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Author's title

CPI: Verse schaal- en schelpdieren ( Descriptive Statistics – Central Tende...

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 13 Mar 2017 09:26:09 +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/2017/Mar/13/t1489397400yo2bzgezhu93hbz.htm/, Retrieved Sat, 18 May 2024 23:19:39 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 18 May 2024 23:19:39 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
88,05
93,25
92,96
93,08
90,67
92,17
94,28
95,01
93,27
95,59
97,4
97,05
97,38
96,23
96,65
96,46
97,87
98,59
99,54
97,39
97,09
97,83
97,58
96,81
97,52
98,19
96,18
97,41
99,23
96,93
98,82
102,47
95,95
101,17
100,55
99,5
99,89
100,43
100,63
99,36
100
99,55
100,12
101,31
96,59
98,79
100,93
102,4
106,99
105,27
107,27
109,21
108,57
110,17
108,1
107,58
106,91
103
106,12
109,69




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean99.41666666666670.635736623621713156.380272856238
Geometric Mean99.2981527675166
Harmonic Mean99.180995667233
Quadratic Mean99.5365215050904
Winsorized Mean ( 1 / 20 )99.45233333333330.621612645143771159.990846567047
Winsorized Mean ( 2 / 20 )99.48633333333330.606090834621079164.144262956115
Winsorized Mean ( 3 / 20 )99.49383333333330.589810995852591168.687654236611
Winsorized Mean ( 4 / 20 )99.47050.580277131580272171.418955851511
Winsorized Mean ( 5 / 20 )99.44133333333330.566908180504048175.409946007338
Winsorized Mean ( 6 / 20 )99.41233333333330.559072393898666177.816566187584
Winsorized Mean ( 7 / 20 )99.49750.530448303364591187.572472885473
Winsorized Mean ( 8 / 20 )99.58416666666670.51238940058736194.352511102907
Winsorized Mean ( 9 / 20 )99.55266666666670.471222467562796211.264686044284
Winsorized Mean ( 10 / 20 )99.4710.429821977338746231.423717828198
Winsorized Mean ( 11 / 20 )99.0970.334232006095025296.491653081919
Winsorized Mean ( 12 / 20 )99.0010.312253672407873317.053116578506
Winsorized Mean ( 13 / 20 )99.03566666666670.302042703482356327.886307216992
Winsorized Mean ( 14 / 20 )98.81166666666670.251974145237509392.150022271244
Winsorized Mean ( 15 / 20 )98.79166666666670.243903074972759405.044777224315
Winsorized Mean ( 16 / 20 )98.77033333333330.227155707898536434.813345643293
Winsorized Mean ( 17 / 20 )98.71933333333330.208745901095339472.91627196189
Winsorized Mean ( 18 / 20 )98.73133333333330.199850292368309494.026464326501
Winsorized Mean ( 19 / 20 )98.7060.192225179864687513.49152108731
Winsorized Mean ( 20 / 20 )98.69933333333330.163198064591013604.782498987849
Trimmed Mean ( 1 / 20 )99.42724137931030.598922292512516166.010253120162
Trimmed Mean ( 2 / 20 )99.40035714285710.570894261156258174.113428538478
Trimmed Mean ( 3 / 20 )99.35259259259260.546638299181222181.751978852208
Trimmed Mean ( 4 / 20 )99.29826923076920.524377366991664189.364140181031
Trimmed Mean ( 5 / 20 )99.24660.500185239971867198.419689484604
Trimmed Mean ( 6 / 20 )99.19791666666670.474264731255908209.161487517697
Trimmed Mean ( 7 / 20 )99.15130434782610.443436689346424223.597430546318
Trimmed Mean ( 8 / 20 )99.08386363636360.412324562719834240.305508317944
Trimmed Mean ( 9 / 20 )98.99452380952380.37602499521242263.265806980732
Trimmed Mean ( 10 / 20 )98.90150.340411242620693290.535351413767
Trimmed Mean ( 11 / 20 )98.81157894736840.305469469694559323.474483542237
Trimmed Mean ( 12 / 20 )98.76833333333330.290949049158696339.469517494319
Trimmed Mean ( 13 / 20 )98.73411764705880.277619469761332355.645509055759
Trimmed Mean ( 14 / 20 )98.6906250.261441004223737377.487170740601
Trimmed Mean ( 15 / 20 )98.67333333333330.254887549392372387.124963806828
Trimmed Mean ( 16 / 20 )98.65642857142860.247170878002908399.142606801225
Trimmed Mean ( 17 / 20 )98.640.240516111726429410.11805526025
Trimmed Mean ( 18 / 20 )98.62833333333330.235883066912483418.123838325056
Trimmed Mean ( 19 / 20 )98.61272727272730.230397907091811428.010516751054
Trimmed Mean ( 20 / 20 )98.5980.22301121048055442.121271785121
Median98.69
Midrange99.11
Midmean - Weighted Average at Xnp98.6061290322581
Midmean - Weighted Average at X(n+1)p98.6733333333333
Midmean - Empirical Distribution Function98.6061290322581
Midmean - Empirical Distribution Function - Averaging98.6733333333333
Midmean - Empirical Distribution Function - Interpolation98.6733333333333
Midmean - Closest Observation98.6061290322581
Midmean - True Basic - Statistics Graphics Toolkit98.6733333333333
Midmean - MS Excel (old versions)98.690625
Number of observations60

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 99.4166666666667 & 0.635736623621713 & 156.380272856238 \tabularnewline
Geometric Mean & 99.2981527675166 &  &  \tabularnewline
Harmonic Mean & 99.180995667233 &  &  \tabularnewline
Quadratic Mean & 99.5365215050904 &  &  \tabularnewline
Winsorized Mean ( 1 / 20 ) & 99.4523333333333 & 0.621612645143771 & 159.990846567047 \tabularnewline
Winsorized Mean ( 2 / 20 ) & 99.4863333333333 & 0.606090834621079 & 164.144262956115 \tabularnewline
Winsorized Mean ( 3 / 20 ) & 99.4938333333333 & 0.589810995852591 & 168.687654236611 \tabularnewline
Winsorized Mean ( 4 / 20 ) & 99.4705 & 0.580277131580272 & 171.418955851511 \tabularnewline
Winsorized Mean ( 5 / 20 ) & 99.4413333333333 & 0.566908180504048 & 175.409946007338 \tabularnewline
Winsorized Mean ( 6 / 20 ) & 99.4123333333333 & 0.559072393898666 & 177.816566187584 \tabularnewline
Winsorized Mean ( 7 / 20 ) & 99.4975 & 0.530448303364591 & 187.572472885473 \tabularnewline
Winsorized Mean ( 8 / 20 ) & 99.5841666666667 & 0.51238940058736 & 194.352511102907 \tabularnewline
Winsorized Mean ( 9 / 20 ) & 99.5526666666667 & 0.471222467562796 & 211.264686044284 \tabularnewline
Winsorized Mean ( 10 / 20 ) & 99.471 & 0.429821977338746 & 231.423717828198 \tabularnewline
Winsorized Mean ( 11 / 20 ) & 99.097 & 0.334232006095025 & 296.491653081919 \tabularnewline
Winsorized Mean ( 12 / 20 ) & 99.001 & 0.312253672407873 & 317.053116578506 \tabularnewline
Winsorized Mean ( 13 / 20 ) & 99.0356666666667 & 0.302042703482356 & 327.886307216992 \tabularnewline
Winsorized Mean ( 14 / 20 ) & 98.8116666666667 & 0.251974145237509 & 392.150022271244 \tabularnewline
Winsorized Mean ( 15 / 20 ) & 98.7916666666667 & 0.243903074972759 & 405.044777224315 \tabularnewline
Winsorized Mean ( 16 / 20 ) & 98.7703333333333 & 0.227155707898536 & 434.813345643293 \tabularnewline
Winsorized Mean ( 17 / 20 ) & 98.7193333333333 & 0.208745901095339 & 472.91627196189 \tabularnewline
Winsorized Mean ( 18 / 20 ) & 98.7313333333333 & 0.199850292368309 & 494.026464326501 \tabularnewline
Winsorized Mean ( 19 / 20 ) & 98.706 & 0.192225179864687 & 513.49152108731 \tabularnewline
Winsorized Mean ( 20 / 20 ) & 98.6993333333333 & 0.163198064591013 & 604.782498987849 \tabularnewline
Trimmed Mean ( 1 / 20 ) & 99.4272413793103 & 0.598922292512516 & 166.010253120162 \tabularnewline
Trimmed Mean ( 2 / 20 ) & 99.4003571428571 & 0.570894261156258 & 174.113428538478 \tabularnewline
Trimmed Mean ( 3 / 20 ) & 99.3525925925926 & 0.546638299181222 & 181.751978852208 \tabularnewline
Trimmed Mean ( 4 / 20 ) & 99.2982692307692 & 0.524377366991664 & 189.364140181031 \tabularnewline
Trimmed Mean ( 5 / 20 ) & 99.2466 & 0.500185239971867 & 198.419689484604 \tabularnewline
Trimmed Mean ( 6 / 20 ) & 99.1979166666667 & 0.474264731255908 & 209.161487517697 \tabularnewline
Trimmed Mean ( 7 / 20 ) & 99.1513043478261 & 0.443436689346424 & 223.597430546318 \tabularnewline
Trimmed Mean ( 8 / 20 ) & 99.0838636363636 & 0.412324562719834 & 240.305508317944 \tabularnewline
Trimmed Mean ( 9 / 20 ) & 98.9945238095238 & 0.37602499521242 & 263.265806980732 \tabularnewline
Trimmed Mean ( 10 / 20 ) & 98.9015 & 0.340411242620693 & 290.535351413767 \tabularnewline
Trimmed Mean ( 11 / 20 ) & 98.8115789473684 & 0.305469469694559 & 323.474483542237 \tabularnewline
Trimmed Mean ( 12 / 20 ) & 98.7683333333333 & 0.290949049158696 & 339.469517494319 \tabularnewline
Trimmed Mean ( 13 / 20 ) & 98.7341176470588 & 0.277619469761332 & 355.645509055759 \tabularnewline
Trimmed Mean ( 14 / 20 ) & 98.690625 & 0.261441004223737 & 377.487170740601 \tabularnewline
Trimmed Mean ( 15 / 20 ) & 98.6733333333333 & 0.254887549392372 & 387.124963806828 \tabularnewline
Trimmed Mean ( 16 / 20 ) & 98.6564285714286 & 0.247170878002908 & 399.142606801225 \tabularnewline
Trimmed Mean ( 17 / 20 ) & 98.64 & 0.240516111726429 & 410.11805526025 \tabularnewline
Trimmed Mean ( 18 / 20 ) & 98.6283333333333 & 0.235883066912483 & 418.123838325056 \tabularnewline
Trimmed Mean ( 19 / 20 ) & 98.6127272727273 & 0.230397907091811 & 428.010516751054 \tabularnewline
Trimmed Mean ( 20 / 20 ) & 98.598 & 0.22301121048055 & 442.121271785121 \tabularnewline
Median & 98.69 &  &  \tabularnewline
Midrange & 99.11 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 98.6061290322581 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 98.6733333333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 98.6061290322581 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 98.6733333333333 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 98.6733333333333 &  &  \tabularnewline
Midmean - Closest Observation & 98.6061290322581 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 98.6733333333333 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 98.690625 &  &  \tabularnewline
Number of observations & 60 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]99.4166666666667[/C][C]0.635736623621713[/C][C]156.380272856238[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]99.2981527675166[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]99.180995667233[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]99.5365215050904[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 20 )[/C][C]99.4523333333333[/C][C]0.621612645143771[/C][C]159.990846567047[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 20 )[/C][C]99.4863333333333[/C][C]0.606090834621079[/C][C]164.144262956115[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 20 )[/C][C]99.4938333333333[/C][C]0.589810995852591[/C][C]168.687654236611[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 20 )[/C][C]99.4705[/C][C]0.580277131580272[/C][C]171.418955851511[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 20 )[/C][C]99.4413333333333[/C][C]0.566908180504048[/C][C]175.409946007338[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 20 )[/C][C]99.4123333333333[/C][C]0.559072393898666[/C][C]177.816566187584[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 20 )[/C][C]99.4975[/C][C]0.530448303364591[/C][C]187.572472885473[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 20 )[/C][C]99.5841666666667[/C][C]0.51238940058736[/C][C]194.352511102907[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 20 )[/C][C]99.5526666666667[/C][C]0.471222467562796[/C][C]211.264686044284[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 20 )[/C][C]99.471[/C][C]0.429821977338746[/C][C]231.423717828198[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 20 )[/C][C]99.097[/C][C]0.334232006095025[/C][C]296.491653081919[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 20 )[/C][C]99.001[/C][C]0.312253672407873[/C][C]317.053116578506[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 20 )[/C][C]99.0356666666667[/C][C]0.302042703482356[/C][C]327.886307216992[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 20 )[/C][C]98.8116666666667[/C][C]0.251974145237509[/C][C]392.150022271244[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 20 )[/C][C]98.7916666666667[/C][C]0.243903074972759[/C][C]405.044777224315[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 20 )[/C][C]98.7703333333333[/C][C]0.227155707898536[/C][C]434.813345643293[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 20 )[/C][C]98.7193333333333[/C][C]0.208745901095339[/C][C]472.91627196189[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 20 )[/C][C]98.7313333333333[/C][C]0.199850292368309[/C][C]494.026464326501[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 20 )[/C][C]98.706[/C][C]0.192225179864687[/C][C]513.49152108731[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 20 )[/C][C]98.6993333333333[/C][C]0.163198064591013[/C][C]604.782498987849[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 20 )[/C][C]99.4272413793103[/C][C]0.598922292512516[/C][C]166.010253120162[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 20 )[/C][C]99.4003571428571[/C][C]0.570894261156258[/C][C]174.113428538478[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 20 )[/C][C]99.3525925925926[/C][C]0.546638299181222[/C][C]181.751978852208[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 20 )[/C][C]99.2982692307692[/C][C]0.524377366991664[/C][C]189.364140181031[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 20 )[/C][C]99.2466[/C][C]0.500185239971867[/C][C]198.419689484604[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 20 )[/C][C]99.1979166666667[/C][C]0.474264731255908[/C][C]209.161487517697[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 20 )[/C][C]99.1513043478261[/C][C]0.443436689346424[/C][C]223.597430546318[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 20 )[/C][C]99.0838636363636[/C][C]0.412324562719834[/C][C]240.305508317944[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 20 )[/C][C]98.9945238095238[/C][C]0.37602499521242[/C][C]263.265806980732[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 20 )[/C][C]98.9015[/C][C]0.340411242620693[/C][C]290.535351413767[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 20 )[/C][C]98.8115789473684[/C][C]0.305469469694559[/C][C]323.474483542237[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 20 )[/C][C]98.7683333333333[/C][C]0.290949049158696[/C][C]339.469517494319[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 20 )[/C][C]98.7341176470588[/C][C]0.277619469761332[/C][C]355.645509055759[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 20 )[/C][C]98.690625[/C][C]0.261441004223737[/C][C]377.487170740601[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 20 )[/C][C]98.6733333333333[/C][C]0.254887549392372[/C][C]387.124963806828[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 20 )[/C][C]98.6564285714286[/C][C]0.247170878002908[/C][C]399.142606801225[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 20 )[/C][C]98.64[/C][C]0.240516111726429[/C][C]410.11805526025[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 20 )[/C][C]98.6283333333333[/C][C]0.235883066912483[/C][C]418.123838325056[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 20 )[/C][C]98.6127272727273[/C][C]0.230397907091811[/C][C]428.010516751054[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 20 )[/C][C]98.598[/C][C]0.22301121048055[/C][C]442.121271785121[/C][/ROW]
[ROW][C]Median[/C][C]98.69[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]99.11[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]98.6061290322581[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]98.6733333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]98.6061290322581[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]98.6733333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]98.6733333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]98.6061290322581[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]98.6733333333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]98.690625[/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=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Mean99.41666666666670.635736623621713156.380272856238
Geometric Mean99.2981527675166
Harmonic Mean99.180995667233
Quadratic Mean99.5365215050904
Winsorized Mean ( 1 / 20 )99.45233333333330.621612645143771159.990846567047
Winsorized Mean ( 2 / 20 )99.48633333333330.606090834621079164.144262956115
Winsorized Mean ( 3 / 20 )99.49383333333330.589810995852591168.687654236611
Winsorized Mean ( 4 / 20 )99.47050.580277131580272171.418955851511
Winsorized Mean ( 5 / 20 )99.44133333333330.566908180504048175.409946007338
Winsorized Mean ( 6 / 20 )99.41233333333330.559072393898666177.816566187584
Winsorized Mean ( 7 / 20 )99.49750.530448303364591187.572472885473
Winsorized Mean ( 8 / 20 )99.58416666666670.51238940058736194.352511102907
Winsorized Mean ( 9 / 20 )99.55266666666670.471222467562796211.264686044284
Winsorized Mean ( 10 / 20 )99.4710.429821977338746231.423717828198
Winsorized Mean ( 11 / 20 )99.0970.334232006095025296.491653081919
Winsorized Mean ( 12 / 20 )99.0010.312253672407873317.053116578506
Winsorized Mean ( 13 / 20 )99.03566666666670.302042703482356327.886307216992
Winsorized Mean ( 14 / 20 )98.81166666666670.251974145237509392.150022271244
Winsorized Mean ( 15 / 20 )98.79166666666670.243903074972759405.044777224315
Winsorized Mean ( 16 / 20 )98.77033333333330.227155707898536434.813345643293
Winsorized Mean ( 17 / 20 )98.71933333333330.208745901095339472.91627196189
Winsorized Mean ( 18 / 20 )98.73133333333330.199850292368309494.026464326501
Winsorized Mean ( 19 / 20 )98.7060.192225179864687513.49152108731
Winsorized Mean ( 20 / 20 )98.69933333333330.163198064591013604.782498987849
Trimmed Mean ( 1 / 20 )99.42724137931030.598922292512516166.010253120162
Trimmed Mean ( 2 / 20 )99.40035714285710.570894261156258174.113428538478
Trimmed Mean ( 3 / 20 )99.35259259259260.546638299181222181.751978852208
Trimmed Mean ( 4 / 20 )99.29826923076920.524377366991664189.364140181031
Trimmed Mean ( 5 / 20 )99.24660.500185239971867198.419689484604
Trimmed Mean ( 6 / 20 )99.19791666666670.474264731255908209.161487517697
Trimmed Mean ( 7 / 20 )99.15130434782610.443436689346424223.597430546318
Trimmed Mean ( 8 / 20 )99.08386363636360.412324562719834240.305508317944
Trimmed Mean ( 9 / 20 )98.99452380952380.37602499521242263.265806980732
Trimmed Mean ( 10 / 20 )98.90150.340411242620693290.535351413767
Trimmed Mean ( 11 / 20 )98.81157894736840.305469469694559323.474483542237
Trimmed Mean ( 12 / 20 )98.76833333333330.290949049158696339.469517494319
Trimmed Mean ( 13 / 20 )98.73411764705880.277619469761332355.645509055759
Trimmed Mean ( 14 / 20 )98.6906250.261441004223737377.487170740601
Trimmed Mean ( 15 / 20 )98.67333333333330.254887549392372387.124963806828
Trimmed Mean ( 16 / 20 )98.65642857142860.247170878002908399.142606801225
Trimmed Mean ( 17 / 20 )98.640.240516111726429410.11805526025
Trimmed Mean ( 18 / 20 )98.62833333333330.235883066912483418.123838325056
Trimmed Mean ( 19 / 20 )98.61272727272730.230397907091811428.010516751054
Trimmed Mean ( 20 / 20 )98.5980.22301121048055442.121271785121
Median98.69
Midrange99.11
Midmean - Weighted Average at Xnp98.6061290322581
Midmean - Weighted Average at X(n+1)p98.6733333333333
Midmean - Empirical Distribution Function98.6061290322581
Midmean - Empirical Distribution Function - Averaging98.6733333333333
Midmean - Empirical Distribution Function - Interpolation98.6733333333333
Midmean - Closest Observation98.6061290322581
Midmean - True Basic - Statistics Graphics Toolkit98.6733333333333
Midmean - MS Excel (old versions)98.690625
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')