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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 computationSun, 28 Nov 2010 17:01:51 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/28/t1290963620a2erwuk6fcozxti.htm/, Retrieved Fri, 03 May 2024 03:17:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102665, Retrieved Fri, 03 May 2024 03:17:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [Bivariate density...] [2008-11-14 00:47:52] [7a4703cb85a198d9845d72899eff0288]
-  MPD  [Bivariate Kernel Density Estimation] [Paper - Wisselkoe...] [2010-11-28 15:16:48] [4a7069087cf9e0eda253aeed7d8c30d6]
-   PD    [Bivariate Kernel Density Estimation] [Paper - Werkloosh...] [2010-11-28 16:24:36] [4a7069087cf9e0eda253aeed7d8c30d6]
- RMPD        [Central Tendency] [Paper - Robustnes...] [2010-11-28 17:01:51] [cfd788255f1b1b5389e58d7f218c70bf] [Current]
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Dataseries X:
376.974
377.632
378.205
370.861
369.167
371.551
382.842
381.903
384.502
392.058
384.359
388.884
386.586
387.495
385.705
378.67
377.367
376.911
389.827
387.82
387.267
380.575
372.402
376.74
377.795
376.126
370.804
367.98
367.866
366.121
379.421
378.519
372.423
355.072
344.693
342.892
344.178
337.606
327.103
323.953
316.532
306.307
327.225
329.573
313.761
307.836
300.074
304.198
306.122
300.414
292.133
290.616
280.244
285.179
305.486
305.957
293.886
289.441
288.776
299.149
306.532
309.914
313.468
314.901
309.16
316.15
336.544
339.196
326.738
320.838
318.62
331.533
335.378




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102665&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102665&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102665&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean343.8456986301374.1155672285717683.5475839740962
Geometric Mean342.043277298795
Harmonic Mean340.220904110257
Quadratic Mean345.614514751009
Winsorized Mean ( 1 / 24 )343.8827397260274.0967171445736483.941050258137
Winsorized Mean ( 2 / 24 )343.9554520547954.0736481543456684.4342562299771
Winsorized Mean ( 3 / 24 )343.9390547945214.0619016331555484.6743928969365
Winsorized Mean ( 4 / 24 )343.9856301369864.0473414792033184.9905133788458
Winsorized Mean ( 5 / 24 )344.0739178082194.0261883637969285.4589717913093
Winsorized Mean ( 6 / 24 )344.162027397263.9923782010879686.204765696665
Winsorized Mean ( 7 / 24 )344.5822191780823.8948939848296188.4702434829319
Winsorized Mean ( 8 / 24 )344.5517534246583.8594252657560589.275404937051
Winsorized Mean ( 9 / 24 )344.5760410958903.8501992557719789.4956385904767
Winsorized Mean ( 10 / 24 )344.8865890410963.7401592191157192.2117398848699
Winsorized Mean ( 11 / 24 )344.9391780821923.6912778251747193.4470918795894
Winsorized Mean ( 12 / 24 )344.7983013698633.6497660202983294.4713440402078
Winsorized Mean ( 13 / 24 )344.6221780821923.6177047343102695.2598963684902
Winsorized Mean ( 14 / 24 )344.5136301369863.5933343979795195.8757499248337
Winsorized Mean ( 15 / 24 )344.5288356164383.5824228220410396.1720189746191
Winsorized Mean ( 16 / 24 )344.7458219178083.5315626545277197.6184923339304
Winsorized Mean ( 17 / 24 )344.9586712328773.4745729666578799.2808827280684
Winsorized Mean ( 18 / 24 )345.1043972602743.44279864518919100.239494907002
Winsorized Mean ( 19 / 24 )345.9604383561643.30485510899815104.682482876243
Winsorized Mean ( 20 / 24 )345.9330410958903.27972341484285105.476284838630
Winsorized Mean ( 21 / 24 )346.2428630136993.23291817948101107.099172880794
Winsorized Mean ( 22 / 24 )346.5677397260273.17574217365188109.129683952743
Winsorized Mean ( 23 / 24 )346.4946438356163.13428194328279110.549928215043
Winsorized Mean ( 24 / 24 )345.9636849315072.88598885236330119.876999749393
Trimmed Mean ( 1 / 24 )344.0624507042254.0780274720867384.369821699158
Trimmed Mean ( 2 / 24 )344.2525797101454.053365300347284.9300653165056
Trimmed Mean ( 3 / 24 )344.4144477611944.0356034217903985.3439775329546
Trimmed Mean ( 4 / 24 )344.5924153846154.0164604633076685.7950472891831
Trimmed Mean ( 5 / 24 )344.7681904761903.9954178718553386.2908966055389
Trimmed Mean ( 6 / 24 )344.9343606557383.9730857925947886.8177478821732
Trimmed Mean ( 7 / 24 )345.0936271186443.9514999648831187.3323118272765
Trimmed Mean ( 8 / 24 )345.1871929824563.9447794357404587.5048145543943
Trimmed Mean ( 9 / 24 )345.2926181818183.9393617363594487.6519195977469
Trimmed Mean ( 10 / 24 )345.4022830188683.9292198150696587.9060727766246
Trimmed Mean ( 11 / 24 )345.4760980392163.9332390662603787.8350113530439
Trimmed Mean ( 12 / 24 )345.5488163265313.9406230796251987.6888779627706
Trimmed Mean ( 13 / 24 )345.6459574468083.9497460162560087.5109326078769
Trimmed Mean ( 14 / 24 )345.7737111111113.9584097913664987.3516713366218
Trimmed Mean ( 15 / 24 )345.9265116279073.9643933563270587.258372349913
Trimmed Mean ( 16 / 24 )346.0924146341463.9639010255320687.3110636226572
Trimmed Mean ( 17 / 24 )346.2499487179493.9627805618413187.3755039711468
Trimmed Mean ( 18 / 24 )346.3998108108113.9612607771012787.4468585388856
Trimmed Mean ( 19 / 24 )346.5499142857143.9528461388299687.670984934489
Trimmed Mean ( 20 / 24 )346.6185454545453.9587695048583587.5571424477132
Trimmed Mean ( 21 / 24 )346.6992580645163.9551526300273687.6576179215915
Trimmed Mean ( 22 / 24 )346.7539655172413.942980403423387.9420971040558
Trimmed Mean ( 23 / 24 )346.7768518518523.9202268945991888.4583625324339
Trimmed Mean ( 24 / 24 )346.812683.8756302583020889.4854918776331
Median342.892
Midrange336.151
Midmean - Weighted Average at Xnp345.53225
Midmean - Weighted Average at X(n+1)p346.399810810811
Midmean - Empirical Distribution Function346.399810810811
Midmean - Empirical Distribution Function - Averaging346.399810810811
Midmean - Empirical Distribution Function - Interpolation346.399810810811
Midmean - Closest Observation345.419815789474
Midmean - True Basic - Statistics Graphics Toolkit346.399810810811
Midmean - MS Excel (old versions)346.399810810811
Number of observations73

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 343.845698630137 & 4.11556722857176 & 83.5475839740962 \tabularnewline
Geometric Mean & 342.043277298795 &  &  \tabularnewline
Harmonic Mean & 340.220904110257 &  &  \tabularnewline
Quadratic Mean & 345.614514751009 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 343.882739726027 & 4.09671714457364 & 83.941050258137 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 343.955452054795 & 4.07364815434566 & 84.4342562299771 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 343.939054794521 & 4.06190163315554 & 84.6743928969365 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 343.985630136986 & 4.04734147920331 & 84.9905133788458 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 344.073917808219 & 4.02618836379692 & 85.4589717913093 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 344.16202739726 & 3.99237820108796 & 86.204765696665 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 344.582219178082 & 3.89489398482961 & 88.4702434829319 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 344.551753424658 & 3.85942526575605 & 89.275404937051 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 344.576041095890 & 3.85019925577197 & 89.4956385904767 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 344.886589041096 & 3.74015921911571 & 92.2117398848699 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 344.939178082192 & 3.69127782517471 & 93.4470918795894 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 344.798301369863 & 3.64976602029832 & 94.4713440402078 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 344.622178082192 & 3.61770473431026 & 95.2598963684902 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 344.513630136986 & 3.59333439797951 & 95.8757499248337 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 344.528835616438 & 3.58242282204103 & 96.1720189746191 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 344.745821917808 & 3.53156265452771 & 97.6184923339304 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 344.958671232877 & 3.47457296665787 & 99.2808827280684 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 345.104397260274 & 3.44279864518919 & 100.239494907002 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 345.960438356164 & 3.30485510899815 & 104.682482876243 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 345.933041095890 & 3.27972341484285 & 105.476284838630 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 346.242863013699 & 3.23291817948101 & 107.099172880794 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 346.567739726027 & 3.17574217365188 & 109.129683952743 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 346.494643835616 & 3.13428194328279 & 110.549928215043 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 345.963684931507 & 2.88598885236330 & 119.876999749393 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 344.062450704225 & 4.07802747208673 & 84.369821699158 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 344.252579710145 & 4.0533653003472 & 84.9300653165056 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 344.414447761194 & 4.03560342179039 & 85.3439775329546 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 344.592415384615 & 4.01646046330766 & 85.7950472891831 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 344.768190476190 & 3.99541787185533 & 86.2908966055389 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 344.934360655738 & 3.97308579259478 & 86.8177478821732 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 345.093627118644 & 3.95149996488311 & 87.3323118272765 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 345.187192982456 & 3.94477943574045 & 87.5048145543943 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 345.292618181818 & 3.93936173635944 & 87.6519195977469 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 345.402283018868 & 3.92921981506965 & 87.9060727766246 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 345.476098039216 & 3.93323906626037 & 87.8350113530439 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 345.548816326531 & 3.94062307962519 & 87.6888779627706 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 345.645957446808 & 3.94974601625600 & 87.5109326078769 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 345.773711111111 & 3.95840979136649 & 87.3516713366218 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 345.926511627907 & 3.96439335632705 & 87.258372349913 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 346.092414634146 & 3.96390102553206 & 87.3110636226572 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 346.249948717949 & 3.96278056184131 & 87.3755039711468 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 346.399810810811 & 3.96126077710127 & 87.4468585388856 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 346.549914285714 & 3.95284613882996 & 87.670984934489 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 346.618545454545 & 3.95876950485835 & 87.5571424477132 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 346.699258064516 & 3.95515263002736 & 87.6576179215915 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 346.753965517241 & 3.9429804034233 & 87.9420971040558 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 346.776851851852 & 3.92022689459918 & 88.4583625324339 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 346.81268 & 3.87563025830208 & 89.4854918776331 \tabularnewline
Median & 342.892 &  &  \tabularnewline
Midrange & 336.151 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 345.53225 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 346.399810810811 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 346.399810810811 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 346.399810810811 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 346.399810810811 &  &  \tabularnewline
Midmean - Closest Observation & 345.419815789474 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 346.399810810811 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 346.399810810811 &  &  \tabularnewline
Number of observations & 73 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102665&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]343.845698630137[/C][C]4.11556722857176[/C][C]83.5475839740962[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]342.043277298795[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]340.220904110257[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]345.614514751009[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]343.882739726027[/C][C]4.09671714457364[/C][C]83.941050258137[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]343.955452054795[/C][C]4.07364815434566[/C][C]84.4342562299771[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]343.939054794521[/C][C]4.06190163315554[/C][C]84.6743928969365[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]343.985630136986[/C][C]4.04734147920331[/C][C]84.9905133788458[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]344.073917808219[/C][C]4.02618836379692[/C][C]85.4589717913093[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]344.16202739726[/C][C]3.99237820108796[/C][C]86.204765696665[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]344.582219178082[/C][C]3.89489398482961[/C][C]88.4702434829319[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]344.551753424658[/C][C]3.85942526575605[/C][C]89.275404937051[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]344.576041095890[/C][C]3.85019925577197[/C][C]89.4956385904767[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]344.886589041096[/C][C]3.74015921911571[/C][C]92.2117398848699[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]344.939178082192[/C][C]3.69127782517471[/C][C]93.4470918795894[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]344.798301369863[/C][C]3.64976602029832[/C][C]94.4713440402078[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]344.622178082192[/C][C]3.61770473431026[/C][C]95.2598963684902[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]344.513630136986[/C][C]3.59333439797951[/C][C]95.8757499248337[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]344.528835616438[/C][C]3.58242282204103[/C][C]96.1720189746191[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]344.745821917808[/C][C]3.53156265452771[/C][C]97.6184923339304[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]344.958671232877[/C][C]3.47457296665787[/C][C]99.2808827280684[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]345.104397260274[/C][C]3.44279864518919[/C][C]100.239494907002[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]345.960438356164[/C][C]3.30485510899815[/C][C]104.682482876243[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]345.933041095890[/C][C]3.27972341484285[/C][C]105.476284838630[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]346.242863013699[/C][C]3.23291817948101[/C][C]107.099172880794[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]346.567739726027[/C][C]3.17574217365188[/C][C]109.129683952743[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]346.494643835616[/C][C]3.13428194328279[/C][C]110.549928215043[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]345.963684931507[/C][C]2.88598885236330[/C][C]119.876999749393[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]344.062450704225[/C][C]4.07802747208673[/C][C]84.369821699158[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]344.252579710145[/C][C]4.0533653003472[/C][C]84.9300653165056[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]344.414447761194[/C][C]4.03560342179039[/C][C]85.3439775329546[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]344.592415384615[/C][C]4.01646046330766[/C][C]85.7950472891831[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]344.768190476190[/C][C]3.99541787185533[/C][C]86.2908966055389[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]344.934360655738[/C][C]3.97308579259478[/C][C]86.8177478821732[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]345.093627118644[/C][C]3.95149996488311[/C][C]87.3323118272765[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]345.187192982456[/C][C]3.94477943574045[/C][C]87.5048145543943[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]345.292618181818[/C][C]3.93936173635944[/C][C]87.6519195977469[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]345.402283018868[/C][C]3.92921981506965[/C][C]87.9060727766246[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]345.476098039216[/C][C]3.93323906626037[/C][C]87.8350113530439[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]345.548816326531[/C][C]3.94062307962519[/C][C]87.6888779627706[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]345.645957446808[/C][C]3.94974601625600[/C][C]87.5109326078769[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]345.773711111111[/C][C]3.95840979136649[/C][C]87.3516713366218[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]345.926511627907[/C][C]3.96439335632705[/C][C]87.258372349913[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]346.092414634146[/C][C]3.96390102553206[/C][C]87.3110636226572[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]346.249948717949[/C][C]3.96278056184131[/C][C]87.3755039711468[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]346.399810810811[/C][C]3.96126077710127[/C][C]87.4468585388856[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]346.549914285714[/C][C]3.95284613882996[/C][C]87.670984934489[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]346.618545454545[/C][C]3.95876950485835[/C][C]87.5571424477132[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]346.699258064516[/C][C]3.95515263002736[/C][C]87.6576179215915[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]346.753965517241[/C][C]3.9429804034233[/C][C]87.9420971040558[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]346.776851851852[/C][C]3.92022689459918[/C][C]88.4583625324339[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]346.81268[/C][C]3.87563025830208[/C][C]89.4854918776331[/C][/ROW]
[ROW][C]Median[/C][C]342.892[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]336.151[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]345.53225[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]346.399810810811[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]346.399810810811[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]346.399810810811[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]346.399810810811[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]345.419815789474[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]346.399810810811[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]346.399810810811[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]73[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102665&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102665&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 Mean343.8456986301374.1155672285717683.5475839740962
Geometric Mean342.043277298795
Harmonic Mean340.220904110257
Quadratic Mean345.614514751009
Winsorized Mean ( 1 / 24 )343.8827397260274.0967171445736483.941050258137
Winsorized Mean ( 2 / 24 )343.9554520547954.0736481543456684.4342562299771
Winsorized Mean ( 3 / 24 )343.9390547945214.0619016331555484.6743928969365
Winsorized Mean ( 4 / 24 )343.9856301369864.0473414792033184.9905133788458
Winsorized Mean ( 5 / 24 )344.0739178082194.0261883637969285.4589717913093
Winsorized Mean ( 6 / 24 )344.162027397263.9923782010879686.204765696665
Winsorized Mean ( 7 / 24 )344.5822191780823.8948939848296188.4702434829319
Winsorized Mean ( 8 / 24 )344.5517534246583.8594252657560589.275404937051
Winsorized Mean ( 9 / 24 )344.5760410958903.8501992557719789.4956385904767
Winsorized Mean ( 10 / 24 )344.8865890410963.7401592191157192.2117398848699
Winsorized Mean ( 11 / 24 )344.9391780821923.6912778251747193.4470918795894
Winsorized Mean ( 12 / 24 )344.7983013698633.6497660202983294.4713440402078
Winsorized Mean ( 13 / 24 )344.6221780821923.6177047343102695.2598963684902
Winsorized Mean ( 14 / 24 )344.5136301369863.5933343979795195.8757499248337
Winsorized Mean ( 15 / 24 )344.5288356164383.5824228220410396.1720189746191
Winsorized Mean ( 16 / 24 )344.7458219178083.5315626545277197.6184923339304
Winsorized Mean ( 17 / 24 )344.9586712328773.4745729666578799.2808827280684
Winsorized Mean ( 18 / 24 )345.1043972602743.44279864518919100.239494907002
Winsorized Mean ( 19 / 24 )345.9604383561643.30485510899815104.682482876243
Winsorized Mean ( 20 / 24 )345.9330410958903.27972341484285105.476284838630
Winsorized Mean ( 21 / 24 )346.2428630136993.23291817948101107.099172880794
Winsorized Mean ( 22 / 24 )346.5677397260273.17574217365188109.129683952743
Winsorized Mean ( 23 / 24 )346.4946438356163.13428194328279110.549928215043
Winsorized Mean ( 24 / 24 )345.9636849315072.88598885236330119.876999749393
Trimmed Mean ( 1 / 24 )344.0624507042254.0780274720867384.369821699158
Trimmed Mean ( 2 / 24 )344.2525797101454.053365300347284.9300653165056
Trimmed Mean ( 3 / 24 )344.4144477611944.0356034217903985.3439775329546
Trimmed Mean ( 4 / 24 )344.5924153846154.0164604633076685.7950472891831
Trimmed Mean ( 5 / 24 )344.7681904761903.9954178718553386.2908966055389
Trimmed Mean ( 6 / 24 )344.9343606557383.9730857925947886.8177478821732
Trimmed Mean ( 7 / 24 )345.0936271186443.9514999648831187.3323118272765
Trimmed Mean ( 8 / 24 )345.1871929824563.9447794357404587.5048145543943
Trimmed Mean ( 9 / 24 )345.2926181818183.9393617363594487.6519195977469
Trimmed Mean ( 10 / 24 )345.4022830188683.9292198150696587.9060727766246
Trimmed Mean ( 11 / 24 )345.4760980392163.9332390662603787.8350113530439
Trimmed Mean ( 12 / 24 )345.5488163265313.9406230796251987.6888779627706
Trimmed Mean ( 13 / 24 )345.6459574468083.9497460162560087.5109326078769
Trimmed Mean ( 14 / 24 )345.7737111111113.9584097913664987.3516713366218
Trimmed Mean ( 15 / 24 )345.9265116279073.9643933563270587.258372349913
Trimmed Mean ( 16 / 24 )346.0924146341463.9639010255320687.3110636226572
Trimmed Mean ( 17 / 24 )346.2499487179493.9627805618413187.3755039711468
Trimmed Mean ( 18 / 24 )346.3998108108113.9612607771012787.4468585388856
Trimmed Mean ( 19 / 24 )346.5499142857143.9528461388299687.670984934489
Trimmed Mean ( 20 / 24 )346.6185454545453.9587695048583587.5571424477132
Trimmed Mean ( 21 / 24 )346.6992580645163.9551526300273687.6576179215915
Trimmed Mean ( 22 / 24 )346.7539655172413.942980403423387.9420971040558
Trimmed Mean ( 23 / 24 )346.7768518518523.9202268945991888.4583625324339
Trimmed Mean ( 24 / 24 )346.812683.8756302583020889.4854918776331
Median342.892
Midrange336.151
Midmean - Weighted Average at Xnp345.53225
Midmean - Weighted Average at X(n+1)p346.399810810811
Midmean - Empirical Distribution Function346.399810810811
Midmean - Empirical Distribution Function - Averaging346.399810810811
Midmean - Empirical Distribution Function - Interpolation346.399810810811
Midmean - Closest Observation345.419815789474
Midmean - True Basic - Statistics Graphics Toolkit346.399810810811
Midmean - MS Excel (old versions)346.399810810811
Number of observations73



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')