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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 computationThu, 26 Feb 2015 10:30:02 +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/2015/Feb/26/t14249466874ms7oeewssxdeow.htm/, Retrieved Sat, 18 May 2024 07:02:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=277542, Retrieved Sat, 18 May 2024 07:02:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataseries X:
473
475
552
530
525
548
487
483
550
528
560
546
521
507
596
520
590
568
503
515
529
573
590
529
524
516
598
532
582
573
535
538
554
590
607
529
563
562
593
588
576
558
543
494
585
586
553
541
506
500
570
541
544
545
552
460
526
569
549
525
473
498
582
573
528
571
518
483
551
562
580
515
492
509
601
579
561
537
513
499
563
561
546
558
507
517
544
529
557
532
512
488
518
567
537
484
487
484
534
514
523
489
495
468
513
544
520
509





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=277542&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=277542&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277542&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'George Udny Yule' @ yule.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean536.3888888888893.31737700490687161.690663465591
Geometric Mean535.284716618406
Harmonic Mean534.174540540007
Quadratic Mean537.485417545513
Winsorized Mean ( 1 / 36 )536.4074074074073.29158795039855162.963109444625
Winsorized Mean ( 2 / 36 )536.4444444444443.26419294445527164.342137114069
Winsorized Mean ( 3 / 36 )536.3888888888893.25454213934135164.812396313738
Winsorized Mean ( 4 / 36 )536.3518518518523.22257083053928166.436016477595
Winsorized Mean ( 5 / 36 )536.5833333333333.13755611804919171.019517466658
Winsorized Mean ( 6 / 36 )536.5833333333333.13755611804919171.019517466658
Winsorized Mean ( 7 / 36 )536.6481481481483.12728462185008171.601952824706
Winsorized Mean ( 8 / 36 )536.53.10398698491025172.842219573776
Winsorized Mean ( 9 / 36 )536.5833333333333.03957754825548176.532207129013
Winsorized Mean ( 10 / 36 )536.4907407407413.02560594614677177.316792169841
Winsorized Mean ( 11 / 36 )536.2870370370372.96515622247179180.862995673793
Winsorized Mean ( 12 / 36 )536.3981481481482.94835375432569181.931407437513
Winsorized Mean ( 13 / 36 )536.5185185185182.86044633763964187.564615863844
Winsorized Mean ( 14 / 36 )536.6481481481482.80481076904017191.331320483982
Winsorized Mean ( 15 / 36 )536.370370370372.72739117391335196.660594747313
Winsorized Mean ( 16 / 36 )536.370370370372.60589476718819205.829635610775
Winsorized Mean ( 17 / 36 )536.5277777777782.5843827076233207.603841410621
Winsorized Mean ( 18 / 36 )536.6944444444442.56191784439343209.489326763136
Winsorized Mean ( 19 / 36 )536.870370370372.44616994911863219.47386385145
Winsorized Mean ( 20 / 36 )537.2407407407412.35157792154009228.459680548834
Winsorized Mean ( 21 / 36 )537.2407407407412.30237850025968233.341625054328
Winsorized Mean ( 22 / 36 )537.0370370370372.27629916521716235.925508054124
Winsorized Mean ( 23 / 36 )537.252.19742623765176244.490573014238
Winsorized Mean ( 24 / 36 )536.3611111111112.08811842301086256.863358514759
Winsorized Mean ( 25 / 36 )537.0555555555562.00500556255409267.857389318872
Winsorized Mean ( 26 / 36 )537.0555555555561.94809033655685275.683085880285
Winsorized Mean ( 27 / 36 )537.0555555555561.94809033655685275.683085880285
Winsorized Mean ( 28 / 36 )537.0555555555561.88744523660218284.541000258304
Winsorized Mean ( 29 / 36 )537.3240740740741.85703217111214289.345592624969
Winsorized Mean ( 30 / 36 )537.0462962962961.82414786904017294.409409133526
Winsorized Mean ( 31 / 36 )536.7592592592591.72498540787595311.167420204553
Winsorized Mean ( 32 / 36 )537.0555555555561.69190820180416317.425942484864
Winsorized Mean ( 33 / 36 )537.0555555555561.62299125429404330.904774831434
Winsorized Mean ( 34 / 36 )536.1111111111111.51662834348062353.488785446771
Winsorized Mean ( 35 / 36 )536.4351851851851.40944946451925380.599091126803
Winsorized Mean ( 36 / 36 )536.1018518518521.37310490032345390.430368230108
Trimmed Mean ( 1 / 36 )536.4433962264153.23325266028829165.914468366534
Trimmed Mean ( 2 / 36 )536.4807692307693.16788109688381169.350033294651
Trimmed Mean ( 3 / 36 )536.53.11067918394677172.470373276906
Trimmed Mean ( 4 / 36 )536.543.0502995381974175.897479339709
Trimmed Mean ( 5 / 36 )536.5918367346942.99269173411171179.300738067486
Trimmed Mean ( 6 / 36 )536.593752.95086138646822181.843089092785
Trimmed Mean ( 7 / 36 )536.5957446808512.90331972396583184.821444311301
Trimmed Mean ( 8 / 36 )536.5869565217392.85143999186602188.181044683529
Trimmed Mean ( 9 / 36 )536.62.79694857806049191.85193614539
Trimmed Mean ( 10 / 36 )536.6022727272732.74673453756178195.36007771745
Trimmed Mean ( 11 / 36 )536.6162790697672.69158737051056199.367958457903
Trimmed Mean ( 12 / 36 )536.6547619047622.63844942901109203.397782047278
Trimmed Mean ( 13 / 36 )536.6829268292682.57988174865267208.02617294748
Trimmed Mean ( 14 / 36 )536.72.52627959806411212.446793463113
Trimmed Mean ( 15 / 36 )536.7051282051282.47270204487256217.052082485251
Trimmed Mean ( 16 / 36 )536.7368421052632.42207453642915221.602115885571
Trimmed Mean ( 17 / 36 )536.770270270272.38093340344478225.445310437353
Trimmed Mean ( 18 / 36 )536.7916666666672.3355068263977229.839476639261
Trimmed Mean ( 19 / 36 )536.82.28503095375694234.920231219371
Trimmed Mean ( 20 / 36 )536.7941176470592.24229818527355239.394618063062
Trimmed Mean ( 21 / 36 )536.7575757575762.20489607830214243.438945281675
Trimmed Mean ( 22 / 36 )536.718752.16683478628885247.697126424319
Trimmed Mean ( 23 / 36 )536.6935483870972.12444520516785252.627625829819
Trimmed Mean ( 24 / 36 )536.652.08462558791931257.432319314299
Trimmed Mean ( 25 / 36 )536.6724137931032.0523086805269261.496927282558
Trimmed Mean ( 26 / 36 )536.6428571428572.02443331359356265.083000531278
Trimmed Mean ( 27 / 36 )536.6111111111111.99762554133674268.62447441077
Trimmed Mean ( 28 / 36 )536.5769230769231.96295752058892273.351265857215
Trimmed Mean ( 29 / 36 )536.541.92856296294438278.207147139677
Trimmed Mean ( 30 / 36 )536.4791666666671.88898204774793284.004375428695
Trimmed Mean ( 31 / 36 )536.4347826086961.84355573622633290.978337170729
Trimmed Mean ( 32 / 36 )536.4090909090911.80330861698583297.458286316894
Trimmed Mean ( 33 / 36 )536.3571428571431.75596591463121305.448493269751
Trimmed Mean ( 34 / 36 )536.31.70714937083987314.149428960721
Trimmed Mean ( 35 / 36 )536.3157894736841.6650987109334322.092489743773
Trimmed Mean ( 36 / 36 )536.3055555555561.63144664815765328.730060625146
Median536
Midrange533.5
Midmean - Weighted Average at Xnp536.642857142857
Midmean - Weighted Average at X(n+1)p536.642857142857
Midmean - Empirical Distribution Function536.642857142857
Midmean - Empirical Distribution Function - Averaging536.642857142857
Midmean - Empirical Distribution Function - Interpolation536.642857142857
Midmean - Closest Observation536.642857142857
Midmean - True Basic - Statistics Graphics Toolkit536.642857142857
Midmean - MS Excel (old versions)536.642857142857
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 536.388888888889 & 3.31737700490687 & 161.690663465591 \tabularnewline
Geometric Mean & 535.284716618406 &  &  \tabularnewline
Harmonic Mean & 534.174540540007 &  &  \tabularnewline
Quadratic Mean & 537.485417545513 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 536.407407407407 & 3.29158795039855 & 162.963109444625 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 536.444444444444 & 3.26419294445527 & 164.342137114069 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 536.388888888889 & 3.25454213934135 & 164.812396313738 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 536.351851851852 & 3.22257083053928 & 166.436016477595 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 536.583333333333 & 3.13755611804919 & 171.019517466658 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 536.583333333333 & 3.13755611804919 & 171.019517466658 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 536.648148148148 & 3.12728462185008 & 171.601952824706 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 536.5 & 3.10398698491025 & 172.842219573776 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 536.583333333333 & 3.03957754825548 & 176.532207129013 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 536.490740740741 & 3.02560594614677 & 177.316792169841 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 536.287037037037 & 2.96515622247179 & 180.862995673793 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 536.398148148148 & 2.94835375432569 & 181.931407437513 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 536.518518518518 & 2.86044633763964 & 187.564615863844 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 536.648148148148 & 2.80481076904017 & 191.331320483982 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 536.37037037037 & 2.72739117391335 & 196.660594747313 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 536.37037037037 & 2.60589476718819 & 205.829635610775 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 536.527777777778 & 2.5843827076233 & 207.603841410621 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 536.694444444444 & 2.56191784439343 & 209.489326763136 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 536.87037037037 & 2.44616994911863 & 219.47386385145 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 537.240740740741 & 2.35157792154009 & 228.459680548834 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 537.240740740741 & 2.30237850025968 & 233.341625054328 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 537.037037037037 & 2.27629916521716 & 235.925508054124 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 537.25 & 2.19742623765176 & 244.490573014238 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 536.361111111111 & 2.08811842301086 & 256.863358514759 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 537.055555555556 & 2.00500556255409 & 267.857389318872 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 537.055555555556 & 1.94809033655685 & 275.683085880285 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 537.055555555556 & 1.94809033655685 & 275.683085880285 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 537.055555555556 & 1.88744523660218 & 284.541000258304 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 537.324074074074 & 1.85703217111214 & 289.345592624969 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 537.046296296296 & 1.82414786904017 & 294.409409133526 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 536.759259259259 & 1.72498540787595 & 311.167420204553 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 537.055555555556 & 1.69190820180416 & 317.425942484864 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 537.055555555556 & 1.62299125429404 & 330.904774831434 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 536.111111111111 & 1.51662834348062 & 353.488785446771 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 536.435185185185 & 1.40944946451925 & 380.599091126803 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 536.101851851852 & 1.37310490032345 & 390.430368230108 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 536.443396226415 & 3.23325266028829 & 165.914468366534 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 536.480769230769 & 3.16788109688381 & 169.350033294651 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 536.5 & 3.11067918394677 & 172.470373276906 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 536.54 & 3.0502995381974 & 175.897479339709 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 536.591836734694 & 2.99269173411171 & 179.300738067486 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 536.59375 & 2.95086138646822 & 181.843089092785 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 536.595744680851 & 2.90331972396583 & 184.821444311301 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 536.586956521739 & 2.85143999186602 & 188.181044683529 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 536.6 & 2.79694857806049 & 191.85193614539 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 536.602272727273 & 2.74673453756178 & 195.36007771745 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 536.616279069767 & 2.69158737051056 & 199.367958457903 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 536.654761904762 & 2.63844942901109 & 203.397782047278 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 536.682926829268 & 2.57988174865267 & 208.02617294748 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 536.7 & 2.52627959806411 & 212.446793463113 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 536.705128205128 & 2.47270204487256 & 217.052082485251 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 536.736842105263 & 2.42207453642915 & 221.602115885571 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 536.77027027027 & 2.38093340344478 & 225.445310437353 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 536.791666666667 & 2.3355068263977 & 229.839476639261 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 536.8 & 2.28503095375694 & 234.920231219371 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 536.794117647059 & 2.24229818527355 & 239.394618063062 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 536.757575757576 & 2.20489607830214 & 243.438945281675 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 536.71875 & 2.16683478628885 & 247.697126424319 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 536.693548387097 & 2.12444520516785 & 252.627625829819 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 536.65 & 2.08462558791931 & 257.432319314299 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 536.672413793103 & 2.0523086805269 & 261.496927282558 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 536.642857142857 & 2.02443331359356 & 265.083000531278 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 536.611111111111 & 1.99762554133674 & 268.62447441077 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 536.576923076923 & 1.96295752058892 & 273.351265857215 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 536.54 & 1.92856296294438 & 278.207147139677 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 536.479166666667 & 1.88898204774793 & 284.004375428695 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 536.434782608696 & 1.84355573622633 & 290.978337170729 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 536.409090909091 & 1.80330861698583 & 297.458286316894 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 536.357142857143 & 1.75596591463121 & 305.448493269751 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 536.3 & 1.70714937083987 & 314.149428960721 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 536.315789473684 & 1.6650987109334 & 322.092489743773 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 536.305555555556 & 1.63144664815765 & 328.730060625146 \tabularnewline
Median & 536 &  &  \tabularnewline
Midrange & 533.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 536.642857142857 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 536.642857142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 536.642857142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 536.642857142857 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 536.642857142857 &  &  \tabularnewline
Midmean - Closest Observation & 536.642857142857 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 536.642857142857 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 536.642857142857 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=277542&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]536.388888888889[/C][C]3.31737700490687[/C][C]161.690663465591[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]535.284716618406[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]534.174540540007[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]537.485417545513[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]536.407407407407[/C][C]3.29158795039855[/C][C]162.963109444625[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]536.444444444444[/C][C]3.26419294445527[/C][C]164.342137114069[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]536.388888888889[/C][C]3.25454213934135[/C][C]164.812396313738[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]536.351851851852[/C][C]3.22257083053928[/C][C]166.436016477595[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]536.583333333333[/C][C]3.13755611804919[/C][C]171.019517466658[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]536.583333333333[/C][C]3.13755611804919[/C][C]171.019517466658[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]536.648148148148[/C][C]3.12728462185008[/C][C]171.601952824706[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]536.5[/C][C]3.10398698491025[/C][C]172.842219573776[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]536.583333333333[/C][C]3.03957754825548[/C][C]176.532207129013[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]536.490740740741[/C][C]3.02560594614677[/C][C]177.316792169841[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]536.287037037037[/C][C]2.96515622247179[/C][C]180.862995673793[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]536.398148148148[/C][C]2.94835375432569[/C][C]181.931407437513[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]536.518518518518[/C][C]2.86044633763964[/C][C]187.564615863844[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]536.648148148148[/C][C]2.80481076904017[/C][C]191.331320483982[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]536.37037037037[/C][C]2.72739117391335[/C][C]196.660594747313[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]536.37037037037[/C][C]2.60589476718819[/C][C]205.829635610775[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]536.527777777778[/C][C]2.5843827076233[/C][C]207.603841410621[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]536.694444444444[/C][C]2.56191784439343[/C][C]209.489326763136[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]536.87037037037[/C][C]2.44616994911863[/C][C]219.47386385145[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]537.240740740741[/C][C]2.35157792154009[/C][C]228.459680548834[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]537.240740740741[/C][C]2.30237850025968[/C][C]233.341625054328[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]537.037037037037[/C][C]2.27629916521716[/C][C]235.925508054124[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]537.25[/C][C]2.19742623765176[/C][C]244.490573014238[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]536.361111111111[/C][C]2.08811842301086[/C][C]256.863358514759[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]537.055555555556[/C][C]2.00500556255409[/C][C]267.857389318872[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]537.055555555556[/C][C]1.94809033655685[/C][C]275.683085880285[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]537.055555555556[/C][C]1.94809033655685[/C][C]275.683085880285[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]537.055555555556[/C][C]1.88744523660218[/C][C]284.541000258304[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]537.324074074074[/C][C]1.85703217111214[/C][C]289.345592624969[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]537.046296296296[/C][C]1.82414786904017[/C][C]294.409409133526[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]536.759259259259[/C][C]1.72498540787595[/C][C]311.167420204553[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]537.055555555556[/C][C]1.69190820180416[/C][C]317.425942484864[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]537.055555555556[/C][C]1.62299125429404[/C][C]330.904774831434[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]536.111111111111[/C][C]1.51662834348062[/C][C]353.488785446771[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]536.435185185185[/C][C]1.40944946451925[/C][C]380.599091126803[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]536.101851851852[/C][C]1.37310490032345[/C][C]390.430368230108[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]536.443396226415[/C][C]3.23325266028829[/C][C]165.914468366534[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]536.480769230769[/C][C]3.16788109688381[/C][C]169.350033294651[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]536.5[/C][C]3.11067918394677[/C][C]172.470373276906[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]536.54[/C][C]3.0502995381974[/C][C]175.897479339709[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]536.591836734694[/C][C]2.99269173411171[/C][C]179.300738067486[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]536.59375[/C][C]2.95086138646822[/C][C]181.843089092785[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]536.595744680851[/C][C]2.90331972396583[/C][C]184.821444311301[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]536.586956521739[/C][C]2.85143999186602[/C][C]188.181044683529[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]536.6[/C][C]2.79694857806049[/C][C]191.85193614539[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]536.602272727273[/C][C]2.74673453756178[/C][C]195.36007771745[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]536.616279069767[/C][C]2.69158737051056[/C][C]199.367958457903[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]536.654761904762[/C][C]2.63844942901109[/C][C]203.397782047278[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]536.682926829268[/C][C]2.57988174865267[/C][C]208.02617294748[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]536.7[/C][C]2.52627959806411[/C][C]212.446793463113[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]536.705128205128[/C][C]2.47270204487256[/C][C]217.052082485251[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]536.736842105263[/C][C]2.42207453642915[/C][C]221.602115885571[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]536.77027027027[/C][C]2.38093340344478[/C][C]225.445310437353[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]536.791666666667[/C][C]2.3355068263977[/C][C]229.839476639261[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]536.8[/C][C]2.28503095375694[/C][C]234.920231219371[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]536.794117647059[/C][C]2.24229818527355[/C][C]239.394618063062[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]536.757575757576[/C][C]2.20489607830214[/C][C]243.438945281675[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]536.71875[/C][C]2.16683478628885[/C][C]247.697126424319[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]536.693548387097[/C][C]2.12444520516785[/C][C]252.627625829819[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]536.65[/C][C]2.08462558791931[/C][C]257.432319314299[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]536.672413793103[/C][C]2.0523086805269[/C][C]261.496927282558[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]536.642857142857[/C][C]2.02443331359356[/C][C]265.083000531278[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]536.611111111111[/C][C]1.99762554133674[/C][C]268.62447441077[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]536.576923076923[/C][C]1.96295752058892[/C][C]273.351265857215[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]536.54[/C][C]1.92856296294438[/C][C]278.207147139677[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]536.479166666667[/C][C]1.88898204774793[/C][C]284.004375428695[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]536.434782608696[/C][C]1.84355573622633[/C][C]290.978337170729[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]536.409090909091[/C][C]1.80330861698583[/C][C]297.458286316894[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]536.357142857143[/C][C]1.75596591463121[/C][C]305.448493269751[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]536.3[/C][C]1.70714937083987[/C][C]314.149428960721[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]536.315789473684[/C][C]1.6650987109334[/C][C]322.092489743773[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]536.305555555556[/C][C]1.63144664815765[/C][C]328.730060625146[/C][/ROW]
[ROW][C]Median[/C][C]536[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]533.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]536.642857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=277542&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=277542&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 Mean536.3888888888893.31737700490687161.690663465591
Geometric Mean535.284716618406
Harmonic Mean534.174540540007
Quadratic Mean537.485417545513
Winsorized Mean ( 1 / 36 )536.4074074074073.29158795039855162.963109444625
Winsorized Mean ( 2 / 36 )536.4444444444443.26419294445527164.342137114069
Winsorized Mean ( 3 / 36 )536.3888888888893.25454213934135164.812396313738
Winsorized Mean ( 4 / 36 )536.3518518518523.22257083053928166.436016477595
Winsorized Mean ( 5 / 36 )536.5833333333333.13755611804919171.019517466658
Winsorized Mean ( 6 / 36 )536.5833333333333.13755611804919171.019517466658
Winsorized Mean ( 7 / 36 )536.6481481481483.12728462185008171.601952824706
Winsorized Mean ( 8 / 36 )536.53.10398698491025172.842219573776
Winsorized Mean ( 9 / 36 )536.5833333333333.03957754825548176.532207129013
Winsorized Mean ( 10 / 36 )536.4907407407413.02560594614677177.316792169841
Winsorized Mean ( 11 / 36 )536.2870370370372.96515622247179180.862995673793
Winsorized Mean ( 12 / 36 )536.3981481481482.94835375432569181.931407437513
Winsorized Mean ( 13 / 36 )536.5185185185182.86044633763964187.564615863844
Winsorized Mean ( 14 / 36 )536.6481481481482.80481076904017191.331320483982
Winsorized Mean ( 15 / 36 )536.370370370372.72739117391335196.660594747313
Winsorized Mean ( 16 / 36 )536.370370370372.60589476718819205.829635610775
Winsorized Mean ( 17 / 36 )536.5277777777782.5843827076233207.603841410621
Winsorized Mean ( 18 / 36 )536.6944444444442.56191784439343209.489326763136
Winsorized Mean ( 19 / 36 )536.870370370372.44616994911863219.47386385145
Winsorized Mean ( 20 / 36 )537.2407407407412.35157792154009228.459680548834
Winsorized Mean ( 21 / 36 )537.2407407407412.30237850025968233.341625054328
Winsorized Mean ( 22 / 36 )537.0370370370372.27629916521716235.925508054124
Winsorized Mean ( 23 / 36 )537.252.19742623765176244.490573014238
Winsorized Mean ( 24 / 36 )536.3611111111112.08811842301086256.863358514759
Winsorized Mean ( 25 / 36 )537.0555555555562.00500556255409267.857389318872
Winsorized Mean ( 26 / 36 )537.0555555555561.94809033655685275.683085880285
Winsorized Mean ( 27 / 36 )537.0555555555561.94809033655685275.683085880285
Winsorized Mean ( 28 / 36 )537.0555555555561.88744523660218284.541000258304
Winsorized Mean ( 29 / 36 )537.3240740740741.85703217111214289.345592624969
Winsorized Mean ( 30 / 36 )537.0462962962961.82414786904017294.409409133526
Winsorized Mean ( 31 / 36 )536.7592592592591.72498540787595311.167420204553
Winsorized Mean ( 32 / 36 )537.0555555555561.69190820180416317.425942484864
Winsorized Mean ( 33 / 36 )537.0555555555561.62299125429404330.904774831434
Winsorized Mean ( 34 / 36 )536.1111111111111.51662834348062353.488785446771
Winsorized Mean ( 35 / 36 )536.4351851851851.40944946451925380.599091126803
Winsorized Mean ( 36 / 36 )536.1018518518521.37310490032345390.430368230108
Trimmed Mean ( 1 / 36 )536.4433962264153.23325266028829165.914468366534
Trimmed Mean ( 2 / 36 )536.4807692307693.16788109688381169.350033294651
Trimmed Mean ( 3 / 36 )536.53.11067918394677172.470373276906
Trimmed Mean ( 4 / 36 )536.543.0502995381974175.897479339709
Trimmed Mean ( 5 / 36 )536.5918367346942.99269173411171179.300738067486
Trimmed Mean ( 6 / 36 )536.593752.95086138646822181.843089092785
Trimmed Mean ( 7 / 36 )536.5957446808512.90331972396583184.821444311301
Trimmed Mean ( 8 / 36 )536.5869565217392.85143999186602188.181044683529
Trimmed Mean ( 9 / 36 )536.62.79694857806049191.85193614539
Trimmed Mean ( 10 / 36 )536.6022727272732.74673453756178195.36007771745
Trimmed Mean ( 11 / 36 )536.6162790697672.69158737051056199.367958457903
Trimmed Mean ( 12 / 36 )536.6547619047622.63844942901109203.397782047278
Trimmed Mean ( 13 / 36 )536.6829268292682.57988174865267208.02617294748
Trimmed Mean ( 14 / 36 )536.72.52627959806411212.446793463113
Trimmed Mean ( 15 / 36 )536.7051282051282.47270204487256217.052082485251
Trimmed Mean ( 16 / 36 )536.7368421052632.42207453642915221.602115885571
Trimmed Mean ( 17 / 36 )536.770270270272.38093340344478225.445310437353
Trimmed Mean ( 18 / 36 )536.7916666666672.3355068263977229.839476639261
Trimmed Mean ( 19 / 36 )536.82.28503095375694234.920231219371
Trimmed Mean ( 20 / 36 )536.7941176470592.24229818527355239.394618063062
Trimmed Mean ( 21 / 36 )536.7575757575762.20489607830214243.438945281675
Trimmed Mean ( 22 / 36 )536.718752.16683478628885247.697126424319
Trimmed Mean ( 23 / 36 )536.6935483870972.12444520516785252.627625829819
Trimmed Mean ( 24 / 36 )536.652.08462558791931257.432319314299
Trimmed Mean ( 25 / 36 )536.6724137931032.0523086805269261.496927282558
Trimmed Mean ( 26 / 36 )536.6428571428572.02443331359356265.083000531278
Trimmed Mean ( 27 / 36 )536.6111111111111.99762554133674268.62447441077
Trimmed Mean ( 28 / 36 )536.5769230769231.96295752058892273.351265857215
Trimmed Mean ( 29 / 36 )536.541.92856296294438278.207147139677
Trimmed Mean ( 30 / 36 )536.4791666666671.88898204774793284.004375428695
Trimmed Mean ( 31 / 36 )536.4347826086961.84355573622633290.978337170729
Trimmed Mean ( 32 / 36 )536.4090909090911.80330861698583297.458286316894
Trimmed Mean ( 33 / 36 )536.3571428571431.75596591463121305.448493269751
Trimmed Mean ( 34 / 36 )536.31.70714937083987314.149428960721
Trimmed Mean ( 35 / 36 )536.3157894736841.6650987109334322.092489743773
Trimmed Mean ( 36 / 36 )536.3055555555561.63144664815765328.730060625146
Median536
Midrange533.5
Midmean - Weighted Average at Xnp536.642857142857
Midmean - Weighted Average at X(n+1)p536.642857142857
Midmean - Empirical Distribution Function536.642857142857
Midmean - Empirical Distribution Function - Averaging536.642857142857
Midmean - Empirical Distribution Function - Interpolation536.642857142857
Midmean - Closest Observation536.642857142857
Midmean - True Basic - Statistics Graphics Toolkit536.642857142857
Midmean - MS Excel (old versions)536.642857142857
Number of observations108



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')