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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 20 May 2013 06:35:55 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/20/t13690461920dyzc11r0bi6lgc.htm/, Retrieved Sat, 04 May 2024 15:13:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=209114, Retrieved Sat, 04 May 2024 15:13:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Gemiddelde consum...] [2013-04-11 11:13:43] [1b535cd3f3704fa56924870d03abd2cc]
- RMP     [Central Tendency] [Opgave 5: eigen r...] [2013-05-20 10:35:55] [7bf0202b24d13a3918d58b8a1b5b6350] [Current]
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Dataseries X:
39,28
39,36
39,55
39,64
39,8
39,79
39,79
39,86
39,91
40
40,01
40,01
40,01
39,96
40
39,76
39,68
39,7
39,7
39,73
39,64
39,56
39,67
39,66
39,66
40,05
39,99
40,06
40,08
40,1
40,1
40,12
40,07
40,24
40,58
40,72
40,72
40,89
40,9
41,04
41,27
41,29
41,29
41,33
41,34
41,37
41,33
41,37
41,37
41,42
41,61
41,58
41,75
41,75
41,75
41,85
41,84
41,97
42,01
42,04
42,04
42,06
41,93
41,93
41,99
42,03
42,03
42,12
42,22
42,21
42,23
42,22




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\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 Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=209114&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=209114&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=209114&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 Maurice George Kendall' @ kendall.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean40.77680555555560.114112864946759357.337497175106
Geometric Mean40.7654884099649
Harmonic Mean40.7541941808895
Quadratic Mean40.7881406205012
Winsorized Mean ( 1 / 24 )40.77777777777780.113887972819706358.051660488613
Winsorized Mean ( 2 / 24 )40.78305555555560.113019559930108360.849534193691
Winsorized Mean ( 3 / 24 )40.78305555555560.11288135483559361.291336509519
Winsorized Mean ( 4 / 24 )40.78250.111352783926864366.245894909872
Winsorized Mean ( 5 / 24 )40.77833333333330.110660451491292368.499611051579
Winsorized Mean ( 6 / 24 )40.77833333333330.110150167807038370.206729097037
Winsorized Mean ( 7 / 24 )40.77833333333330.110150167807038370.206729097037
Winsorized Mean ( 8 / 24 )40.77833333333330.109812936688547371.34361909462
Winsorized Mean ( 9 / 24 )40.77958333333330.109635802965374371.954983959142
Winsorized Mean ( 10 / 24 )40.77958333333330.108801163472301374.808338733575
Winsorized Mean ( 11 / 24 )40.77652777777780.108316748409479376.456350255518
Winsorized Mean ( 12 / 24 )40.77819444444440.107097926315879380.756153244008
Winsorized Mean ( 13 / 24 )40.77638888888890.105232491983955387.488580001565
Winsorized Mean ( 14 / 24 )40.78222222222220.104445443340876390.464350743594
Winsorized Mean ( 15 / 24 )40.76555555555560.101906107804486400.030542170908
Winsorized Mean ( 16 / 24 )40.76555555555560.101274524433603402.525272604782
Winsorized Mean ( 17 / 24 )40.75847222222220.0962614259060078423.41438264191
Winsorized Mean ( 18 / 24 )40.77097222222220.0946387910510535430.806139527164
Winsorized Mean ( 19 / 24 )40.78416666666670.0929695606200112438.683009736502
Winsorized Mean ( 20 / 24 )40.75361111111110.0863648830173783471.877106611847
Winsorized Mean ( 21 / 24 )40.74777777777780.0847862132948256480.59438196734
Winsorized Mean ( 22 / 24 )40.69888888888890.0782247663283105520.281373779694
Winsorized Mean ( 23 / 24 )40.68611111111110.0757705734095915536.964540193922
Winsorized Mean ( 24 / 24 )40.68611111111110.0757705734095915536.964540193922
Trimmed Mean ( 1 / 24 )40.77742857142860.113494226139708359.290775913418
Trimmed Mean ( 2 / 24 )40.77705882352940.112950698768171361.01643697861
Trimmed Mean ( 3 / 24 )40.77378787878790.112749441700614361.631838382448
Trimmed Mean ( 4 / 24 )40.77031250.112466478416287362.51079498632
Trimmed Mean ( 5 / 24 )40.76677419354840.112539498722869362.24414233386
Trimmed Mean ( 6 / 24 )40.7640.112693073494156361.725869532823
Trimmed Mean ( 7 / 24 )40.76103448275860.112859679687493361.1656048965
Trimmed Mean ( 8 / 24 )40.75785714285710.112902875823436360.999282308775
Trimmed Mean ( 9 / 24 )40.75444444444440.112866428376882361.085621566385
Trimmed Mean ( 10 / 24 )40.75057692307690.112687388250435361.625001304613
Trimmed Mean ( 11 / 24 )40.74640.112459610890456362.320300393803
Trimmed Mean ( 12 / 24 )40.74229166666670.112087003782607363.488096672531
Trimmed Mean ( 13 / 24 )40.73760869565220.111663393758053364.825099118162
Trimmed Mean ( 14 / 24 )40.73272727272730.111286140356993366.017970809854
Trimmed Mean ( 15 / 24 )40.72666666666670.110714953852592367.851543531247
Trimmed Mean ( 16 / 24 )40.7220.1102672743604369.302680565978
Trimmed Mean ( 17 / 24 )40.71684210526320.109527697584423371.749274414164
Trimmed Mean ( 18 / 24 )40.71194444444440.109342783741137372.333162294713
Trimmed Mean ( 19 / 24 )40.7050.109047284058008373.278439271784
Trimmed Mean ( 20 / 24 )40.6956250.108565553168016374.848410130783
Trimmed Mean ( 21 / 24 )40.68866666666670.109106858232698372.924922646823
Trimmed Mean ( 22 / 24 )40.68142857142860.109632278930625371.071631167786
Trimmed Mean ( 23 / 24 )40.67923076923080.111469793185865364.935016084602
Trimmed Mean ( 24 / 24 )40.67833333333330.113823004390599357.382354745619
Median40.72
Midrange40.755
Midmean - Weighted Average at Xnp40.7168421052631
Midmean - Weighted Average at X(n+1)p40.74
Midmean - Empirical Distribution Function40.7168421052631
Midmean - Empirical Distribution Function - Averaging40.74
Midmean - Empirical Distribution Function - Interpolation40.74
Midmean - Closest Observation40.7168421052631
Midmean - True Basic - Statistics Graphics Toolkit40.74
Midmean - MS Excel (old versions)40.7168421052631
Number of observations72

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 40.7768055555556 & 0.114112864946759 & 357.337497175106 \tabularnewline
Geometric Mean & 40.7654884099649 &  &  \tabularnewline
Harmonic Mean & 40.7541941808895 &  &  \tabularnewline
Quadratic Mean & 40.7881406205012 &  &  \tabularnewline
Winsorized Mean ( 1 / 24 ) & 40.7777777777778 & 0.113887972819706 & 358.051660488613 \tabularnewline
Winsorized Mean ( 2 / 24 ) & 40.7830555555556 & 0.113019559930108 & 360.849534193691 \tabularnewline
Winsorized Mean ( 3 / 24 ) & 40.7830555555556 & 0.11288135483559 & 361.291336509519 \tabularnewline
Winsorized Mean ( 4 / 24 ) & 40.7825 & 0.111352783926864 & 366.245894909872 \tabularnewline
Winsorized Mean ( 5 / 24 ) & 40.7783333333333 & 0.110660451491292 & 368.499611051579 \tabularnewline
Winsorized Mean ( 6 / 24 ) & 40.7783333333333 & 0.110150167807038 & 370.206729097037 \tabularnewline
Winsorized Mean ( 7 / 24 ) & 40.7783333333333 & 0.110150167807038 & 370.206729097037 \tabularnewline
Winsorized Mean ( 8 / 24 ) & 40.7783333333333 & 0.109812936688547 & 371.34361909462 \tabularnewline
Winsorized Mean ( 9 / 24 ) & 40.7795833333333 & 0.109635802965374 & 371.954983959142 \tabularnewline
Winsorized Mean ( 10 / 24 ) & 40.7795833333333 & 0.108801163472301 & 374.808338733575 \tabularnewline
Winsorized Mean ( 11 / 24 ) & 40.7765277777778 & 0.108316748409479 & 376.456350255518 \tabularnewline
Winsorized Mean ( 12 / 24 ) & 40.7781944444444 & 0.107097926315879 & 380.756153244008 \tabularnewline
Winsorized Mean ( 13 / 24 ) & 40.7763888888889 & 0.105232491983955 & 387.488580001565 \tabularnewline
Winsorized Mean ( 14 / 24 ) & 40.7822222222222 & 0.104445443340876 & 390.464350743594 \tabularnewline
Winsorized Mean ( 15 / 24 ) & 40.7655555555556 & 0.101906107804486 & 400.030542170908 \tabularnewline
Winsorized Mean ( 16 / 24 ) & 40.7655555555556 & 0.101274524433603 & 402.525272604782 \tabularnewline
Winsorized Mean ( 17 / 24 ) & 40.7584722222222 & 0.0962614259060078 & 423.41438264191 \tabularnewline
Winsorized Mean ( 18 / 24 ) & 40.7709722222222 & 0.0946387910510535 & 430.806139527164 \tabularnewline
Winsorized Mean ( 19 / 24 ) & 40.7841666666667 & 0.0929695606200112 & 438.683009736502 \tabularnewline
Winsorized Mean ( 20 / 24 ) & 40.7536111111111 & 0.0863648830173783 & 471.877106611847 \tabularnewline
Winsorized Mean ( 21 / 24 ) & 40.7477777777778 & 0.0847862132948256 & 480.59438196734 \tabularnewline
Winsorized Mean ( 22 / 24 ) & 40.6988888888889 & 0.0782247663283105 & 520.281373779694 \tabularnewline
Winsorized Mean ( 23 / 24 ) & 40.6861111111111 & 0.0757705734095915 & 536.964540193922 \tabularnewline
Winsorized Mean ( 24 / 24 ) & 40.6861111111111 & 0.0757705734095915 & 536.964540193922 \tabularnewline
Trimmed Mean ( 1 / 24 ) & 40.7774285714286 & 0.113494226139708 & 359.290775913418 \tabularnewline
Trimmed Mean ( 2 / 24 ) & 40.7770588235294 & 0.112950698768171 & 361.01643697861 \tabularnewline
Trimmed Mean ( 3 / 24 ) & 40.7737878787879 & 0.112749441700614 & 361.631838382448 \tabularnewline
Trimmed Mean ( 4 / 24 ) & 40.7703125 & 0.112466478416287 & 362.51079498632 \tabularnewline
Trimmed Mean ( 5 / 24 ) & 40.7667741935484 & 0.112539498722869 & 362.24414233386 \tabularnewline
Trimmed Mean ( 6 / 24 ) & 40.764 & 0.112693073494156 & 361.725869532823 \tabularnewline
Trimmed Mean ( 7 / 24 ) & 40.7610344827586 & 0.112859679687493 & 361.1656048965 \tabularnewline
Trimmed Mean ( 8 / 24 ) & 40.7578571428571 & 0.112902875823436 & 360.999282308775 \tabularnewline
Trimmed Mean ( 9 / 24 ) & 40.7544444444444 & 0.112866428376882 & 361.085621566385 \tabularnewline
Trimmed Mean ( 10 / 24 ) & 40.7505769230769 & 0.112687388250435 & 361.625001304613 \tabularnewline
Trimmed Mean ( 11 / 24 ) & 40.7464 & 0.112459610890456 & 362.320300393803 \tabularnewline
Trimmed Mean ( 12 / 24 ) & 40.7422916666667 & 0.112087003782607 & 363.488096672531 \tabularnewline
Trimmed Mean ( 13 / 24 ) & 40.7376086956522 & 0.111663393758053 & 364.825099118162 \tabularnewline
Trimmed Mean ( 14 / 24 ) & 40.7327272727273 & 0.111286140356993 & 366.017970809854 \tabularnewline
Trimmed Mean ( 15 / 24 ) & 40.7266666666667 & 0.110714953852592 & 367.851543531247 \tabularnewline
Trimmed Mean ( 16 / 24 ) & 40.722 & 0.1102672743604 & 369.302680565978 \tabularnewline
Trimmed Mean ( 17 / 24 ) & 40.7168421052632 & 0.109527697584423 & 371.749274414164 \tabularnewline
Trimmed Mean ( 18 / 24 ) & 40.7119444444444 & 0.109342783741137 & 372.333162294713 \tabularnewline
Trimmed Mean ( 19 / 24 ) & 40.705 & 0.109047284058008 & 373.278439271784 \tabularnewline
Trimmed Mean ( 20 / 24 ) & 40.695625 & 0.108565553168016 & 374.848410130783 \tabularnewline
Trimmed Mean ( 21 / 24 ) & 40.6886666666667 & 0.109106858232698 & 372.924922646823 \tabularnewline
Trimmed Mean ( 22 / 24 ) & 40.6814285714286 & 0.109632278930625 & 371.071631167786 \tabularnewline
Trimmed Mean ( 23 / 24 ) & 40.6792307692308 & 0.111469793185865 & 364.935016084602 \tabularnewline
Trimmed Mean ( 24 / 24 ) & 40.6783333333333 & 0.113823004390599 & 357.382354745619 \tabularnewline
Median & 40.72 &  &  \tabularnewline
Midrange & 40.755 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 40.7168421052631 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 40.74 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 40.7168421052631 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 40.74 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 40.74 &  &  \tabularnewline
Midmean - Closest Observation & 40.7168421052631 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 40.74 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 40.7168421052631 &  &  \tabularnewline
Number of observations & 72 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=209114&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]40.7768055555556[/C][C]0.114112864946759[/C][C]357.337497175106[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]40.7654884099649[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]40.7541941808895[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]40.7881406205012[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 24 )[/C][C]40.7777777777778[/C][C]0.113887972819706[/C][C]358.051660488613[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 24 )[/C][C]40.7830555555556[/C][C]0.113019559930108[/C][C]360.849534193691[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 24 )[/C][C]40.7830555555556[/C][C]0.11288135483559[/C][C]361.291336509519[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 24 )[/C][C]40.7825[/C][C]0.111352783926864[/C][C]366.245894909872[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 24 )[/C][C]40.7783333333333[/C][C]0.110660451491292[/C][C]368.499611051579[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 24 )[/C][C]40.7783333333333[/C][C]0.110150167807038[/C][C]370.206729097037[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 24 )[/C][C]40.7783333333333[/C][C]0.110150167807038[/C][C]370.206729097037[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 24 )[/C][C]40.7783333333333[/C][C]0.109812936688547[/C][C]371.34361909462[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 24 )[/C][C]40.7795833333333[/C][C]0.109635802965374[/C][C]371.954983959142[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 24 )[/C][C]40.7795833333333[/C][C]0.108801163472301[/C][C]374.808338733575[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 24 )[/C][C]40.7765277777778[/C][C]0.108316748409479[/C][C]376.456350255518[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 24 )[/C][C]40.7781944444444[/C][C]0.107097926315879[/C][C]380.756153244008[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 24 )[/C][C]40.7763888888889[/C][C]0.105232491983955[/C][C]387.488580001565[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 24 )[/C][C]40.7822222222222[/C][C]0.104445443340876[/C][C]390.464350743594[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 24 )[/C][C]40.7655555555556[/C][C]0.101906107804486[/C][C]400.030542170908[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 24 )[/C][C]40.7655555555556[/C][C]0.101274524433603[/C][C]402.525272604782[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 24 )[/C][C]40.7584722222222[/C][C]0.0962614259060078[/C][C]423.41438264191[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 24 )[/C][C]40.7709722222222[/C][C]0.0946387910510535[/C][C]430.806139527164[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 24 )[/C][C]40.7841666666667[/C][C]0.0929695606200112[/C][C]438.683009736502[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 24 )[/C][C]40.7536111111111[/C][C]0.0863648830173783[/C][C]471.877106611847[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 24 )[/C][C]40.7477777777778[/C][C]0.0847862132948256[/C][C]480.59438196734[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 24 )[/C][C]40.6988888888889[/C][C]0.0782247663283105[/C][C]520.281373779694[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 24 )[/C][C]40.6861111111111[/C][C]0.0757705734095915[/C][C]536.964540193922[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 24 )[/C][C]40.6861111111111[/C][C]0.0757705734095915[/C][C]536.964540193922[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 24 )[/C][C]40.7774285714286[/C][C]0.113494226139708[/C][C]359.290775913418[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 24 )[/C][C]40.7770588235294[/C][C]0.112950698768171[/C][C]361.01643697861[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 24 )[/C][C]40.7737878787879[/C][C]0.112749441700614[/C][C]361.631838382448[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 24 )[/C][C]40.7703125[/C][C]0.112466478416287[/C][C]362.51079498632[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 24 )[/C][C]40.7667741935484[/C][C]0.112539498722869[/C][C]362.24414233386[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 24 )[/C][C]40.764[/C][C]0.112693073494156[/C][C]361.725869532823[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 24 )[/C][C]40.7610344827586[/C][C]0.112859679687493[/C][C]361.1656048965[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 24 )[/C][C]40.7578571428571[/C][C]0.112902875823436[/C][C]360.999282308775[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 24 )[/C][C]40.7544444444444[/C][C]0.112866428376882[/C][C]361.085621566385[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 24 )[/C][C]40.7505769230769[/C][C]0.112687388250435[/C][C]361.625001304613[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 24 )[/C][C]40.7464[/C][C]0.112459610890456[/C][C]362.320300393803[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 24 )[/C][C]40.7422916666667[/C][C]0.112087003782607[/C][C]363.488096672531[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 24 )[/C][C]40.7376086956522[/C][C]0.111663393758053[/C][C]364.825099118162[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 24 )[/C][C]40.7327272727273[/C][C]0.111286140356993[/C][C]366.017970809854[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 24 )[/C][C]40.7266666666667[/C][C]0.110714953852592[/C][C]367.851543531247[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 24 )[/C][C]40.722[/C][C]0.1102672743604[/C][C]369.302680565978[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 24 )[/C][C]40.7168421052632[/C][C]0.109527697584423[/C][C]371.749274414164[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 24 )[/C][C]40.7119444444444[/C][C]0.109342783741137[/C][C]372.333162294713[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 24 )[/C][C]40.705[/C][C]0.109047284058008[/C][C]373.278439271784[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 24 )[/C][C]40.695625[/C][C]0.108565553168016[/C][C]374.848410130783[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 24 )[/C][C]40.6886666666667[/C][C]0.109106858232698[/C][C]372.924922646823[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 24 )[/C][C]40.6814285714286[/C][C]0.109632278930625[/C][C]371.071631167786[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 24 )[/C][C]40.6792307692308[/C][C]0.111469793185865[/C][C]364.935016084602[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 24 )[/C][C]40.6783333333333[/C][C]0.113823004390599[/C][C]357.382354745619[/C][/ROW]
[ROW][C]Median[/C][C]40.72[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]40.755[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]40.7168421052631[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]40.74[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]40.7168421052631[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]40.74[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]40.74[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]40.7168421052631[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]40.74[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]40.7168421052631[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]72[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=209114&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=209114&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 Mean40.77680555555560.114112864946759357.337497175106
Geometric Mean40.7654884099649
Harmonic Mean40.7541941808895
Quadratic Mean40.7881406205012
Winsorized Mean ( 1 / 24 )40.77777777777780.113887972819706358.051660488613
Winsorized Mean ( 2 / 24 )40.78305555555560.113019559930108360.849534193691
Winsorized Mean ( 3 / 24 )40.78305555555560.11288135483559361.291336509519
Winsorized Mean ( 4 / 24 )40.78250.111352783926864366.245894909872
Winsorized Mean ( 5 / 24 )40.77833333333330.110660451491292368.499611051579
Winsorized Mean ( 6 / 24 )40.77833333333330.110150167807038370.206729097037
Winsorized Mean ( 7 / 24 )40.77833333333330.110150167807038370.206729097037
Winsorized Mean ( 8 / 24 )40.77833333333330.109812936688547371.34361909462
Winsorized Mean ( 9 / 24 )40.77958333333330.109635802965374371.954983959142
Winsorized Mean ( 10 / 24 )40.77958333333330.108801163472301374.808338733575
Winsorized Mean ( 11 / 24 )40.77652777777780.108316748409479376.456350255518
Winsorized Mean ( 12 / 24 )40.77819444444440.107097926315879380.756153244008
Winsorized Mean ( 13 / 24 )40.77638888888890.105232491983955387.488580001565
Winsorized Mean ( 14 / 24 )40.78222222222220.104445443340876390.464350743594
Winsorized Mean ( 15 / 24 )40.76555555555560.101906107804486400.030542170908
Winsorized Mean ( 16 / 24 )40.76555555555560.101274524433603402.525272604782
Winsorized Mean ( 17 / 24 )40.75847222222220.0962614259060078423.41438264191
Winsorized Mean ( 18 / 24 )40.77097222222220.0946387910510535430.806139527164
Winsorized Mean ( 19 / 24 )40.78416666666670.0929695606200112438.683009736502
Winsorized Mean ( 20 / 24 )40.75361111111110.0863648830173783471.877106611847
Winsorized Mean ( 21 / 24 )40.74777777777780.0847862132948256480.59438196734
Winsorized Mean ( 22 / 24 )40.69888888888890.0782247663283105520.281373779694
Winsorized Mean ( 23 / 24 )40.68611111111110.0757705734095915536.964540193922
Winsorized Mean ( 24 / 24 )40.68611111111110.0757705734095915536.964540193922
Trimmed Mean ( 1 / 24 )40.77742857142860.113494226139708359.290775913418
Trimmed Mean ( 2 / 24 )40.77705882352940.112950698768171361.01643697861
Trimmed Mean ( 3 / 24 )40.77378787878790.112749441700614361.631838382448
Trimmed Mean ( 4 / 24 )40.77031250.112466478416287362.51079498632
Trimmed Mean ( 5 / 24 )40.76677419354840.112539498722869362.24414233386
Trimmed Mean ( 6 / 24 )40.7640.112693073494156361.725869532823
Trimmed Mean ( 7 / 24 )40.76103448275860.112859679687493361.1656048965
Trimmed Mean ( 8 / 24 )40.75785714285710.112902875823436360.999282308775
Trimmed Mean ( 9 / 24 )40.75444444444440.112866428376882361.085621566385
Trimmed Mean ( 10 / 24 )40.75057692307690.112687388250435361.625001304613
Trimmed Mean ( 11 / 24 )40.74640.112459610890456362.320300393803
Trimmed Mean ( 12 / 24 )40.74229166666670.112087003782607363.488096672531
Trimmed Mean ( 13 / 24 )40.73760869565220.111663393758053364.825099118162
Trimmed Mean ( 14 / 24 )40.73272727272730.111286140356993366.017970809854
Trimmed Mean ( 15 / 24 )40.72666666666670.110714953852592367.851543531247
Trimmed Mean ( 16 / 24 )40.7220.1102672743604369.302680565978
Trimmed Mean ( 17 / 24 )40.71684210526320.109527697584423371.749274414164
Trimmed Mean ( 18 / 24 )40.71194444444440.109342783741137372.333162294713
Trimmed Mean ( 19 / 24 )40.7050.109047284058008373.278439271784
Trimmed Mean ( 20 / 24 )40.6956250.108565553168016374.848410130783
Trimmed Mean ( 21 / 24 )40.68866666666670.109106858232698372.924922646823
Trimmed Mean ( 22 / 24 )40.68142857142860.109632278930625371.071631167786
Trimmed Mean ( 23 / 24 )40.67923076923080.111469793185865364.935016084602
Trimmed Mean ( 24 / 24 )40.67833333333330.113823004390599357.382354745619
Median40.72
Midrange40.755
Midmean - Weighted Average at Xnp40.7168421052631
Midmean - Weighted Average at X(n+1)p40.74
Midmean - Empirical Distribution Function40.7168421052631
Midmean - Empirical Distribution Function - Averaging40.74
Midmean - Empirical Distribution Function - Interpolation40.74
Midmean - Closest Observation40.7168421052631
Midmean - True Basic - Statistics Graphics Toolkit40.74
Midmean - MS Excel (old versions)40.7168421052631
Number of observations72



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')