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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 computationTue, 15 Apr 2008 12:08:09 -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/2008/Apr/15/t1208282946mx5lkhbsf3ztsyc.htm/, Retrieved Thu, 31 Oct 2024 22:57:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=10131, Retrieved Thu, 31 Oct 2024 22:57:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact292
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [inschrijvingsgeld...] [2008-04-15 18:08:09] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
513,13
513,13
513,13
513,13
513,13
513,13
513,13
513,13
513,13
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
527,96
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
536,61
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
545,06
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
564,24
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
573,68
576,3
576,29
576,29
576,29
576,29
576,29
576,29
576,29
576,3
576,29
576,3
576,29
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
599,12
599,12
599,12




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=10131&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=10131&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10131&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean556.042.58110131787923215.427420902978
Geometric Mean555.467820466117
Harmonic Mean554.892981000722
Quadratic Mean556.608820969674
Winsorized Mean ( 1 / 32 )556.042.58110131787923215.427420902978
Winsorized Mean ( 2 / 32 )556.042.58110131787923215.427420902978
Winsorized Mean ( 3 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 4 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 5 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 6 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 7 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 8 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 9 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 10 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 11 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 12 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 13 / 32 )557.1406252.31860722624000240.291075907451
Winsorized Mean ( 14 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 15 / 32 )555.02343752.04274298962679271.704977238181
Winsorized Mean ( 16 / 32 )555.02343752.04274298962679271.704977238181
Winsorized Mean ( 17 / 32 )555.02343752.04274298962679271.704977238181
Winsorized Mean ( 18 / 32 )555.02156252.04253744585553271.731401363624
Winsorized Mean ( 19 / 32 )555.02156252.04253744585553271.731401363624
Winsorized Mean ( 20 / 32 )555.02156252.04253744585553271.731401363624
Winsorized Mean ( 21 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 22 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 23 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 24 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 25 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 26 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 27 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 28 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 29 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 30 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 31 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 32 / 32 )556.17968751.71569342058706324.171953349155
Trimmed Mean ( 1 / 32 )556.0381914893622.55484456868491217.640712200187
Trimmed Mean ( 2 / 32 )556.0363043478262.52469636344676220.238881949636
Trimmed Mean ( 3 / 32 )556.0343333333332.49009874032723223.298106347487
Trimmed Mean ( 4 / 32 )556.1376136363642.46928678373579225.221961782415
Trimmed Mean ( 5 / 32 )556.2456976744192.44485935767587227.516440128972
Trimmed Mean ( 6 / 32 )556.3589285714292.41626985495965230.255295131644
Trimmed Mean ( 7 / 32 )556.4776829268292.38286242622818233.533281989626
Trimmed Mean ( 8 / 32 )556.6023752.34384193317587237.474365110369
Trimmed Mean ( 9 / 32 )556.7334615384612.29823254293584242.244181621095
Trimmed Mean ( 10 / 32 )556.6763157894742.28642303833943243.470393035304
Trimmed Mean ( 11 / 32 )556.6160810810812.27149627521306245.043800931996
Trimmed Mean ( 12 / 32 )556.55252.25292015121408247.036052165488
Trimmed Mean ( 13 / 32 )556.4852857142862.23004832154266249.539563936144
Trimmed Mean ( 14 / 32 )556.4141176470592.20208753655926252.675748992454
Trimmed Mean ( 15 / 32 )556.3386363636362.16805243709501256.607555631393
Trimmed Mean ( 16 / 32 )556.470156252.16849889896464256.61537412617
Trimmed Mean ( 17 / 32 )556.6101612903232.16656723039587256.908788004063
Trimmed Mean ( 18 / 32 )556.75952.16174362592729257.551123695889
Trimmed Mean ( 19 / 32 )556.9193103448282.15341473733653258.621481820849
Trimmed Mean ( 20 / 32 )557.0905357142862.14075023897957260.231448569093
Trimmed Mean ( 21 / 32 )557.2744444444442.12272204811361262.528221695194
Trimmed Mean ( 22 / 32 )557.3061538461542.13667278726471260.828966029747
Trimmed Mean ( 23 / 32 )557.34042.14937931164002259.302951778548
Trimmed Mean ( 24 / 32 )557.37752.16041967332591257.995012210722
Trimmed Mean ( 25 / 32 )557.4178260869572.16924457371314256.964029248584
Trimmed Mean ( 26 / 32 )557.4618181818182.17513187062815256.288745390333
Trimmed Mean ( 27 / 32 )557.512.17712097714595256.076720518699
Trimmed Mean ( 28 / 32 )557.628252.18725817381265254.943955257
Trimmed Mean ( 29 / 32 )557.7589473684212.19321317667297254.31132427105
Trimmed Mean ( 30 / 32 )557.9041666666672.19335245233381254.361384588708
Trimmed Mean ( 31 / 32 )558.0664705882352.18534814230896255.367307287983
Trimmed Mean ( 32 / 32 )558.24906252.16579863833402257.756678122865
Median564.24
Midrange556.125
Midmean - Weighted Average at Xnp558.275263157895
Midmean - Weighted Average at X(n+1)p558.275263157895
Midmean - Empirical Distribution Function558.275263157895
Midmean - Empirical Distribution Function - Averaging558.275263157895
Midmean - Empirical Distribution Function - Interpolation558.275263157895
Midmean - Closest Observation558.275263157895
Midmean - True Basic - Statistics Graphics Toolkit558.275263157895
Midmean - MS Excel (old versions)558.275263157895
Number of observations96

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 556.04 & 2.58110131787923 & 215.427420902978 \tabularnewline
Geometric Mean & 555.467820466117 &  &  \tabularnewline
Harmonic Mean & 554.892981000722 &  &  \tabularnewline
Quadratic Mean & 556.608820969674 &  &  \tabularnewline
Winsorized Mean ( 1 / 32 ) & 556.04 & 2.58110131787923 & 215.427420902978 \tabularnewline
Winsorized Mean ( 2 / 32 ) & 556.04 & 2.58110131787923 & 215.427420902978 \tabularnewline
Winsorized Mean ( 3 / 32 ) & 555.7503125 & 2.53510093337387 & 219.222163971346 \tabularnewline
Winsorized Mean ( 4 / 32 ) & 555.7503125 & 2.53510093337387 & 219.222163971346 \tabularnewline
Winsorized Mean ( 5 / 32 ) & 555.7503125 & 2.53510093337387 & 219.222163971346 \tabularnewline
Winsorized Mean ( 6 / 32 ) & 555.7503125 & 2.53510093337387 & 219.222163971346 \tabularnewline
Winsorized Mean ( 7 / 32 ) & 555.7503125 & 2.53510093337387 & 219.222163971346 \tabularnewline
Winsorized Mean ( 8 / 32 ) & 555.7503125 & 2.53510093337387 & 219.222163971346 \tabularnewline
Winsorized Mean ( 9 / 32 ) & 557.140625 & 2.31860722624000 & 240.291075907450 \tabularnewline
Winsorized Mean ( 10 / 32 ) & 557.140625 & 2.31860722624000 & 240.291075907450 \tabularnewline
Winsorized Mean ( 11 / 32 ) & 557.140625 & 2.31860722624000 & 240.291075907450 \tabularnewline
Winsorized Mean ( 12 / 32 ) & 557.140625 & 2.31860722624000 & 240.291075907450 \tabularnewline
Winsorized Mean ( 13 / 32 ) & 557.140625 & 2.31860722624000 & 240.291075907451 \tabularnewline
Winsorized Mean ( 14 / 32 ) & 557.140625 & 2.31860722624000 & 240.291075907450 \tabularnewline
Winsorized Mean ( 15 / 32 ) & 555.0234375 & 2.04274298962679 & 271.704977238181 \tabularnewline
Winsorized Mean ( 16 / 32 ) & 555.0234375 & 2.04274298962679 & 271.704977238181 \tabularnewline
Winsorized Mean ( 17 / 32 ) & 555.0234375 & 2.04274298962679 & 271.704977238181 \tabularnewline
Winsorized Mean ( 18 / 32 ) & 555.0215625 & 2.04253744585553 & 271.731401363624 \tabularnewline
Winsorized Mean ( 19 / 32 ) & 555.0215625 & 2.04253744585553 & 271.731401363624 \tabularnewline
Winsorized Mean ( 20 / 32 ) & 555.0215625 & 2.04253744585553 & 271.731401363624 \tabularnewline
Winsorized Mean ( 21 / 32 ) & 556.91375 & 1.79681611230737 & 309.944766292664 \tabularnewline
Winsorized Mean ( 22 / 32 ) & 556.91375 & 1.79681611230737 & 309.944766292664 \tabularnewline
Winsorized Mean ( 23 / 32 ) & 556.91375 & 1.79681611230737 & 309.944766292664 \tabularnewline
Winsorized Mean ( 24 / 32 ) & 556.91375 & 1.79681611230737 & 309.944766292664 \tabularnewline
Winsorized Mean ( 25 / 32 ) & 556.91375 & 1.79681611230737 & 309.944766292664 \tabularnewline
Winsorized Mean ( 26 / 32 ) & 556.91375 & 1.79681611230737 & 309.944766292664 \tabularnewline
Winsorized Mean ( 27 / 32 ) & 556.1796875 & 1.71569342058706 & 324.171953349155 \tabularnewline
Winsorized Mean ( 28 / 32 ) & 556.1796875 & 1.71569342058706 & 324.171953349155 \tabularnewline
Winsorized Mean ( 29 / 32 ) & 556.1796875 & 1.71569342058706 & 324.171953349155 \tabularnewline
Winsorized Mean ( 30 / 32 ) & 556.1796875 & 1.71569342058706 & 324.171953349155 \tabularnewline
Winsorized Mean ( 31 / 32 ) & 556.1796875 & 1.71569342058706 & 324.171953349155 \tabularnewline
Winsorized Mean ( 32 / 32 ) & 556.1796875 & 1.71569342058706 & 324.171953349155 \tabularnewline
Trimmed Mean ( 1 / 32 ) & 556.038191489362 & 2.55484456868491 & 217.640712200187 \tabularnewline
Trimmed Mean ( 2 / 32 ) & 556.036304347826 & 2.52469636344676 & 220.238881949636 \tabularnewline
Trimmed Mean ( 3 / 32 ) & 556.034333333333 & 2.49009874032723 & 223.298106347487 \tabularnewline
Trimmed Mean ( 4 / 32 ) & 556.137613636364 & 2.46928678373579 & 225.221961782415 \tabularnewline
Trimmed Mean ( 5 / 32 ) & 556.245697674419 & 2.44485935767587 & 227.516440128972 \tabularnewline
Trimmed Mean ( 6 / 32 ) & 556.358928571429 & 2.41626985495965 & 230.255295131644 \tabularnewline
Trimmed Mean ( 7 / 32 ) & 556.477682926829 & 2.38286242622818 & 233.533281989626 \tabularnewline
Trimmed Mean ( 8 / 32 ) & 556.602375 & 2.34384193317587 & 237.474365110369 \tabularnewline
Trimmed Mean ( 9 / 32 ) & 556.733461538461 & 2.29823254293584 & 242.244181621095 \tabularnewline
Trimmed Mean ( 10 / 32 ) & 556.676315789474 & 2.28642303833943 & 243.470393035304 \tabularnewline
Trimmed Mean ( 11 / 32 ) & 556.616081081081 & 2.27149627521306 & 245.043800931996 \tabularnewline
Trimmed Mean ( 12 / 32 ) & 556.5525 & 2.25292015121408 & 247.036052165488 \tabularnewline
Trimmed Mean ( 13 / 32 ) & 556.485285714286 & 2.23004832154266 & 249.539563936144 \tabularnewline
Trimmed Mean ( 14 / 32 ) & 556.414117647059 & 2.20208753655926 & 252.675748992454 \tabularnewline
Trimmed Mean ( 15 / 32 ) & 556.338636363636 & 2.16805243709501 & 256.607555631393 \tabularnewline
Trimmed Mean ( 16 / 32 ) & 556.47015625 & 2.16849889896464 & 256.61537412617 \tabularnewline
Trimmed Mean ( 17 / 32 ) & 556.610161290323 & 2.16656723039587 & 256.908788004063 \tabularnewline
Trimmed Mean ( 18 / 32 ) & 556.7595 & 2.16174362592729 & 257.551123695889 \tabularnewline
Trimmed Mean ( 19 / 32 ) & 556.919310344828 & 2.15341473733653 & 258.621481820849 \tabularnewline
Trimmed Mean ( 20 / 32 ) & 557.090535714286 & 2.14075023897957 & 260.231448569093 \tabularnewline
Trimmed Mean ( 21 / 32 ) & 557.274444444444 & 2.12272204811361 & 262.528221695194 \tabularnewline
Trimmed Mean ( 22 / 32 ) & 557.306153846154 & 2.13667278726471 & 260.828966029747 \tabularnewline
Trimmed Mean ( 23 / 32 ) & 557.3404 & 2.14937931164002 & 259.302951778548 \tabularnewline
Trimmed Mean ( 24 / 32 ) & 557.3775 & 2.16041967332591 & 257.995012210722 \tabularnewline
Trimmed Mean ( 25 / 32 ) & 557.417826086957 & 2.16924457371314 & 256.964029248584 \tabularnewline
Trimmed Mean ( 26 / 32 ) & 557.461818181818 & 2.17513187062815 & 256.288745390333 \tabularnewline
Trimmed Mean ( 27 / 32 ) & 557.51 & 2.17712097714595 & 256.076720518699 \tabularnewline
Trimmed Mean ( 28 / 32 ) & 557.62825 & 2.18725817381265 & 254.943955257 \tabularnewline
Trimmed Mean ( 29 / 32 ) & 557.758947368421 & 2.19321317667297 & 254.31132427105 \tabularnewline
Trimmed Mean ( 30 / 32 ) & 557.904166666667 & 2.19335245233381 & 254.361384588708 \tabularnewline
Trimmed Mean ( 31 / 32 ) & 558.066470588235 & 2.18534814230896 & 255.367307287983 \tabularnewline
Trimmed Mean ( 32 / 32 ) & 558.2490625 & 2.16579863833402 & 257.756678122865 \tabularnewline
Median & 564.24 &  &  \tabularnewline
Midrange & 556.125 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 558.275263157895 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 558.275263157895 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 558.275263157895 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 558.275263157895 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 558.275263157895 &  &  \tabularnewline
Midmean - Closest Observation & 558.275263157895 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 558.275263157895 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 558.275263157895 &  &  \tabularnewline
Number of observations & 96 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=10131&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]556.04[/C][C]2.58110131787923[/C][C]215.427420902978[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]555.467820466117[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]554.892981000722[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]556.608820969674[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 32 )[/C][C]556.04[/C][C]2.58110131787923[/C][C]215.427420902978[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 32 )[/C][C]556.04[/C][C]2.58110131787923[/C][C]215.427420902978[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 32 )[/C][C]555.7503125[/C][C]2.53510093337387[/C][C]219.222163971346[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 32 )[/C][C]555.7503125[/C][C]2.53510093337387[/C][C]219.222163971346[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 32 )[/C][C]555.7503125[/C][C]2.53510093337387[/C][C]219.222163971346[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 32 )[/C][C]555.7503125[/C][C]2.53510093337387[/C][C]219.222163971346[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 32 )[/C][C]555.7503125[/C][C]2.53510093337387[/C][C]219.222163971346[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 32 )[/C][C]555.7503125[/C][C]2.53510093337387[/C][C]219.222163971346[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 32 )[/C][C]557.140625[/C][C]2.31860722624000[/C][C]240.291075907450[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 32 )[/C][C]557.140625[/C][C]2.31860722624000[/C][C]240.291075907450[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 32 )[/C][C]557.140625[/C][C]2.31860722624000[/C][C]240.291075907450[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 32 )[/C][C]557.140625[/C][C]2.31860722624000[/C][C]240.291075907450[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 32 )[/C][C]557.140625[/C][C]2.31860722624000[/C][C]240.291075907451[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 32 )[/C][C]557.140625[/C][C]2.31860722624000[/C][C]240.291075907450[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 32 )[/C][C]555.0234375[/C][C]2.04274298962679[/C][C]271.704977238181[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 32 )[/C][C]555.0234375[/C][C]2.04274298962679[/C][C]271.704977238181[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 32 )[/C][C]555.0234375[/C][C]2.04274298962679[/C][C]271.704977238181[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 32 )[/C][C]555.0215625[/C][C]2.04253744585553[/C][C]271.731401363624[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 32 )[/C][C]555.0215625[/C][C]2.04253744585553[/C][C]271.731401363624[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 32 )[/C][C]555.0215625[/C][C]2.04253744585553[/C][C]271.731401363624[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 32 )[/C][C]556.91375[/C][C]1.79681611230737[/C][C]309.944766292664[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 32 )[/C][C]556.91375[/C][C]1.79681611230737[/C][C]309.944766292664[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 32 )[/C][C]556.91375[/C][C]1.79681611230737[/C][C]309.944766292664[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 32 )[/C][C]556.91375[/C][C]1.79681611230737[/C][C]309.944766292664[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 32 )[/C][C]556.91375[/C][C]1.79681611230737[/C][C]309.944766292664[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 32 )[/C][C]556.91375[/C][C]1.79681611230737[/C][C]309.944766292664[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 32 )[/C][C]556.1796875[/C][C]1.71569342058706[/C][C]324.171953349155[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 32 )[/C][C]556.1796875[/C][C]1.71569342058706[/C][C]324.171953349155[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 32 )[/C][C]556.1796875[/C][C]1.71569342058706[/C][C]324.171953349155[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 32 )[/C][C]556.1796875[/C][C]1.71569342058706[/C][C]324.171953349155[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 32 )[/C][C]556.1796875[/C][C]1.71569342058706[/C][C]324.171953349155[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 32 )[/C][C]556.1796875[/C][C]1.71569342058706[/C][C]324.171953349155[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 32 )[/C][C]556.038191489362[/C][C]2.55484456868491[/C][C]217.640712200187[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 32 )[/C][C]556.036304347826[/C][C]2.52469636344676[/C][C]220.238881949636[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 32 )[/C][C]556.034333333333[/C][C]2.49009874032723[/C][C]223.298106347487[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 32 )[/C][C]556.137613636364[/C][C]2.46928678373579[/C][C]225.221961782415[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 32 )[/C][C]556.245697674419[/C][C]2.44485935767587[/C][C]227.516440128972[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 32 )[/C][C]556.358928571429[/C][C]2.41626985495965[/C][C]230.255295131644[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 32 )[/C][C]556.477682926829[/C][C]2.38286242622818[/C][C]233.533281989626[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 32 )[/C][C]556.602375[/C][C]2.34384193317587[/C][C]237.474365110369[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 32 )[/C][C]556.733461538461[/C][C]2.29823254293584[/C][C]242.244181621095[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 32 )[/C][C]556.676315789474[/C][C]2.28642303833943[/C][C]243.470393035304[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 32 )[/C][C]556.616081081081[/C][C]2.27149627521306[/C][C]245.043800931996[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 32 )[/C][C]556.5525[/C][C]2.25292015121408[/C][C]247.036052165488[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 32 )[/C][C]556.485285714286[/C][C]2.23004832154266[/C][C]249.539563936144[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 32 )[/C][C]556.414117647059[/C][C]2.20208753655926[/C][C]252.675748992454[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 32 )[/C][C]556.338636363636[/C][C]2.16805243709501[/C][C]256.607555631393[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 32 )[/C][C]556.47015625[/C][C]2.16849889896464[/C][C]256.61537412617[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 32 )[/C][C]556.610161290323[/C][C]2.16656723039587[/C][C]256.908788004063[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 32 )[/C][C]556.7595[/C][C]2.16174362592729[/C][C]257.551123695889[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 32 )[/C][C]556.919310344828[/C][C]2.15341473733653[/C][C]258.621481820849[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 32 )[/C][C]557.090535714286[/C][C]2.14075023897957[/C][C]260.231448569093[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 32 )[/C][C]557.274444444444[/C][C]2.12272204811361[/C][C]262.528221695194[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 32 )[/C][C]557.306153846154[/C][C]2.13667278726471[/C][C]260.828966029747[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 32 )[/C][C]557.3404[/C][C]2.14937931164002[/C][C]259.302951778548[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 32 )[/C][C]557.3775[/C][C]2.16041967332591[/C][C]257.995012210722[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 32 )[/C][C]557.417826086957[/C][C]2.16924457371314[/C][C]256.964029248584[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 32 )[/C][C]557.461818181818[/C][C]2.17513187062815[/C][C]256.288745390333[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 32 )[/C][C]557.51[/C][C]2.17712097714595[/C][C]256.076720518699[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 32 )[/C][C]557.62825[/C][C]2.18725817381265[/C][C]254.943955257[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 32 )[/C][C]557.758947368421[/C][C]2.19321317667297[/C][C]254.31132427105[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 32 )[/C][C]557.904166666667[/C][C]2.19335245233381[/C][C]254.361384588708[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 32 )[/C][C]558.066470588235[/C][C]2.18534814230896[/C][C]255.367307287983[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 32 )[/C][C]558.2490625[/C][C]2.16579863833402[/C][C]257.756678122865[/C][/ROW]
[ROW][C]Median[/C][C]564.24[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]556.125[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]558.275263157895[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]558.275263157895[/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=10131&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=10131&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 Mean556.042.58110131787923215.427420902978
Geometric Mean555.467820466117
Harmonic Mean554.892981000722
Quadratic Mean556.608820969674
Winsorized Mean ( 1 / 32 )556.042.58110131787923215.427420902978
Winsorized Mean ( 2 / 32 )556.042.58110131787923215.427420902978
Winsorized Mean ( 3 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 4 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 5 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 6 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 7 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 8 / 32 )555.75031252.53510093337387219.222163971346
Winsorized Mean ( 9 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 10 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 11 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 12 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 13 / 32 )557.1406252.31860722624000240.291075907451
Winsorized Mean ( 14 / 32 )557.1406252.31860722624000240.291075907450
Winsorized Mean ( 15 / 32 )555.02343752.04274298962679271.704977238181
Winsorized Mean ( 16 / 32 )555.02343752.04274298962679271.704977238181
Winsorized Mean ( 17 / 32 )555.02343752.04274298962679271.704977238181
Winsorized Mean ( 18 / 32 )555.02156252.04253744585553271.731401363624
Winsorized Mean ( 19 / 32 )555.02156252.04253744585553271.731401363624
Winsorized Mean ( 20 / 32 )555.02156252.04253744585553271.731401363624
Winsorized Mean ( 21 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 22 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 23 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 24 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 25 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 26 / 32 )556.913751.79681611230737309.944766292664
Winsorized Mean ( 27 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 28 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 29 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 30 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 31 / 32 )556.17968751.71569342058706324.171953349155
Winsorized Mean ( 32 / 32 )556.17968751.71569342058706324.171953349155
Trimmed Mean ( 1 / 32 )556.0381914893622.55484456868491217.640712200187
Trimmed Mean ( 2 / 32 )556.0363043478262.52469636344676220.238881949636
Trimmed Mean ( 3 / 32 )556.0343333333332.49009874032723223.298106347487
Trimmed Mean ( 4 / 32 )556.1376136363642.46928678373579225.221961782415
Trimmed Mean ( 5 / 32 )556.2456976744192.44485935767587227.516440128972
Trimmed Mean ( 6 / 32 )556.3589285714292.41626985495965230.255295131644
Trimmed Mean ( 7 / 32 )556.4776829268292.38286242622818233.533281989626
Trimmed Mean ( 8 / 32 )556.6023752.34384193317587237.474365110369
Trimmed Mean ( 9 / 32 )556.7334615384612.29823254293584242.244181621095
Trimmed Mean ( 10 / 32 )556.6763157894742.28642303833943243.470393035304
Trimmed Mean ( 11 / 32 )556.6160810810812.27149627521306245.043800931996
Trimmed Mean ( 12 / 32 )556.55252.25292015121408247.036052165488
Trimmed Mean ( 13 / 32 )556.4852857142862.23004832154266249.539563936144
Trimmed Mean ( 14 / 32 )556.4141176470592.20208753655926252.675748992454
Trimmed Mean ( 15 / 32 )556.3386363636362.16805243709501256.607555631393
Trimmed Mean ( 16 / 32 )556.470156252.16849889896464256.61537412617
Trimmed Mean ( 17 / 32 )556.6101612903232.16656723039587256.908788004063
Trimmed Mean ( 18 / 32 )556.75952.16174362592729257.551123695889
Trimmed Mean ( 19 / 32 )556.9193103448282.15341473733653258.621481820849
Trimmed Mean ( 20 / 32 )557.0905357142862.14075023897957260.231448569093
Trimmed Mean ( 21 / 32 )557.2744444444442.12272204811361262.528221695194
Trimmed Mean ( 22 / 32 )557.3061538461542.13667278726471260.828966029747
Trimmed Mean ( 23 / 32 )557.34042.14937931164002259.302951778548
Trimmed Mean ( 24 / 32 )557.37752.16041967332591257.995012210722
Trimmed Mean ( 25 / 32 )557.4178260869572.16924457371314256.964029248584
Trimmed Mean ( 26 / 32 )557.4618181818182.17513187062815256.288745390333
Trimmed Mean ( 27 / 32 )557.512.17712097714595256.076720518699
Trimmed Mean ( 28 / 32 )557.628252.18725817381265254.943955257
Trimmed Mean ( 29 / 32 )557.7589473684212.19321317667297254.31132427105
Trimmed Mean ( 30 / 32 )557.9041666666672.19335245233381254.361384588708
Trimmed Mean ( 31 / 32 )558.0664705882352.18534814230896255.367307287983
Trimmed Mean ( 32 / 32 )558.24906252.16579863833402257.756678122865
Median564.24
Midrange556.125
Midmean - Weighted Average at Xnp558.275263157895
Midmean - Weighted Average at X(n+1)p558.275263157895
Midmean - Empirical Distribution Function558.275263157895
Midmean - Empirical Distribution Function - Averaging558.275263157895
Midmean - Empirical Distribution Function - Interpolation558.275263157895
Midmean - Closest Observation558.275263157895
Midmean - True Basic - Statistics Graphics Toolkit558.275263157895
Midmean - MS Excel (old versions)558.275263157895
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')