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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 04 Apr 2011 18:30:36 +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/2011/Apr/04/t1301941691id7oqkz4vtiyobs.htm/, Retrieved Wed, 08 May 2024 22:43:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=120193, Retrieved Wed, 08 May 2024 22:43:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W52
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Werkloosheid 2002...] [2011-04-04 18:30:36] [3a3658f0c037a8b0bdf60c7ef617ad7f] [Current]
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Dataseries X:
476
475
470
461
455
456
517
525
523
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org

\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 & 'Herman Ole Andreas Wold' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120193&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]'Herman Ole Andreas Wold' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120193&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120193&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'Herman Ole Andreas Wold' @ www.yougetit.org







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean546.9047619047624.94553291042598110.585607620121
Geometric Mean545.032577193729
Harmonic Mean543.146157836955
Quadratic Mean548.757557709101
Winsorized Mean ( 1 / 28 )546.9047619047624.94051299850116110.697970447741
Winsorized Mean ( 2 / 28 )546.976190476194.90541565528759111.504555151529
Winsorized Mean ( 3 / 28 )547.0833333333334.8134507564866113.657199587237
Winsorized Mean ( 4 / 28 )547.0833333333334.79541903263979114.084573133158
Winsorized Mean ( 5 / 28 )547.3809523809524.73920867856622115.500495864756
Winsorized Mean ( 6 / 28 )546.9523809523814.63696096473738117.954924596472
Winsorized Mean ( 7 / 28 )547.0357142857144.59225090110076119.121477912844
Winsorized Mean ( 8 / 28 )548.0833333333334.38083135948734125.10943434204
Winsorized Mean ( 9 / 28 )548.4047619047624.3303793844421126.64127394358
Winsorized Mean ( 10 / 28 )547.4523809523813.9505115888341138.577591444036
Winsorized Mean ( 11 / 28 )547.4523809523813.87307240239149141.34834675808
Winsorized Mean ( 12 / 28 )547.5952380952383.85256540466889142.137817422025
Winsorized Mean ( 13 / 28 )548.0595238095243.74358702713597146.399568071165
Winsorized Mean ( 14 / 28 )548.226190476193.72118306988635147.32577789916
Winsorized Mean ( 15 / 28 )548.226190476193.67112405190793149.334694966592
Winsorized Mean ( 16 / 28 )548.0357142857143.59062040788659152.629811015942
Winsorized Mean ( 17 / 28 )547.8333333333333.56159767622161153.816737075849
Winsorized Mean ( 18 / 28 )547.8333333333333.50312676223093156.384102122657
Winsorized Mean ( 19 / 28 )547.6071428571433.47125801436288157.754664329569
Winsorized Mean ( 20 / 28 )546.8928571428573.30900550884785165.274084821115
Winsorized Mean ( 21 / 28 )546.1428571428573.14381537574866173.719761457939
Winsorized Mean ( 22 / 28 )546.6666666666673.07602714717146177.718414211445
Winsorized Mean ( 23 / 28 )546.6666666666672.93554459499925186.22325397404
Winsorized Mean ( 24 / 28 )545.8095238095242.75555435478998198.076123180348
Winsorized Mean ( 25 / 28 )545.5119047619052.71908608889313200.62325609704
Winsorized Mean ( 26 / 28 )545.5119047619052.71908608889313200.62325609704
Winsorized Mean ( 27 / 28 )545.8333333333332.67866099168171203.770964309541
Winsorized Mean ( 28 / 28 )544.8333333333332.47690614795695219.965271507252
Trimmed Mean ( 1 / 28 )547.0243902439024.83600292626538113.114983300133
Trimmed Mean ( 2 / 28 )547.154.71484660206593116.048314225165
Trimmed Mean ( 3 / 28 )547.243589743594.59575249820823119.075948923913
Trimmed Mean ( 4 / 28 )547.3026315789474.49736842105263121.693973083675
Trimmed Mean ( 5 / 28 )547.3648648648654.38833963368682124.73165492093
Trimmed Mean ( 6 / 28 )547.3611111111114.27709560034307127.974953626757
Trimmed Mean ( 7 / 28 )547.4428571428574.17314869948666131.182207144979
Trimmed Mean ( 8 / 28 )547.5147058823534.0606947341442134.832766737819
Trimmed Mean ( 9 / 28 )547.4242424242423.97504222059416137.715327799064
Trimmed Mean ( 10 / 28 )547.281253.88260702064807140.957157675115
Trimmed Mean ( 11 / 28 )547.2580645161293.84722358177154142.247533288443
Trimmed Mean ( 12 / 28 )547.2333333333333.81636134766742143.391383435902
Trimmed Mean ( 13 / 28 )547.1896551724143.77973845721255144.769184790619
Trimmed Mean ( 14 / 28 )547.0892857142863.75130079479922145.839887452578
Trimmed Mean ( 15 / 28 )546.9629629629633.71663709673799147.16609362884
Trimmed Mean ( 16 / 28 )546.8269230769233.6790263190133148.633599126733
Trimmed Mean ( 17 / 28 )546.73.64285714285714150.074509803922
Trimmed Mean ( 18 / 28 )546.5833333333333.59863958403616151.886100446963
Trimmed Mean ( 19 / 28 )546.456521739133.54933572362139153.960223627868
Trimmed Mean ( 20 / 28 )546.3409090909093.48826834524433156.622385383783
Trimmed Mean ( 21 / 28 )546.2857142857143.43806756932574158.893245484658
Trimmed Mean ( 22 / 28 )546.33.40082946141688160.637281639049
Trimmed Mean ( 23 / 28 )546.2631578947373.35896164663504162.628578519786
Trimmed Mean ( 24 / 28 )546.2222222222223.32620931847878164.217633324421
Trimmed Mean ( 25 / 28 )546.2647058823533.31294356288401164.888020430633
Trimmed Mean ( 26 / 28 )546.343753.29087490052221166.017781445689
Trimmed Mean ( 27 / 28 )546.4333333333333.24681394081699168.298320536297
Trimmed Mean ( 28 / 28 )546.53.18250009871278171.720340313906
Median548
Midrange542
Midmean - Weighted Average at Xnp545.46511627907
Midmean - Weighted Average at X(n+1)p546.285714285714
Midmean - Empirical Distribution Function545.46511627907
Midmean - Empirical Distribution Function - Averaging546.285714285714
Midmean - Empirical Distribution Function - Interpolation546.285714285714
Midmean - Closest Observation545.46511627907
Midmean - True Basic - Statistics Graphics Toolkit546.285714285714
Midmean - MS Excel (old versions)546.340909090909
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 546.904761904762 & 4.94553291042598 & 110.585607620121 \tabularnewline
Geometric Mean & 545.032577193729 &  &  \tabularnewline
Harmonic Mean & 543.146157836955 &  &  \tabularnewline
Quadratic Mean & 548.757557709101 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 546.904761904762 & 4.94051299850116 & 110.697970447741 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 546.97619047619 & 4.90541565528759 & 111.504555151529 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 547.083333333333 & 4.8134507564866 & 113.657199587237 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 547.083333333333 & 4.79541903263979 & 114.084573133158 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 547.380952380952 & 4.73920867856622 & 115.500495864756 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 546.952380952381 & 4.63696096473738 & 117.954924596472 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 547.035714285714 & 4.59225090110076 & 119.121477912844 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 548.083333333333 & 4.38083135948734 & 125.10943434204 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 548.404761904762 & 4.3303793844421 & 126.64127394358 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 547.452380952381 & 3.9505115888341 & 138.577591444036 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 547.452380952381 & 3.87307240239149 & 141.34834675808 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 547.595238095238 & 3.85256540466889 & 142.137817422025 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 548.059523809524 & 3.74358702713597 & 146.399568071165 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 548.22619047619 & 3.72118306988635 & 147.32577789916 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 548.22619047619 & 3.67112405190793 & 149.334694966592 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 548.035714285714 & 3.59062040788659 & 152.629811015942 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 547.833333333333 & 3.56159767622161 & 153.816737075849 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 547.833333333333 & 3.50312676223093 & 156.384102122657 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 547.607142857143 & 3.47125801436288 & 157.754664329569 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 546.892857142857 & 3.30900550884785 & 165.274084821115 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 546.142857142857 & 3.14381537574866 & 173.719761457939 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 546.666666666667 & 3.07602714717146 & 177.718414211445 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 546.666666666667 & 2.93554459499925 & 186.22325397404 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 545.809523809524 & 2.75555435478998 & 198.076123180348 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 545.511904761905 & 2.71908608889313 & 200.62325609704 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 545.511904761905 & 2.71908608889313 & 200.62325609704 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 545.833333333333 & 2.67866099168171 & 203.770964309541 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 544.833333333333 & 2.47690614795695 & 219.965271507252 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 547.024390243902 & 4.83600292626538 & 113.114983300133 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 547.15 & 4.71484660206593 & 116.048314225165 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 547.24358974359 & 4.59575249820823 & 119.075948923913 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 547.302631578947 & 4.49736842105263 & 121.693973083675 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 547.364864864865 & 4.38833963368682 & 124.73165492093 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 547.361111111111 & 4.27709560034307 & 127.974953626757 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 547.442857142857 & 4.17314869948666 & 131.182207144979 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 547.514705882353 & 4.0606947341442 & 134.832766737819 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 547.424242424242 & 3.97504222059416 & 137.715327799064 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 547.28125 & 3.88260702064807 & 140.957157675115 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 547.258064516129 & 3.84722358177154 & 142.247533288443 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 547.233333333333 & 3.81636134766742 & 143.391383435902 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 547.189655172414 & 3.77973845721255 & 144.769184790619 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 547.089285714286 & 3.75130079479922 & 145.839887452578 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 546.962962962963 & 3.71663709673799 & 147.16609362884 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 546.826923076923 & 3.6790263190133 & 148.633599126733 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 546.7 & 3.64285714285714 & 150.074509803922 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 546.583333333333 & 3.59863958403616 & 151.886100446963 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 546.45652173913 & 3.54933572362139 & 153.960223627868 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 546.340909090909 & 3.48826834524433 & 156.622385383783 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 546.285714285714 & 3.43806756932574 & 158.893245484658 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 546.3 & 3.40082946141688 & 160.637281639049 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 546.263157894737 & 3.35896164663504 & 162.628578519786 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 546.222222222222 & 3.32620931847878 & 164.217633324421 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 546.264705882353 & 3.31294356288401 & 164.888020430633 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 546.34375 & 3.29087490052221 & 166.017781445689 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 546.433333333333 & 3.24681394081699 & 168.298320536297 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 546.5 & 3.18250009871278 & 171.720340313906 \tabularnewline
Median & 548 &  &  \tabularnewline
Midrange & 542 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 545.46511627907 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 546.285714285714 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 545.46511627907 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 546.285714285714 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 546.285714285714 &  &  \tabularnewline
Midmean - Closest Observation & 545.46511627907 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 546.285714285714 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 546.340909090909 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120193&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]546.904761904762[/C][C]4.94553291042598[/C][C]110.585607620121[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]545.032577193729[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]543.146157836955[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]548.757557709101[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]546.904761904762[/C][C]4.94051299850116[/C][C]110.697970447741[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]546.97619047619[/C][C]4.90541565528759[/C][C]111.504555151529[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]547.083333333333[/C][C]4.8134507564866[/C][C]113.657199587237[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]547.083333333333[/C][C]4.79541903263979[/C][C]114.084573133158[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]547.380952380952[/C][C]4.73920867856622[/C][C]115.500495864756[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]546.952380952381[/C][C]4.63696096473738[/C][C]117.954924596472[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]547.035714285714[/C][C]4.59225090110076[/C][C]119.121477912844[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]548.083333333333[/C][C]4.38083135948734[/C][C]125.10943434204[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]548.404761904762[/C][C]4.3303793844421[/C][C]126.64127394358[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]547.452380952381[/C][C]3.9505115888341[/C][C]138.577591444036[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]547.452380952381[/C][C]3.87307240239149[/C][C]141.34834675808[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]547.595238095238[/C][C]3.85256540466889[/C][C]142.137817422025[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]548.059523809524[/C][C]3.74358702713597[/C][C]146.399568071165[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]548.22619047619[/C][C]3.72118306988635[/C][C]147.32577789916[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]548.22619047619[/C][C]3.67112405190793[/C][C]149.334694966592[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]548.035714285714[/C][C]3.59062040788659[/C][C]152.629811015942[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]547.833333333333[/C][C]3.56159767622161[/C][C]153.816737075849[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]547.833333333333[/C][C]3.50312676223093[/C][C]156.384102122657[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]547.607142857143[/C][C]3.47125801436288[/C][C]157.754664329569[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]546.892857142857[/C][C]3.30900550884785[/C][C]165.274084821115[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]546.142857142857[/C][C]3.14381537574866[/C][C]173.719761457939[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]546.666666666667[/C][C]3.07602714717146[/C][C]177.718414211445[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]546.666666666667[/C][C]2.93554459499925[/C][C]186.22325397404[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]545.809523809524[/C][C]2.75555435478998[/C][C]198.076123180348[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]545.511904761905[/C][C]2.71908608889313[/C][C]200.62325609704[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]545.511904761905[/C][C]2.71908608889313[/C][C]200.62325609704[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]545.833333333333[/C][C]2.67866099168171[/C][C]203.770964309541[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]544.833333333333[/C][C]2.47690614795695[/C][C]219.965271507252[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]547.024390243902[/C][C]4.83600292626538[/C][C]113.114983300133[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]547.15[/C][C]4.71484660206593[/C][C]116.048314225165[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]547.24358974359[/C][C]4.59575249820823[/C][C]119.075948923913[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]547.302631578947[/C][C]4.49736842105263[/C][C]121.693973083675[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]547.364864864865[/C][C]4.38833963368682[/C][C]124.73165492093[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]547.361111111111[/C][C]4.27709560034307[/C][C]127.974953626757[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]547.442857142857[/C][C]4.17314869948666[/C][C]131.182207144979[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]547.514705882353[/C][C]4.0606947341442[/C][C]134.832766737819[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]547.424242424242[/C][C]3.97504222059416[/C][C]137.715327799064[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]547.28125[/C][C]3.88260702064807[/C][C]140.957157675115[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]547.258064516129[/C][C]3.84722358177154[/C][C]142.247533288443[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]547.233333333333[/C][C]3.81636134766742[/C][C]143.391383435902[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]547.189655172414[/C][C]3.77973845721255[/C][C]144.769184790619[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]547.089285714286[/C][C]3.75130079479922[/C][C]145.839887452578[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]546.962962962963[/C][C]3.71663709673799[/C][C]147.16609362884[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]546.826923076923[/C][C]3.6790263190133[/C][C]148.633599126733[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]546.7[/C][C]3.64285714285714[/C][C]150.074509803922[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]546.583333333333[/C][C]3.59863958403616[/C][C]151.886100446963[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]546.45652173913[/C][C]3.54933572362139[/C][C]153.960223627868[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]546.340909090909[/C][C]3.48826834524433[/C][C]156.622385383783[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]546.285714285714[/C][C]3.43806756932574[/C][C]158.893245484658[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]546.3[/C][C]3.40082946141688[/C][C]160.637281639049[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]546.263157894737[/C][C]3.35896164663504[/C][C]162.628578519786[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]546.222222222222[/C][C]3.32620931847878[/C][C]164.217633324421[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]546.264705882353[/C][C]3.31294356288401[/C][C]164.888020430633[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]546.34375[/C][C]3.29087490052221[/C][C]166.017781445689[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]546.433333333333[/C][C]3.24681394081699[/C][C]168.298320536297[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]546.5[/C][C]3.18250009871278[/C][C]171.720340313906[/C][/ROW]
[ROW][C]Median[/C][C]548[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]542[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]545.46511627907[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]546.285714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]545.46511627907[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]546.285714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]546.285714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]545.46511627907[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]546.285714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]546.340909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120193&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120193&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 Mean546.9047619047624.94553291042598110.585607620121
Geometric Mean545.032577193729
Harmonic Mean543.146157836955
Quadratic Mean548.757557709101
Winsorized Mean ( 1 / 28 )546.9047619047624.94051299850116110.697970447741
Winsorized Mean ( 2 / 28 )546.976190476194.90541565528759111.504555151529
Winsorized Mean ( 3 / 28 )547.0833333333334.8134507564866113.657199587237
Winsorized Mean ( 4 / 28 )547.0833333333334.79541903263979114.084573133158
Winsorized Mean ( 5 / 28 )547.3809523809524.73920867856622115.500495864756
Winsorized Mean ( 6 / 28 )546.9523809523814.63696096473738117.954924596472
Winsorized Mean ( 7 / 28 )547.0357142857144.59225090110076119.121477912844
Winsorized Mean ( 8 / 28 )548.0833333333334.38083135948734125.10943434204
Winsorized Mean ( 9 / 28 )548.4047619047624.3303793844421126.64127394358
Winsorized Mean ( 10 / 28 )547.4523809523813.9505115888341138.577591444036
Winsorized Mean ( 11 / 28 )547.4523809523813.87307240239149141.34834675808
Winsorized Mean ( 12 / 28 )547.5952380952383.85256540466889142.137817422025
Winsorized Mean ( 13 / 28 )548.0595238095243.74358702713597146.399568071165
Winsorized Mean ( 14 / 28 )548.226190476193.72118306988635147.32577789916
Winsorized Mean ( 15 / 28 )548.226190476193.67112405190793149.334694966592
Winsorized Mean ( 16 / 28 )548.0357142857143.59062040788659152.629811015942
Winsorized Mean ( 17 / 28 )547.8333333333333.56159767622161153.816737075849
Winsorized Mean ( 18 / 28 )547.8333333333333.50312676223093156.384102122657
Winsorized Mean ( 19 / 28 )547.6071428571433.47125801436288157.754664329569
Winsorized Mean ( 20 / 28 )546.8928571428573.30900550884785165.274084821115
Winsorized Mean ( 21 / 28 )546.1428571428573.14381537574866173.719761457939
Winsorized Mean ( 22 / 28 )546.6666666666673.07602714717146177.718414211445
Winsorized Mean ( 23 / 28 )546.6666666666672.93554459499925186.22325397404
Winsorized Mean ( 24 / 28 )545.8095238095242.75555435478998198.076123180348
Winsorized Mean ( 25 / 28 )545.5119047619052.71908608889313200.62325609704
Winsorized Mean ( 26 / 28 )545.5119047619052.71908608889313200.62325609704
Winsorized Mean ( 27 / 28 )545.8333333333332.67866099168171203.770964309541
Winsorized Mean ( 28 / 28 )544.8333333333332.47690614795695219.965271507252
Trimmed Mean ( 1 / 28 )547.0243902439024.83600292626538113.114983300133
Trimmed Mean ( 2 / 28 )547.154.71484660206593116.048314225165
Trimmed Mean ( 3 / 28 )547.243589743594.59575249820823119.075948923913
Trimmed Mean ( 4 / 28 )547.3026315789474.49736842105263121.693973083675
Trimmed Mean ( 5 / 28 )547.3648648648654.38833963368682124.73165492093
Trimmed Mean ( 6 / 28 )547.3611111111114.27709560034307127.974953626757
Trimmed Mean ( 7 / 28 )547.4428571428574.17314869948666131.182207144979
Trimmed Mean ( 8 / 28 )547.5147058823534.0606947341442134.832766737819
Trimmed Mean ( 9 / 28 )547.4242424242423.97504222059416137.715327799064
Trimmed Mean ( 10 / 28 )547.281253.88260702064807140.957157675115
Trimmed Mean ( 11 / 28 )547.2580645161293.84722358177154142.247533288443
Trimmed Mean ( 12 / 28 )547.2333333333333.81636134766742143.391383435902
Trimmed Mean ( 13 / 28 )547.1896551724143.77973845721255144.769184790619
Trimmed Mean ( 14 / 28 )547.0892857142863.75130079479922145.839887452578
Trimmed Mean ( 15 / 28 )546.9629629629633.71663709673799147.16609362884
Trimmed Mean ( 16 / 28 )546.8269230769233.6790263190133148.633599126733
Trimmed Mean ( 17 / 28 )546.73.64285714285714150.074509803922
Trimmed Mean ( 18 / 28 )546.5833333333333.59863958403616151.886100446963
Trimmed Mean ( 19 / 28 )546.456521739133.54933572362139153.960223627868
Trimmed Mean ( 20 / 28 )546.3409090909093.48826834524433156.622385383783
Trimmed Mean ( 21 / 28 )546.2857142857143.43806756932574158.893245484658
Trimmed Mean ( 22 / 28 )546.33.40082946141688160.637281639049
Trimmed Mean ( 23 / 28 )546.2631578947373.35896164663504162.628578519786
Trimmed Mean ( 24 / 28 )546.2222222222223.32620931847878164.217633324421
Trimmed Mean ( 25 / 28 )546.2647058823533.31294356288401164.888020430633
Trimmed Mean ( 26 / 28 )546.343753.29087490052221166.017781445689
Trimmed Mean ( 27 / 28 )546.4333333333333.24681394081699168.298320536297
Trimmed Mean ( 28 / 28 )546.53.18250009871278171.720340313906
Median548
Midrange542
Midmean - Weighted Average at Xnp545.46511627907
Midmean - Weighted Average at X(n+1)p546.285714285714
Midmean - Empirical Distribution Function545.46511627907
Midmean - Empirical Distribution Function - Averaging546.285714285714
Midmean - Empirical Distribution Function - Interpolation546.285714285714
Midmean - Closest Observation545.46511627907
Midmean - True Basic - Statistics Graphics Toolkit546.285714285714
Midmean - MS Excel (old versions)546.340909090909
Number of observations84



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')