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central tendancy Gemiddelde consumptieprijzen per product - vervoersdienste...

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 20 Oct 2008 13:17:40 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/20/t1224530317wmdk791iiobwzeh.htm/, Retrieved Sun, 19 May 2024 15:55:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=17938, Retrieved Sun, 19 May 2024 15:55:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [central tendancy ...] [2008-10-20 19:17:40] [2fdb1a8e4a6fa49ce74bdce2c154874d] [Current]
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Dataseries X:
267,67
267,67
267,67
267,67
267,67
267,67
267,67
267,67
267,67
267,67
267,67
267,67
267,67
285,68
285,68
285,68
285,68
285,68
285,68
285,68
285,68
285,68
285,68
285,68
285,68
292,96
292,96
292,96
292,96
292,96
292,96
292,96
292,96
292,96
292,96
292,96
292,96
302,09
302,09
302,09
302,09
302,09
302,09
302,09
302,09
302,09
302,09
302,09
302,09
348,33
348,33
348,33
348,33
348,33
348,33
348,33
348,33
348,33
348,33
348,33




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17938&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17938&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17938&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean298.0016666666673.4506184917370886.361812347632
Geometric Mean296.876963081449
Harmonic Mean295.805419276297
Quadratic Mean299.178028348785
Winsorized Mean ( 1 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 2 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 3 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 4 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 5 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 6 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 7 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 8 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 9 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 10 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 11 / 20 )289.5243333333331.69408696417408170.902875387206
Winsorized Mean ( 12 / 20 )289.5243333333331.69408696417408170.902875387206
Winsorized Mean ( 13 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 14 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 15 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 16 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 17 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 18 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 19 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 20 / 20 )293.42650.955080285470762307.227051446643
Trimmed Mean ( 1 / 20 )297.6568965517243.4209645658221687.009640358607
Trimmed Mean ( 2 / 20 )297.28753.3813609825269887.9194802140968
Trimmed Mean ( 3 / 20 )296.8907407407413.3293719002694989.173198319091
Trimmed Mean ( 4 / 20 )296.4634615384623.2617763309165290.8901872665066
Trimmed Mean ( 5 / 20 )296.0023.1742117517421593.2521278196205
Trimmed Mean ( 6 / 20 )295.5020833333333.0605844560505496.5508671878497
Trimmed Mean ( 7 / 20 )294.9586956521742.91202369344384101.289936725531
Trimmed Mean ( 8 / 20 )294.3659090909092.71484109849594108.428411981089
Trimmed Mean ( 9 / 20 )293.7166666666672.44595792726673120.082468873406
Trimmed Mean ( 10 / 20 )293.00252.06011895194279142.226010650349
Trimmed Mean ( 11 / 20 )292.2131578947371.43474375095525203.669232014554
Trimmed Mean ( 12 / 20 )292.6205555555561.31786948943424222.040617755843
Trimmed Mean ( 13 / 20 )293.0758823529411.14426930795811256.124917722314
Trimmed Mean ( 14 / 20 )293.02531251.15922752925891252.776357620948
Trimmed Mean ( 15 / 20 )292.9681.17289174030801249.782643983037
Trimmed Mean ( 16 / 20 )292.90251.18432851345299247.315247984719
Trimmed Mean ( 17 / 20 )292.8269230769231.19206876017874245.646000347343
Trimmed Mean ( 18 / 20 )292.738751.19373247198604245.229778756846
Trimmed Mean ( 19 / 20 )292.6345454545451.18530663964570246.885097633483
Trimmed Mean ( 20 / 20 )292.50951.15963208208012252.243366253980
Median292.96
Midrange308
Midmean - Weighted Average at Xnp293.576666666667
Midmean - Weighted Average at X(n+1)p293.576666666667
Midmean - Empirical Distribution Function293.576666666667
Midmean - Empirical Distribution Function - Averaging293.576666666667
Midmean - Empirical Distribution Function - Interpolation293.576666666667
Midmean - Closest Observation293.576666666667
Midmean - True Basic - Statistics Graphics Toolkit293.576666666667
Midmean - MS Excel (old versions)293.576666666667
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Geometric Mean & 296.876963081449 &  &  \tabularnewline
Harmonic Mean & 295.805419276297 &  &  \tabularnewline
Quadratic Mean & 299.178028348785 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 298.001666666667 & 3.45061849173708 & 86.361812347632 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 289.524333333333 & 1.69408696417408 & 170.902875387206 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 289.524333333333 & 1.69408696417408 & 170.902875387206 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 293.4265 & 0.955080285470762 & 307.227051446643 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 297.656896551724 & 3.42096456582216 & 87.009640358607 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 297.2875 & 3.38136098252698 & 87.9194802140968 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 296.890740740741 & 3.32937190026949 & 89.173198319091 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 296.463461538462 & 3.26177633091652 & 90.8901872665066 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 296.002 & 3.17421175174215 & 93.2521278196205 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 295.502083333333 & 3.06058445605054 & 96.5508671878497 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 294.958695652174 & 2.91202369344384 & 101.289936725531 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 294.365909090909 & 2.71484109849594 & 108.428411981089 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 293.716666666667 & 2.44595792726673 & 120.082468873406 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 293.0025 & 2.06011895194279 & 142.226010650349 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 292.213157894737 & 1.43474375095525 & 203.669232014554 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 292.620555555556 & 1.31786948943424 & 222.040617755843 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 293.075882352941 & 1.14426930795811 & 256.124917722314 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 293.0253125 & 1.15922752925891 & 252.776357620948 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 292.968 & 1.17289174030801 & 249.782643983037 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 292.9025 & 1.18432851345299 & 247.315247984719 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 292.826923076923 & 1.19206876017874 & 245.646000347343 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 292.73875 & 1.19373247198604 & 245.229778756846 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 292.634545454545 & 1.18530663964570 & 246.885097633483 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 292.5095 & 1.15963208208012 & 252.243366253980 \tabularnewline
Median & 292.96 &  &  \tabularnewline
Midrange & 308 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 293.576666666667 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 293.576666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 293.576666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 293.576666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 293.576666666667 &  &  \tabularnewline
Midmean - Closest Observation & 293.576666666667 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 293.576666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 293.576666666667 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=17938&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]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]296.876963081449[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]295.805419276297[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]299.178028348785[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]298.001666666667[/C][C]3.45061849173708[/C][C]86.361812347632[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]289.524333333333[/C][C]1.69408696417408[/C][C]170.902875387206[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]289.524333333333[/C][C]1.69408696417408[/C][C]170.902875387206[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]293.4265[/C][C]0.955080285470762[/C][C]307.227051446643[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]297.656896551724[/C][C]3.42096456582216[/C][C]87.009640358607[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]297.2875[/C][C]3.38136098252698[/C][C]87.9194802140968[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]296.890740740741[/C][C]3.32937190026949[/C][C]89.173198319091[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]296.463461538462[/C][C]3.26177633091652[/C][C]90.8901872665066[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]296.002[/C][C]3.17421175174215[/C][C]93.2521278196205[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]295.502083333333[/C][C]3.06058445605054[/C][C]96.5508671878497[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]294.958695652174[/C][C]2.91202369344384[/C][C]101.289936725531[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]294.365909090909[/C][C]2.71484109849594[/C][C]108.428411981089[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]293.716666666667[/C][C]2.44595792726673[/C][C]120.082468873406[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]293.0025[/C][C]2.06011895194279[/C][C]142.226010650349[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]292.213157894737[/C][C]1.43474375095525[/C][C]203.669232014554[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]292.620555555556[/C][C]1.31786948943424[/C][C]222.040617755843[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]293.075882352941[/C][C]1.14426930795811[/C][C]256.124917722314[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]293.0253125[/C][C]1.15922752925891[/C][C]252.776357620948[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]292.968[/C][C]1.17289174030801[/C][C]249.782643983037[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]292.9025[/C][C]1.18432851345299[/C][C]247.315247984719[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]292.826923076923[/C][C]1.19206876017874[/C][C]245.646000347343[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]292.73875[/C][C]1.19373247198604[/C][C]245.229778756846[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]292.634545454545[/C][C]1.18530663964570[/C][C]246.885097633483[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]292.5095[/C][C]1.15963208208012[/C][C]252.243366253980[/C][/ROW]
[ROW][C]Median[/C][C]292.96[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]308[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]293.576666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]60[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=17938&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=17938&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 Mean298.0016666666673.4506184917370886.361812347632
Geometric Mean296.876963081449
Harmonic Mean295.805419276297
Quadratic Mean299.178028348785
Winsorized Mean ( 1 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 2 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 3 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 4 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 5 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 6 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 7 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 8 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 9 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 10 / 20 )298.0016666666673.4506184917370886.361812347632
Winsorized Mean ( 11 / 20 )289.5243333333331.69408696417408170.902875387206
Winsorized Mean ( 12 / 20 )289.5243333333331.69408696417408170.902875387206
Winsorized Mean ( 13 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 14 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 15 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 16 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 17 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 18 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 19 / 20 )293.42650.955080285470762307.227051446643
Winsorized Mean ( 20 / 20 )293.42650.955080285470762307.227051446643
Trimmed Mean ( 1 / 20 )297.6568965517243.4209645658221687.009640358607
Trimmed Mean ( 2 / 20 )297.28753.3813609825269887.9194802140968
Trimmed Mean ( 3 / 20 )296.8907407407413.3293719002694989.173198319091
Trimmed Mean ( 4 / 20 )296.4634615384623.2617763309165290.8901872665066
Trimmed Mean ( 5 / 20 )296.0023.1742117517421593.2521278196205
Trimmed Mean ( 6 / 20 )295.5020833333333.0605844560505496.5508671878497
Trimmed Mean ( 7 / 20 )294.9586956521742.91202369344384101.289936725531
Trimmed Mean ( 8 / 20 )294.3659090909092.71484109849594108.428411981089
Trimmed Mean ( 9 / 20 )293.7166666666672.44595792726673120.082468873406
Trimmed Mean ( 10 / 20 )293.00252.06011895194279142.226010650349
Trimmed Mean ( 11 / 20 )292.2131578947371.43474375095525203.669232014554
Trimmed Mean ( 12 / 20 )292.6205555555561.31786948943424222.040617755843
Trimmed Mean ( 13 / 20 )293.0758823529411.14426930795811256.124917722314
Trimmed Mean ( 14 / 20 )293.02531251.15922752925891252.776357620948
Trimmed Mean ( 15 / 20 )292.9681.17289174030801249.782643983037
Trimmed Mean ( 16 / 20 )292.90251.18432851345299247.315247984719
Trimmed Mean ( 17 / 20 )292.8269230769231.19206876017874245.646000347343
Trimmed Mean ( 18 / 20 )292.738751.19373247198604245.229778756846
Trimmed Mean ( 19 / 20 )292.6345454545451.18530663964570246.885097633483
Trimmed Mean ( 20 / 20 )292.50951.15963208208012252.243366253980
Median292.96
Midrange308
Midmean - Weighted Average at Xnp293.576666666667
Midmean - Weighted Average at X(n+1)p293.576666666667
Midmean - Empirical Distribution Function293.576666666667
Midmean - Empirical Distribution Function - Averaging293.576666666667
Midmean - Empirical Distribution Function - Interpolation293.576666666667
Midmean - Closest Observation293.576666666667
Midmean - True Basic - Statistics Graphics Toolkit293.576666666667
Midmean - MS Excel (old versions)293.576666666667
Number of observations60



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')