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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 computationThu, 10 Dec 2009 08:49:24 -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/10/t12604602282zm2eo3axrefj2f.htm/, Retrieved Fri, 19 Apr 2024 07:26:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65507, Retrieved Fri, 19 Apr 2024 07:26:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
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] [a931a0a30926b49d162330b43e89b999] [Current]
-    D        [Central Tendency] [central tendency ...] [2009-12-18 18:52:37] [74be16979710d4c4e7c6647856088456]
-             [Central Tendency] [central tendency-...] [2009-12-21 15:07:17] [03c44f58d7d4de05d4cfabfda8c46d2c]
-   P         [Central Tendency] [central tendency ] [2009-12-21 15:34:04] [12f02da0296cb21dc23d82ae014a8b71]
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Dataseries X:
9.21658481064732e-06
-0.00029788936701127
-0.000237595445619398
0.000176386639516741
-0.000354517420077153
-0.000704448564633498
0.000513049322447122
-0.000153768338800356
-0.000165495788075780
0.000140072526121174
0.000346620687208592
0.000161916908058288
-0.000165099254299721
-1.69432824053433e-06
-0.000354149939969856
-0.000342774975550734
-4.96908925173395e-06
0.000111232688614015
-5.71770531287065e-05
-0.000121692129730065
0.000224672210051711
-0.000246864010604340
0.000322726843768265
-4.30529292240296e-05
-0.000418419406504748
-0.000378004975610374
-3.24021390863647e-05
-2.7363752224343e-05
-0.000183622849538695
9.90770631009303e-05
0.000173737572911515
-0.000202839888158976
-0.000286608152931299
4.11099519259386e-05
3.30589617581101e-05
-0.00050937217008082
-1.86226730255005e-05
-0.000118364395817495
-0.000351397442503670
-0.000205285906638802
-0.000344501241171445
4.54893857804128e-05
0.000109739140624292
-2.35892220696581e-05
-0.000303095753286898
0.000127032893461342
0.000362429017832127
9.35340989467158e-05
0.00092306316611607
-2.51463122583867e-05
-4.81959851185288e-06
-0.000551396477544085
0.000275472153350846
4.66854128330299e-05
-0.000300923258584334
-0.000370178149715601
7.01982462032013e-06
0.00042811187175734
-0.000220158172407577
0.000276271760846798
-0.000249130118572832




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65507&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]3 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=65507&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65507&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean-5.45689180983375e-053.61690667128068e-05-1.50871789232581
Geometric MeanNaN
Harmonic Mean-6.74243809774903e-05
Quadratic Mean0.000285429238227185
Winsorized Mean ( 1 / 20 )-5.87814059111168e-053.29673404849238e-05-1.78301934722329
Winsorized Mean ( 2 / 20 )-6.01883942136255e-053.18749612007567e-05-1.88826564633424
Winsorized Mean ( 3 / 20 )-5.894561177178e-053.01123083702865e-05-1.95752550906874
Winsorized Mean ( 4 / 20 )-5.73320969999217e-052.93675126483139e-05-1.95222856244223
Winsorized Mean ( 5 / 20 )-5.86490656511966e-052.88107004595516e-05-2.03566955039973
Winsorized Mean ( 6 / 20 )-6.16780184331329e-052.75637340501096e-05-2.23765104978176
Winsorized Mean ( 7 / 20 )-6.1727606821995e-052.75375304983576e-05-2.24158106064291
Winsorized Mean ( 8 / 20 )-6.80289111935293e-052.61707544869581e-05-2.59942491254621
Winsorized Mean ( 9 / 20 )-7.41355394365572e-052.47187906739629e-05-2.99915721664517
Winsorized Mean ( 10 / 20 )-7.42868182864777e-052.45940774430600e-05-3.02051656373231
Winsorized Mean ( 11 / 20 )-6.92631439993187e-052.29769479668386e-05-3.01446232542644
Winsorized Mean ( 12 / 20 )-7.31330234552958e-052.21996558869410e-05-3.29433139989871
Winsorized Mean ( 13 / 20 )-7.52653945065742e-052.16500965561174e-05-3.47644613553963
Winsorized Mean ( 14 / 20 )-7.63025399285903e-052.06514911772830e-05-3.69477144645732
Winsorized Mean ( 15 / 20 )-6.74538957395549e-051.90799299707527e-05-3.53533245892169
Winsorized Mean ( 16 / 20 )-6.96561172621437e-051.85570678404221e-05-3.75361656599729
Winsorized Mean ( 17 / 20 )-6.86178350634164e-051.79148615287793e-05-3.83021855643067
Winsorized Mean ( 18 / 20 )-7.72966126410159e-051.51087265087535e-05-5.11602434501894
Winsorized Mean ( 19 / 20 )-7.30368005818847e-051.43362402958805e-05-5.09455750423433
Winsorized Mean ( 20 / 20 )-7.36707072620972e-051.40160717559334e-05-5.25615939650926
Trimmed Mean ( 1 / 20 )-6.01240441606977e-053.15584320829115e-05-1.90516575737152
Trimmed Mean ( 2 / 20 )-6.15609026383193e-052.98182376508132e-05-2.06453860081300
Trimmed Mean ( 3 / 20 )-6.23220209465585e-052.84134228247542e-05-2.19340068005684
Trimmed Mean ( 4 / 20 )-6.3617372894115e-052.75409734893860e-05-2.30991736434561
Trimmed Mean ( 5 / 20 )-6.54967936271827e-052.67385703222047e-05-2.44952489373718
Trimmed Mean ( 6 / 20 )-6.72017381436526e-052.59138638760297e-05-2.59327356449588
Trimmed Mean ( 7 / 20 )-6.83965853150771e-052.52539663804341e-05-2.70835021654533
Trimmed Mean ( 8 / 20 )-6.96880382931025e-052.44005657947030e-05-2.85600091733244
Trimmed Mean ( 9 / 20 )-6.99822439706431e-052.36818101201624e-05-2.95510535789075
Trimmed Mean ( 10 / 20 )-6.92956558312915e-052.31218665602290e-05-2.99697499121824
Trimmed Mean ( 11 / 20 )-6.85149868318906e-052.23893005219065e-05-3.0601664739304
Trimmed Mean ( 12 / 20 )-6.84028551679763e-052.18301292848066e-05-3.13341502817317
Trimmed Mean ( 13 / 20 )-6.77158545357703e-052.12473708080215e-05-3.18702276849264
Trimmed Mean ( 14 / 20 )-6.66423768243041e-052.05576025404489e-05-3.24173875300777
Trimmed Mean ( 15 / 20 )-6.52846119640242e-051.98434689725479e-05-3.28997979407436
Trimmed Mean ( 16 / 20 )-6.49804135495245e-051.92777426208107e-05-3.37074806047969
Trimmed Mean ( 17 / 20 )-6.43201868678815e-051.85575411049552e-05-3.46598649595377
Trimmed Mean ( 18 / 20 )-6.37033479504047e-051.76448573180922e-05-3.61030677675621
Trimmed Mean ( 19 / 20 )-6.1700475616764e-051.72202965788766e-05-3.58300888339225
Trimmed Mean ( 20 / 20 )-5.99673532536753e-051.67530394153573e-05-3.57949096679758
Median-2.7363752224343e-05
Midrange0.000109307300741286
Midmean - Weighted Average at Xnp-7.11187370503014e-05
Midmean - Weighted Average at X(n+1)p-6.52846119640242e-05
Midmean - Empirical Distribution Function-6.52846119640242e-05
Midmean - Empirical Distribution Function - Averaging-6.52846119640242e-05
Midmean - Empirical Distribution Function - Interpolation-6.52846119640242e-05
Midmean - Closest Observation-7.22009726192516e-05
Midmean - True Basic - Statistics Graphics Toolkit-6.52846119640242e-05
Midmean - MS Excel (old versions)-6.52846119640242e-05
Number of observations61

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & -5.45689180983375e-05 & 3.61690667128068e-05 & -1.50871789232581 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -6.74243809774903e-05 &  &  \tabularnewline
Quadratic Mean & 0.000285429238227185 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & -5.87814059111168e-05 & 3.29673404849238e-05 & -1.78301934722329 \tabularnewline
Winsorized Mean ( 2 / 20 ) & -6.01883942136255e-05 & 3.18749612007567e-05 & -1.88826564633424 \tabularnewline
Winsorized Mean ( 3 / 20 ) & -5.894561177178e-05 & 3.01123083702865e-05 & -1.95752550906874 \tabularnewline
Winsorized Mean ( 4 / 20 ) & -5.73320969999217e-05 & 2.93675126483139e-05 & -1.95222856244223 \tabularnewline
Winsorized Mean ( 5 / 20 ) & -5.86490656511966e-05 & 2.88107004595516e-05 & -2.03566955039973 \tabularnewline
Winsorized Mean ( 6 / 20 ) & -6.16780184331329e-05 & 2.75637340501096e-05 & -2.23765104978176 \tabularnewline
Winsorized Mean ( 7 / 20 ) & -6.1727606821995e-05 & 2.75375304983576e-05 & -2.24158106064291 \tabularnewline
Winsorized Mean ( 8 / 20 ) & -6.80289111935293e-05 & 2.61707544869581e-05 & -2.59942491254621 \tabularnewline
Winsorized Mean ( 9 / 20 ) & -7.41355394365572e-05 & 2.47187906739629e-05 & -2.99915721664517 \tabularnewline
Winsorized Mean ( 10 / 20 ) & -7.42868182864777e-05 & 2.45940774430600e-05 & -3.02051656373231 \tabularnewline
Winsorized Mean ( 11 / 20 ) & -6.92631439993187e-05 & 2.29769479668386e-05 & -3.01446232542644 \tabularnewline
Winsorized Mean ( 12 / 20 ) & -7.31330234552958e-05 & 2.21996558869410e-05 & -3.29433139989871 \tabularnewline
Winsorized Mean ( 13 / 20 ) & -7.52653945065742e-05 & 2.16500965561174e-05 & -3.47644613553963 \tabularnewline
Winsorized Mean ( 14 / 20 ) & -7.63025399285903e-05 & 2.06514911772830e-05 & -3.69477144645732 \tabularnewline
Winsorized Mean ( 15 / 20 ) & -6.74538957395549e-05 & 1.90799299707527e-05 & -3.53533245892169 \tabularnewline
Winsorized Mean ( 16 / 20 ) & -6.96561172621437e-05 & 1.85570678404221e-05 & -3.75361656599729 \tabularnewline
Winsorized Mean ( 17 / 20 ) & -6.86178350634164e-05 & 1.79148615287793e-05 & -3.83021855643067 \tabularnewline
Winsorized Mean ( 18 / 20 ) & -7.72966126410159e-05 & 1.51087265087535e-05 & -5.11602434501894 \tabularnewline
Winsorized Mean ( 19 / 20 ) & -7.30368005818847e-05 & 1.43362402958805e-05 & -5.09455750423433 \tabularnewline
Winsorized Mean ( 20 / 20 ) & -7.36707072620972e-05 & 1.40160717559334e-05 & -5.25615939650926 \tabularnewline
Trimmed Mean ( 1 / 20 ) & -6.01240441606977e-05 & 3.15584320829115e-05 & -1.90516575737152 \tabularnewline
Trimmed Mean ( 2 / 20 ) & -6.15609026383193e-05 & 2.98182376508132e-05 & -2.06453860081300 \tabularnewline
Trimmed Mean ( 3 / 20 ) & -6.23220209465585e-05 & 2.84134228247542e-05 & -2.19340068005684 \tabularnewline
Trimmed Mean ( 4 / 20 ) & -6.3617372894115e-05 & 2.75409734893860e-05 & -2.30991736434561 \tabularnewline
Trimmed Mean ( 5 / 20 ) & -6.54967936271827e-05 & 2.67385703222047e-05 & -2.44952489373718 \tabularnewline
Trimmed Mean ( 6 / 20 ) & -6.72017381436526e-05 & 2.59138638760297e-05 & -2.59327356449588 \tabularnewline
Trimmed Mean ( 7 / 20 ) & -6.83965853150771e-05 & 2.52539663804341e-05 & -2.70835021654533 \tabularnewline
Trimmed Mean ( 8 / 20 ) & -6.96880382931025e-05 & 2.44005657947030e-05 & -2.85600091733244 \tabularnewline
Trimmed Mean ( 9 / 20 ) & -6.99822439706431e-05 & 2.36818101201624e-05 & -2.95510535789075 \tabularnewline
Trimmed Mean ( 10 / 20 ) & -6.92956558312915e-05 & 2.31218665602290e-05 & -2.99697499121824 \tabularnewline
Trimmed Mean ( 11 / 20 ) & -6.85149868318906e-05 & 2.23893005219065e-05 & -3.0601664739304 \tabularnewline
Trimmed Mean ( 12 / 20 ) & -6.84028551679763e-05 & 2.18301292848066e-05 & -3.13341502817317 \tabularnewline
Trimmed Mean ( 13 / 20 ) & -6.77158545357703e-05 & 2.12473708080215e-05 & -3.18702276849264 \tabularnewline
Trimmed Mean ( 14 / 20 ) & -6.66423768243041e-05 & 2.05576025404489e-05 & -3.24173875300777 \tabularnewline
Trimmed Mean ( 15 / 20 ) & -6.52846119640242e-05 & 1.98434689725479e-05 & -3.28997979407436 \tabularnewline
Trimmed Mean ( 16 / 20 ) & -6.49804135495245e-05 & 1.92777426208107e-05 & -3.37074806047969 \tabularnewline
Trimmed Mean ( 17 / 20 ) & -6.43201868678815e-05 & 1.85575411049552e-05 & -3.46598649595377 \tabularnewline
Trimmed Mean ( 18 / 20 ) & -6.37033479504047e-05 & 1.76448573180922e-05 & -3.61030677675621 \tabularnewline
Trimmed Mean ( 19 / 20 ) & -6.1700475616764e-05 & 1.72202965788766e-05 & -3.58300888339225 \tabularnewline
Trimmed Mean ( 20 / 20 ) & -5.99673532536753e-05 & 1.67530394153573e-05 & -3.57949096679758 \tabularnewline
Median & -2.7363752224343e-05 &  &  \tabularnewline
Midrange & 0.000109307300741286 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -7.11187370503014e-05 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -6.52846119640242e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -6.52846119640242e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -6.52846119640242e-05 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -6.52846119640242e-05 &  &  \tabularnewline
Midmean - Closest Observation & -7.22009726192516e-05 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -6.52846119640242e-05 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -6.52846119640242e-05 &  &  \tabularnewline
Number of observations & 61 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65507&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]-5.45689180983375e-05[/C][C]3.61690667128068e-05[/C][C]-1.50871789232581[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-6.74243809774903e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]0.000285429238227185[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]-5.87814059111168e-05[/C][C]3.29673404849238e-05[/C][C]-1.78301934722329[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]-6.01883942136255e-05[/C][C]3.18749612007567e-05[/C][C]-1.88826564633424[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]-5.894561177178e-05[/C][C]3.01123083702865e-05[/C][C]-1.95752550906874[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]-5.73320969999217e-05[/C][C]2.93675126483139e-05[/C][C]-1.95222856244223[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]-5.86490656511966e-05[/C][C]2.88107004595516e-05[/C][C]-2.03566955039973[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]-6.16780184331329e-05[/C][C]2.75637340501096e-05[/C][C]-2.23765104978176[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]-6.1727606821995e-05[/C][C]2.75375304983576e-05[/C][C]-2.24158106064291[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]-6.80289111935293e-05[/C][C]2.61707544869581e-05[/C][C]-2.59942491254621[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]-7.41355394365572e-05[/C][C]2.47187906739629e-05[/C][C]-2.99915721664517[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]-7.42868182864777e-05[/C][C]2.45940774430600e-05[/C][C]-3.02051656373231[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]-6.92631439993187e-05[/C][C]2.29769479668386e-05[/C][C]-3.01446232542644[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]-7.31330234552958e-05[/C][C]2.21996558869410e-05[/C][C]-3.29433139989871[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]-7.52653945065742e-05[/C][C]2.16500965561174e-05[/C][C]-3.47644613553963[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]-7.63025399285903e-05[/C][C]2.06514911772830e-05[/C][C]-3.69477144645732[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]-6.74538957395549e-05[/C][C]1.90799299707527e-05[/C][C]-3.53533245892169[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]-6.96561172621437e-05[/C][C]1.85570678404221e-05[/C][C]-3.75361656599729[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]-6.86178350634164e-05[/C][C]1.79148615287793e-05[/C][C]-3.83021855643067[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]-7.72966126410159e-05[/C][C]1.51087265087535e-05[/C][C]-5.11602434501894[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]-7.30368005818847e-05[/C][C]1.43362402958805e-05[/C][C]-5.09455750423433[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]-7.36707072620972e-05[/C][C]1.40160717559334e-05[/C][C]-5.25615939650926[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]-6.01240441606977e-05[/C][C]3.15584320829115e-05[/C][C]-1.90516575737152[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]-6.15609026383193e-05[/C][C]2.98182376508132e-05[/C][C]-2.06453860081300[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]-6.23220209465585e-05[/C][C]2.84134228247542e-05[/C][C]-2.19340068005684[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]-6.3617372894115e-05[/C][C]2.75409734893860e-05[/C][C]-2.30991736434561[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]-6.54967936271827e-05[/C][C]2.67385703222047e-05[/C][C]-2.44952489373718[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]-6.72017381436526e-05[/C][C]2.59138638760297e-05[/C][C]-2.59327356449588[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]-6.83965853150771e-05[/C][C]2.52539663804341e-05[/C][C]-2.70835021654533[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]-6.96880382931025e-05[/C][C]2.44005657947030e-05[/C][C]-2.85600091733244[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]-6.99822439706431e-05[/C][C]2.36818101201624e-05[/C][C]-2.95510535789075[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]-6.92956558312915e-05[/C][C]2.31218665602290e-05[/C][C]-2.99697499121824[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]-6.85149868318906e-05[/C][C]2.23893005219065e-05[/C][C]-3.0601664739304[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]-6.84028551679763e-05[/C][C]2.18301292848066e-05[/C][C]-3.13341502817317[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]-6.77158545357703e-05[/C][C]2.12473708080215e-05[/C][C]-3.18702276849264[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]-6.66423768243041e-05[/C][C]2.05576025404489e-05[/C][C]-3.24173875300777[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]-6.52846119640242e-05[/C][C]1.98434689725479e-05[/C][C]-3.28997979407436[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]-6.49804135495245e-05[/C][C]1.92777426208107e-05[/C][C]-3.37074806047969[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]-6.43201868678815e-05[/C][C]1.85575411049552e-05[/C][C]-3.46598649595377[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]-6.37033479504047e-05[/C][C]1.76448573180922e-05[/C][C]-3.61030677675621[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]-6.1700475616764e-05[/C][C]1.72202965788766e-05[/C][C]-3.58300888339225[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]-5.99673532536753e-05[/C][C]1.67530394153573e-05[/C][C]-3.57949096679758[/C][/ROW]
[ROW][C]Median[/C][C]-2.7363752224343e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]0.000109307300741286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-7.11187370503014e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-6.52846119640242e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-6.52846119640242e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-6.52846119640242e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-6.52846119640242e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-7.22009726192516e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-6.52846119640242e-05[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-6.52846119640242e-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=65507&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65507&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-5.45689180983375e-053.61690667128068e-05-1.50871789232581
Geometric MeanNaN
Harmonic Mean-6.74243809774903e-05
Quadratic Mean0.000285429238227185
Winsorized Mean ( 1 / 20 )-5.87814059111168e-053.29673404849238e-05-1.78301934722329
Winsorized Mean ( 2 / 20 )-6.01883942136255e-053.18749612007567e-05-1.88826564633424
Winsorized Mean ( 3 / 20 )-5.894561177178e-053.01123083702865e-05-1.95752550906874
Winsorized Mean ( 4 / 20 )-5.73320969999217e-052.93675126483139e-05-1.95222856244223
Winsorized Mean ( 5 / 20 )-5.86490656511966e-052.88107004595516e-05-2.03566955039973
Winsorized Mean ( 6 / 20 )-6.16780184331329e-052.75637340501096e-05-2.23765104978176
Winsorized Mean ( 7 / 20 )-6.1727606821995e-052.75375304983576e-05-2.24158106064291
Winsorized Mean ( 8 / 20 )-6.80289111935293e-052.61707544869581e-05-2.59942491254621
Winsorized Mean ( 9 / 20 )-7.41355394365572e-052.47187906739629e-05-2.99915721664517
Winsorized Mean ( 10 / 20 )-7.42868182864777e-052.45940774430600e-05-3.02051656373231
Winsorized Mean ( 11 / 20 )-6.92631439993187e-052.29769479668386e-05-3.01446232542644
Winsorized Mean ( 12 / 20 )-7.31330234552958e-052.21996558869410e-05-3.29433139989871
Winsorized Mean ( 13 / 20 )-7.52653945065742e-052.16500965561174e-05-3.47644613553963
Winsorized Mean ( 14 / 20 )-7.63025399285903e-052.06514911772830e-05-3.69477144645732
Winsorized Mean ( 15 / 20 )-6.74538957395549e-051.90799299707527e-05-3.53533245892169
Winsorized Mean ( 16 / 20 )-6.96561172621437e-051.85570678404221e-05-3.75361656599729
Winsorized Mean ( 17 / 20 )-6.86178350634164e-051.79148615287793e-05-3.83021855643067
Winsorized Mean ( 18 / 20 )-7.72966126410159e-051.51087265087535e-05-5.11602434501894
Winsorized Mean ( 19 / 20 )-7.30368005818847e-051.43362402958805e-05-5.09455750423433
Winsorized Mean ( 20 / 20 )-7.36707072620972e-051.40160717559334e-05-5.25615939650926
Trimmed Mean ( 1 / 20 )-6.01240441606977e-053.15584320829115e-05-1.90516575737152
Trimmed Mean ( 2 / 20 )-6.15609026383193e-052.98182376508132e-05-2.06453860081300
Trimmed Mean ( 3 / 20 )-6.23220209465585e-052.84134228247542e-05-2.19340068005684
Trimmed Mean ( 4 / 20 )-6.3617372894115e-052.75409734893860e-05-2.30991736434561
Trimmed Mean ( 5 / 20 )-6.54967936271827e-052.67385703222047e-05-2.44952489373718
Trimmed Mean ( 6 / 20 )-6.72017381436526e-052.59138638760297e-05-2.59327356449588
Trimmed Mean ( 7 / 20 )-6.83965853150771e-052.52539663804341e-05-2.70835021654533
Trimmed Mean ( 8 / 20 )-6.96880382931025e-052.44005657947030e-05-2.85600091733244
Trimmed Mean ( 9 / 20 )-6.99822439706431e-052.36818101201624e-05-2.95510535789075
Trimmed Mean ( 10 / 20 )-6.92956558312915e-052.31218665602290e-05-2.99697499121824
Trimmed Mean ( 11 / 20 )-6.85149868318906e-052.23893005219065e-05-3.0601664739304
Trimmed Mean ( 12 / 20 )-6.84028551679763e-052.18301292848066e-05-3.13341502817317
Trimmed Mean ( 13 / 20 )-6.77158545357703e-052.12473708080215e-05-3.18702276849264
Trimmed Mean ( 14 / 20 )-6.66423768243041e-052.05576025404489e-05-3.24173875300777
Trimmed Mean ( 15 / 20 )-6.52846119640242e-051.98434689725479e-05-3.28997979407436
Trimmed Mean ( 16 / 20 )-6.49804135495245e-051.92777426208107e-05-3.37074806047969
Trimmed Mean ( 17 / 20 )-6.43201868678815e-051.85575411049552e-05-3.46598649595377
Trimmed Mean ( 18 / 20 )-6.37033479504047e-051.76448573180922e-05-3.61030677675621
Trimmed Mean ( 19 / 20 )-6.1700475616764e-051.72202965788766e-05-3.58300888339225
Trimmed Mean ( 20 / 20 )-5.99673532536753e-051.67530394153573e-05-3.57949096679758
Median-2.7363752224343e-05
Midrange0.000109307300741286
Midmean - Weighted Average at Xnp-7.11187370503014e-05
Midmean - Weighted Average at X(n+1)p-6.52846119640242e-05
Midmean - Empirical Distribution Function-6.52846119640242e-05
Midmean - Empirical Distribution Function - Averaging-6.52846119640242e-05
Midmean - Empirical Distribution Function - Interpolation-6.52846119640242e-05
Midmean - Closest Observation-7.22009726192516e-05
Midmean - True Basic - Statistics Graphics Toolkit-6.52846119640242e-05
Midmean - MS Excel (old versions)-6.52846119640242e-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')