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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSun, 02 Dec 2007 10:43:40 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Dec/02/t1196616734kw6iotcli6bug7h.htm/, Retrieved Sun, 28 Apr 2024 12:37:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2284, Retrieved Sun, 28 Apr 2024 12:37:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 8, question 4, central tendency, niet-duurzame consumptiegoederen
Estimated Impact271
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Workshop 8, quest...] [2007-12-02 17:43:40] [181c187d2008ac66a37ecc12859b08c5] [Current]
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Dataseries X:
0.108397535296406 
6.88213942205853 
1.13142667186215 
0.56842960925653 
7.82742281638304 
-15.2979948582366 
0.65956803546223 
-2.48486689481669 
3.73313676756849 
3.18702414495066 
7.32489609667369 
-0.826443398080632 
3.58457655371833 
-2.42080842085776 
-3.95682307990883 
4.70539386241296 
3.53848252551747 
3.77975438026032 
-3.10333312499743 
-3.27846833664851 
0.537515693943329 
6.68876610023075 
-3.16186845831888 
-8.81909609403227 
-0.462228478616628 
4.14441899832538 
-0.246011670977238 
1.83640731341084 
-5.42672268797816 
-3.24644821372414 
4.87556643608679 
12.7968770664302 
-4.87312769210229 
8.62556292564284 
-1.57473737229226 
-0.453717354633755 
1.19829354872597 
-3.92351600170314 
4.25933697979798 
4.2493248781215 
-0.95964896934972 
-1.33019448960345 
-5.69289276248916 
-0.470982315604962 
-2.06183336001489 
5.08234650818225 
-1.7300665391551 
0.187291292100408 
-1.47555964136607 




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2284&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2284&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2284&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.4945911417736830.6921074875975930.71461608295914
Geometric MeanNaN
Harmonic Mean7.90789100901878
Quadratic Mean4.82050138141006
Winsorized Mean ( 1 / 16 )0.5416847055168870.6112031020346570.886259745269047
Winsorized Mean ( 2 / 16 )0.6367076941815120.5670028232138121.12293566824343
Winsorized Mean ( 3 / 16 )0.6222368791693680.5553236001869961.12049421087063
Winsorized Mean ( 4 / 16 )0.6312849053947320.5364262336870171.17683451283828
Winsorized Mean ( 5 / 16 )0.7050534044116380.5127577411717851.37502244783357
Winsorized Mean ( 6 / 16 )0.5124273823084370.4678660133294691.09524386834995
Winsorized Mean ( 7 / 16 )0.5750370384454610.4444385510053061.29385049326784
Winsorized Mean ( 8 / 16 )0.5524815362822840.4379488293823931.26152075132021
Winsorized Mean ( 9 / 16 )0.4860877782233560.4193569402862491.15912658531788
Winsorized Mean ( 10 / 16 )0.4959904785590640.4168167266093811.18994859585825
Winsorized Mean ( 11 / 16 )0.6112795368086720.388322873876061.57415279380059
Winsorized Mean ( 12 / 16 )0.5376617055990080.3690667720766571.45681417639877
Winsorized Mean ( 13 / 16 )0.6205320489860190.351255947813431.76660937088420
Winsorized Mean ( 14 / 16 )0.6728767938459130.3286503405962942.04739417773024
Winsorized Mean ( 15 / 16 )0.7063161220077430.3188769036871752.21501185517235
Winsorized Mean ( 16 / 16 )0.6239387670230510.2929635679433152.12974866261793
Trimmed Mean ( 1 / 16 )0.4945911417736830.5793337420975710.853724038207987
Trimmed Mean ( 2 / 16 )0.5688528455046140.5377390440643031.05786040977265
Trimmed Mean ( 3 / 16 )0.5766299268188940.5159063344466251.11770274625025
Trimmed Mean ( 4 / 16 )0.5766299268188940.4933032670388931.16891568604477
Trimmed Mean ( 5 / 16 )0.5355872234502730.4715806224353651.13572780129167
Trimmed Mean ( 6 / 16 )0.4907015863307770.4514420760748791.08696466797522
Trimmed Mean ( 7 / 16 )0.4856322339359890.4404849422345631.10249451768407
Trimmed Mean ( 8 / 16 )0.4856322339359890.4324002197424641.1231082033798
Trimmed Mean ( 9 / 16 )0.4497124012784690.4220754226282331.06547876793712
Trimmed Mean ( 10 / 16 )0.4428833075225320.4124288531358231.07384171634733
Trimmed Mean ( 11 / 16 )0.4332453394455320.3977358666402951.08927903109465
Trimmed Mean ( 12 / 16 )0.4015228824608270.3845749050849431.04406937933753
Trimmed Mean ( 13 / 16 )0.3773533087877440.370202584918721.01931570486088
Trimmed Mean ( 14 / 16 )0.333705842598310.3521916256969420.947512144668258
Trimmed Mean ( 15 / 16 )0.2712269831579620.3297831554736170.822440378340246
Trimmed Mean ( 16 / 16 )0.2712269831579620.290748901085770.93285643434969
Median0.108397535296406
Midrange-1.2505588959032
Midmean - Weighted Average at Xnp0.260763236719181
Midmean - Weighted Average at X(n+1)p0.401522882460827
Midmean - Empirical Distribution Function0.401522882460827
Midmean - Empirical Distribution Function - Averaging0.401522882460827
Midmean - Empirical Distribution Function - Interpolation0.401522882460827
Midmean - Closest Observation0.290507891027076
Midmean - True Basic - Statistics Graphics Toolkit0.401522882460827
Midmean - MS Excel (old versions)0.401522882460827
Number of observations49

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 0.494591141773683 & 0.692107487597593 & 0.71461608295914 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 7.90789100901878 &  &  \tabularnewline
Quadratic Mean & 4.82050138141006 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & 0.541684705516887 & 0.611203102034657 & 0.886259745269047 \tabularnewline
Winsorized Mean ( 2 / 16 ) & 0.636707694181512 & 0.567002823213812 & 1.12293566824343 \tabularnewline
Winsorized Mean ( 3 / 16 ) & 0.622236879169368 & 0.555323600186996 & 1.12049421087063 \tabularnewline
Winsorized Mean ( 4 / 16 ) & 0.631284905394732 & 0.536426233687017 & 1.17683451283828 \tabularnewline
Winsorized Mean ( 5 / 16 ) & 0.705053404411638 & 0.512757741171785 & 1.37502244783357 \tabularnewline
Winsorized Mean ( 6 / 16 ) & 0.512427382308437 & 0.467866013329469 & 1.09524386834995 \tabularnewline
Winsorized Mean ( 7 / 16 ) & 0.575037038445461 & 0.444438551005306 & 1.29385049326784 \tabularnewline
Winsorized Mean ( 8 / 16 ) & 0.552481536282284 & 0.437948829382393 & 1.26152075132021 \tabularnewline
Winsorized Mean ( 9 / 16 ) & 0.486087778223356 & 0.419356940286249 & 1.15912658531788 \tabularnewline
Winsorized Mean ( 10 / 16 ) & 0.495990478559064 & 0.416816726609381 & 1.18994859585825 \tabularnewline
Winsorized Mean ( 11 / 16 ) & 0.611279536808672 & 0.38832287387606 & 1.57415279380059 \tabularnewline
Winsorized Mean ( 12 / 16 ) & 0.537661705599008 & 0.369066772076657 & 1.45681417639877 \tabularnewline
Winsorized Mean ( 13 / 16 ) & 0.620532048986019 & 0.35125594781343 & 1.76660937088420 \tabularnewline
Winsorized Mean ( 14 / 16 ) & 0.672876793845913 & 0.328650340596294 & 2.04739417773024 \tabularnewline
Winsorized Mean ( 15 / 16 ) & 0.706316122007743 & 0.318876903687175 & 2.21501185517235 \tabularnewline
Winsorized Mean ( 16 / 16 ) & 0.623938767023051 & 0.292963567943315 & 2.12974866261793 \tabularnewline
Trimmed Mean ( 1 / 16 ) & 0.494591141773683 & 0.579333742097571 & 0.853724038207987 \tabularnewline
Trimmed Mean ( 2 / 16 ) & 0.568852845504614 & 0.537739044064303 & 1.05786040977265 \tabularnewline
Trimmed Mean ( 3 / 16 ) & 0.576629926818894 & 0.515906334446625 & 1.11770274625025 \tabularnewline
Trimmed Mean ( 4 / 16 ) & 0.576629926818894 & 0.493303267038893 & 1.16891568604477 \tabularnewline
Trimmed Mean ( 5 / 16 ) & 0.535587223450273 & 0.471580622435365 & 1.13572780129167 \tabularnewline
Trimmed Mean ( 6 / 16 ) & 0.490701586330777 & 0.451442076074879 & 1.08696466797522 \tabularnewline
Trimmed Mean ( 7 / 16 ) & 0.485632233935989 & 0.440484942234563 & 1.10249451768407 \tabularnewline
Trimmed Mean ( 8 / 16 ) & 0.485632233935989 & 0.432400219742464 & 1.1231082033798 \tabularnewline
Trimmed Mean ( 9 / 16 ) & 0.449712401278469 & 0.422075422628233 & 1.06547876793712 \tabularnewline
Trimmed Mean ( 10 / 16 ) & 0.442883307522532 & 0.412428853135823 & 1.07384171634733 \tabularnewline
Trimmed Mean ( 11 / 16 ) & 0.433245339445532 & 0.397735866640295 & 1.08927903109465 \tabularnewline
Trimmed Mean ( 12 / 16 ) & 0.401522882460827 & 0.384574905084943 & 1.04406937933753 \tabularnewline
Trimmed Mean ( 13 / 16 ) & 0.377353308787744 & 0.37020258491872 & 1.01931570486088 \tabularnewline
Trimmed Mean ( 14 / 16 ) & 0.33370584259831 & 0.352191625696942 & 0.947512144668258 \tabularnewline
Trimmed Mean ( 15 / 16 ) & 0.271226983157962 & 0.329783155473617 & 0.822440378340246 \tabularnewline
Trimmed Mean ( 16 / 16 ) & 0.271226983157962 & 0.29074890108577 & 0.93285643434969 \tabularnewline
Median & 0.108397535296406 &  &  \tabularnewline
Midrange & -1.2505588959032 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.260763236719181 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.401522882460827 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.401522882460827 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.401522882460827 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.401522882460827 &  &  \tabularnewline
Midmean - Closest Observation & 0.290507891027076 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.401522882460827 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.401522882460827 &  &  \tabularnewline
Number of observations & 49 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2284&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]0.494591141773683[/C][C]0.692107487597593[/C][C]0.71461608295914[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]7.90789100901878[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4.82050138141006[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]0.541684705516887[/C][C]0.611203102034657[/C][C]0.886259745269047[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]0.636707694181512[/C][C]0.567002823213812[/C][C]1.12293566824343[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]0.622236879169368[/C][C]0.555323600186996[/C][C]1.12049421087063[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]0.631284905394732[/C][C]0.536426233687017[/C][C]1.17683451283828[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]0.705053404411638[/C][C]0.512757741171785[/C][C]1.37502244783357[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]0.512427382308437[/C][C]0.467866013329469[/C][C]1.09524386834995[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]0.575037038445461[/C][C]0.444438551005306[/C][C]1.29385049326784[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]0.552481536282284[/C][C]0.437948829382393[/C][C]1.26152075132021[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]0.486087778223356[/C][C]0.419356940286249[/C][C]1.15912658531788[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]0.495990478559064[/C][C]0.416816726609381[/C][C]1.18994859585825[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]0.611279536808672[/C][C]0.38832287387606[/C][C]1.57415279380059[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]0.537661705599008[/C][C]0.369066772076657[/C][C]1.45681417639877[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]0.620532048986019[/C][C]0.35125594781343[/C][C]1.76660937088420[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]0.672876793845913[/C][C]0.328650340596294[/C][C]2.04739417773024[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]0.706316122007743[/C][C]0.318876903687175[/C][C]2.21501185517235[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]0.623938767023051[/C][C]0.292963567943315[/C][C]2.12974866261793[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]0.494591141773683[/C][C]0.579333742097571[/C][C]0.853724038207987[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]0.568852845504614[/C][C]0.537739044064303[/C][C]1.05786040977265[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]0.576629926818894[/C][C]0.515906334446625[/C][C]1.11770274625025[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]0.576629926818894[/C][C]0.493303267038893[/C][C]1.16891568604477[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]0.535587223450273[/C][C]0.471580622435365[/C][C]1.13572780129167[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]0.490701586330777[/C][C]0.451442076074879[/C][C]1.08696466797522[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]0.485632233935989[/C][C]0.440484942234563[/C][C]1.10249451768407[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]0.485632233935989[/C][C]0.432400219742464[/C][C]1.1231082033798[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]0.449712401278469[/C][C]0.422075422628233[/C][C]1.06547876793712[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]0.442883307522532[/C][C]0.412428853135823[/C][C]1.07384171634733[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]0.433245339445532[/C][C]0.397735866640295[/C][C]1.08927903109465[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]0.401522882460827[/C][C]0.384574905084943[/C][C]1.04406937933753[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]0.377353308787744[/C][C]0.37020258491872[/C][C]1.01931570486088[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]0.33370584259831[/C][C]0.352191625696942[/C][C]0.947512144668258[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]0.271226983157962[/C][C]0.329783155473617[/C][C]0.822440378340246[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]0.271226983157962[/C][C]0.29074890108577[/C][C]0.93285643434969[/C][/ROW]
[ROW][C]Median[/C][C]0.108397535296406[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-1.2505588959032[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.260763236719181[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.401522882460827[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.401522882460827[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.401522882460827[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.401522882460827[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.290507891027076[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.401522882460827[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.401522882460827[/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=2284&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2284&T=1

As an alternative you can also use a QR Code:  

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

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean0.4945911417736830.6921074875975930.71461608295914
Geometric MeanNaN
Harmonic Mean7.90789100901878
Quadratic Mean4.82050138141006
Winsorized Mean ( 1 / 16 )0.5416847055168870.6112031020346570.886259745269047
Winsorized Mean ( 2 / 16 )0.6367076941815120.5670028232138121.12293566824343
Winsorized Mean ( 3 / 16 )0.6222368791693680.5553236001869961.12049421087063
Winsorized Mean ( 4 / 16 )0.6312849053947320.5364262336870171.17683451283828
Winsorized Mean ( 5 / 16 )0.7050534044116380.5127577411717851.37502244783357
Winsorized Mean ( 6 / 16 )0.5124273823084370.4678660133294691.09524386834995
Winsorized Mean ( 7 / 16 )0.5750370384454610.4444385510053061.29385049326784
Winsorized Mean ( 8 / 16 )0.5524815362822840.4379488293823931.26152075132021
Winsorized Mean ( 9 / 16 )0.4860877782233560.4193569402862491.15912658531788
Winsorized Mean ( 10 / 16 )0.4959904785590640.4168167266093811.18994859585825
Winsorized Mean ( 11 / 16 )0.6112795368086720.388322873876061.57415279380059
Winsorized Mean ( 12 / 16 )0.5376617055990080.3690667720766571.45681417639877
Winsorized Mean ( 13 / 16 )0.6205320489860190.351255947813431.76660937088420
Winsorized Mean ( 14 / 16 )0.6728767938459130.3286503405962942.04739417773024
Winsorized Mean ( 15 / 16 )0.7063161220077430.3188769036871752.21501185517235
Winsorized Mean ( 16 / 16 )0.6239387670230510.2929635679433152.12974866261793
Trimmed Mean ( 1 / 16 )0.4945911417736830.5793337420975710.853724038207987
Trimmed Mean ( 2 / 16 )0.5688528455046140.5377390440643031.05786040977265
Trimmed Mean ( 3 / 16 )0.5766299268188940.5159063344466251.11770274625025
Trimmed Mean ( 4 / 16 )0.5766299268188940.4933032670388931.16891568604477
Trimmed Mean ( 5 / 16 )0.5355872234502730.4715806224353651.13572780129167
Trimmed Mean ( 6 / 16 )0.4907015863307770.4514420760748791.08696466797522
Trimmed Mean ( 7 / 16 )0.4856322339359890.4404849422345631.10249451768407
Trimmed Mean ( 8 / 16 )0.4856322339359890.4324002197424641.1231082033798
Trimmed Mean ( 9 / 16 )0.4497124012784690.4220754226282331.06547876793712
Trimmed Mean ( 10 / 16 )0.4428833075225320.4124288531358231.07384171634733
Trimmed Mean ( 11 / 16 )0.4332453394455320.3977358666402951.08927903109465
Trimmed Mean ( 12 / 16 )0.4015228824608270.3845749050849431.04406937933753
Trimmed Mean ( 13 / 16 )0.3773533087877440.370202584918721.01931570486088
Trimmed Mean ( 14 / 16 )0.333705842598310.3521916256969420.947512144668258
Trimmed Mean ( 15 / 16 )0.2712269831579620.3297831554736170.822440378340246
Trimmed Mean ( 16 / 16 )0.2712269831579620.290748901085770.93285643434969
Median0.108397535296406
Midrange-1.2505588959032
Midmean - Weighted Average at Xnp0.260763236719181
Midmean - Weighted Average at X(n+1)p0.401522882460827
Midmean - Empirical Distribution Function0.401522882460827
Midmean - Empirical Distribution Function - Averaging0.401522882460827
Midmean - Empirical Distribution Function - Interpolation0.401522882460827
Midmean - Closest Observation0.290507891027076
Midmean - True Basic - Statistics Graphics Toolkit0.401522882460827
Midmean - MS Excel (old versions)0.401522882460827
Number of observations49



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')