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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationThu, 25 Nov 2010 16:23:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/25/t1290702146ig8fush7r60xq82.htm/, Retrieved Fri, 26 Apr 2024 08:21:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=101151, Retrieved Fri, 26 Apr 2024 08:21:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-06 21:28:17] [74be16979710d4c4e7c6647856088456]
- RM D    [Central Tendency] [workshop 3 onderd...] [2010-11-25 16:23:39] [531024149246456e4f6d79ace2e85c12] [Current]
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Dataseries X:
10788500
10708433
10625700
10547958
10478617
10421137
10376133
10332785
10286570
10251250
10226419
10203008
10181245
10156637
10136811
10115603
10084475
10045158
10004486
9967379
9937697
9901664
9870234
9861823
9858308
9855372
9855520
9856303
9858982
9859242
9848382
9839534
9830358
9818227
9800700
9772419
9741720
9711115
9673162
9655549
9646032
9618756
9580991
9527807
9463667
9378113
9289770
9220578
9183948
9153489




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101151&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101151&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101151&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean9928155.3253987.1943398254183.898338141202
Geometric Mean9920972.98447631
Harmonic Mean9913799.21235882
Quadratic Mean9935345.20278616
Winsorized Mean ( 1 / 16 )9927163.1653311.3294323101186.211134963434
Winsorized Mean ( 2 / 16 )9925319.0451949.3458929334191.05763257262
Winsorized Mean ( 3 / 16 )9924806.0449590.6169690784200.134756262228
Winsorized Mean ( 4 / 16 )9926326.246427.2927636848213.803683331808
Winsorized Mean ( 5 / 16 )9929133.643081.3523114925230.474046594663
Winsorized Mean ( 6 / 16 )9931429.9240202.616958102247.034413962411
Winsorized Mean ( 7 / 16 )9932806.9637374.3665025824265.765225995568
Winsorized Mean ( 8 / 16 )9931454.9634654.7387808971286.58288330468
Winsorized Mean ( 9 / 16 )9930007.0432456.2823872103305.950229343365
Winsorized Mean ( 10 / 16 )9926944.2431127.5856795021318.911474285557
Winsorized Mean ( 11 / 16 )9925668.6829442.6185454592337.119086900332
Winsorized Mean ( 12 / 16 )9929554.2826887.3763288313369.301718344031
Winsorized Mean ( 13 / 16 )9931113.524380.1176729385407.344773032961
Winsorized Mean ( 14 / 16 )9934157.9422006.4705875973451.419863101484
Winsorized Mean ( 15 / 16 )9936279.8419575.6645109064507.583271794636
Winsorized Mean ( 16 / 16 )9931927.5216947.2479510533586.049578591472
Trimmed Mean ( 1 / 16 )9926370.3541666750705.8257918427195.763902848488
Trimmed Mean ( 2 / 16 )9925508.6086956547332.2673975351209.698566209244
Trimmed Mean ( 3 / 16 )9925616.3181818243924.2781522397225.97107421504
Trimmed Mean ( 4 / 16 )9925937.8571428640744.3904067467243.61483281633
Trimmed Mean ( 5 / 16 )9925816.538004.1707721767261.177031318542
Trimmed Mean ( 6 / 16 )9924943.5789473735722.3866056252277.83540020768
Trimmed Mean ( 7 / 16 )9923442.1111111133721.6722450066294.274911368921
Trimmed Mean ( 8 / 16 )9921474.7058823531984.9078453599310.192380539301
Trimmed Mean ( 9 / 16 )9919525.437530499.6982522731325.233559868439
Trimmed Mean ( 10 / 16 )9917584.429121.9565271497340.553506106435
Trimmed Mean ( 11 / 16 )991591327547.8728334059359.952039127155
Trimmed Mean ( 12 / 16 )9914207.4615384625788.7890847185384.438657781465
Trimmed Mean ( 13 / 16 )9911543.0833333324060.7661749083411.937966201158
Trimmed Mean ( 14 / 16 )9908121.6818181822331.4106953046443.685435595945
Trimmed Mean ( 15 / 16 )9903472.3520471.3735720826483.771756454371
Trimmed Mean ( 16 / 16 )9897396.8888888918348.7761127514539.403654394734
Median9859112
Midrange9970994.5
Midmean - Weighted Average at Xnp9903525.96
Midmean - Weighted Average at X(n+1)p9914207.46153846
Midmean - Empirical Distribution Function9914207.46153846
Midmean - Empirical Distribution Function - Averaging9914207.46153846
Midmean - Empirical Distribution Function - Interpolation9911543.08333333
Midmean - Closest Observation9914207.46153846
Midmean - True Basic - Statistics Graphics Toolkit9914207.46153846
Midmean - MS Excel (old versions)9914207.46153846
Number of observations50

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 9928155.32 & 53987.1943398254 & 183.898338141202 \tabularnewline
Geometric Mean & 9920972.98447631 &  &  \tabularnewline
Harmonic Mean & 9913799.21235882 &  &  \tabularnewline
Quadratic Mean & 9935345.20278616 &  &  \tabularnewline
Winsorized Mean ( 1 / 16 ) & 9927163.16 & 53311.3294323101 & 186.211134963434 \tabularnewline
Winsorized Mean ( 2 / 16 ) & 9925319.04 & 51949.3458929334 & 191.05763257262 \tabularnewline
Winsorized Mean ( 3 / 16 ) & 9924806.04 & 49590.6169690784 & 200.134756262228 \tabularnewline
Winsorized Mean ( 4 / 16 ) & 9926326.2 & 46427.2927636848 & 213.803683331808 \tabularnewline
Winsorized Mean ( 5 / 16 ) & 9929133.6 & 43081.3523114925 & 230.474046594663 \tabularnewline
Winsorized Mean ( 6 / 16 ) & 9931429.92 & 40202.616958102 & 247.034413962411 \tabularnewline
Winsorized Mean ( 7 / 16 ) & 9932806.96 & 37374.3665025824 & 265.765225995568 \tabularnewline
Winsorized Mean ( 8 / 16 ) & 9931454.96 & 34654.7387808971 & 286.58288330468 \tabularnewline
Winsorized Mean ( 9 / 16 ) & 9930007.04 & 32456.2823872103 & 305.950229343365 \tabularnewline
Winsorized Mean ( 10 / 16 ) & 9926944.24 & 31127.5856795021 & 318.911474285557 \tabularnewline
Winsorized Mean ( 11 / 16 ) & 9925668.68 & 29442.6185454592 & 337.119086900332 \tabularnewline
Winsorized Mean ( 12 / 16 ) & 9929554.28 & 26887.3763288313 & 369.301718344031 \tabularnewline
Winsorized Mean ( 13 / 16 ) & 9931113.5 & 24380.1176729385 & 407.344773032961 \tabularnewline
Winsorized Mean ( 14 / 16 ) & 9934157.94 & 22006.4705875973 & 451.419863101484 \tabularnewline
Winsorized Mean ( 15 / 16 ) & 9936279.84 & 19575.6645109064 & 507.583271794636 \tabularnewline
Winsorized Mean ( 16 / 16 ) & 9931927.52 & 16947.2479510533 & 586.049578591472 \tabularnewline
Trimmed Mean ( 1 / 16 ) & 9926370.35416667 & 50705.8257918427 & 195.763902848488 \tabularnewline
Trimmed Mean ( 2 / 16 ) & 9925508.60869565 & 47332.2673975351 & 209.698566209244 \tabularnewline
Trimmed Mean ( 3 / 16 ) & 9925616.31818182 & 43924.2781522397 & 225.97107421504 \tabularnewline
Trimmed Mean ( 4 / 16 ) & 9925937.85714286 & 40744.3904067467 & 243.61483281633 \tabularnewline
Trimmed Mean ( 5 / 16 ) & 9925816.5 & 38004.1707721767 & 261.177031318542 \tabularnewline
Trimmed Mean ( 6 / 16 ) & 9924943.57894737 & 35722.3866056252 & 277.83540020768 \tabularnewline
Trimmed Mean ( 7 / 16 ) & 9923442.11111111 & 33721.6722450066 & 294.274911368921 \tabularnewline
Trimmed Mean ( 8 / 16 ) & 9921474.70588235 & 31984.9078453599 & 310.192380539301 \tabularnewline
Trimmed Mean ( 9 / 16 ) & 9919525.4375 & 30499.6982522731 & 325.233559868439 \tabularnewline
Trimmed Mean ( 10 / 16 ) & 9917584.4 & 29121.9565271497 & 340.553506106435 \tabularnewline
Trimmed Mean ( 11 / 16 ) & 9915913 & 27547.8728334059 & 359.952039127155 \tabularnewline
Trimmed Mean ( 12 / 16 ) & 9914207.46153846 & 25788.7890847185 & 384.438657781465 \tabularnewline
Trimmed Mean ( 13 / 16 ) & 9911543.08333333 & 24060.7661749083 & 411.937966201158 \tabularnewline
Trimmed Mean ( 14 / 16 ) & 9908121.68181818 & 22331.4106953046 & 443.685435595945 \tabularnewline
Trimmed Mean ( 15 / 16 ) & 9903472.35 & 20471.3735720826 & 483.771756454371 \tabularnewline
Trimmed Mean ( 16 / 16 ) & 9897396.88888889 & 18348.7761127514 & 539.403654394734 \tabularnewline
Median & 9859112 &  &  \tabularnewline
Midrange & 9970994.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 9903525.96 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 9914207.46153846 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 9914207.46153846 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 9914207.46153846 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 9911543.08333333 &  &  \tabularnewline
Midmean - Closest Observation & 9914207.46153846 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 9914207.46153846 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 9914207.46153846 &  &  \tabularnewline
Number of observations & 50 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101151&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]9928155.32[/C][C]53987.1943398254[/C][C]183.898338141202[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]9920972.98447631[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]9913799.21235882[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]9935345.20278616[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 16 )[/C][C]9927163.16[/C][C]53311.3294323101[/C][C]186.211134963434[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 16 )[/C][C]9925319.04[/C][C]51949.3458929334[/C][C]191.05763257262[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 16 )[/C][C]9924806.04[/C][C]49590.6169690784[/C][C]200.134756262228[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 16 )[/C][C]9926326.2[/C][C]46427.2927636848[/C][C]213.803683331808[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 16 )[/C][C]9929133.6[/C][C]43081.3523114925[/C][C]230.474046594663[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 16 )[/C][C]9931429.92[/C][C]40202.616958102[/C][C]247.034413962411[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 16 )[/C][C]9932806.96[/C][C]37374.3665025824[/C][C]265.765225995568[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 16 )[/C][C]9931454.96[/C][C]34654.7387808971[/C][C]286.58288330468[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 16 )[/C][C]9930007.04[/C][C]32456.2823872103[/C][C]305.950229343365[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 16 )[/C][C]9926944.24[/C][C]31127.5856795021[/C][C]318.911474285557[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 16 )[/C][C]9925668.68[/C][C]29442.6185454592[/C][C]337.119086900332[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 16 )[/C][C]9929554.28[/C][C]26887.3763288313[/C][C]369.301718344031[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 16 )[/C][C]9931113.5[/C][C]24380.1176729385[/C][C]407.344773032961[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 16 )[/C][C]9934157.94[/C][C]22006.4705875973[/C][C]451.419863101484[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 16 )[/C][C]9936279.84[/C][C]19575.6645109064[/C][C]507.583271794636[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 16 )[/C][C]9931927.52[/C][C]16947.2479510533[/C][C]586.049578591472[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 16 )[/C][C]9926370.35416667[/C][C]50705.8257918427[/C][C]195.763902848488[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 16 )[/C][C]9925508.60869565[/C][C]47332.2673975351[/C][C]209.698566209244[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 16 )[/C][C]9925616.31818182[/C][C]43924.2781522397[/C][C]225.97107421504[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 16 )[/C][C]9925937.85714286[/C][C]40744.3904067467[/C][C]243.61483281633[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 16 )[/C][C]9925816.5[/C][C]38004.1707721767[/C][C]261.177031318542[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 16 )[/C][C]9924943.57894737[/C][C]35722.3866056252[/C][C]277.83540020768[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 16 )[/C][C]9923442.11111111[/C][C]33721.6722450066[/C][C]294.274911368921[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 16 )[/C][C]9921474.70588235[/C][C]31984.9078453599[/C][C]310.192380539301[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 16 )[/C][C]9919525.4375[/C][C]30499.6982522731[/C][C]325.233559868439[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 16 )[/C][C]9917584.4[/C][C]29121.9565271497[/C][C]340.553506106435[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 16 )[/C][C]9915913[/C][C]27547.8728334059[/C][C]359.952039127155[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 16 )[/C][C]9914207.46153846[/C][C]25788.7890847185[/C][C]384.438657781465[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 16 )[/C][C]9911543.08333333[/C][C]24060.7661749083[/C][C]411.937966201158[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 16 )[/C][C]9908121.68181818[/C][C]22331.4106953046[/C][C]443.685435595945[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 16 )[/C][C]9903472.35[/C][C]20471.3735720826[/C][C]483.771756454371[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 16 )[/C][C]9897396.88888889[/C][C]18348.7761127514[/C][C]539.403654394734[/C][/ROW]
[ROW][C]Median[/C][C]9859112[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]9970994.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]9903525.96[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]9914207.46153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]9914207.46153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]9914207.46153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]9911543.08333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]9914207.46153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]9914207.46153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]9914207.46153846[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]50[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101151&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101151&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 Mean9928155.3253987.1943398254183.898338141202
Geometric Mean9920972.98447631
Harmonic Mean9913799.21235882
Quadratic Mean9935345.20278616
Winsorized Mean ( 1 / 16 )9927163.1653311.3294323101186.211134963434
Winsorized Mean ( 2 / 16 )9925319.0451949.3458929334191.05763257262
Winsorized Mean ( 3 / 16 )9924806.0449590.6169690784200.134756262228
Winsorized Mean ( 4 / 16 )9926326.246427.2927636848213.803683331808
Winsorized Mean ( 5 / 16 )9929133.643081.3523114925230.474046594663
Winsorized Mean ( 6 / 16 )9931429.9240202.616958102247.034413962411
Winsorized Mean ( 7 / 16 )9932806.9637374.3665025824265.765225995568
Winsorized Mean ( 8 / 16 )9931454.9634654.7387808971286.58288330468
Winsorized Mean ( 9 / 16 )9930007.0432456.2823872103305.950229343365
Winsorized Mean ( 10 / 16 )9926944.2431127.5856795021318.911474285557
Winsorized Mean ( 11 / 16 )9925668.6829442.6185454592337.119086900332
Winsorized Mean ( 12 / 16 )9929554.2826887.3763288313369.301718344031
Winsorized Mean ( 13 / 16 )9931113.524380.1176729385407.344773032961
Winsorized Mean ( 14 / 16 )9934157.9422006.4705875973451.419863101484
Winsorized Mean ( 15 / 16 )9936279.8419575.6645109064507.583271794636
Winsorized Mean ( 16 / 16 )9931927.5216947.2479510533586.049578591472
Trimmed Mean ( 1 / 16 )9926370.3541666750705.8257918427195.763902848488
Trimmed Mean ( 2 / 16 )9925508.6086956547332.2673975351209.698566209244
Trimmed Mean ( 3 / 16 )9925616.3181818243924.2781522397225.97107421504
Trimmed Mean ( 4 / 16 )9925937.8571428640744.3904067467243.61483281633
Trimmed Mean ( 5 / 16 )9925816.538004.1707721767261.177031318542
Trimmed Mean ( 6 / 16 )9924943.5789473735722.3866056252277.83540020768
Trimmed Mean ( 7 / 16 )9923442.1111111133721.6722450066294.274911368921
Trimmed Mean ( 8 / 16 )9921474.7058823531984.9078453599310.192380539301
Trimmed Mean ( 9 / 16 )9919525.437530499.6982522731325.233559868439
Trimmed Mean ( 10 / 16 )9917584.429121.9565271497340.553506106435
Trimmed Mean ( 11 / 16 )991591327547.8728334059359.952039127155
Trimmed Mean ( 12 / 16 )9914207.4615384625788.7890847185384.438657781465
Trimmed Mean ( 13 / 16 )9911543.0833333324060.7661749083411.937966201158
Trimmed Mean ( 14 / 16 )9908121.6818181822331.4106953046443.685435595945
Trimmed Mean ( 15 / 16 )9903472.3520471.3735720826483.771756454371
Trimmed Mean ( 16 / 16 )9897396.8888888918348.7761127514539.403654394734
Median9859112
Midrange9970994.5
Midmean - Weighted Average at Xnp9903525.96
Midmean - Weighted Average at X(n+1)p9914207.46153846
Midmean - Empirical Distribution Function9914207.46153846
Midmean - Empirical Distribution Function - Averaging9914207.46153846
Midmean - Empirical Distribution Function - Interpolation9911543.08333333
Midmean - Closest Observation9914207.46153846
Midmean - True Basic - Statistics Graphics Toolkit9914207.46153846
Midmean - MS Excel (old versions)9914207.46153846
Number of observations50



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')