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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 11:52:37 -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/t1261162430pie0bs75upj931t.htm/, Retrieved Sat, 27 Apr 2024 10:32:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69441, Retrieved Sat, 27 Apr 2024 10:32:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Totaal levensmidd...] [2009-11-29 09:56:44] [757146c69eaf0537be37c7b0c18216d8]
- RMPD  [ARIMA Backward Selection] [arima backwards p...] [2009-12-10 13:12:43] [757146c69eaf0537be37c7b0c18216d8]
- RMPD    [Central Tendency] [central tendency ...] [2009-12-10 15:49:24] [757146c69eaf0537be37c7b0c18216d8]
-    D        [Central Tendency] [central tendency ...] [2009-12-18 18:52:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
9.24213940292237e-06 
-5.01436247120433e-05 
-0.000107628855262499 
7.89437033465196e-05 
-1.03999760701062e-05 
-0.000511730436151787 
0.000463858746270277 
-0.000138911847509148 
-0.000135732966869185 
-0.000348969538818215 
0.000435277890219176 
-0.000142107922504690 
-8.93489759523983e-06 
0.000363808701421896 
-0.000469078513096003 
-0.00015889491567783 
-0.000442633184117679 
6.38107302816139e-06 
-0.000194163665146138 
-0.00045116843316107 
0.000243326557885233 
-0.000318234693021503 
0.000493984555653654 
-0.00036621158276608 
-0.000819049116082925 
-0.000252856913737942 
-8.09481427817768e-05 
1.65184118488919e-06 
-0.000155704261745119 
4.71460516281883e-05 
0.000346616740328420 
-0.000155128332265254 
-0.000376010452074696 
0.000286587173792775 
-0.000249105277994040 
-0.00064903882504374 
3.7432734785646e-05 
2.4540539848893e-06 
-0.000542823158273806 
-0.000132368069829196 
-0.000355077086932987 
-0.000172685691937221 
-5.7506123644475e-05 
7.64745770715563e-05 
-0.000182852720970503 
0.000213405860479219 
0.000296051528097605 
7.9556637817437e-05 
0.000953832263301986 
0.000286566258669741 
6.38643803455019e-05 
-0.000419682809513409 
0.000319807750998863 
-0.000126403312603000 
2.97700554380909e-05 
-0.000366183820098218 
6.951813747686e-05 
0.000661175568042886 
8.7933125346198e-05 
0.000233061814792656 
-0.000513744335922 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69441&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69441&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69441&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-5.36784193953816e-054.21688497310258e-05-1.27294009055902
Geometric MeanNaN
Harmonic Mean5.55468572026654e-05
Quadratic Mean0.000331019766731621
Winsorized Mean ( 1 / 20 )-5.5689016185872e-053.97141737136724e-05-1.40224536930753
Winsorized Mean ( 2 / 20 )-5.76882078455211e-053.73995157572999e-05-1.54248542200071
Winsorized Mean ( 3 / 20 )-5.77396990110082e-053.67394750793927e-05-1.57159836623237
Winsorized Mean ( 4 / 20 )-5.94817945048369e-053.62773084649358e-05-1.63964188694786
Winsorized Mean ( 5 / 20 )-6.18438654672546e-053.4294286991382e-05-1.80332851016251
Winsorized Mean ( 6 / 20 )-6.17732308271113e-053.36036034902944e-05-1.83829186191157
Winsorized Mean ( 7 / 20 )-6.38702174173271e-053.28032018864292e-05-1.94707265584798
Winsorized Mean ( 8 / 20 )-6.39759024398829e-053.16320688676126e-05-2.02250136428435
Winsorized Mean ( 9 / 20 )-5.89288200102936e-053.01979503309096e-05-1.95141787321824
Winsorized Mean ( 10 / 20 )-5.73258767011818e-052.99185204780159e-05-1.91606656296072
Winsorized Mean ( 11 / 20 )-6.51181934107409e-052.8465633354225e-05-2.28760739662502
Winsorized Mean ( 12 / 20 )-6.49525560193992e-052.77191895224561e-05-2.34323431306602
Winsorized Mean ( 13 / 20 )-6.78399212748523e-052.67491909856053e-05-2.53614852543987
Winsorized Mean ( 14 / 20 )-8.95830434176118e-052.08663324958961e-05-4.29318585023174
Winsorized Mean ( 15 / 20 )-7.55663323303659e-051.77543097731056e-05-4.25622473056286
Winsorized Mean ( 16 / 20 )-7.47430664226978e-051.75676050416113e-05-4.25459624380549
Winsorized Mean ( 17 / 20 )-6.01195865581083e-051.50528539312105e-05-3.99389955106497
Winsorized Mean ( 18 / 20 )-5.88346507801264e-051.42537247892068e-05-4.12766849719711
Winsorized Mean ( 19 / 20 )-5.74288775647731e-051.35356080699266e-05-4.24279997382375
Winsorized Mean ( 20 / 20 )-5.83887308296657e-051.20925837628047e-05-4.82847437528299
Trimmed Mean ( 1 / 20 )-5.77824869548701e-053.78652740695366e-05-1.52600207907533
Trimmed Mean ( 2 / 20 )-6.00228679532716e-053.55745045252612e-05-1.68724396177183
Trimmed Mean ( 3 / 20 )-6.13175431039333e-053.43261652430372e-05-1.78632080425503
Trimmed Mean ( 4 / 20 )-6.26901751144266e-053.30967503315786e-05-1.89414895681199
Trimmed Mean ( 5 / 20 )-6.36495438261176e-053.17419250578896e-05-2.0052200271419
Trimmed Mean ( 6 / 20 )-6.40991208868957e-053.07374559742725e-05-2.08537495557691
Trimmed Mean ( 7 / 20 )-6.46022389494732e-052.96731098402718e-05-2.17713071859412
Trimmed Mean ( 8 / 20 )-6.47439955001428e-052.85415477197032e-05-2.26841221562234
Trimmed Mean ( 9 / 20 )-6.48801980486191e-052.74092858414136e-05-2.36708823513342
Trimmed Mean ( 10 / 20 )-6.58640301904561e-052.63237430028452e-05-2.50207693424667
Trimmed Mean ( 11 / 20 )-6.71994849669836e-052.49417049883769e-05-2.69426187978325
Trimmed Mean ( 12 / 20 )-6.75114230134967e-052.35082523318024e-05-2.8718180348169
Trimmed Mean ( 13 / 20 )-6.7883067981687e-052.17524383476356e-05-3.12071074041525
Trimmed Mean ( 14 / 20 )-6.78892030612136e-051.95822260293758e-05-3.46687873786009
Trimmed Mean ( 15 / 20 )-6.48400688175724e-051.84826527315077e-05-3.50815815021176
Trimmed Mean ( 16 / 20 )-6.33359261180772e-051.79431747586489e-05-3.52980601092058
Trimmed Mean ( 17 / 20 )-6.1725195658397e-051.71554693920407e-05-3.59798932036418
Trimmed Mean ( 18 / 20 )-6.19556477880855e-051.68307881680927e-05-3.68109010518824
Trimmed Mean ( 19 / 20 )-6.24155048351519e-051.65179825307245e-05-3.77863971699055
Trimmed Mean ( 20 / 20 )-6.31778714103226e-051.61791022692645e-05-3.90490586924231
Median-5.7506123644475e-05
Midrange6.73915736095305e-05
Midmean - Weighted Average at Xnp-6.96532923720727e-05
Midmean - Weighted Average at X(n+1)p-6.48400688175724e-05
Midmean - Empirical Distribution Function-6.48400688175724e-05
Midmean - Empirical Distribution Function - Averaging-6.48400688175724e-05
Midmean - Empirical Distribution Function - Interpolation-6.48400688175724e-05
Midmean - Closest Observation-7.27586508239452e-05
Midmean - True Basic - Statistics Graphics Toolkit-6.48400688175724e-05
Midmean - MS Excel (old versions)-6.48400688175724e-05
Number of observations61

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -5.36784193953816e-05 & 4.21688497310258e-05 & -1.27294009055902 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & 5.55468572026654e-05 &  &  \tabularnewline
Quadratic Mean & 0.000331019766731621 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & -5.5689016185872e-05 & 3.97141737136724e-05 & -1.40224536930753 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -5.76882078455211e-05 & 3.73995157572999e-05 & -1.54248542200071 \tabularnewline
Winsorized Mean ( 3 / 20 ) & -5.77396990110082e-05 & 3.67394750793927e-05 & -1.57159836623237 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -5.94817945048369e-05 & 3.62773084649358e-05 & -1.63964188694786 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -6.18438654672546e-05 & 3.4294286991382e-05 & -1.80332851016251 \tabularnewline
Winsorized Mean ( 6 / 20 ) & -6.17732308271113e-05 & 3.36036034902944e-05 & -1.83829186191157 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -6.38702174173271e-05 & 3.28032018864292e-05 & -1.94707265584798 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -6.39759024398829e-05 & 3.16320688676126e-05 & -2.02250136428435 \tabularnewline
Winsorized Mean ( 9 / 20 ) & -5.89288200102936e-05 & 3.01979503309096e-05 & -1.95141787321824 \tabularnewline
Winsorized Mean ( 10 / 20 ) & -5.73258767011818e-05 & 2.99185204780159e-05 & -1.91606656296072 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -6.51181934107409e-05 & 2.8465633354225e-05 & -2.28760739662502 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -6.49525560193992e-05 & 2.77191895224561e-05 & -2.34323431306602 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -6.78399212748523e-05 & 2.67491909856053e-05 & -2.53614852543987 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -8.95830434176118e-05 & 2.08663324958961e-05 & -4.29318585023174 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -7.55663323303659e-05 & 1.77543097731056e-05 & -4.25622473056286 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -7.47430664226978e-05 & 1.75676050416113e-05 & -4.25459624380549 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -6.01195865581083e-05 & 1.50528539312105e-05 & -3.99389955106497 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -5.88346507801264e-05 & 1.42537247892068e-05 & -4.12766849719711 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -5.74288775647731e-05 & 1.35356080699266e-05 & -4.24279997382375 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -5.83887308296657e-05 & 1.20925837628047e-05 & -4.82847437528299 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -5.77824869548701e-05 & 3.78652740695366e-05 & -1.52600207907533 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -6.00228679532716e-05 & 3.55745045252612e-05 & -1.68724396177183 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -6.13175431039333e-05 & 3.43261652430372e-05 & -1.78632080425503 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -6.26901751144266e-05 & 3.30967503315786e-05 & -1.89414895681199 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -6.36495438261176e-05 & 3.17419250578896e-05 & -2.0052200271419 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -6.40991208868957e-05 & 3.07374559742725e-05 & -2.08537495557691 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -6.46022389494732e-05 & 2.96731098402718e-05 & -2.17713071859412 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -6.47439955001428e-05 & 2.85415477197032e-05 & -2.26841221562234 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -6.48801980486191e-05 & 2.74092858414136e-05 & -2.36708823513342 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -6.58640301904561e-05 & 2.63237430028452e-05 & -2.50207693424667 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -6.71994849669836e-05 & 2.49417049883769e-05 & -2.69426187978325 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -6.75114230134967e-05 & 2.35082523318024e-05 & -2.8718180348169 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -6.7883067981687e-05 & 2.17524383476356e-05 & -3.12071074041525 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -6.78892030612136e-05 & 1.95822260293758e-05 & -3.46687873786009 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -6.48400688175724e-05 & 1.84826527315077e-05 & -3.50815815021176 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -6.33359261180772e-05 & 1.79431747586489e-05 & -3.52980601092058 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -6.1725195658397e-05 & 1.71554693920407e-05 & -3.59798932036418 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -6.19556477880855e-05 & 1.68307881680927e-05 & -3.68109010518824 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -6.24155048351519e-05 & 1.65179825307245e-05 & -3.77863971699055 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -6.31778714103226e-05 & 1.61791022692645e-05 & -3.90490586924231 \tabularnewline
Median & -5.7506123644475e-05 &  &  \tabularnewline
Midrange & 6.73915736095305e-05 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -6.96532923720727e-05 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -6.48400688175724e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -6.48400688175724e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -6.48400688175724e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -6.48400688175724e-05 &  &  \tabularnewline
Midmean - Closest Observation & -7.27586508239452e-05 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -6.48400688175724e-05 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -6.48400688175724e-05 &  &  \tabularnewline
Number of observations & 61 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69441&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]-5.36784193953816e-05[/C][C]4.21688497310258e-05[/C][C]-1.27294009055902[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]5.55468572026654e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]0.000331019766731621[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]-5.5689016185872e-05[/C][C]3.97141737136724e-05[/C][C]-1.40224536930753[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-5.76882078455211e-05[/C][C]3.73995157572999e-05[/C][C]-1.54248542200071[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]-5.77396990110082e-05[/C][C]3.67394750793927e-05[/C][C]-1.57159836623237[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-5.94817945048369e-05[/C][C]3.62773084649358e-05[/C][C]-1.63964188694786[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-6.18438654672546e-05[/C][C]3.4294286991382e-05[/C][C]-1.80332851016251[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]-6.17732308271113e-05[/C][C]3.36036034902944e-05[/C][C]-1.83829186191157[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-6.38702174173271e-05[/C][C]3.28032018864292e-05[/C][C]-1.94707265584798[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-6.39759024398829e-05[/C][C]3.16320688676126e-05[/C][C]-2.02250136428435[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]-5.89288200102936e-05[/C][C]3.01979503309096e-05[/C][C]-1.95141787321824[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]-5.73258767011818e-05[/C][C]2.99185204780159e-05[/C][C]-1.91606656296072[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-6.51181934107409e-05[/C][C]2.8465633354225e-05[/C][C]-2.28760739662502[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-6.49525560193992e-05[/C][C]2.77191895224561e-05[/C][C]-2.34323431306602[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-6.78399212748523e-05[/C][C]2.67491909856053e-05[/C][C]-2.53614852543987[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-8.95830434176118e-05[/C][C]2.08663324958961e-05[/C][C]-4.29318585023174[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-7.55663323303659e-05[/C][C]1.77543097731056e-05[/C][C]-4.25622473056286[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-7.47430664226978e-05[/C][C]1.75676050416113e-05[/C][C]-4.25459624380549[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-6.01195865581083e-05[/C][C]1.50528539312105e-05[/C][C]-3.99389955106497[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-5.88346507801264e-05[/C][C]1.42537247892068e-05[/C][C]-4.12766849719711[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-5.74288775647731e-05[/C][C]1.35356080699266e-05[/C][C]-4.24279997382375[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-5.83887308296657e-05[/C][C]1.20925837628047e-05[/C][C]-4.82847437528299[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-5.77824869548701e-05[/C][C]3.78652740695366e-05[/C][C]-1.52600207907533[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-6.00228679532716e-05[/C][C]3.55745045252612e-05[/C][C]-1.68724396177183[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-6.13175431039333e-05[/C][C]3.43261652430372e-05[/C][C]-1.78632080425503[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-6.26901751144266e-05[/C][C]3.30967503315786e-05[/C][C]-1.89414895681199[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-6.36495438261176e-05[/C][C]3.17419250578896e-05[/C][C]-2.0052200271419[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-6.40991208868957e-05[/C][C]3.07374559742725e-05[/C][C]-2.08537495557691[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-6.46022389494732e-05[/C][C]2.96731098402718e-05[/C][C]-2.17713071859412[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-6.47439955001428e-05[/C][C]2.85415477197032e-05[/C][C]-2.26841221562234[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-6.48801980486191e-05[/C][C]2.74092858414136e-05[/C][C]-2.36708823513342[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-6.58640301904561e-05[/C][C]2.63237430028452e-05[/C][C]-2.50207693424667[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-6.71994849669836e-05[/C][C]2.49417049883769e-05[/C][C]-2.69426187978325[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-6.75114230134967e-05[/C][C]2.35082523318024e-05[/C][C]-2.8718180348169[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-6.7883067981687e-05[/C][C]2.17524383476356e-05[/C][C]-3.12071074041525[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-6.78892030612136e-05[/C][C]1.95822260293758e-05[/C][C]-3.46687873786009[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-6.48400688175724e-05[/C][C]1.84826527315077e-05[/C][C]-3.50815815021176[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-6.33359261180772e-05[/C][C]1.79431747586489e-05[/C][C]-3.52980601092058[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-6.1725195658397e-05[/C][C]1.71554693920407e-05[/C][C]-3.59798932036418[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-6.19556477880855e-05[/C][C]1.68307881680927e-05[/C][C]-3.68109010518824[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-6.24155048351519e-05[/C][C]1.65179825307245e-05[/C][C]-3.77863971699055[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-6.31778714103226e-05[/C][C]1.61791022692645e-05[/C][C]-3.90490586924231[/C][/ROW]
[ROW][C]Median[/C][C]-5.7506123644475e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]6.73915736095305e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-6.96532923720727e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-6.48400688175724e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-6.48400688175724e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-6.48400688175724e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-6.48400688175724e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-7.27586508239452e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-6.48400688175724e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-6.48400688175724e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]61[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69441&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69441&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-5.36784193953816e-054.21688497310258e-05-1.27294009055902
Geometric MeanNaN
Harmonic Mean5.55468572026654e-05
Quadratic Mean0.000331019766731621
Winsorized Mean ( 1 / 20 )-5.5689016185872e-053.97141737136724e-05-1.40224536930753
Winsorized Mean ( 2 / 20 )-5.76882078455211e-053.73995157572999e-05-1.54248542200071
Winsorized Mean ( 3 / 20 )-5.77396990110082e-053.67394750793927e-05-1.57159836623237
Winsorized Mean ( 4 / 20 )-5.94817945048369e-053.62773084649358e-05-1.63964188694786
Winsorized Mean ( 5 / 20 )-6.18438654672546e-053.4294286991382e-05-1.80332851016251
Winsorized Mean ( 6 / 20 )-6.17732308271113e-053.36036034902944e-05-1.83829186191157
Winsorized Mean ( 7 / 20 )-6.38702174173271e-053.28032018864292e-05-1.94707265584798
Winsorized Mean ( 8 / 20 )-6.39759024398829e-053.16320688676126e-05-2.02250136428435
Winsorized Mean ( 9 / 20 )-5.89288200102936e-053.01979503309096e-05-1.95141787321824
Winsorized Mean ( 10 / 20 )-5.73258767011818e-052.99185204780159e-05-1.91606656296072
Winsorized Mean ( 11 / 20 )-6.51181934107409e-052.8465633354225e-05-2.28760739662502
Winsorized Mean ( 12 / 20 )-6.49525560193992e-052.77191895224561e-05-2.34323431306602
Winsorized Mean ( 13 / 20 )-6.78399212748523e-052.67491909856053e-05-2.53614852543987
Winsorized Mean ( 14 / 20 )-8.95830434176118e-052.08663324958961e-05-4.29318585023174
Winsorized Mean ( 15 / 20 )-7.55663323303659e-051.77543097731056e-05-4.25622473056286
Winsorized Mean ( 16 / 20 )-7.47430664226978e-051.75676050416113e-05-4.25459624380549
Winsorized Mean ( 17 / 20 )-6.01195865581083e-051.50528539312105e-05-3.99389955106497
Winsorized Mean ( 18 / 20 )-5.88346507801264e-051.42537247892068e-05-4.12766849719711
Winsorized Mean ( 19 / 20 )-5.74288775647731e-051.35356080699266e-05-4.24279997382375
Winsorized Mean ( 20 / 20 )-5.83887308296657e-051.20925837628047e-05-4.82847437528299
Trimmed Mean ( 1 / 20 )-5.77824869548701e-053.78652740695366e-05-1.52600207907533
Trimmed Mean ( 2 / 20 )-6.00228679532716e-053.55745045252612e-05-1.68724396177183
Trimmed Mean ( 3 / 20 )-6.13175431039333e-053.43261652430372e-05-1.78632080425503
Trimmed Mean ( 4 / 20 )-6.26901751144266e-053.30967503315786e-05-1.89414895681199
Trimmed Mean ( 5 / 20 )-6.36495438261176e-053.17419250578896e-05-2.0052200271419
Trimmed Mean ( 6 / 20 )-6.40991208868957e-053.07374559742725e-05-2.08537495557691
Trimmed Mean ( 7 / 20 )-6.46022389494732e-052.96731098402718e-05-2.17713071859412
Trimmed Mean ( 8 / 20 )-6.47439955001428e-052.85415477197032e-05-2.26841221562234
Trimmed Mean ( 9 / 20 )-6.48801980486191e-052.74092858414136e-05-2.36708823513342
Trimmed Mean ( 10 / 20 )-6.58640301904561e-052.63237430028452e-05-2.50207693424667
Trimmed Mean ( 11 / 20 )-6.71994849669836e-052.49417049883769e-05-2.69426187978325
Trimmed Mean ( 12 / 20 )-6.75114230134967e-052.35082523318024e-05-2.8718180348169
Trimmed Mean ( 13 / 20 )-6.7883067981687e-052.17524383476356e-05-3.12071074041525
Trimmed Mean ( 14 / 20 )-6.78892030612136e-051.95822260293758e-05-3.46687873786009
Trimmed Mean ( 15 / 20 )-6.48400688175724e-051.84826527315077e-05-3.50815815021176
Trimmed Mean ( 16 / 20 )-6.33359261180772e-051.79431747586489e-05-3.52980601092058
Trimmed Mean ( 17 / 20 )-6.1725195658397e-051.71554693920407e-05-3.59798932036418
Trimmed Mean ( 18 / 20 )-6.19556477880855e-051.68307881680927e-05-3.68109010518824
Trimmed Mean ( 19 / 20 )-6.24155048351519e-051.65179825307245e-05-3.77863971699055
Trimmed Mean ( 20 / 20 )-6.31778714103226e-051.61791022692645e-05-3.90490586924231
Median-5.7506123644475e-05
Midrange6.73915736095305e-05
Midmean - Weighted Average at Xnp-6.96532923720727e-05
Midmean - Weighted Average at X(n+1)p-6.48400688175724e-05
Midmean - Empirical Distribution Function-6.48400688175724e-05
Midmean - Empirical Distribution Function - Averaging-6.48400688175724e-05
Midmean - Empirical Distribution Function - Interpolation-6.48400688175724e-05
Midmean - Closest Observation-7.27586508239452e-05
Midmean - True Basic - Statistics Graphics Toolkit-6.48400688175724e-05
Midmean - MS Excel (old versions)-6.48400688175724e-05
Number of observations61



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')