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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 12:40:39 +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/t1293194358oj88kmekj28ervw.htm/, Retrieved Tue, 30 Apr 2024 04:13:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114866, Retrieved Tue, 30 Apr 2024 04:13:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [paper] [2007-12-11 21:01:08] [b3bb3ec527e23fa7d74d4348b38c8499]
- RMPD  [Univariate Explorative Data Analysis] [PAPER] [2009-12-30 15:50:30] [23722951c28e05bb35cc9a97084fe0d9]
- RMPD    [(Partial) Autocorrelation Function] [Central tendency ...] [2010-12-17 14:53:08] [b659239b537e56f17142ee5c56ad6265]
- RM        [Central Tendency] [Central tendency ...] [2010-12-18 14:24:52] [b659239b537e56f17142ee5c56ad6265]
-    D          [Central Tendency] [Central tendency ...] [2010-12-24 12:40:39] [efffa7146cfe4c2b113f6c7f36d84ca0] [Current]
Feedback Forum

Post a new message
Dataseries X:
-49.7893339813624 
-115.855857347157 
358.642252325575 
-1280.23404859543 
1269.7990218444 
-482.344439925045 
535.432156472485 
-653.350665670356 
-150.255607623481 
809.700340422624 
-454.25759298969 
-944.643265379427 
315.20994572738 
-4.19622349469063 
122.766997172271 
0.263819130037385 
7.82728106033063 
309.789819115024 
550.179633243721 
-154.686633687727 
-905.855795506139 
855.608436659643 
-873.24999022707 
-190.895544647361 
123.512252726179 
579.148230586512 
-1330.15873241708 
1493.42083518269 
-471.236978042281 
375.446281752056 
84.7030430928148 
-1448.7429878622 
556.696970316013 
-994.720490616971 
-2762.85125636168 
-1223.45771147529 
-1064.55765279704 
821.83469984857 
-437.67345344376 
375.180756215468 
-396.843780362746 
837.847042453338 
864.953789085965 
493.563033484152 
-378.994495101279 
280.453936285203 
754.180578928203 
1349.24340665111 
-212.749295852145 




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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114866&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114866&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114866&T=0

As an alternative you can also use a QR Code:  

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

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







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-58.2897402780744117.981975990522-0.494056314862509
Geometric MeanNaN
Harmonic Mean13.3551951912123
Quadratic Mean819.478818173988
Winsorized Mean ( 1 / 16 )-34.4136006868927106.950942800414-0.321769960935394
Winsorized Mean ( 2 / 16 )-32.8160549465495104.802657332588-0.313122355689978
Winsorized Mean ( 3 / 16 )-54.545884473291498.3639506091063-0.554531249868706
Winsorized Mean ( 4 / 16 )-50.673967355428797.030181850638-0.522249535030583
Winsorized Mean ( 5 / 16 )-36.272062817475192.7583711448408-0.391038160435535
Winsorized Mean ( 6 / 16 )-29.681268583764890.4350826398365-0.328205246430440
Winsorized Mean ( 7 / 16 )-24.260859182108088.5247566347138-0.274057338358097
Winsorized Mean ( 8 / 16 )-26.992661895762385.4063895565534-0.316049677733873
Winsorized Mean ( 9 / 16 )-53.152639192978678.329937951529-0.678573743105346
Winsorized Mean ( 10 / 16 )-12.857115869261268.2296203171826-0.188438918602972
Winsorized Mean ( 11 / 16 )24.068961179783860.86557348516590.395444580599407
Winsorized Mean ( 12 / 16 )23.177528962198859.7475645911680.387924246298484
Winsorized Mean ( 13 / 16 )16.574129101695957.01100078736120.290718087260278
Winsorized Mean ( 14 / 16 )-12.435188665780150.5344341799162-0.246073570775672
Winsorized Mean ( 15 / 16 )-0.017592478710941248.3567652119218-0.000363805945948676
Winsorized Mean ( 16 / 16 )0.41041776506831346.49309602423240.00882749913781612
Trimmed Mean ( 1 / 16 )-58.2897402780744103.116352583692-0.565281246063907
Trimmed Mean ( 2 / 16 )-33.760996860567198.1485410884132-0.343978590880478
Trimmed Mean ( 3 / 16 )-33.183896759601993.2188689759144-0.355978324175719
Trimmed Mean ( 4 / 16 )-33.183896759601990.1521324466263-0.368087762973861
Trimmed Mean ( 5 / 16 )-16.507128880455786.6000731101831-0.190613336543646
Trimmed Mean ( 6 / 16 )-11.272092324164083.4909398254021-0.135009766900893
Trimmed Mean ( 7 / 16 )-6.9766178635905280.0374820810095-0.0871668833425966
Trimmed Mean ( 8 / 16 )-6.9766178635905275.8569394219912-0.0919707269598592
Trimmed Mean ( 9 / 16 )1.3689198809377670.99488942510230.0192819496166965
Trimmed Mean ( 10 / 16 )11.604768136194166.45148557086840.174635194932068
Trimmed Mean ( 11 / 16 )16.044147085332363.66989062788370.251989549960148
Trimmed Mean ( 12 / 16 )14.614271119411862.07607128722520.235425193901073
Trimmed Mean ( 13 / 16 )13.093982589351859.72114565300620.219252032863383
Trimmed Mean ( 14 / 16 )12.469340907649056.80859912893460.219497419384488
Trimmed Mean ( 15 / 16 )17.057017408017654.62927767900510.312232160715038
Trimmed Mean ( 16 / 16 )17.057017408017651.48175510810580.331321598733372
Median0.263819130037385
Midrange-634.715210589495
Midmean - Weighted Average at Xnp-7.08647410363285
Midmean - Weighted Average at X(n+1)p14.6142711194119
Midmean - Empirical Distribution Function14.6142711194119
Midmean - Empirical Distribution Function - Averaging14.6142711194119
Midmean - Empirical Distribution Function - Interpolation14.6142711194119
Midmean - Closest Observation-4.49952545922109
Midmean - True Basic - Statistics Graphics Toolkit14.6142711194119
Midmean - MS Excel (old versions)14.6142711194119
Number of observations49

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -58.2897402780744 & 117.981975990522 & -0.494056314862509 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 13.3551951912123 &  &  \tabularnewline
Quadratic Mean & 819.478818173988 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & -34.4136006868927 & 106.950942800414 & -0.321769960935394 \tabularnewline
Winsorized Mean ( 2 / 16 ) & -32.8160549465495 & 104.802657332588 & -0.313122355689978 \tabularnewline
Winsorized Mean ( 3 / 16 ) & -54.5458844732914 & 98.3639506091063 & -0.554531249868706 \tabularnewline
Winsorized Mean ( 4 / 16 ) & -50.6739673554287 & 97.030181850638 & -0.522249535030583 \tabularnewline
Winsorized Mean ( 5 / 16 ) & -36.2720628174751 & 92.7583711448408 & -0.391038160435535 \tabularnewline
Winsorized Mean ( 6 / 16 ) & -29.6812685837648 & 90.4350826398365 & -0.328205246430440 \tabularnewline
Winsorized Mean ( 7 / 16 ) & -24.2608591821080 & 88.5247566347138 & -0.274057338358097 \tabularnewline
Winsorized Mean ( 8 / 16 ) & -26.9926618957623 & 85.4063895565534 & -0.316049677733873 \tabularnewline
Winsorized Mean ( 9 / 16 ) & -53.1526391929786 & 78.329937951529 & -0.678573743105346 \tabularnewline
Winsorized Mean ( 10 / 16 ) & -12.8571158692612 & 68.2296203171826 & -0.188438918602972 \tabularnewline
Winsorized Mean ( 11 / 16 ) & 24.0689611797838 & 60.8655734851659 & 0.395444580599407 \tabularnewline
Winsorized Mean ( 12 / 16 ) & 23.1775289621988 & 59.747564591168 & 0.387924246298484 \tabularnewline
Winsorized Mean ( 13 / 16 ) & 16.5741291016959 & 57.0110007873612 & 0.290718087260278 \tabularnewline
Winsorized Mean ( 14 / 16 ) & -12.4351886657801 & 50.5344341799162 & -0.246073570775672 \tabularnewline
Winsorized Mean ( 15 / 16 ) & -0.0175924787109412 & 48.3567652119218 & -0.000363805945948676 \tabularnewline
Winsorized Mean ( 16 / 16 ) & 0.410417765068313 & 46.4930960242324 & 0.00882749913781612 \tabularnewline
Trimmed Mean ( 1 / 16 ) & -58.2897402780744 & 103.116352583692 & -0.565281246063907 \tabularnewline
Trimmed Mean ( 2 / 16 ) & -33.7609968605671 & 98.1485410884132 & -0.343978590880478 \tabularnewline
Trimmed Mean ( 3 / 16 ) & -33.1838967596019 & 93.2188689759144 & -0.355978324175719 \tabularnewline
Trimmed Mean ( 4 / 16 ) & -33.1838967596019 & 90.1521324466263 & -0.368087762973861 \tabularnewline
Trimmed Mean ( 5 / 16 ) & -16.5071288804557 & 86.6000731101831 & -0.190613336543646 \tabularnewline
Trimmed Mean ( 6 / 16 ) & -11.2720923241640 & 83.4909398254021 & -0.135009766900893 \tabularnewline
Trimmed Mean ( 7 / 16 ) & -6.97661786359052 & 80.0374820810095 & -0.0871668833425966 \tabularnewline
Trimmed Mean ( 8 / 16 ) & -6.97661786359052 & 75.8569394219912 & -0.0919707269598592 \tabularnewline
Trimmed Mean ( 9 / 16 ) & 1.36891988093776 & 70.9948894251023 & 0.0192819496166965 \tabularnewline
Trimmed Mean ( 10 / 16 ) & 11.6047681361941 & 66.4514855708684 & 0.174635194932068 \tabularnewline
Trimmed Mean ( 11 / 16 ) & 16.0441470853323 & 63.6698906278837 & 0.251989549960148 \tabularnewline
Trimmed Mean ( 12 / 16 ) & 14.6142711194118 & 62.0760712872252 & 0.235425193901073 \tabularnewline
Trimmed Mean ( 13 / 16 ) & 13.0939825893518 & 59.7211456530062 & 0.219252032863383 \tabularnewline
Trimmed Mean ( 14 / 16 ) & 12.4693409076490 & 56.8085991289346 & 0.219497419384488 \tabularnewline
Trimmed Mean ( 15 / 16 ) & 17.0570174080176 & 54.6292776790051 & 0.312232160715038 \tabularnewline
Trimmed Mean ( 16 / 16 ) & 17.0570174080176 & 51.4817551081058 & 0.331321598733372 \tabularnewline
Median & 0.263819130037385 &  &  \tabularnewline
Midrange & -634.715210589495 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -7.08647410363285 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 14.6142711194119 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 14.6142711194119 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 14.6142711194119 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 14.6142711194119 &  &  \tabularnewline
Midmean - Closest Observation & -4.49952545922109 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 14.6142711194119 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 14.6142711194119 &  &  \tabularnewline
Number of observations & 49 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114866&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]-58.2897402780744[/C][C]117.981975990522[/C][C]-0.494056314862509[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]13.3551951912123[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]819.478818173988[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]-34.4136006868927[/C][C]106.950942800414[/C][C]-0.321769960935394[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]-32.8160549465495[/C][C]104.802657332588[/C][C]-0.313122355689978[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]-54.5458844732914[/C][C]98.3639506091063[/C][C]-0.554531249868706[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]-50.6739673554287[/C][C]97.030181850638[/C][C]-0.522249535030583[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]-36.2720628174751[/C][C]92.7583711448408[/C][C]-0.391038160435535[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]-29.6812685837648[/C][C]90.4350826398365[/C][C]-0.328205246430440[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]-24.2608591821080[/C][C]88.5247566347138[/C][C]-0.274057338358097[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]-26.9926618957623[/C][C]85.4063895565534[/C][C]-0.316049677733873[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]-53.1526391929786[/C][C]78.329937951529[/C][C]-0.678573743105346[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]-12.8571158692612[/C][C]68.2296203171826[/C][C]-0.188438918602972[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]24.0689611797838[/C][C]60.8655734851659[/C][C]0.395444580599407[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]23.1775289621988[/C][C]59.747564591168[/C][C]0.387924246298484[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]16.5741291016959[/C][C]57.0110007873612[/C][C]0.290718087260278[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]-12.4351886657801[/C][C]50.5344341799162[/C][C]-0.246073570775672[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]-0.0175924787109412[/C][C]48.3567652119218[/C][C]-0.000363805945948676[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]0.410417765068313[/C][C]46.4930960242324[/C][C]0.00882749913781612[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]-58.2897402780744[/C][C]103.116352583692[/C][C]-0.565281246063907[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]-33.7609968605671[/C][C]98.1485410884132[/C][C]-0.343978590880478[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]-33.1838967596019[/C][C]93.2188689759144[/C][C]-0.355978324175719[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]-33.1838967596019[/C][C]90.1521324466263[/C][C]-0.368087762973861[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]-16.5071288804557[/C][C]86.6000731101831[/C][C]-0.190613336543646[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]-11.2720923241640[/C][C]83.4909398254021[/C][C]-0.135009766900893[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]-6.97661786359052[/C][C]80.0374820810095[/C][C]-0.0871668833425966[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]-6.97661786359052[/C][C]75.8569394219912[/C][C]-0.0919707269598592[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]1.36891988093776[/C][C]70.9948894251023[/C][C]0.0192819496166965[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]11.6047681361941[/C][C]66.4514855708684[/C][C]0.174635194932068[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]16.0441470853323[/C][C]63.6698906278837[/C][C]0.251989549960148[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]14.6142711194118[/C][C]62.0760712872252[/C][C]0.235425193901073[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]13.0939825893518[/C][C]59.7211456530062[/C][C]0.219252032863383[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]12.4693409076490[/C][C]56.8085991289346[/C][C]0.219497419384488[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]17.0570174080176[/C][C]54.6292776790051[/C][C]0.312232160715038[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]17.0570174080176[/C][C]51.4817551081058[/C][C]0.331321598733372[/C][/ROW]
[ROW][C]Median[/C][C]0.263819130037385[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-634.715210589495[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-7.08647410363285[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]14.6142711194119[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]14.6142711194119[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]14.6142711194119[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]14.6142711194119[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-4.49952545922109[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]14.6142711194119[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]14.6142711194119[/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=114866&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114866&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-58.2897402780744117.981975990522-0.494056314862509
Geometric MeanNaN
Harmonic Mean13.3551951912123
Quadratic Mean819.478818173988
Winsorized Mean ( 1 / 16 )-34.4136006868927106.950942800414-0.321769960935394
Winsorized Mean ( 2 / 16 )-32.8160549465495104.802657332588-0.313122355689978
Winsorized Mean ( 3 / 16 )-54.545884473291498.3639506091063-0.554531249868706
Winsorized Mean ( 4 / 16 )-50.673967355428797.030181850638-0.522249535030583
Winsorized Mean ( 5 / 16 )-36.272062817475192.7583711448408-0.391038160435535
Winsorized Mean ( 6 / 16 )-29.681268583764890.4350826398365-0.328205246430440
Winsorized Mean ( 7 / 16 )-24.260859182108088.5247566347138-0.274057338358097
Winsorized Mean ( 8 / 16 )-26.992661895762385.4063895565534-0.316049677733873
Winsorized Mean ( 9 / 16 )-53.152639192978678.329937951529-0.678573743105346
Winsorized Mean ( 10 / 16 )-12.857115869261268.2296203171826-0.188438918602972
Winsorized Mean ( 11 / 16 )24.068961179783860.86557348516590.395444580599407
Winsorized Mean ( 12 / 16 )23.177528962198859.7475645911680.387924246298484
Winsorized Mean ( 13 / 16 )16.574129101695957.01100078736120.290718087260278
Winsorized Mean ( 14 / 16 )-12.435188665780150.5344341799162-0.246073570775672
Winsorized Mean ( 15 / 16 )-0.017592478710941248.3567652119218-0.000363805945948676
Winsorized Mean ( 16 / 16 )0.41041776506831346.49309602423240.00882749913781612
Trimmed Mean ( 1 / 16 )-58.2897402780744103.116352583692-0.565281246063907
Trimmed Mean ( 2 / 16 )-33.760996860567198.1485410884132-0.343978590880478
Trimmed Mean ( 3 / 16 )-33.183896759601993.2188689759144-0.355978324175719
Trimmed Mean ( 4 / 16 )-33.183896759601990.1521324466263-0.368087762973861
Trimmed Mean ( 5 / 16 )-16.507128880455786.6000731101831-0.190613336543646
Trimmed Mean ( 6 / 16 )-11.272092324164083.4909398254021-0.135009766900893
Trimmed Mean ( 7 / 16 )-6.9766178635905280.0374820810095-0.0871668833425966
Trimmed Mean ( 8 / 16 )-6.9766178635905275.8569394219912-0.0919707269598592
Trimmed Mean ( 9 / 16 )1.3689198809377670.99488942510230.0192819496166965
Trimmed Mean ( 10 / 16 )11.604768136194166.45148557086840.174635194932068
Trimmed Mean ( 11 / 16 )16.044147085332363.66989062788370.251989549960148
Trimmed Mean ( 12 / 16 )14.614271119411862.07607128722520.235425193901073
Trimmed Mean ( 13 / 16 )13.093982589351859.72114565300620.219252032863383
Trimmed Mean ( 14 / 16 )12.469340907649056.80859912893460.219497419384488
Trimmed Mean ( 15 / 16 )17.057017408017654.62927767900510.312232160715038
Trimmed Mean ( 16 / 16 )17.057017408017651.48175510810580.331321598733372
Median0.263819130037385
Midrange-634.715210589495
Midmean - Weighted Average at Xnp-7.08647410363285
Midmean - Weighted Average at X(n+1)p14.6142711194119
Midmean - Empirical Distribution Function14.6142711194119
Midmean - Empirical Distribution Function - Averaging14.6142711194119
Midmean - Empirical Distribution Function - Interpolation14.6142711194119
Midmean - Closest Observation-4.49952545922109
Midmean - True Basic - Statistics Graphics Toolkit14.6142711194119
Midmean - MS Excel (old versions)14.6142711194119
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')