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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 computationWed, 22 Apr 2009 12:09:53 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Apr/22/t1240423867dyukmrmowraeh3r.htm/, Retrieved Sun, 12 May 2024 08:26:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=39278, Retrieved Sun, 12 May 2024 08:26:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean versus Median] [Rekenkundig vs me...] [2009-04-22 17:39:57] [74be16979710d4c4e7c6647856088456]
- RM D    [Central Tendency] [Werkloosheidcentr...] [2009-04-22 18:09:53] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- RM        [Mean versus Median] [rekenkundig vs me...] [2009-04-22 18:15:20] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
467
460
448
443
436
431
484
510
513
503
471
471
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
528




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39278&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=39278&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39278&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean537.1649484536085.09623202420979105.404335183679
Geometric Mean534.818000949388
Harmonic Mean532.447746196509
Quadratic Mean539.48072589134
Winsorized Mean ( 1 / 32 )537.206185567015.08336723576795105.679200547834
Winsorized Mean ( 2 / 32 )537.3092783505155.04673946374647106.466617151590
Winsorized Mean ( 3 / 32 )537.3092783505154.98960174830503107.685804489915
Winsorized Mean ( 4 / 32 )537.5567010309284.93031267245247109.030955386351
Winsorized Mean ( 5 / 32 )537.608247422684.92136526395044109.239655784284
Winsorized Mean ( 6 / 32 )537.4226804123714.8059830590621111.823673493608
Winsorized Mean ( 7 / 32 )537.4226804123714.7821491849609112.380994324159
Winsorized Mean ( 8 / 32 )537.8350515463924.68859936506559114.711240963295
Winsorized Mean ( 9 / 32 )538.0206185567014.65968072271000115.462979241161
Winsorized Mean ( 10 / 32 )536.6804123711344.42298904914005121.338851715104
Winsorized Mean ( 11 / 32 )536.5670103092784.37333442071753122.690596851554
Winsorized Mean ( 12 / 32 )536.5670103092784.37333442071753122.690596851554
Winsorized Mean ( 13 / 32 )536.9690721649484.27231491629999125.685742433516
Winsorized Mean ( 14 / 32 )537.1134020618564.25060325940569126.361687808275
Winsorized Mean ( 15 / 32 )537.2680412371134.18310799484616128.437525853758
Winsorized Mean ( 16 / 32 )537.9278350515463.99468739295257134.660808753285
Winsorized Mean ( 17 / 32 )538.804123711343.82647224702191140.809625401225
Winsorized Mean ( 18 / 32 )539.1752577319593.7277118380483144.639736427227
Winsorized Mean ( 19 / 32 )540.1546391752583.55351032238464152.005929396817
Winsorized Mean ( 20 / 32 )539.7422680412373.39012863388992159.209967033588
Winsorized Mean ( 21 / 32 )539.0927835051553.24864769890678165.943750590921
Winsorized Mean ( 22 / 32 )539.3195876288663.22184294951753167.394747689247
Winsorized Mean ( 23 / 32 )539.5567010309283.07760342506305175.317162905703
Winsorized Mean ( 24 / 32 )538.8144329896912.92302926153139184.334259010258
Winsorized Mean ( 25 / 32 )538.8144329896912.86176844284610188.280234320366
Winsorized Mean ( 26 / 32 )539.0824742268042.83190547088442190.360335035635
Winsorized Mean ( 27 / 32 )539.0824742268042.83190547088442190.360335035635
Winsorized Mean ( 28 / 32 )538.2164948453612.65823247948238202.471566726987
Winsorized Mean ( 29 / 32 )538.2164948453612.65823247948238202.471566726987
Winsorized Mean ( 30 / 32 )537.597938144332.58426127028683208.027703826039
Winsorized Mean ( 31 / 32 )537.597938144332.51108623496436214.089795347852
Winsorized Mean ( 32 / 32 )537.597938144332.43606651362580220.682783141327
Trimmed Mean ( 1 / 32 )537.3157894736844.98756040825134107.731184284958
Trimmed Mean ( 2 / 32 )537.4301075268824.87873992790344110.157564344249
Trimmed Mean ( 3 / 32 )537.4945054945054.77693823057189112.518621667452
Trimmed Mean ( 4 / 32 )537.5617977528094.68499427562733114.741185608136
Trimmed Mean ( 5 / 32 )537.5632183908054.59962636783870116.871061995281
Trimmed Mean ( 6 / 32 )537.5529411764714.5040444284603119.348942870049
Trimmed Mean ( 7 / 32 )537.5529411764714.42288283695811121.539041614355
Trimmed Mean ( 8 / 32 )537.6049382716054.33431894105899124.034466679153
Trimmed Mean ( 9 / 32 )537.5696202531654.25118818163023126.451617121080
Trimmed Mean ( 10 / 32 )537.5064935064934.15993582751844129.210284916134
Trimmed Mean ( 11 / 32 )537.6133333333334.09728072132107131.212228280027
Trimmed Mean ( 12 / 32 )537.7397260273974.03183806565866133.373344184534
Trimmed Mean ( 13 / 32 )537.873239436623.95410947260111136.028919574347
Trimmed Mean ( 14 / 32 )537.873239436623.87908523014337138.659814756568
Trimmed Mean ( 15 / 32 )538.0597014925373.79309285588876141.852499249314
Trimmed Mean ( 16 / 32 )538.1384615384623.70147299961298145.384948531228
Trimmed Mean ( 17 / 32 )538.158730158733.6229912667573148.539891635014
Trimmed Mean ( 18 / 32 )538.0983606557383.55531656979984151.350336908545
Trimmed Mean ( 19 / 32 )5383.48822851384709154.233014799438
Trimmed Mean ( 20 / 32 )537.807017543863.43279906145084156.667200123435
Trimmed Mean ( 21 / 32 )537.6363636363643.38966180651322158.610620859963
Trimmed Mean ( 22 / 32 )537.5094339622643.35703479481182160.114346980545
Trimmed Mean ( 23 / 32 )537.3529411764713.31731329151294161.984381321849
Trimmed Mean ( 24 / 32 )537.1632653061223.28782889236794163.379325047311
Trimmed Mean ( 25 / 32 )537.1632653061223.27275204950250164.131977363754
Trimmed Mean ( 26 / 32 )536.8666666666673.25818317099539164.774857179884
Trimmed Mean ( 27 / 32 )536.6744186046513.23801494538329165.741797878306
Trimmed Mean ( 28 / 32 )536.6744186046513.20519729634649167.438809216640
Trimmed Mean ( 29 / 32 )536.3076923076923.19077487873922168.080705373863
Trimmed Mean ( 30 / 32 )536.1351351351353.16302829440941169.500581478434
Trimmed Mean ( 31 / 32 )536.1351351351353.13425101288405171.056859495691
Trimmed Mean ( 32 / 32 )535.8484848484853.10245540957665172.717545978076
Median532
Midrange530
Midmean - Weighted Average at Xnp536.395833333333
Midmean - Weighted Average at X(n+1)p537.163265306122
Midmean - Empirical Distribution Function537.163265306122
Midmean - Empirical Distribution Function - Averaging537.163265306122
Midmean - Empirical Distribution Function - Interpolation537.163265306122
Midmean - Closest Observation536.54
Midmean - True Basic - Statistics Graphics Toolkit537.163265306122
Midmean - MS Excel (old versions)537.163265306122
Number of observations97

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 537.164948453608 & 5.09623202420979 & 105.404335183679 \tabularnewline
Geometric Mean & 534.818000949388 &  &  \tabularnewline
Harmonic Mean & 532.447746196509 &  &  \tabularnewline
Quadratic Mean & 539.48072589134 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 537.20618556701 & 5.08336723576795 & 105.679200547834 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 537.309278350515 & 5.04673946374647 & 106.466617151590 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 537.309278350515 & 4.98960174830503 & 107.685804489915 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 537.556701030928 & 4.93031267245247 & 109.030955386351 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 537.60824742268 & 4.92136526395044 & 109.239655784284 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 537.422680412371 & 4.8059830590621 & 111.823673493608 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 537.422680412371 & 4.7821491849609 & 112.380994324159 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 537.835051546392 & 4.68859936506559 & 114.711240963295 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 538.020618556701 & 4.65968072271000 & 115.462979241161 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 536.680412371134 & 4.42298904914005 & 121.338851715104 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 536.567010309278 & 4.37333442071753 & 122.690596851554 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 536.567010309278 & 4.37333442071753 & 122.690596851554 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 536.969072164948 & 4.27231491629999 & 125.685742433516 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 537.113402061856 & 4.25060325940569 & 126.361687808275 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 537.268041237113 & 4.18310799484616 & 128.437525853758 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 537.927835051546 & 3.99468739295257 & 134.660808753285 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 538.80412371134 & 3.82647224702191 & 140.809625401225 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 539.175257731959 & 3.7277118380483 & 144.639736427227 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 540.154639175258 & 3.55351032238464 & 152.005929396817 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 539.742268041237 & 3.39012863388992 & 159.209967033588 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 539.092783505155 & 3.24864769890678 & 165.943750590921 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 539.319587628866 & 3.22184294951753 & 167.394747689247 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 539.556701030928 & 3.07760342506305 & 175.317162905703 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 538.814432989691 & 2.92302926153139 & 184.334259010258 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 538.814432989691 & 2.86176844284610 & 188.280234320366 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 539.082474226804 & 2.83190547088442 & 190.360335035635 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 539.082474226804 & 2.83190547088442 & 190.360335035635 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 538.216494845361 & 2.65823247948238 & 202.471566726987 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 538.216494845361 & 2.65823247948238 & 202.471566726987 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 537.59793814433 & 2.58426127028683 & 208.027703826039 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 537.59793814433 & 2.51108623496436 & 214.089795347852 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 537.59793814433 & 2.43606651362580 & 220.682783141327 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 537.315789473684 & 4.98756040825134 & 107.731184284958 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 537.430107526882 & 4.87873992790344 & 110.157564344249 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 537.494505494505 & 4.77693823057189 & 112.518621667452 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 537.561797752809 & 4.68499427562733 & 114.741185608136 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 537.563218390805 & 4.59962636783870 & 116.871061995281 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 537.552941176471 & 4.5040444284603 & 119.348942870049 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 537.552941176471 & 4.42288283695811 & 121.539041614355 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 537.604938271605 & 4.33431894105899 & 124.034466679153 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 537.569620253165 & 4.25118818163023 & 126.451617121080 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 537.506493506493 & 4.15993582751844 & 129.210284916134 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 537.613333333333 & 4.09728072132107 & 131.212228280027 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 537.739726027397 & 4.03183806565866 & 133.373344184534 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 537.87323943662 & 3.95410947260111 & 136.028919574347 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 537.87323943662 & 3.87908523014337 & 138.659814756568 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 538.059701492537 & 3.79309285588876 & 141.852499249314 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 538.138461538462 & 3.70147299961298 & 145.384948531228 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 538.15873015873 & 3.6229912667573 & 148.539891635014 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 538.098360655738 & 3.55531656979984 & 151.350336908545 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 538 & 3.48822851384709 & 154.233014799438 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 537.80701754386 & 3.43279906145084 & 156.667200123435 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 537.636363636364 & 3.38966180651322 & 158.610620859963 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 537.509433962264 & 3.35703479481182 & 160.114346980545 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 537.352941176471 & 3.31731329151294 & 161.984381321849 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 537.163265306122 & 3.28782889236794 & 163.379325047311 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 537.163265306122 & 3.27275204950250 & 164.131977363754 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 536.866666666667 & 3.25818317099539 & 164.774857179884 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 536.674418604651 & 3.23801494538329 & 165.741797878306 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 536.674418604651 & 3.20519729634649 & 167.438809216640 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 536.307692307692 & 3.19077487873922 & 168.080705373863 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 536.135135135135 & 3.16302829440941 & 169.500581478434 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 536.135135135135 & 3.13425101288405 & 171.056859495691 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 535.848484848485 & 3.10245540957665 & 172.717545978076 \tabularnewline
Median & 532 &  &  \tabularnewline
Midrange & 530 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 536.395833333333 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 537.163265306122 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 537.163265306122 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 537.163265306122 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 537.163265306122 &  &  \tabularnewline
Midmean - Closest Observation & 536.54 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 537.163265306122 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 537.163265306122 &  &  \tabularnewline
Number of observations & 97 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=39278&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]537.164948453608[/C][C]5.09623202420979[/C][C]105.404335183679[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]534.818000949388[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]532.447746196509[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]539.48072589134[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]537.20618556701[/C][C]5.08336723576795[/C][C]105.679200547834[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]537.309278350515[/C][C]5.04673946374647[/C][C]106.466617151590[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]537.309278350515[/C][C]4.98960174830503[/C][C]107.685804489915[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]537.556701030928[/C][C]4.93031267245247[/C][C]109.030955386351[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]537.60824742268[/C][C]4.92136526395044[/C][C]109.239655784284[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]537.422680412371[/C][C]4.8059830590621[/C][C]111.823673493608[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]537.422680412371[/C][C]4.7821491849609[/C][C]112.380994324159[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]537.835051546392[/C][C]4.68859936506559[/C][C]114.711240963295[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]538.020618556701[/C][C]4.65968072271000[/C][C]115.462979241161[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]536.680412371134[/C][C]4.42298904914005[/C][C]121.338851715104[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]536.567010309278[/C][C]4.37333442071753[/C][C]122.690596851554[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]536.567010309278[/C][C]4.37333442071753[/C][C]122.690596851554[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]536.969072164948[/C][C]4.27231491629999[/C][C]125.685742433516[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]537.113402061856[/C][C]4.25060325940569[/C][C]126.361687808275[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]537.268041237113[/C][C]4.18310799484616[/C][C]128.437525853758[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]537.927835051546[/C][C]3.99468739295257[/C][C]134.660808753285[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]538.80412371134[/C][C]3.82647224702191[/C][C]140.809625401225[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]539.175257731959[/C][C]3.7277118380483[/C][C]144.639736427227[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]540.154639175258[/C][C]3.55351032238464[/C][C]152.005929396817[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]539.742268041237[/C][C]3.39012863388992[/C][C]159.209967033588[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]539.092783505155[/C][C]3.24864769890678[/C][C]165.943750590921[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]539.319587628866[/C][C]3.22184294951753[/C][C]167.394747689247[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]539.556701030928[/C][C]3.07760342506305[/C][C]175.317162905703[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]538.814432989691[/C][C]2.92302926153139[/C][C]184.334259010258[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]538.814432989691[/C][C]2.86176844284610[/C][C]188.280234320366[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]539.082474226804[/C][C]2.83190547088442[/C][C]190.360335035635[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]539.082474226804[/C][C]2.83190547088442[/C][C]190.360335035635[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]538.216494845361[/C][C]2.65823247948238[/C][C]202.471566726987[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]538.216494845361[/C][C]2.65823247948238[/C][C]202.471566726987[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]537.59793814433[/C][C]2.58426127028683[/C][C]208.027703826039[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]537.59793814433[/C][C]2.51108623496436[/C][C]214.089795347852[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]537.59793814433[/C][C]2.43606651362580[/C][C]220.682783141327[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]537.315789473684[/C][C]4.98756040825134[/C][C]107.731184284958[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]537.430107526882[/C][C]4.87873992790344[/C][C]110.157564344249[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]537.494505494505[/C][C]4.77693823057189[/C][C]112.518621667452[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]537.561797752809[/C][C]4.68499427562733[/C][C]114.741185608136[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]537.563218390805[/C][C]4.59962636783870[/C][C]116.871061995281[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]537.552941176471[/C][C]4.5040444284603[/C][C]119.348942870049[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]537.552941176471[/C][C]4.42288283695811[/C][C]121.539041614355[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]537.604938271605[/C][C]4.33431894105899[/C][C]124.034466679153[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]537.569620253165[/C][C]4.25118818163023[/C][C]126.451617121080[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]537.506493506493[/C][C]4.15993582751844[/C][C]129.210284916134[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]537.613333333333[/C][C]4.09728072132107[/C][C]131.212228280027[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]537.739726027397[/C][C]4.03183806565866[/C][C]133.373344184534[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]537.87323943662[/C][C]3.95410947260111[/C][C]136.028919574347[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]537.87323943662[/C][C]3.87908523014337[/C][C]138.659814756568[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]538.059701492537[/C][C]3.79309285588876[/C][C]141.852499249314[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]538.138461538462[/C][C]3.70147299961298[/C][C]145.384948531228[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]538.15873015873[/C][C]3.6229912667573[/C][C]148.539891635014[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]538.098360655738[/C][C]3.55531656979984[/C][C]151.350336908545[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]538[/C][C]3.48822851384709[/C][C]154.233014799438[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]537.80701754386[/C][C]3.43279906145084[/C][C]156.667200123435[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]537.636363636364[/C][C]3.38966180651322[/C][C]158.610620859963[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]537.509433962264[/C][C]3.35703479481182[/C][C]160.114346980545[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]537.352941176471[/C][C]3.31731329151294[/C][C]161.984381321849[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]537.163265306122[/C][C]3.28782889236794[/C][C]163.379325047311[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]537.163265306122[/C][C]3.27275204950250[/C][C]164.131977363754[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]536.866666666667[/C][C]3.25818317099539[/C][C]164.774857179884[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]536.674418604651[/C][C]3.23801494538329[/C][C]165.741797878306[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]536.674418604651[/C][C]3.20519729634649[/C][C]167.438809216640[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]536.307692307692[/C][C]3.19077487873922[/C][C]168.080705373863[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]536.135135135135[/C][C]3.16302829440941[/C][C]169.500581478434[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]536.135135135135[/C][C]3.13425101288405[/C][C]171.056859495691[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]535.848484848485[/C][C]3.10245540957665[/C][C]172.717545978076[/C][/ROW]
[ROW][C]Median[/C][C]532[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]530[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]536.395833333333[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]537.163265306122[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]537.163265306122[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]537.163265306122[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]537.163265306122[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]536.54[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]537.163265306122[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]537.163265306122[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]97[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=39278&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=39278&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 Mean537.1649484536085.09623202420979105.404335183679
Geometric Mean534.818000949388
Harmonic Mean532.447746196509
Quadratic Mean539.48072589134
Winsorized Mean ( 1 / 32 )537.206185567015.08336723576795105.679200547834
Winsorized Mean ( 2 / 32 )537.3092783505155.04673946374647106.466617151590
Winsorized Mean ( 3 / 32 )537.3092783505154.98960174830503107.685804489915
Winsorized Mean ( 4 / 32 )537.5567010309284.93031267245247109.030955386351
Winsorized Mean ( 5 / 32 )537.608247422684.92136526395044109.239655784284
Winsorized Mean ( 6 / 32 )537.4226804123714.8059830590621111.823673493608
Winsorized Mean ( 7 / 32 )537.4226804123714.7821491849609112.380994324159
Winsorized Mean ( 8 / 32 )537.8350515463924.68859936506559114.711240963295
Winsorized Mean ( 9 / 32 )538.0206185567014.65968072271000115.462979241161
Winsorized Mean ( 10 / 32 )536.6804123711344.42298904914005121.338851715104
Winsorized Mean ( 11 / 32 )536.5670103092784.37333442071753122.690596851554
Winsorized Mean ( 12 / 32 )536.5670103092784.37333442071753122.690596851554
Winsorized Mean ( 13 / 32 )536.9690721649484.27231491629999125.685742433516
Winsorized Mean ( 14 / 32 )537.1134020618564.25060325940569126.361687808275
Winsorized Mean ( 15 / 32 )537.2680412371134.18310799484616128.437525853758
Winsorized Mean ( 16 / 32 )537.9278350515463.99468739295257134.660808753285
Winsorized Mean ( 17 / 32 )538.804123711343.82647224702191140.809625401225
Winsorized Mean ( 18 / 32 )539.1752577319593.7277118380483144.639736427227
Winsorized Mean ( 19 / 32 )540.1546391752583.55351032238464152.005929396817
Winsorized Mean ( 20 / 32 )539.7422680412373.39012863388992159.209967033588
Winsorized Mean ( 21 / 32 )539.0927835051553.24864769890678165.943750590921
Winsorized Mean ( 22 / 32 )539.3195876288663.22184294951753167.394747689247
Winsorized Mean ( 23 / 32 )539.5567010309283.07760342506305175.317162905703
Winsorized Mean ( 24 / 32 )538.8144329896912.92302926153139184.334259010258
Winsorized Mean ( 25 / 32 )538.8144329896912.86176844284610188.280234320366
Winsorized Mean ( 26 / 32 )539.0824742268042.83190547088442190.360335035635
Winsorized Mean ( 27 / 32 )539.0824742268042.83190547088442190.360335035635
Winsorized Mean ( 28 / 32 )538.2164948453612.65823247948238202.471566726987
Winsorized Mean ( 29 / 32 )538.2164948453612.65823247948238202.471566726987
Winsorized Mean ( 30 / 32 )537.597938144332.58426127028683208.027703826039
Winsorized Mean ( 31 / 32 )537.597938144332.51108623496436214.089795347852
Winsorized Mean ( 32 / 32 )537.597938144332.43606651362580220.682783141327
Trimmed Mean ( 1 / 32 )537.3157894736844.98756040825134107.731184284958
Trimmed Mean ( 2 / 32 )537.4301075268824.87873992790344110.157564344249
Trimmed Mean ( 3 / 32 )537.4945054945054.77693823057189112.518621667452
Trimmed Mean ( 4 / 32 )537.5617977528094.68499427562733114.741185608136
Trimmed Mean ( 5 / 32 )537.5632183908054.59962636783870116.871061995281
Trimmed Mean ( 6 / 32 )537.5529411764714.5040444284603119.348942870049
Trimmed Mean ( 7 / 32 )537.5529411764714.42288283695811121.539041614355
Trimmed Mean ( 8 / 32 )537.6049382716054.33431894105899124.034466679153
Trimmed Mean ( 9 / 32 )537.5696202531654.25118818163023126.451617121080
Trimmed Mean ( 10 / 32 )537.5064935064934.15993582751844129.210284916134
Trimmed Mean ( 11 / 32 )537.6133333333334.09728072132107131.212228280027
Trimmed Mean ( 12 / 32 )537.7397260273974.03183806565866133.373344184534
Trimmed Mean ( 13 / 32 )537.873239436623.95410947260111136.028919574347
Trimmed Mean ( 14 / 32 )537.873239436623.87908523014337138.659814756568
Trimmed Mean ( 15 / 32 )538.0597014925373.79309285588876141.852499249314
Trimmed Mean ( 16 / 32 )538.1384615384623.70147299961298145.384948531228
Trimmed Mean ( 17 / 32 )538.158730158733.6229912667573148.539891635014
Trimmed Mean ( 18 / 32 )538.0983606557383.55531656979984151.350336908545
Trimmed Mean ( 19 / 32 )5383.48822851384709154.233014799438
Trimmed Mean ( 20 / 32 )537.807017543863.43279906145084156.667200123435
Trimmed Mean ( 21 / 32 )537.6363636363643.38966180651322158.610620859963
Trimmed Mean ( 22 / 32 )537.5094339622643.35703479481182160.114346980545
Trimmed Mean ( 23 / 32 )537.3529411764713.31731329151294161.984381321849
Trimmed Mean ( 24 / 32 )537.1632653061223.28782889236794163.379325047311
Trimmed Mean ( 25 / 32 )537.1632653061223.27275204950250164.131977363754
Trimmed Mean ( 26 / 32 )536.8666666666673.25818317099539164.774857179884
Trimmed Mean ( 27 / 32 )536.6744186046513.23801494538329165.741797878306
Trimmed Mean ( 28 / 32 )536.6744186046513.20519729634649167.438809216640
Trimmed Mean ( 29 / 32 )536.3076923076923.19077487873922168.080705373863
Trimmed Mean ( 30 / 32 )536.1351351351353.16302829440941169.500581478434
Trimmed Mean ( 31 / 32 )536.1351351351353.13425101288405171.056859495691
Trimmed Mean ( 32 / 32 )535.8484848484853.10245540957665172.717545978076
Median532
Midrange530
Midmean - Weighted Average at Xnp536.395833333333
Midmean - Weighted Average at X(n+1)p537.163265306122
Midmean - Empirical Distribution Function537.163265306122
Midmean - Empirical Distribution Function - Averaging537.163265306122
Midmean - Empirical Distribution Function - Interpolation537.163265306122
Midmean - Closest Observation536.54
Midmean - True Basic - Statistics Graphics Toolkit537.163265306122
Midmean - MS Excel (old versions)537.163265306122
Number of observations97



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')