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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 19:37:16 +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/t1301945647i96jdfjcx8dxcny.htm/, Retrieved Wed, 08 May 2024 22:00:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=120229, Retrieved Wed, 08 May 2024 22:00:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W52
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [prijs ton per kof...] [2011-04-04 19:37:16] [fc42f3d005062709f652b08fadb3432c] [Current]
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Dataseries X:
600
425
398
582
458
455
621
635
589
220
351
379
683
524
536
598
581
632
645
722
689
645
354
486
423
479
684
601
608
463
602
485
563
645
486
435
479
579
563
202
389
467
466
706
546
689
531
528
579
684
651
637
548
496
582
467
693
615
708
648
899
852
745
689
582
674
684
542
489
472
398
486
549
766
654
628
689
648
578
536
548
496
475
687
642
584
596
609
678
694
485
489
537
706
489
598




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ www.wessa.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120229&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]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120229&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120229&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'Gwilym Jenkins' @ www.wessa.org







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean568.83333333333311.998205884399747.4098660094623
Geometric Mean555.001361369815
Harmonic Mean538.005668367031
Quadratic Mean580.729946561509
Winsorized Mean ( 1 / 32 )568.5312511.806043586188948.1559504544849
Winsorized Mean ( 2 / 32 )569.4687510.679008277483953.3259957481906
Winsorized Mean ( 3 / 32 )568.9062510.537527737419553.9885886117075
Winsorized Mean ( 4 / 32 )568.98958333333310.162673519716655.9881789205803
Winsorized Mean ( 5 / 32 )568.781259.95036148427657.1618680284946
Winsorized Mean ( 6 / 32 )569.218759.82691438343457.9244641593272
Winsorized Mean ( 7 / 32 )569.218759.82691438343457.9244641593272
Winsorized Mean ( 8 / 32 )570.3020833333339.3188655071461261.1986601690946
Winsorized Mean ( 9 / 32 )570.3958333333339.274723705709661.5000350880742
Winsorized Mean ( 10 / 32 )571.0208333333339.0487347565526863.1050471359906
Winsorized Mean ( 11 / 32 )573.31258.7031239665028265.8743345730343
Winsorized Mean ( 12 / 32 )573.68758.6498949453614566.323059831801
Winsorized Mean ( 13 / 32 )574.3645833333338.5558423636018567.1312722843969
Winsorized Mean ( 14 / 32 )574.5104166666678.4553262927855667.9465696263979
Winsorized Mean ( 15 / 32 )574.1979166666678.3690456679904368.6097243874334
Winsorized Mean ( 16 / 32 )574.1979166666678.3690456679904368.6097243874334
Winsorized Mean ( 17 / 32 )575.0833333333338.2511252112340469.697564709156
Winsorized Mean ( 18 / 32 )575.4583333333338.1516051140663470.5944811213104
Winsorized Mean ( 19 / 32 )575.2604166666677.913211315989672.696203057826
Winsorized Mean ( 20 / 32 )574.4270833333337.8002719362131473.6419304391848
Winsorized Mean ( 21 / 32 )571.3645833333337.0669281614095580.8504869843435
Winsorized Mean ( 22 / 32 )570.6770833333336.9829914728899181.723869426001
Winsorized Mean ( 23 / 32 )570.1979166666676.8656694226404183.0505929671427
Winsorized Mean ( 24 / 32 )570.1979166666676.8656694226404183.0505929671427
Winsorized Mean ( 25 / 32 )569.4166666666676.7731841398128984.0692730202957
Winsorized Mean ( 26 / 32 )570.2291666666676.6684232197952285.5118440854115
Winsorized Mean ( 27 / 32 )570.2291666666676.6684232197952285.5118440854115
Winsorized Mean ( 28 / 32 )569.3541666666676.5658269205473986.7147692981221
Winsorized Mean ( 29 / 32 )569.9583333333336.1199973602983393.1304867924894
Winsorized Mean ( 30 / 32 )569.3333333333336.0482465681970794.1319648453166
Winsorized Mean ( 31 / 32 )577.406254.82622537219324119.639305144509
Winsorized Mean ( 32 / 32 )577.406254.5136629357527127.924095843836
Trimmed Mean ( 1 / 32 )569.22340425531911.059707283712351.4682160796078
Trimmed Mean ( 2 / 32 )569.94565217391310.1783470757855.9958948079235
Trimmed Mean ( 3 / 32 )570.29.8740406699112457.7473821570887
Trimmed Mean ( 4 / 32 )570.6704545454559.5867556234215759.5269637572945
Trimmed Mean ( 5 / 32 )571.1395348837219.385892764125960.8508481011726
Trimmed Mean ( 6 / 32 )571.6785714285719.2150653781607462.0373863850627
Trimmed Mean ( 7 / 32 )572.1585365853669.0485237052384663.2322525998497
Trimmed Mean ( 8 / 32 )572.66258.854966134172564.6713371144379
Trimmed Mean ( 9 / 32 )573.0256410256418.7365514242674365.5894543737193
Trimmed Mean ( 10 / 32 )573.3947368421058.6054466421771166.6316067816604
Trimmed Mean ( 11 / 32 )573.7027027027038.4922320000536967.5561740069131
Trimmed Mean ( 12 / 32 )573.758.4173871304156168.1624821468406
Trimmed Mean ( 13 / 32 )573.7571428571438.3345780200296368.8405749491206
Trimmed Mean ( 14 / 32 )573.6911764705888.248347197967569.5522584951266
Trimmed Mean ( 15 / 32 )573.6060606060618.1582791842660270.3096875763104
Trimmed Mean ( 16 / 32 )573.5468758.0607173089909571.1533295380877
Trimmed Mean ( 17 / 32 )573.4838709677427.939943199371572.2277044769208
Trimmed Mean ( 18 / 32 )573.3333333333337.8097674128820673.4123441867976
Trimmed Mean ( 19 / 32 )573.1379310344837.6646061676185174.7772186202965
Trimmed Mean ( 20 / 32 )572.9464285714297.5238762651842876.1504320881326
Trimmed Mean ( 21 / 32 )572.8148148148157.3667085987818877.757224564242
Trimmed Mean ( 22 / 32 )572.9423076923087.291930986540778.5720968492205
Trimmed Mean ( 23 / 32 )573.147.2049875015824479.5476744233242
Trimmed Mean ( 24 / 32 )573.3958333333337.1080652662448380.6683410823908
Trimmed Mean ( 25 / 32 )573.6739130434786.9773999800062682.2188658651275
Trimmed Mean ( 26 / 32 )574.0454545454556.8197848714508284.1735429146072
Trimmed Mean ( 27 / 32 )574.3809523809526.6313191002421486.6163946717598
Trimmed Mean ( 28 / 32 )574.756.3771175467548290.1269258071742
Trimmed Mean ( 29 / 32 )575.2368421052636.0555083150638194.9939810460323
Trimmed Mean ( 30 / 32 )575.7222222222225.73593671666945100.371090313652
Trimmed Mean ( 31 / 32 )576.3235294117655.30474522518874108.643017703317
Trimmed Mean ( 32 / 32 )576.218755.09342839871364113.129842002987
Median581.5
Midrange550.5
Midmean - Weighted Average at Xnp573.14
Midmean - Weighted Average at X(n+1)p573.14
Midmean - Empirical Distribution Function573.14
Midmean - Empirical Distribution Function - Averaging573.14
Midmean - Empirical Distribution Function - Interpolation573.14
Midmean - Closest Observation573.14
Midmean - True Basic - Statistics Graphics Toolkit573.14
Midmean - MS Excel (old versions)573.14
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 568.833333333333 & 11.9982058843997 & 47.4098660094623 \tabularnewline
Geometric Mean & 555.001361369815 &  &  \tabularnewline
Harmonic Mean & 538.005668367031 &  &  \tabularnewline
Quadratic Mean & 580.729946561509 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 568.53125 & 11.8060435861889 & 48.1559504544849 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 569.46875 & 10.6790082774839 & 53.3259957481906 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 568.90625 & 10.5375277374195 & 53.9885886117075 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 568.989583333333 & 10.1626735197166 & 55.9881789205803 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 568.78125 & 9.950361484276 & 57.1618680284946 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 569.21875 & 9.826914383434 & 57.9244641593272 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 569.21875 & 9.826914383434 & 57.9244641593272 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 570.302083333333 & 9.31886550714612 & 61.1986601690946 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 570.395833333333 & 9.2747237057096 & 61.5000350880742 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 571.020833333333 & 9.04873475655268 & 63.1050471359906 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 573.3125 & 8.70312396650282 & 65.8743345730343 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 573.6875 & 8.64989494536145 & 66.323059831801 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 574.364583333333 & 8.55584236360185 & 67.1312722843969 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 574.510416666667 & 8.45532629278556 & 67.9465696263979 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 574.197916666667 & 8.36904566799043 & 68.6097243874334 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 574.197916666667 & 8.36904566799043 & 68.6097243874334 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 575.083333333333 & 8.25112521123404 & 69.697564709156 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 575.458333333333 & 8.15160511406634 & 70.5944811213104 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 575.260416666667 & 7.9132113159896 & 72.696203057826 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 574.427083333333 & 7.80027193621314 & 73.6419304391848 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 571.364583333333 & 7.06692816140955 & 80.8504869843435 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 570.677083333333 & 6.98299147288991 & 81.723869426001 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 570.197916666667 & 6.86566942264041 & 83.0505929671427 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 570.197916666667 & 6.86566942264041 & 83.0505929671427 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 569.416666666667 & 6.77318413981289 & 84.0692730202957 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 570.229166666667 & 6.66842321979522 & 85.5118440854115 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 570.229166666667 & 6.66842321979522 & 85.5118440854115 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 569.354166666667 & 6.56582692054739 & 86.7147692981221 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 569.958333333333 & 6.11999736029833 & 93.1304867924894 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 569.333333333333 & 6.04824656819707 & 94.1319648453166 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 577.40625 & 4.82622537219324 & 119.639305144509 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 577.40625 & 4.5136629357527 & 127.924095843836 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 569.223404255319 & 11.0597072837123 & 51.4682160796078 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 569.945652173913 & 10.17834707578 & 55.9958948079235 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 570.2 & 9.87404066991124 & 57.7473821570887 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 570.670454545455 & 9.58675562342157 & 59.5269637572945 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 571.139534883721 & 9.3858927641259 & 60.8508481011726 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 571.678571428571 & 9.21506537816074 & 62.0373863850627 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 572.158536585366 & 9.04852370523846 & 63.2322525998497 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 572.6625 & 8.8549661341725 & 64.6713371144379 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 573.025641025641 & 8.73655142426743 & 65.5894543737193 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 573.394736842105 & 8.60544664217711 & 66.6316067816604 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 573.702702702703 & 8.49223200005369 & 67.5561740069131 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 573.75 & 8.41738713041561 & 68.1624821468406 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 573.757142857143 & 8.33457802002963 & 68.8405749491206 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 573.691176470588 & 8.2483471979675 & 69.5522584951266 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 573.606060606061 & 8.15827918426602 & 70.3096875763104 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 573.546875 & 8.06071730899095 & 71.1533295380877 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 573.483870967742 & 7.9399431993715 & 72.2277044769208 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 573.333333333333 & 7.80976741288206 & 73.4123441867976 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 573.137931034483 & 7.66460616761851 & 74.7772186202965 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 572.946428571429 & 7.52387626518428 & 76.1504320881326 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 572.814814814815 & 7.36670859878188 & 77.757224564242 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 572.942307692308 & 7.2919309865407 & 78.5720968492205 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 573.14 & 7.20498750158244 & 79.5476744233242 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 573.395833333333 & 7.10806526624483 & 80.6683410823908 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 573.673913043478 & 6.97739998000626 & 82.2188658651275 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 574.045454545455 & 6.81978487145082 & 84.1735429146072 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 574.380952380952 & 6.63131910024214 & 86.6163946717598 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 574.75 & 6.37711754675482 & 90.1269258071742 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 575.236842105263 & 6.05550831506381 & 94.9939810460323 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 575.722222222222 & 5.73593671666945 & 100.371090313652 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 576.323529411765 & 5.30474522518874 & 108.643017703317 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 576.21875 & 5.09342839871364 & 113.129842002987 \tabularnewline
Median & 581.5 &  &  \tabularnewline
Midrange & 550.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 573.14 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 573.14 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 573.14 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 573.14 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 573.14 &  &  \tabularnewline
Midmean - Closest Observation & 573.14 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 573.14 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 573.14 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=120229&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]568.833333333333[/C][C]11.9982058843997[/C][C]47.4098660094623[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]555.001361369815[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]538.005668367031[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]580.729946561509[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]568.53125[/C][C]11.8060435861889[/C][C]48.1559504544849[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]569.46875[/C][C]10.6790082774839[/C][C]53.3259957481906[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]568.90625[/C][C]10.5375277374195[/C][C]53.9885886117075[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]568.989583333333[/C][C]10.1626735197166[/C][C]55.9881789205803[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]568.78125[/C][C]9.950361484276[/C][C]57.1618680284946[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]569.21875[/C][C]9.826914383434[/C][C]57.9244641593272[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]569.21875[/C][C]9.826914383434[/C][C]57.9244641593272[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]570.302083333333[/C][C]9.31886550714612[/C][C]61.1986601690946[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]570.395833333333[/C][C]9.2747237057096[/C][C]61.5000350880742[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]571.020833333333[/C][C]9.04873475655268[/C][C]63.1050471359906[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]573.3125[/C][C]8.70312396650282[/C][C]65.8743345730343[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]573.6875[/C][C]8.64989494536145[/C][C]66.323059831801[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]574.364583333333[/C][C]8.55584236360185[/C][C]67.1312722843969[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]574.510416666667[/C][C]8.45532629278556[/C][C]67.9465696263979[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]574.197916666667[/C][C]8.36904566799043[/C][C]68.6097243874334[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]574.197916666667[/C][C]8.36904566799043[/C][C]68.6097243874334[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]575.083333333333[/C][C]8.25112521123404[/C][C]69.697564709156[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]575.458333333333[/C][C]8.15160511406634[/C][C]70.5944811213104[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]575.260416666667[/C][C]7.9132113159896[/C][C]72.696203057826[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]574.427083333333[/C][C]7.80027193621314[/C][C]73.6419304391848[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]571.364583333333[/C][C]7.06692816140955[/C][C]80.8504869843435[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]570.677083333333[/C][C]6.98299147288991[/C][C]81.723869426001[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]570.197916666667[/C][C]6.86566942264041[/C][C]83.0505929671427[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]570.197916666667[/C][C]6.86566942264041[/C][C]83.0505929671427[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]569.416666666667[/C][C]6.77318413981289[/C][C]84.0692730202957[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]570.229166666667[/C][C]6.66842321979522[/C][C]85.5118440854115[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]570.229166666667[/C][C]6.66842321979522[/C][C]85.5118440854115[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]569.354166666667[/C][C]6.56582692054739[/C][C]86.7147692981221[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]569.958333333333[/C][C]6.11999736029833[/C][C]93.1304867924894[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]569.333333333333[/C][C]6.04824656819707[/C][C]94.1319648453166[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]577.40625[/C][C]4.82622537219324[/C][C]119.639305144509[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]577.40625[/C][C]4.5136629357527[/C][C]127.924095843836[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]569.223404255319[/C][C]11.0597072837123[/C][C]51.4682160796078[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]569.945652173913[/C][C]10.17834707578[/C][C]55.9958948079235[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]570.2[/C][C]9.87404066991124[/C][C]57.7473821570887[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]570.670454545455[/C][C]9.58675562342157[/C][C]59.5269637572945[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]571.139534883721[/C][C]9.3858927641259[/C][C]60.8508481011726[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]571.678571428571[/C][C]9.21506537816074[/C][C]62.0373863850627[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]572.158536585366[/C][C]9.04852370523846[/C][C]63.2322525998497[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]572.6625[/C][C]8.8549661341725[/C][C]64.6713371144379[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]573.025641025641[/C][C]8.73655142426743[/C][C]65.5894543737193[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]573.394736842105[/C][C]8.60544664217711[/C][C]66.6316067816604[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]573.702702702703[/C][C]8.49223200005369[/C][C]67.5561740069131[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]573.75[/C][C]8.41738713041561[/C][C]68.1624821468406[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]573.757142857143[/C][C]8.33457802002963[/C][C]68.8405749491206[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]573.691176470588[/C][C]8.2483471979675[/C][C]69.5522584951266[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]573.606060606061[/C][C]8.15827918426602[/C][C]70.3096875763104[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]573.546875[/C][C]8.06071730899095[/C][C]71.1533295380877[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]573.483870967742[/C][C]7.9399431993715[/C][C]72.2277044769208[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]573.333333333333[/C][C]7.80976741288206[/C][C]73.4123441867976[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]573.137931034483[/C][C]7.66460616761851[/C][C]74.7772186202965[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]572.946428571429[/C][C]7.52387626518428[/C][C]76.1504320881326[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]572.814814814815[/C][C]7.36670859878188[/C][C]77.757224564242[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]572.942307692308[/C][C]7.2919309865407[/C][C]78.5720968492205[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]573.14[/C][C]7.20498750158244[/C][C]79.5476744233242[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]573.395833333333[/C][C]7.10806526624483[/C][C]80.6683410823908[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]573.673913043478[/C][C]6.97739998000626[/C][C]82.2188658651275[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]574.045454545455[/C][C]6.81978487145082[/C][C]84.1735429146072[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]574.380952380952[/C][C]6.63131910024214[/C][C]86.6163946717598[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]574.75[/C][C]6.37711754675482[/C][C]90.1269258071742[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]575.236842105263[/C][C]6.05550831506381[/C][C]94.9939810460323[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]575.722222222222[/C][C]5.73593671666945[/C][C]100.371090313652[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]576.323529411765[/C][C]5.30474522518874[/C][C]108.643017703317[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]576.21875[/C][C]5.09342839871364[/C][C]113.129842002987[/C][/ROW]
[ROW][C]Median[/C][C]581.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]550.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]573.14[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]96[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=120229&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=120229&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 Mean568.83333333333311.998205884399747.4098660094623
Geometric Mean555.001361369815
Harmonic Mean538.005668367031
Quadratic Mean580.729946561509
Winsorized Mean ( 1 / 32 )568.5312511.806043586188948.1559504544849
Winsorized Mean ( 2 / 32 )569.4687510.679008277483953.3259957481906
Winsorized Mean ( 3 / 32 )568.9062510.537527737419553.9885886117075
Winsorized Mean ( 4 / 32 )568.98958333333310.162673519716655.9881789205803
Winsorized Mean ( 5 / 32 )568.781259.95036148427657.1618680284946
Winsorized Mean ( 6 / 32 )569.218759.82691438343457.9244641593272
Winsorized Mean ( 7 / 32 )569.218759.82691438343457.9244641593272
Winsorized Mean ( 8 / 32 )570.3020833333339.3188655071461261.1986601690946
Winsorized Mean ( 9 / 32 )570.3958333333339.274723705709661.5000350880742
Winsorized Mean ( 10 / 32 )571.0208333333339.0487347565526863.1050471359906
Winsorized Mean ( 11 / 32 )573.31258.7031239665028265.8743345730343
Winsorized Mean ( 12 / 32 )573.68758.6498949453614566.323059831801
Winsorized Mean ( 13 / 32 )574.3645833333338.5558423636018567.1312722843969
Winsorized Mean ( 14 / 32 )574.5104166666678.4553262927855667.9465696263979
Winsorized Mean ( 15 / 32 )574.1979166666678.3690456679904368.6097243874334
Winsorized Mean ( 16 / 32 )574.1979166666678.3690456679904368.6097243874334
Winsorized Mean ( 17 / 32 )575.0833333333338.2511252112340469.697564709156
Winsorized Mean ( 18 / 32 )575.4583333333338.1516051140663470.5944811213104
Winsorized Mean ( 19 / 32 )575.2604166666677.913211315989672.696203057826
Winsorized Mean ( 20 / 32 )574.4270833333337.8002719362131473.6419304391848
Winsorized Mean ( 21 / 32 )571.3645833333337.0669281614095580.8504869843435
Winsorized Mean ( 22 / 32 )570.6770833333336.9829914728899181.723869426001
Winsorized Mean ( 23 / 32 )570.1979166666676.8656694226404183.0505929671427
Winsorized Mean ( 24 / 32 )570.1979166666676.8656694226404183.0505929671427
Winsorized Mean ( 25 / 32 )569.4166666666676.7731841398128984.0692730202957
Winsorized Mean ( 26 / 32 )570.2291666666676.6684232197952285.5118440854115
Winsorized Mean ( 27 / 32 )570.2291666666676.6684232197952285.5118440854115
Winsorized Mean ( 28 / 32 )569.3541666666676.5658269205473986.7147692981221
Winsorized Mean ( 29 / 32 )569.9583333333336.1199973602983393.1304867924894
Winsorized Mean ( 30 / 32 )569.3333333333336.0482465681970794.1319648453166
Winsorized Mean ( 31 / 32 )577.406254.82622537219324119.639305144509
Winsorized Mean ( 32 / 32 )577.406254.5136629357527127.924095843836
Trimmed Mean ( 1 / 32 )569.22340425531911.059707283712351.4682160796078
Trimmed Mean ( 2 / 32 )569.94565217391310.1783470757855.9958948079235
Trimmed Mean ( 3 / 32 )570.29.8740406699112457.7473821570887
Trimmed Mean ( 4 / 32 )570.6704545454559.5867556234215759.5269637572945
Trimmed Mean ( 5 / 32 )571.1395348837219.385892764125960.8508481011726
Trimmed Mean ( 6 / 32 )571.6785714285719.2150653781607462.0373863850627
Trimmed Mean ( 7 / 32 )572.1585365853669.0485237052384663.2322525998497
Trimmed Mean ( 8 / 32 )572.66258.854966134172564.6713371144379
Trimmed Mean ( 9 / 32 )573.0256410256418.7365514242674365.5894543737193
Trimmed Mean ( 10 / 32 )573.3947368421058.6054466421771166.6316067816604
Trimmed Mean ( 11 / 32 )573.7027027027038.4922320000536967.5561740069131
Trimmed Mean ( 12 / 32 )573.758.4173871304156168.1624821468406
Trimmed Mean ( 13 / 32 )573.7571428571438.3345780200296368.8405749491206
Trimmed Mean ( 14 / 32 )573.6911764705888.248347197967569.5522584951266
Trimmed Mean ( 15 / 32 )573.6060606060618.1582791842660270.3096875763104
Trimmed Mean ( 16 / 32 )573.5468758.0607173089909571.1533295380877
Trimmed Mean ( 17 / 32 )573.4838709677427.939943199371572.2277044769208
Trimmed Mean ( 18 / 32 )573.3333333333337.8097674128820673.4123441867976
Trimmed Mean ( 19 / 32 )573.1379310344837.6646061676185174.7772186202965
Trimmed Mean ( 20 / 32 )572.9464285714297.5238762651842876.1504320881326
Trimmed Mean ( 21 / 32 )572.8148148148157.3667085987818877.757224564242
Trimmed Mean ( 22 / 32 )572.9423076923087.291930986540778.5720968492205
Trimmed Mean ( 23 / 32 )573.147.2049875015824479.5476744233242
Trimmed Mean ( 24 / 32 )573.3958333333337.1080652662448380.6683410823908
Trimmed Mean ( 25 / 32 )573.6739130434786.9773999800062682.2188658651275
Trimmed Mean ( 26 / 32 )574.0454545454556.8197848714508284.1735429146072
Trimmed Mean ( 27 / 32 )574.3809523809526.6313191002421486.6163946717598
Trimmed Mean ( 28 / 32 )574.756.3771175467548290.1269258071742
Trimmed Mean ( 29 / 32 )575.2368421052636.0555083150638194.9939810460323
Trimmed Mean ( 30 / 32 )575.7222222222225.73593671666945100.371090313652
Trimmed Mean ( 31 / 32 )576.3235294117655.30474522518874108.643017703317
Trimmed Mean ( 32 / 32 )576.218755.09342839871364113.129842002987
Median581.5
Midrange550.5
Midmean - Weighted Average at Xnp573.14
Midmean - Weighted Average at X(n+1)p573.14
Midmean - Empirical Distribution Function573.14
Midmean - Empirical Distribution Function - Averaging573.14
Midmean - Empirical Distribution Function - Interpolation573.14
Midmean - Closest Observation573.14
Midmean - True Basic - Statistics Graphics Toolkit573.14
Midmean - MS Excel (old versions)573.14
Number of observations96



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')