Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 22 Dec 2007 12:14:48 -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/22/t1198349798a5ay2tvocpvlx0f.htm/, Retrieved Sun, 05 May 2024 01:44:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4826, Retrieved Sun, 05 May 2024 01:44:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsLise Swinnen
Estimated Impact262
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [paper (residuals ...] [2007-12-22 19:14:48] [a526d213baffe7453818dd375c9a7100] [Current]
Feedback Forum

Post a new message
Dataseries X:
8,46E+06
5,36E+09
-0.000383957211587875
-0.000195163574356706
-0.000229231116156105
0.000453355062196361
0.000702535691719339
0.000321335159538991
0.000661418746014698
-0.00037271139529584
6,96E+09
0.000814121375190822
0.000680091088790831
9,45E+08
0.000300685511050917
0.000202350536591252
0.000467049025429473
0.000292313534689647
-0.000377915702519248
-0.000178475900972563
-0.000237541091688458
3,34E+09
-5,33E+09
-8,43E+09
-0.00127373070311155
0.000377718157951627
0.000288636443643395
-0.000559374177509154
-0.000546745137218085
0.000226398087079409
0.000253955284742154
0.000758393654471886
0.000147115364194525
-0.000192888325661302
0.000208941151906886
-0.000334892885540213
0.000344674177797457
-9,97E+08
0.000256466554879747
0.000631977286823292
0.000411584191864834
-0.000264354029865536
-0.000636085722406521
-8,02E+09
-0.000115717801447431
0.000159653927232449
0.000581883991506058
0.000116088183319055
0.000947153188491333




Summary of compuational 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 compuational 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=4826&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]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=4826&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4826&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-125786530.612149328126520.248316-0.38334765052504
Geometric MeanNaN
Harmonic Mean0.00182745670104634
Quadratic Mean2276804534.69689
Winsorized Mean ( 1 / 16 )-150072244.897863310288462.533222-0.483653964032888
Winsorized Mean ( 2 / 16 )-122725306.122353225728781.965764-0.543684793111437
Winsorized Mean ( 3 / 16 )-4072244.8978631256647386.9107401-0.0718876036467453
Winsorized Mean ( 4 / 16 )863265.306114534369628.1211415652.33549683246072
Winsorized Mean ( 5 / 16 )0.0001537995639860307.43935032510759e-052.06737896811985
Winsorized Mean ( 6 / 16 )0.0001469032045897266.8890750536241e-052.13240824706135
Winsorized Mean ( 7 / 16 )0.0001407462502428886.69361311453861e-052.10269473055121
Winsorized Mean ( 8 / 16 )0.0001582042033657725.98232265329196e-052.64452809610186
Winsorized Mean ( 9 / 16 )0.0001551913902078355.88398629899329e-052.63752127081579
Winsorized Mean ( 10 / 16 )0.0001524428115236055.79364703006638e-052.63120640129605
Winsorized Mean ( 11 / 16 )0.0001543233738951655.51485961823365e-052.79831916999173
Winsorized Mean ( 12 / 16 )0.0001593304499010694.98271875923081e-053.19766090762998
Winsorized Mean ( 13 / 16 )0.0001359776669889554.34311397826088e-053.13087954102934
Winsorized Mean ( 14 / 16 )0.0001344393847887384.23888892388716e-053.17157130565842
Winsorized Mean ( 15 / 16 )0.0001320812229931893.85653763508821e-053.42486539717556
Winsorized Mean ( 16 / 16 )0.0001217658645547233.67966601651488e-053.30915534203973
Trimmed Mean ( 1 / 16 )-125786530.612149248987679.074756-0.505191787318853
Trimmed Mean ( 2 / 16 )-99862553.1913892144529383.176791-0.690949833150781
Trimmed Mean ( 3 / 16 )-1012558.1394254232324673.9053766-0.0313246203933707
Trimmed Mean ( 4 / 16 )-1012558.13942542206341.463411764-4.9071966568581
Trimmed Mean ( 5 / 16 )0.0001533549052536266.74893988559656e-052.27228139312535
Trimmed Mean ( 6 / 16 )0.0001532371307785566.42402407456713e-052.38537603533004
Trimmed Mean ( 7 / 16 )0.0001547150468892836.18499787973128e-052.50145674902002
Trimmed Mean ( 8 / 16 )0.0001547150468892835.91566813088766e-052.61534358361763
Trimmed Mean ( 9 / 16 )0.0001575741820561185.77838643207924e-052.72695818994262
Trimmed Mean ( 10 / 16 )0.0001580215261195895.59893945561428e-052.82234747084350
Trimmed Mean ( 11 / 16 )0.0001590339595092305.35140330850653e-052.97181786423071
Trimmed Mean ( 12 / 16 )0.0001598733002186455.07066233011466e-053.15290764421756
Trimmed Mean ( 13 / 16 )0.0001599696758185054.83856976545017e-053.30613556428946
Trimmed Mean ( 14 / 16 )0.0001642759338135524.71050741611042e-053.48743605098066
Trimmed Mean ( 15 / 16 )0.000169772140212864.50128138569125e-053.77164024343234
Trimmed Mean ( 16 / 16 )0.000169772140212864.28918609029246e-053.95814349480193
Median0.000226398087079409
Midrange-7.35e+08
Midmean - Weighted Average at Xnp0.000142289521415003
Midmean - Weighted Average at X(n+1)p0.000159873300218645
Midmean - Empirical Distribution Function0.000159873300218645
Midmean - Empirical Distribution Function - Averaging0.000159873300218645
Midmean - Empirical Distribution Function - Interpolation0.000159873300218645
Midmean - Closest Observation0.000140843831535612
Midmean - True Basic - Statistics Graphics Toolkit0.000159873300218645
Midmean - MS Excel (old versions)0.000159873300218645
Number of observations49

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -125786530.612149 & 328126520.248316 & -0.38334765052504 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 0.00182745670104634 &  &  \tabularnewline
Quadratic Mean & 2276804534.69689 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & -150072244.897863 & 310288462.533222 & -0.483653964032888 \tabularnewline
Winsorized Mean ( 2 / 16 ) & -122725306.122353 & 225728781.965764 & -0.543684793111437 \tabularnewline
Winsorized Mean ( 3 / 16 ) & -4072244.89786312 & 56647386.9107401 & -0.0718876036467453 \tabularnewline
Winsorized Mean ( 4 / 16 ) & 863265.306114534 & 369628.121141565 & 2.33549683246072 \tabularnewline
Winsorized Mean ( 5 / 16 ) & 0.000153799563986030 & 7.43935032510759e-05 & 2.06737896811985 \tabularnewline
Winsorized Mean ( 6 / 16 ) & 0.000146903204589726 & 6.8890750536241e-05 & 2.13240824706135 \tabularnewline
Winsorized Mean ( 7 / 16 ) & 0.000140746250242888 & 6.69361311453861e-05 & 2.10269473055121 \tabularnewline
Winsorized Mean ( 8 / 16 ) & 0.000158204203365772 & 5.98232265329196e-05 & 2.64452809610186 \tabularnewline
Winsorized Mean ( 9 / 16 ) & 0.000155191390207835 & 5.88398629899329e-05 & 2.63752127081579 \tabularnewline
Winsorized Mean ( 10 / 16 ) & 0.000152442811523605 & 5.79364703006638e-05 & 2.63120640129605 \tabularnewline
Winsorized Mean ( 11 / 16 ) & 0.000154323373895165 & 5.51485961823365e-05 & 2.79831916999173 \tabularnewline
Winsorized Mean ( 12 / 16 ) & 0.000159330449901069 & 4.98271875923081e-05 & 3.19766090762998 \tabularnewline
Winsorized Mean ( 13 / 16 ) & 0.000135977666988955 & 4.34311397826088e-05 & 3.13087954102934 \tabularnewline
Winsorized Mean ( 14 / 16 ) & 0.000134439384788738 & 4.23888892388716e-05 & 3.17157130565842 \tabularnewline
Winsorized Mean ( 15 / 16 ) & 0.000132081222993189 & 3.85653763508821e-05 & 3.42486539717556 \tabularnewline
Winsorized Mean ( 16 / 16 ) & 0.000121765864554723 & 3.67966601651488e-05 & 3.30915534203973 \tabularnewline
Trimmed Mean ( 1 / 16 ) & -125786530.612149 & 248987679.074756 & -0.505191787318853 \tabularnewline
Trimmed Mean ( 2 / 16 ) & -99862553.1913892 & 144529383.176791 & -0.690949833150781 \tabularnewline
Trimmed Mean ( 3 / 16 ) & -1012558.13942542 & 32324673.9053766 & -0.0313246203933707 \tabularnewline
Trimmed Mean ( 4 / 16 ) & -1012558.13942542 & 206341.463411764 & -4.9071966568581 \tabularnewline
Trimmed Mean ( 5 / 16 ) & 0.000153354905253626 & 6.74893988559656e-05 & 2.27228139312535 \tabularnewline
Trimmed Mean ( 6 / 16 ) & 0.000153237130778556 & 6.42402407456713e-05 & 2.38537603533004 \tabularnewline
Trimmed Mean ( 7 / 16 ) & 0.000154715046889283 & 6.18499787973128e-05 & 2.50145674902002 \tabularnewline
Trimmed Mean ( 8 / 16 ) & 0.000154715046889283 & 5.91566813088766e-05 & 2.61534358361763 \tabularnewline
Trimmed Mean ( 9 / 16 ) & 0.000157574182056118 & 5.77838643207924e-05 & 2.72695818994262 \tabularnewline
Trimmed Mean ( 10 / 16 ) & 0.000158021526119589 & 5.59893945561428e-05 & 2.82234747084350 \tabularnewline
Trimmed Mean ( 11 / 16 ) & 0.000159033959509230 & 5.35140330850653e-05 & 2.97181786423071 \tabularnewline
Trimmed Mean ( 12 / 16 ) & 0.000159873300218645 & 5.07066233011466e-05 & 3.15290764421756 \tabularnewline
Trimmed Mean ( 13 / 16 ) & 0.000159969675818505 & 4.83856976545017e-05 & 3.30613556428946 \tabularnewline
Trimmed Mean ( 14 / 16 ) & 0.000164275933813552 & 4.71050741611042e-05 & 3.48743605098066 \tabularnewline
Trimmed Mean ( 15 / 16 ) & 0.00016977214021286 & 4.50128138569125e-05 & 3.77164024343234 \tabularnewline
Trimmed Mean ( 16 / 16 ) & 0.00016977214021286 & 4.28918609029246e-05 & 3.95814349480193 \tabularnewline
Median & 0.000226398087079409 &  &  \tabularnewline
Midrange & -7.35e+08 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 0.000142289521415003 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 0.000159873300218645 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 0.000159873300218645 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 0.000159873300218645 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 0.000159873300218645 &  &  \tabularnewline
Midmean - Closest Observation & 0.000140843831535612 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 0.000159873300218645 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 0.000159873300218645 &  &  \tabularnewline
Number of observations & 49 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4826&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]-125786530.612149[/C][C]328126520.248316[/C][C]-0.38334765052504[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0.00182745670104634[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]2276804534.69689[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]-150072244.897863[/C][C]310288462.533222[/C][C]-0.483653964032888[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]-122725306.122353[/C][C]225728781.965764[/C][C]-0.543684793111437[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]-4072244.89786312[/C][C]56647386.9107401[/C][C]-0.0718876036467453[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]863265.306114534[/C][C]369628.121141565[/C][C]2.33549683246072[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]0.000153799563986030[/C][C]7.43935032510759e-05[/C][C]2.06737896811985[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]0.000146903204589726[/C][C]6.8890750536241e-05[/C][C]2.13240824706135[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]0.000140746250242888[/C][C]6.69361311453861e-05[/C][C]2.10269473055121[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]0.000158204203365772[/C][C]5.98232265329196e-05[/C][C]2.64452809610186[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]0.000155191390207835[/C][C]5.88398629899329e-05[/C][C]2.63752127081579[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]0.000152442811523605[/C][C]5.79364703006638e-05[/C][C]2.63120640129605[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]0.000154323373895165[/C][C]5.51485961823365e-05[/C][C]2.79831916999173[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]0.000159330449901069[/C][C]4.98271875923081e-05[/C][C]3.19766090762998[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]0.000135977666988955[/C][C]4.34311397826088e-05[/C][C]3.13087954102934[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]0.000134439384788738[/C][C]4.23888892388716e-05[/C][C]3.17157130565842[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]0.000132081222993189[/C][C]3.85653763508821e-05[/C][C]3.42486539717556[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]0.000121765864554723[/C][C]3.67966601651488e-05[/C][C]3.30915534203973[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]-125786530.612149[/C][C]248987679.074756[/C][C]-0.505191787318853[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]-99862553.1913892[/C][C]144529383.176791[/C][C]-0.690949833150781[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]-1012558.13942542[/C][C]32324673.9053766[/C][C]-0.0313246203933707[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]-1012558.13942542[/C][C]206341.463411764[/C][C]-4.9071966568581[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]0.000153354905253626[/C][C]6.74893988559656e-05[/C][C]2.27228139312535[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]0.000153237130778556[/C][C]6.42402407456713e-05[/C][C]2.38537603533004[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]0.000154715046889283[/C][C]6.18499787973128e-05[/C][C]2.50145674902002[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]0.000154715046889283[/C][C]5.91566813088766e-05[/C][C]2.61534358361763[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]0.000157574182056118[/C][C]5.77838643207924e-05[/C][C]2.72695818994262[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]0.000158021526119589[/C][C]5.59893945561428e-05[/C][C]2.82234747084350[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]0.000159033959509230[/C][C]5.35140330850653e-05[/C][C]2.97181786423071[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]0.000159873300218645[/C][C]5.07066233011466e-05[/C][C]3.15290764421756[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]0.000159969675818505[/C][C]4.83856976545017e-05[/C][C]3.30613556428946[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]0.000164275933813552[/C][C]4.71050741611042e-05[/C][C]3.48743605098066[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]0.00016977214021286[/C][C]4.50128138569125e-05[/C][C]3.77164024343234[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]0.00016977214021286[/C][C]4.28918609029246e-05[/C][C]3.95814349480193[/C][/ROW]
[ROW][C]Median[/C][C]0.000226398087079409[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]-7.35e+08[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]0.000142289521415003[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]0.000159873300218645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]0.000159873300218645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]0.000159873300218645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]0.000159873300218645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]0.000140843831535612[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]0.000159873300218645[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]0.000159873300218645[/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=4826&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4826&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-125786530.612149328126520.248316-0.38334765052504
Geometric MeanNaN
Harmonic Mean0.00182745670104634
Quadratic Mean2276804534.69689
Winsorized Mean ( 1 / 16 )-150072244.897863310288462.533222-0.483653964032888
Winsorized Mean ( 2 / 16 )-122725306.122353225728781.965764-0.543684793111437
Winsorized Mean ( 3 / 16 )-4072244.8978631256647386.9107401-0.0718876036467453
Winsorized Mean ( 4 / 16 )863265.306114534369628.1211415652.33549683246072
Winsorized Mean ( 5 / 16 )0.0001537995639860307.43935032510759e-052.06737896811985
Winsorized Mean ( 6 / 16 )0.0001469032045897266.8890750536241e-052.13240824706135
Winsorized Mean ( 7 / 16 )0.0001407462502428886.69361311453861e-052.10269473055121
Winsorized Mean ( 8 / 16 )0.0001582042033657725.98232265329196e-052.64452809610186
Winsorized Mean ( 9 / 16 )0.0001551913902078355.88398629899329e-052.63752127081579
Winsorized Mean ( 10 / 16 )0.0001524428115236055.79364703006638e-052.63120640129605
Winsorized Mean ( 11 / 16 )0.0001543233738951655.51485961823365e-052.79831916999173
Winsorized Mean ( 12 / 16 )0.0001593304499010694.98271875923081e-053.19766090762998
Winsorized Mean ( 13 / 16 )0.0001359776669889554.34311397826088e-053.13087954102934
Winsorized Mean ( 14 / 16 )0.0001344393847887384.23888892388716e-053.17157130565842
Winsorized Mean ( 15 / 16 )0.0001320812229931893.85653763508821e-053.42486539717556
Winsorized Mean ( 16 / 16 )0.0001217658645547233.67966601651488e-053.30915534203973
Trimmed Mean ( 1 / 16 )-125786530.612149248987679.074756-0.505191787318853
Trimmed Mean ( 2 / 16 )-99862553.1913892144529383.176791-0.690949833150781
Trimmed Mean ( 3 / 16 )-1012558.1394254232324673.9053766-0.0313246203933707
Trimmed Mean ( 4 / 16 )-1012558.13942542206341.463411764-4.9071966568581
Trimmed Mean ( 5 / 16 )0.0001533549052536266.74893988559656e-052.27228139312535
Trimmed Mean ( 6 / 16 )0.0001532371307785566.42402407456713e-052.38537603533004
Trimmed Mean ( 7 / 16 )0.0001547150468892836.18499787973128e-052.50145674902002
Trimmed Mean ( 8 / 16 )0.0001547150468892835.91566813088766e-052.61534358361763
Trimmed Mean ( 9 / 16 )0.0001575741820561185.77838643207924e-052.72695818994262
Trimmed Mean ( 10 / 16 )0.0001580215261195895.59893945561428e-052.82234747084350
Trimmed Mean ( 11 / 16 )0.0001590339595092305.35140330850653e-052.97181786423071
Trimmed Mean ( 12 / 16 )0.0001598733002186455.07066233011466e-053.15290764421756
Trimmed Mean ( 13 / 16 )0.0001599696758185054.83856976545017e-053.30613556428946
Trimmed Mean ( 14 / 16 )0.0001642759338135524.71050741611042e-053.48743605098066
Trimmed Mean ( 15 / 16 )0.000169772140212864.50128138569125e-053.77164024343234
Trimmed Mean ( 16 / 16 )0.000169772140212864.28918609029246e-053.95814349480193
Median0.000226398087079409
Midrange-7.35e+08
Midmean - Weighted Average at Xnp0.000142289521415003
Midmean - Weighted Average at X(n+1)p0.000159873300218645
Midmean - Empirical Distribution Function0.000159873300218645
Midmean - Empirical Distribution Function - Averaging0.000159873300218645
Midmean - Empirical Distribution Function - Interpolation0.000159873300218645
Midmean - Closest Observation0.000140843831535612
Midmean - True Basic - Statistics Graphics Toolkit0.000159873300218645
Midmean - MS Excel (old versions)0.000159873300218645
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')