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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, 18 Dec 2009 04:30:36 -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/2009/Dec/18/t1261135877l8ktzrtnfrbjdbt.htm/, Retrieved Sat, 27 Apr 2024 08:57:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69244, Retrieved Sat, 27 Apr 2024 08:57:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwpaper25
Estimated Impact134
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2009-12-18 11:30:36] [4407d6264e55b051ec65750e6dca2820] [Current]
-    D    [Central Tendency] [] [2009-12-20 09:36:58] [ebd107afac1bd6180acb277edd05815b]
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Dataseries X:
-56.404923233245 
527.836603046086 
478.714348211866 
-908.36869953975 
1050.52260239472 
896.809975301159 
795.431903881218 
-1771.21958364157 
1177.21170861071 
-2119.66518035102 
920.64060675515 
-1047.66382083267 
933.973094138826 
-528.000966128935 
-133.407591549358 
1125.75465854243 
-504.762600179679 
-2393.82902634230 
311.89186039671 
1096.91429998511 
-297.684996323743 
-92.9867283359076 
1299.88683909719 
229.150739388125 
1369.70507742263 
-1095.34792801021 
-1304.85320746412 
1510.38605140235 
636.881228714159 
-978.430535088919 
883.058618889536 
977.707360415901 
-1696.64473497727 
2640.32160285349 
-1025.81015019782 
1330.80561497152 
-911.435330053074 
-212.950188748477 
-51.4533641138587 
-1379.76186837010 
-3782.08991963700 
-2270.77027311182 
-1853.8583573614 
476.772054338646 
-20.3169587413759 
-792.62978037154 
-807.807186039036 
622.005863856947 
314.456965319724 




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=69244&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=69244&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69244&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-131.251310628775179.830058071761-0.729863027550153
Geometric MeanNaN
Harmonic Mean-508.727656541304
Quadratic Mean1252.79355692558
Winsorized Mean ( 1 / 16 )-125.979364876866163.486156037695-0.770581240211062
Winsorized Mean ( 2 / 16 )-126.698639193162160.907703599052-0.787399461674425
Winsorized Mean ( 3 / 16 )-119.828906725221157.944250549148-0.758678497688866
Winsorized Mean ( 4 / 16 )-100.654372266830151.98648661259-0.662258694902237
Winsorized Mean ( 5 / 16 )-104.739714794039147.646759368578-0.709393929416171
Winsorized Mean ( 6 / 16 )-101.908963945547144.394298308473-0.705768615100278
Winsorized Mean ( 7 / 16 )-60.7600342241401133.779715993545-0.454179722037022
Winsorized Mean ( 8 / 16 )-56.1042034787377129.944128474606-0.431756356653712
Winsorized Mean ( 9 / 16 )-30.9978700649454120.173710139518-0.257942190758344
Winsorized Mean ( 10 / 16 )-30.1917800852586116.845238081853-0.258391189755706
Winsorized Mean ( 11 / 16 )-28.2788613962196115.445110596311-0.24495503750787
Winsorized Mean ( 12 / 16 )-22.5117633582825112.375312721350-0.200326591429413
Winsorized Mean ( 13 / 16 )-8.38584433552974108.637981238437-0.0771907231700542
Winsorized Mean ( 14 / 16 )-32.5458684769566104.273249554562-0.31212097653029
Winsorized Mean ( 15 / 16 )-50.297652660531691.06767824012-0.552310694996646
Winsorized Mean ( 16 / 16 )-50.199027089826689.4477312939709-0.561210735740709
Trimmed Mean ( 1 / 16 )-131.251310628775159.547067375933-0.822649471328197
Trimmed Mean ( 2 / 16 )-112.543529872904154.374742215463-0.729028131530902
Trimmed Mean ( 3 / 16 )-81.5125054278452149.379879704019-0.545672587160694
Trimmed Mean ( 4 / 16 )-81.5125054278452144.284296806702-0.564943706500840
Trimmed Mean ( 5 / 16 )-55.4411961475291140.067030749210-0.395819029296027
Trimmed Mean ( 6 / 16 )-42.3837506681831135.91361606722-0.311843300874439
Trimmed Mean ( 7 / 16 )-28.4945342367981131.243266610183-0.217112351534438
Trimmed Mean ( 8 / 16 )-28.4945342367981128.376708826550-0.221960311159692
Trimmed Mean ( 9 / 16 )-14.8429201559208125.320624612009-0.118439564132993
Trimmed Mean ( 10 / 16 )-11.8099985254909123.839325303337-0.0953654947373379
Trimmed Mean ( 11 / 16 )-8.47404557575526122.213544741844-0.0693380229961852
Trimmed Mean ( 12 / 16 )-4.94518748410889119.628867446811-0.0413377438878421
Trimmed Mean ( 13 / 16 )-1.82648379630271116.143394360927-0.0157261100069689
Trimmed Mean ( 14 / 16 )-0.649162673877342111.431601370009-0.00582566045804004
Trimmed Mean ( 15 / 16 )5.22654628984778104.8081646625290.04986773985287
Trimmed Mean ( 16 / 16 )5.2265462898477899.53639384981480.0525088973761079
Median-51.4533641138587
Midrange-570.884158391755
Midmean - Weighted Average at Xnp-42.5183192668283
Midmean - Weighted Average at X(n+1)p-4.94518748410882
Midmean - Empirical Distribution Function-4.94518748410882
Midmean - Empirical Distribution Function - Averaging-4.94518748410882
Midmean - Empirical Distribution Function - Interpolation-4.94518748410882
Midmean - Closest Observation-44.2092245115592
Midmean - True Basic - Statistics Graphics Toolkit-4.94518748410882
Midmean - MS Excel (old versions)-4.94518748410882
Number of observations49

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -131.251310628775 & 179.830058071761 & -0.729863027550153 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -508.727656541304 &  &  \tabularnewline
Quadratic Mean & 1252.79355692558 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & -125.979364876866 & 163.486156037695 & -0.770581240211062 \tabularnewline
Winsorized Mean ( 2 / 16 ) & -126.698639193162 & 160.907703599052 & -0.787399461674425 \tabularnewline
Winsorized Mean ( 3 / 16 ) & -119.828906725221 & 157.944250549148 & -0.758678497688866 \tabularnewline
Winsorized Mean ( 4 / 16 ) & -100.654372266830 & 151.98648661259 & -0.662258694902237 \tabularnewline
Winsorized Mean ( 5 / 16 ) & -104.739714794039 & 147.646759368578 & -0.709393929416171 \tabularnewline
Winsorized Mean ( 6 / 16 ) & -101.908963945547 & 144.394298308473 & -0.705768615100278 \tabularnewline
Winsorized Mean ( 7 / 16 ) & -60.7600342241401 & 133.779715993545 & -0.454179722037022 \tabularnewline
Winsorized Mean ( 8 / 16 ) & -56.1042034787377 & 129.944128474606 & -0.431756356653712 \tabularnewline
Winsorized Mean ( 9 / 16 ) & -30.9978700649454 & 120.173710139518 & -0.257942190758344 \tabularnewline
Winsorized Mean ( 10 / 16 ) & -30.1917800852586 & 116.845238081853 & -0.258391189755706 \tabularnewline
Winsorized Mean ( 11 / 16 ) & -28.2788613962196 & 115.445110596311 & -0.24495503750787 \tabularnewline
Winsorized Mean ( 12 / 16 ) & -22.5117633582825 & 112.375312721350 & -0.200326591429413 \tabularnewline
Winsorized Mean ( 13 / 16 ) & -8.38584433552974 & 108.637981238437 & -0.0771907231700542 \tabularnewline
Winsorized Mean ( 14 / 16 ) & -32.5458684769566 & 104.273249554562 & -0.31212097653029 \tabularnewline
Winsorized Mean ( 15 / 16 ) & -50.2976526605316 & 91.06767824012 & -0.552310694996646 \tabularnewline
Winsorized Mean ( 16 / 16 ) & -50.1990270898266 & 89.4477312939709 & -0.561210735740709 \tabularnewline
Trimmed Mean ( 1 / 16 ) & -131.251310628775 & 159.547067375933 & -0.822649471328197 \tabularnewline
Trimmed Mean ( 2 / 16 ) & -112.543529872904 & 154.374742215463 & -0.729028131530902 \tabularnewline
Trimmed Mean ( 3 / 16 ) & -81.5125054278452 & 149.379879704019 & -0.545672587160694 \tabularnewline
Trimmed Mean ( 4 / 16 ) & -81.5125054278452 & 144.284296806702 & -0.564943706500840 \tabularnewline
Trimmed Mean ( 5 / 16 ) & -55.4411961475291 & 140.067030749210 & -0.395819029296027 \tabularnewline
Trimmed Mean ( 6 / 16 ) & -42.3837506681831 & 135.91361606722 & -0.311843300874439 \tabularnewline
Trimmed Mean ( 7 / 16 ) & -28.4945342367981 & 131.243266610183 & -0.217112351534438 \tabularnewline
Trimmed Mean ( 8 / 16 ) & -28.4945342367981 & 128.376708826550 & -0.221960311159692 \tabularnewline
Trimmed Mean ( 9 / 16 ) & -14.8429201559208 & 125.320624612009 & -0.118439564132993 \tabularnewline
Trimmed Mean ( 10 / 16 ) & -11.8099985254909 & 123.839325303337 & -0.0953654947373379 \tabularnewline
Trimmed Mean ( 11 / 16 ) & -8.47404557575526 & 122.213544741844 & -0.0693380229961852 \tabularnewline
Trimmed Mean ( 12 / 16 ) & -4.94518748410889 & 119.628867446811 & -0.0413377438878421 \tabularnewline
Trimmed Mean ( 13 / 16 ) & -1.82648379630271 & 116.143394360927 & -0.0157261100069689 \tabularnewline
Trimmed Mean ( 14 / 16 ) & -0.649162673877342 & 111.431601370009 & -0.00582566045804004 \tabularnewline
Trimmed Mean ( 15 / 16 ) & 5.22654628984778 & 104.808164662529 & 0.04986773985287 \tabularnewline
Trimmed Mean ( 16 / 16 ) & 5.22654628984778 & 99.5363938498148 & 0.0525088973761079 \tabularnewline
Median & -51.4533641138587 &  &  \tabularnewline
Midrange & -570.884158391755 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -42.5183192668283 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -4.94518748410882 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -4.94518748410882 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -4.94518748410882 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -4.94518748410882 &  &  \tabularnewline
Midmean - Closest Observation & -44.2092245115592 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -4.94518748410882 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -4.94518748410882 &  &  \tabularnewline
Number of observations & 49 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69244&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]-131.251310628775[/C][C]179.830058071761[/C][C]-0.729863027550153[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-508.727656541304[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1252.79355692558[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]-125.979364876866[/C][C]163.486156037695[/C][C]-0.770581240211062[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]-126.698639193162[/C][C]160.907703599052[/C][C]-0.787399461674425[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]-119.828906725221[/C][C]157.944250549148[/C][C]-0.758678497688866[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]-100.654372266830[/C][C]151.98648661259[/C][C]-0.662258694902237[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]-104.739714794039[/C][C]147.646759368578[/C][C]-0.709393929416171[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]-101.908963945547[/C][C]144.394298308473[/C][C]-0.705768615100278[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]-60.7600342241401[/C][C]133.779715993545[/C][C]-0.454179722037022[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]-56.1042034787377[/C][C]129.944128474606[/C][C]-0.431756356653712[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]-30.9978700649454[/C][C]120.173710139518[/C][C]-0.257942190758344[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]-30.1917800852586[/C][C]116.845238081853[/C][C]-0.258391189755706[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]-28.2788613962196[/C][C]115.445110596311[/C][C]-0.24495503750787[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]-22.5117633582825[/C][C]112.375312721350[/C][C]-0.200326591429413[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]-8.38584433552974[/C][C]108.637981238437[/C][C]-0.0771907231700542[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]-32.5458684769566[/C][C]104.273249554562[/C][C]-0.31212097653029[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]-50.2976526605316[/C][C]91.06767824012[/C][C]-0.552310694996646[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]-50.1990270898266[/C][C]89.4477312939709[/C][C]-0.561210735740709[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]-131.251310628775[/C][C]159.547067375933[/C][C]-0.822649471328197[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]-112.543529872904[/C][C]154.374742215463[/C][C]-0.729028131530902[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]-81.5125054278452[/C][C]149.379879704019[/C][C]-0.545672587160694[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]-81.5125054278452[/C][C]144.284296806702[/C][C]-0.564943706500840[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]-55.4411961475291[/C][C]140.067030749210[/C][C]-0.395819029296027[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]-42.3837506681831[/C][C]135.91361606722[/C][C]-0.311843300874439[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]-28.4945342367981[/C][C]131.243266610183[/C][C]-0.217112351534438[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]-28.4945342367981[/C][C]128.376708826550[/C][C]-0.221960311159692[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]-14.8429201559208[/C][C]125.320624612009[/C][C]-0.118439564132993[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]-11.8099985254909[/C][C]123.839325303337[/C][C]-0.0953654947373379[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]-8.47404557575526[/C][C]122.213544741844[/C][C]-0.0693380229961852[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]-4.94518748410889[/C][C]119.628867446811[/C][C]-0.0413377438878421[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]-1.82648379630271[/C][C]116.143394360927[/C][C]-0.0157261100069689[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]-0.649162673877342[/C][C]111.431601370009[/C][C]-0.00582566045804004[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]5.22654628984778[/C][C]104.808164662529[/C][C]0.04986773985287[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]5.22654628984778[/C][C]99.5363938498148[/C][C]0.0525088973761079[/C][/ROW]
[ROW][C]Median[/C][C]-51.4533641138587[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-570.884158391755[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-42.5183192668283[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-4.94518748410882[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-4.94518748410882[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-4.94518748410882[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-4.94518748410882[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-44.2092245115592[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-4.94518748410882[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-4.94518748410882[/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=69244&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69244&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-131.251310628775179.830058071761-0.729863027550153
Geometric MeanNaN
Harmonic Mean-508.727656541304
Quadratic Mean1252.79355692558
Winsorized Mean ( 1 / 16 )-125.979364876866163.486156037695-0.770581240211062
Winsorized Mean ( 2 / 16 )-126.698639193162160.907703599052-0.787399461674425
Winsorized Mean ( 3 / 16 )-119.828906725221157.944250549148-0.758678497688866
Winsorized Mean ( 4 / 16 )-100.654372266830151.98648661259-0.662258694902237
Winsorized Mean ( 5 / 16 )-104.739714794039147.646759368578-0.709393929416171
Winsorized Mean ( 6 / 16 )-101.908963945547144.394298308473-0.705768615100278
Winsorized Mean ( 7 / 16 )-60.7600342241401133.779715993545-0.454179722037022
Winsorized Mean ( 8 / 16 )-56.1042034787377129.944128474606-0.431756356653712
Winsorized Mean ( 9 / 16 )-30.9978700649454120.173710139518-0.257942190758344
Winsorized Mean ( 10 / 16 )-30.1917800852586116.845238081853-0.258391189755706
Winsorized Mean ( 11 / 16 )-28.2788613962196115.445110596311-0.24495503750787
Winsorized Mean ( 12 / 16 )-22.5117633582825112.375312721350-0.200326591429413
Winsorized Mean ( 13 / 16 )-8.38584433552974108.637981238437-0.0771907231700542
Winsorized Mean ( 14 / 16 )-32.5458684769566104.273249554562-0.31212097653029
Winsorized Mean ( 15 / 16 )-50.297652660531691.06767824012-0.552310694996646
Winsorized Mean ( 16 / 16 )-50.199027089826689.4477312939709-0.561210735740709
Trimmed Mean ( 1 / 16 )-131.251310628775159.547067375933-0.822649471328197
Trimmed Mean ( 2 / 16 )-112.543529872904154.374742215463-0.729028131530902
Trimmed Mean ( 3 / 16 )-81.5125054278452149.379879704019-0.545672587160694
Trimmed Mean ( 4 / 16 )-81.5125054278452144.284296806702-0.564943706500840
Trimmed Mean ( 5 / 16 )-55.4411961475291140.067030749210-0.395819029296027
Trimmed Mean ( 6 / 16 )-42.3837506681831135.91361606722-0.311843300874439
Trimmed Mean ( 7 / 16 )-28.4945342367981131.243266610183-0.217112351534438
Trimmed Mean ( 8 / 16 )-28.4945342367981128.376708826550-0.221960311159692
Trimmed Mean ( 9 / 16 )-14.8429201559208125.320624612009-0.118439564132993
Trimmed Mean ( 10 / 16 )-11.8099985254909123.839325303337-0.0953654947373379
Trimmed Mean ( 11 / 16 )-8.47404557575526122.213544741844-0.0693380229961852
Trimmed Mean ( 12 / 16 )-4.94518748410889119.628867446811-0.0413377438878421
Trimmed Mean ( 13 / 16 )-1.82648379630271116.143394360927-0.0157261100069689
Trimmed Mean ( 14 / 16 )-0.649162673877342111.431601370009-0.00582566045804004
Trimmed Mean ( 15 / 16 )5.22654628984778104.8081646625290.04986773985287
Trimmed Mean ( 16 / 16 )5.2265462898477899.53639384981480.0525088973761079
Median-51.4533641138587
Midrange-570.884158391755
Midmean - Weighted Average at Xnp-42.5183192668283
Midmean - Weighted Average at X(n+1)p-4.94518748410882
Midmean - Empirical Distribution Function-4.94518748410882
Midmean - Empirical Distribution Function - Averaging-4.94518748410882
Midmean - Empirical Distribution Function - Interpolation-4.94518748410882
Midmean - Closest Observation-44.2092245115592
Midmean - True Basic - Statistics Graphics Toolkit-4.94518748410882
Midmean - MS Excel (old versions)-4.94518748410882
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')