularnewline
Trimmed Mean ( 10 / 16 ) & -23.585171066730 & 78.5632932510545 & -0.300205987946075 \tabularnewline
Trimmed Mean ( 11 / 16 ) & -27.3322893828311 & 73.1946497102463 & -0.373419225189693 \tabularnewline
Trimmed Mean ( 12 / 16 ) & -28.4446075722846 & 67.8046238182154 & -0.419508375248047 \tabularnewline
Trimmed Mean ( 13 / 16 ) & -29.2183074210910 & 65.512408636933 & -0.445996537587521 \tabularnewline
Trimmed Mean ( 14 / 16 ) & -28.5515911816696 & 62.7736192009141 & -0.454834236819881 \tabularnewline
Trimmed Mean ( 15 / 16 ) & -26.7309504702147 & 58.8766801138016 & -0.454015926484764 \tabularnewline
Trimmed Mean ( 16 / 16 ) & -26.7309504702147 & 56.3363539460025 & -0.47448847143775 \tabularnewline
Median & -37.9117683928118 &  &  \tabularnewline
Midrange & 825.643484817935 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -51.3811954766227 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -28.4446075722845 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -28.4446075722845 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -28.4446075722845 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -28.4446075722845 &  &  \tabularnewline
Midmean - Closest Observation & -55.0911559140935 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -28.4446075722845 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -28.4446075722845 &  &  \tabularnewline
Number of observations & 49 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115173&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]-0.686240100345076[/C][C]176.339143701456[/C][C]-0.00389159256385460[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-1450.36012687447[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1221.71361774799[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]-19.6132614564935[/C][C]166.685877180623[/C][C]-0.117666006192236[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]-58.0898261844359[/C][C]150.953070725013[/C][C]-0.384820433962927[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]-60.8719186232643[/C][C]149.079580926077[/C][C]-0.408318283732285[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]-43.3233453744316[/C][C]141.420831445892[/C][C]-0.306343449769685[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]-62.3084458953245[/C][C]128.837896943095[/C][C]-0.483618930250351[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]-75.2122067550906[/C][C]119.865357437020[/C][C]-0.627472427090613[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]-74.3732054144234[/C][C]115.421009652013[/C][C]-0.64436453673949[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]-49.831034321554[/C][C]99.5879140678894[/C][C]-0.500372307101282[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]-33.7604269513286[/C][C]95.0778378752567[/C][C]-0.355081980257299[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]-2.9377844269892[/C][C]86.2482958831174[/C][C]-0.0340619417103666[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]-21.089687299164[/C][C]79.2870108709672[/C][C]-0.265991706176005[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]-24.0866247504363[/C][C]64.5460261991212[/C][C]-0.373169754496276[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]-32.9328693264387[/C][C]61.4713687520877[/C][C]-0.535743224772756[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]-38.4350693295672[/C][C]59.1256680100651[/C][C]-0.650057253019524[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]-71.835374976883[/C][C]50.0875287005826[/C][C]-1.43419683183626[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]-69.9725166647711[/C][C]49.0693466300043[/C][C]-1.42599242644053[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]-0.686240100345075[/C][C]155.175247600179[/C][C]-0.00442235543978784[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]-35.8492071181442[/C][C]139.884087864894[/C][C]-0.256277948874134[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]-50.929366164823[/C][C]131.684578135093[/C][C]-0.386752700172494[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]-50.929366164823[/C][C]121.801204110864[/C][C]-0.418135161606998[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]-48.1134680961679[/C][C]112.188139333703[/C][C]-0.428864123978872[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]-44.3537172196346[/C][C]104.595951191178[/C][C]-0.424048127241236[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]-37.1534029946948[/C][C]97.7026669319188[/C][C]-0.380270100718787[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]-37.1534029946948[/C][C]89.6877673812539[/C][C]-0.414252735679765[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]-25.1935179646182[/C][C]84.4795845805346[/C][C]-0.298220192366135[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]-23.585171066730[/C][C]78.5632932510545[/C][C]-0.300205987946075[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]-27.3322893828311[/C][C]73.1946497102463[/C][C]-0.373419225189693[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]-28.4446075722846[/C][C]67.8046238182154[/C][C]-0.419508375248047[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]-29.2183074210910[/C][C]65.512408636933[/C][C]-0.445996537587521[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]-28.5515911816696[/C][C]62.7736192009141[/C][C]-0.454834236819881[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]-26.7309504702147[/C][C]58.8766801138016[/C][C]-0.454015926484764[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]-26.7309504702147[/C][C]56.3363539460025[/C][C]-0.47448847143775[/C][/ROW]
[ROW][C]Median[/C][C]-37.9117683928118[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]825.643484817935[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-51.3811954766227[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-28.4446075722845[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-28.4446075722845[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-28.4446075722845[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-28.4446075722845[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-55.0911559140935[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-28.4446075722845[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-28.4446075722845[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]49[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115173&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115173&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-0.686240100345076176.339143701456-0.00389159256385460
Geometric MeanNaN
Harmonic Mean-1450.36012687447
Quadratic Mean1221.71361774799
Winsorized Mean ( 1 / 16 )-19.6132614564935166.685877180623-0.117666006192236
Winsorized Mean ( 2 / 16 )-58.0898261844359150.953070725013-0.384820433962927
Winsorized Mean ( 3 / 16 )-60.8719186232643149.079580926077-0.408318283732285
Winsorized Mean ( 4 / 16 )-43.3233453744316141.420831445892-0.306343449769685
Winsorized Mean ( 5 / 16 )-62.3084458953245128.837896943095-0.483618930250351
Winsorized Mean ( 6 / 16 )-75.2122067550906119.865357437020-0.627472427090613
Winsorized Mean ( 7 / 16 )-74.3732054144234115.421009652013-0.64436453673949
Winsorized Mean ( 8 / 16 )-49.83103432155499.5879140678894-0.500372307101282
Winsorized Mean ( 9 / 16 )-33.760426951328695.0778378752567-0.355081980257299
Winsorized Mean ( 10 / 16 )-2.937784426989286.2482958831174-0.0340619417103666
Winsorized Mean ( 11 / 16 )-21.08968729916479.2870108709672-0.265991706176005
Winsorized Mean ( 12 / 16 )-24.086624750436364.5460261991212-0.373169754496276
Winsorized Mean ( 13 / 16 )-32.932869326438761.4713687520877-0.535743224772756
Winsorized Mean ( 14 / 16 )-38.435069329567259.1256680100651-0.650057253019524
Winsorized Mean ( 15 / 16 )-71.83537497688350.0875287005826-1.43419683183626
Winsorized Mean ( 16 / 16 )-69.972516664771149.0693466300043-1.42599242644053
Trimmed Mean ( 1 / 16 )-0.686240100345075155.175247600179-0.00442235543978784
Trimmed Mean ( 2 / 16 )-35.8492071181442139.884087864894-0.256277948874134
Trimmed Mean ( 3 / 16 )-50.929366164823131.684578135093-0.386752700172494
Trimmed Mean ( 4 / 16 )-50.929366164823121.801204110864-0.418135161606998
Trimmed Mean ( 5 / 16 )-48.1134680961679112.188139333703-0.428864123978872
Trimmed Mean ( 6 / 16 )-44.3537172196346104.595951191178-0.424048127241236
Trimmed Mean ( 7 / 16 )-37.153402994694897.7026669319188-0.380270100718787
Trimmed Mean ( 8 / 16 )-37.153402994694889.6877673812539-0.414252735679765
Trimmed Mean ( 9 / 16 )-25.193517964618284.4795845805346-0.298220192366135
Trimmed Mean ( 10 / 16 )-23.58517106673078.5632932510545-0.300205987946075
Trimmed Mean ( 11 / 16 )-27.332289382831173.1946497102463-0.373419225189693
Trimmed Mean ( 12 / 16 )-28.444607572284667.8046238182154-0.419508375248047
Trimmed Mean ( 13 / 16 )-29.218307421091065.512408636933-0.445996537587521
Trimmed Mean ( 14 / 16 )-28.551591181669662.7736192009141-0.454834236819881
Trimmed Mean ( 15 / 16 )-26.730950470214758.8766801138016-0.454015926484764
Trimmed Mean ( 16 / 16 )-26.730950470214756.3363539460025-0.47448847143775
Median-37.9117683928118
Midrange825.643484817935
Midmean - Weighted Average at Xnp-51.3811954766227
Midmean - Weighted Average at X(n+1)p-28.4446075722845
Midmean - Empirical Distribution Function-28.4446075722845
Midmean - Empirical Distribution Function - Averaging-28.4446075722845
Midmean - Empirical Distribution Function - Interpolation-28.4446075722845
Midmean - Closest Observation-55.0911559140935
Midmean - True Basic - Statistics Graphics Toolkit-28.4446075722845
Midmean - MS Excel (old versions)-28.4446075722845
Number of observations49



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