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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 computationFri, 11 Oct 2013 03:39:40 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/11/t13814772066o3po6ts3c8vdnq.htm/, Retrieved Sat, 27 Apr 2024 19:49:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=214693, Retrieved Sat, 27 Apr 2024 19:49:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Reserve positie I...] [2013-10-11 07:39:40] [a3fde7297e5409122ee2dd3b0c427a94] [Current]
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Dataseries X:
679
687
638
628
604
713
712
693
697
555
486
470
465
426
384
379
381
380
351
346
339
336
333
324
324
321
304
343
407
389
361
353
361
387
692
704
742
721
843
847
945
946
946
945
1082
1075
820
832
851
1090
1203
1239
1535
1527
1480
1452
1383
1381
1429
1376
1602
1597
2003
1958
1997
1986
2129
2115
2297
2250
2309
2648
2627
2711
2732
2825
2932
2910
2969
2999
2965
2846
2847
2751




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214693&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=214693&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214693&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' @ jenkins.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1221.988095238196.138589384897112.7106930011817
Geometric Mean933.977635011231
Harmonic Mean721.44587230593
Quadratic Mean1503.46036180666
Winsorized Mean ( 1 / 28 )1221.8333333333396.036603501406912.7225796080495
Winsorized Mean ( 2 / 28 )1221.8095238095296.007688895614112.7261632673812
Winsorized Mean ( 3 / 28 )1220.6309523809595.751881292306912.7478534719821
Winsorized Mean ( 4 / 28 )1220.011904761995.479219028128612.7777742338098
Winsorized Mean ( 5 / 28 )1216.4404761904894.670237751915212.8492386316614
Winsorized Mean ( 6 / 28 )1216.5833333333394.631441080355212.8560161342179
Winsorized Mean ( 7 / 28 )1215.1666666666794.23261162013912.8953941292121
Winsorized Mean ( 8 / 28 )1208.4047619047692.76927300913613.0259160464237
Winsorized Mean ( 9 / 28 )1206.9047619047692.302801255622813.0754944106449
Winsorized Mean ( 10 / 28 )1204.6428571428691.780172217609613.1253061313359
Winsorized Mean ( 11 / 28 )1197.4404761904890.046558925338513.2980148323416
Winsorized Mean ( 12 / 28 )1194.4404761904889.466047482222913.3507683619064
Winsorized Mean ( 13 / 28 )1148.011904761980.07848898893814.3360835007825
Winsorized Mean ( 14 / 28 )1146.1785714285779.710572908279414.3792539635544
Winsorized Mean ( 15 / 28 )1137.9642857142978.241172906702914.5443152682697
Winsorized Mean ( 16 / 28 )1115.488095238174.304824668608115.0123238997341
Winsorized Mean ( 17 / 28 )1113.261904761973.768217348119115.0913488868562
Winsorized Mean ( 18 / 28 )1089.6904761904869.861528018029415.5978620437454
Winsorized Mean ( 19 / 28 )1092.4047619047669.158627059831115.7956397971824
Winsorized Mean ( 20 / 28 )1094.3095238095268.208883588568416.0435043976138
Winsorized Mean ( 21 / 28 )1097.0595238095265.968821090345816.6299701234175
Winsorized Mean ( 22 / 28 )1005.1309523809551.921469618936119.3586768586838
Winsorized Mean ( 23 / 28 )1008.1428571428651.190578926900619.6939139637876
Winsorized Mean ( 24 / 28 )1010.1428571428646.375148221783721.7819866000636
Winsorized Mean ( 25 / 28 )1022.3452380952444.358170631713423.047506773517
Winsorized Mean ( 26 / 28 )1015.2261904761941.540748408165724.4392850244515
Winsorized Mean ( 27 / 28 )1009.4404761904839.973339333665425.2528433455228
Winsorized Mean ( 28 / 28 )1015.4404761904837.446359996546527.1172011454284
Trimmed Mean ( 1 / 28 )1211.5121951219595.384396789143712.7013666375656
Trimmed Mean ( 2 / 28 )1200.67594.583498666187612.6943390436161
Trimmed Mean ( 3 / 28 )1189.2948717948793.6259075208312.7026258360195
Trimmed Mean ( 4 / 28 )1177.7592.576731806268812.7218792132847
Trimmed Mean ( 5 / 28 )1165.7567567567691.398525234061812.7546560928787
Trimmed Mean ( 6 / 28 )1153.9305555555690.210901662229312.7914756896693
Trimmed Mean ( 7 / 28 )1141.488.772732836373212.8575516775386
Trimmed Mean ( 8 / 28 )1128.3823529411887.120321441065812.9519994219086
Trimmed Mean ( 9 / 28 )1115.6515151515285.449731654492813.056231933677
Trimmed Mean ( 10 / 28 )1102.3437583.505029131501913.2009264767042
Trimmed Mean ( 11 / 28 )1088.4838709677481.229150575342713.4001631588913
Trimmed Mean ( 12 / 28 )1074.6166666666778.800033309188313.637261578941
Trimmed Mean ( 13 / 28 )1060.1551724137975.909814520567613.9659829115581
Trimmed Mean ( 14 / 28 )1050.0178571428674.338692670563314.1247823901892
Trimmed Mean ( 15 / 28 )1039.3333333333372.421359069516914.3511989651517
Trimmed Mean ( 16 / 28 )1028.7115384615470.298294277919514.6335206142356
Trimmed Mean ( 17 / 28 )1019.668.438406689548814.8980674641524
Trimmed Mean ( 18 / 28 )1009.9583333333366.146469743406315.2685145140948
Trimmed Mean ( 19 / 28 )1001.8695652173964.065452707553815.6382187727718
Trimmed Mean ( 20 / 28 )992.77272727272761.46672610624616.1513844995861
Trimmed Mean ( 21 / 28 )982.61904761904858.216893433490616.8785895238748
Trimmed Mean ( 22 / 28 )971.17554.370982168092917.8620094998013
Trimmed Mean ( 23 / 28 )967.76315789473753.084910568156718.2304754314733
Trimmed Mean ( 24 / 28 )963.66666666666751.435581532816818.7354091846289
Trimmed Mean ( 25 / 28 )958.88235294117650.304523008635619.0615534268473
Trimmed Mean ( 26 / 28 )952.2187549.075643850126319.403082166543
Trimmed Mean ( 27 / 28 )945.43333333333347.99544239218419.6983981438891
Trimmed Mean ( 28 / 28 )938.32142857142946.739711924913320.0754645231624
Median849
Midrange1651.5
Midmean - Weighted Average at Xnp969.674418604651
Midmean - Weighted Average at X(n+1)p982.619047619048
Midmean - Empirical Distribution Function969.674418604651
Midmean - Empirical Distribution Function - Averaging982.619047619048
Midmean - Empirical Distribution Function - Interpolation982.619047619048
Midmean - Closest Observation969.674418604651
Midmean - True Basic - Statistics Graphics Toolkit982.619047619048
Midmean - MS Excel (old versions)992.772727272727
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1221.9880952381 & 96.1385893848971 & 12.7106930011817 \tabularnewline
Geometric Mean & 933.977635011231 &  &  \tabularnewline
Harmonic Mean & 721.44587230593 &  &  \tabularnewline
Quadratic Mean & 1503.46036180666 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 1221.83333333333 & 96.0366035014069 & 12.7225796080495 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 1221.80952380952 & 96.0076888956141 & 12.7261632673812 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 1220.63095238095 & 95.7518812923069 & 12.7478534719821 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 1220.0119047619 & 95.4792190281286 & 12.7777742338098 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 1216.44047619048 & 94.6702377519152 & 12.8492386316614 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 1216.58333333333 & 94.6314410803552 & 12.8560161342179 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 1215.16666666667 & 94.232611620139 & 12.8953941292121 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 1208.40476190476 & 92.769273009136 & 13.0259160464237 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 1206.90476190476 & 92.3028012556228 & 13.0754944106449 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 1204.64285714286 & 91.7801722176096 & 13.1253061313359 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 1197.44047619048 & 90.0465589253385 & 13.2980148323416 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 1194.44047619048 & 89.4660474822229 & 13.3507683619064 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 1148.0119047619 & 80.078488988938 & 14.3360835007825 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 1146.17857142857 & 79.7105729082794 & 14.3792539635544 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 1137.96428571429 & 78.2411729067029 & 14.5443152682697 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 1115.4880952381 & 74.3048246686081 & 15.0123238997341 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 1113.2619047619 & 73.7682173481191 & 15.0913488868562 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 1089.69047619048 & 69.8615280180294 & 15.5978620437454 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 1092.40476190476 & 69.1586270598311 & 15.7956397971824 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 1094.30952380952 & 68.2088835885684 & 16.0435043976138 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 1097.05952380952 & 65.9688210903458 & 16.6299701234175 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 1005.13095238095 & 51.9214696189361 & 19.3586768586838 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 1008.14285714286 & 51.1905789269006 & 19.6939139637876 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 1010.14285714286 & 46.3751482217837 & 21.7819866000636 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 1022.34523809524 & 44.3581706317134 & 23.047506773517 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 1015.22619047619 & 41.5407484081657 & 24.4392850244515 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 1009.44047619048 & 39.9733393336654 & 25.2528433455228 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 1015.44047619048 & 37.4463599965465 & 27.1172011454284 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 1211.51219512195 & 95.3843967891437 & 12.7013666375656 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 1200.675 & 94.5834986661876 & 12.6943390436161 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 1189.29487179487 & 93.62590752083 & 12.7026258360195 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 1177.75 & 92.5767318062688 & 12.7218792132847 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 1165.75675675676 & 91.3985252340618 & 12.7546560928787 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 1153.93055555556 & 90.2109016622293 & 12.7914756896693 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 1141.4 & 88.7727328363732 & 12.8575516775386 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 1128.38235294118 & 87.1203214410658 & 12.9519994219086 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 1115.65151515152 & 85.4497316544928 & 13.056231933677 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 1102.34375 & 83.5050291315019 & 13.2009264767042 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 1088.48387096774 & 81.2291505753427 & 13.4001631588913 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 1074.61666666667 & 78.8000333091883 & 13.637261578941 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 1060.15517241379 & 75.9098145205676 & 13.9659829115581 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 1050.01785714286 & 74.3386926705633 & 14.1247823901892 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 1039.33333333333 & 72.4213590695169 & 14.3511989651517 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 1028.71153846154 & 70.2982942779195 & 14.6335206142356 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 1019.6 & 68.4384066895488 & 14.8980674641524 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 1009.95833333333 & 66.1464697434063 & 15.2685145140948 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 1001.86956521739 & 64.0654527075538 & 15.6382187727718 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 992.772727272727 & 61.466726106246 & 16.1513844995861 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 982.619047619048 & 58.2168934334906 & 16.8785895238748 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 971.175 & 54.3709821680929 & 17.8620094998013 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 967.763157894737 & 53.0849105681567 & 18.2304754314733 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 963.666666666667 & 51.4355815328168 & 18.7354091846289 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 958.882352941176 & 50.3045230086356 & 19.0615534268473 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 952.21875 & 49.0756438501263 & 19.403082166543 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 945.433333333333 & 47.995442392184 & 19.6983981438891 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 938.321428571429 & 46.7397119249133 & 20.0754645231624 \tabularnewline
Median & 849 &  &  \tabularnewline
Midrange & 1651.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 969.674418604651 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 982.619047619048 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 969.674418604651 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 982.619047619048 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 982.619047619048 &  &  \tabularnewline
Midmean - Closest Observation & 969.674418604651 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 982.619047619048 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 992.772727272727 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214693&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]1221.9880952381[/C][C]96.1385893848971[/C][C]12.7106930011817[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]933.977635011231[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]721.44587230593[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1503.46036180666[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]1221.83333333333[/C][C]96.0366035014069[/C][C]12.7225796080495[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]1221.80952380952[/C][C]96.0076888956141[/C][C]12.7261632673812[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]1220.63095238095[/C][C]95.7518812923069[/C][C]12.7478534719821[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]1220.0119047619[/C][C]95.4792190281286[/C][C]12.7777742338098[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]1216.44047619048[/C][C]94.6702377519152[/C][C]12.8492386316614[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]1216.58333333333[/C][C]94.6314410803552[/C][C]12.8560161342179[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]1215.16666666667[/C][C]94.232611620139[/C][C]12.8953941292121[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]1208.40476190476[/C][C]92.769273009136[/C][C]13.0259160464237[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]1206.90476190476[/C][C]92.3028012556228[/C][C]13.0754944106449[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]1204.64285714286[/C][C]91.7801722176096[/C][C]13.1253061313359[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]1197.44047619048[/C][C]90.0465589253385[/C][C]13.2980148323416[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]1194.44047619048[/C][C]89.4660474822229[/C][C]13.3507683619064[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]1148.0119047619[/C][C]80.078488988938[/C][C]14.3360835007825[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]1146.17857142857[/C][C]79.7105729082794[/C][C]14.3792539635544[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]1137.96428571429[/C][C]78.2411729067029[/C][C]14.5443152682697[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]1115.4880952381[/C][C]74.3048246686081[/C][C]15.0123238997341[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]1113.2619047619[/C][C]73.7682173481191[/C][C]15.0913488868562[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]1089.69047619048[/C][C]69.8615280180294[/C][C]15.5978620437454[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]1092.40476190476[/C][C]69.1586270598311[/C][C]15.7956397971824[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]1094.30952380952[/C][C]68.2088835885684[/C][C]16.0435043976138[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]1097.05952380952[/C][C]65.9688210903458[/C][C]16.6299701234175[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]1005.13095238095[/C][C]51.9214696189361[/C][C]19.3586768586838[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]1008.14285714286[/C][C]51.1905789269006[/C][C]19.6939139637876[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]1010.14285714286[/C][C]46.3751482217837[/C][C]21.7819866000636[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]1022.34523809524[/C][C]44.3581706317134[/C][C]23.047506773517[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]1015.22619047619[/C][C]41.5407484081657[/C][C]24.4392850244515[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]1009.44047619048[/C][C]39.9733393336654[/C][C]25.2528433455228[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]1015.44047619048[/C][C]37.4463599965465[/C][C]27.1172011454284[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]1211.51219512195[/C][C]95.3843967891437[/C][C]12.7013666375656[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]1200.675[/C][C]94.5834986661876[/C][C]12.6943390436161[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]1189.29487179487[/C][C]93.62590752083[/C][C]12.7026258360195[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]1177.75[/C][C]92.5767318062688[/C][C]12.7218792132847[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]1165.75675675676[/C][C]91.3985252340618[/C][C]12.7546560928787[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]1153.93055555556[/C][C]90.2109016622293[/C][C]12.7914756896693[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]1141.4[/C][C]88.7727328363732[/C][C]12.8575516775386[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]1128.38235294118[/C][C]87.1203214410658[/C][C]12.9519994219086[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]1115.65151515152[/C][C]85.4497316544928[/C][C]13.056231933677[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]1102.34375[/C][C]83.5050291315019[/C][C]13.2009264767042[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]1088.48387096774[/C][C]81.2291505753427[/C][C]13.4001631588913[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]1074.61666666667[/C][C]78.8000333091883[/C][C]13.637261578941[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]1060.15517241379[/C][C]75.9098145205676[/C][C]13.9659829115581[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]1050.01785714286[/C][C]74.3386926705633[/C][C]14.1247823901892[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]1039.33333333333[/C][C]72.4213590695169[/C][C]14.3511989651517[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]1028.71153846154[/C][C]70.2982942779195[/C][C]14.6335206142356[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]1019.6[/C][C]68.4384066895488[/C][C]14.8980674641524[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]1009.95833333333[/C][C]66.1464697434063[/C][C]15.2685145140948[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]1001.86956521739[/C][C]64.0654527075538[/C][C]15.6382187727718[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]992.772727272727[/C][C]61.466726106246[/C][C]16.1513844995861[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]982.619047619048[/C][C]58.2168934334906[/C][C]16.8785895238748[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]971.175[/C][C]54.3709821680929[/C][C]17.8620094998013[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]967.763157894737[/C][C]53.0849105681567[/C][C]18.2304754314733[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]963.666666666667[/C][C]51.4355815328168[/C][C]18.7354091846289[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]958.882352941176[/C][C]50.3045230086356[/C][C]19.0615534268473[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]952.21875[/C][C]49.0756438501263[/C][C]19.403082166543[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]945.433333333333[/C][C]47.995442392184[/C][C]19.6983981438891[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]938.321428571429[/C][C]46.7397119249133[/C][C]20.0754645231624[/C][/ROW]
[ROW][C]Median[/C][C]849[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]1651.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]969.674418604651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]982.619047619048[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]969.674418604651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]982.619047619048[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]982.619047619048[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]969.674418604651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]982.619047619048[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]992.772727272727[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]84[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=214693&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214693&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 Mean1221.988095238196.138589384897112.7106930011817
Geometric Mean933.977635011231
Harmonic Mean721.44587230593
Quadratic Mean1503.46036180666
Winsorized Mean ( 1 / 28 )1221.8333333333396.036603501406912.7225796080495
Winsorized Mean ( 2 / 28 )1221.8095238095296.007688895614112.7261632673812
Winsorized Mean ( 3 / 28 )1220.6309523809595.751881292306912.7478534719821
Winsorized Mean ( 4 / 28 )1220.011904761995.479219028128612.7777742338098
Winsorized Mean ( 5 / 28 )1216.4404761904894.670237751915212.8492386316614
Winsorized Mean ( 6 / 28 )1216.5833333333394.631441080355212.8560161342179
Winsorized Mean ( 7 / 28 )1215.1666666666794.23261162013912.8953941292121
Winsorized Mean ( 8 / 28 )1208.4047619047692.76927300913613.0259160464237
Winsorized Mean ( 9 / 28 )1206.9047619047692.302801255622813.0754944106449
Winsorized Mean ( 10 / 28 )1204.6428571428691.780172217609613.1253061313359
Winsorized Mean ( 11 / 28 )1197.4404761904890.046558925338513.2980148323416
Winsorized Mean ( 12 / 28 )1194.4404761904889.466047482222913.3507683619064
Winsorized Mean ( 13 / 28 )1148.011904761980.07848898893814.3360835007825
Winsorized Mean ( 14 / 28 )1146.1785714285779.710572908279414.3792539635544
Winsorized Mean ( 15 / 28 )1137.9642857142978.241172906702914.5443152682697
Winsorized Mean ( 16 / 28 )1115.488095238174.304824668608115.0123238997341
Winsorized Mean ( 17 / 28 )1113.261904761973.768217348119115.0913488868562
Winsorized Mean ( 18 / 28 )1089.6904761904869.861528018029415.5978620437454
Winsorized Mean ( 19 / 28 )1092.4047619047669.158627059831115.7956397971824
Winsorized Mean ( 20 / 28 )1094.3095238095268.208883588568416.0435043976138
Winsorized Mean ( 21 / 28 )1097.0595238095265.968821090345816.6299701234175
Winsorized Mean ( 22 / 28 )1005.1309523809551.921469618936119.3586768586838
Winsorized Mean ( 23 / 28 )1008.1428571428651.190578926900619.6939139637876
Winsorized Mean ( 24 / 28 )1010.1428571428646.375148221783721.7819866000636
Winsorized Mean ( 25 / 28 )1022.3452380952444.358170631713423.047506773517
Winsorized Mean ( 26 / 28 )1015.2261904761941.540748408165724.4392850244515
Winsorized Mean ( 27 / 28 )1009.4404761904839.973339333665425.2528433455228
Winsorized Mean ( 28 / 28 )1015.4404761904837.446359996546527.1172011454284
Trimmed Mean ( 1 / 28 )1211.5121951219595.384396789143712.7013666375656
Trimmed Mean ( 2 / 28 )1200.67594.583498666187612.6943390436161
Trimmed Mean ( 3 / 28 )1189.2948717948793.6259075208312.7026258360195
Trimmed Mean ( 4 / 28 )1177.7592.576731806268812.7218792132847
Trimmed Mean ( 5 / 28 )1165.7567567567691.398525234061812.7546560928787
Trimmed Mean ( 6 / 28 )1153.9305555555690.210901662229312.7914756896693
Trimmed Mean ( 7 / 28 )1141.488.772732836373212.8575516775386
Trimmed Mean ( 8 / 28 )1128.3823529411887.120321441065812.9519994219086
Trimmed Mean ( 9 / 28 )1115.6515151515285.449731654492813.056231933677
Trimmed Mean ( 10 / 28 )1102.3437583.505029131501913.2009264767042
Trimmed Mean ( 11 / 28 )1088.4838709677481.229150575342713.4001631588913
Trimmed Mean ( 12 / 28 )1074.6166666666778.800033309188313.637261578941
Trimmed Mean ( 13 / 28 )1060.1551724137975.909814520567613.9659829115581
Trimmed Mean ( 14 / 28 )1050.0178571428674.338692670563314.1247823901892
Trimmed Mean ( 15 / 28 )1039.3333333333372.421359069516914.3511989651517
Trimmed Mean ( 16 / 28 )1028.7115384615470.298294277919514.6335206142356
Trimmed Mean ( 17 / 28 )1019.668.438406689548814.8980674641524
Trimmed Mean ( 18 / 28 )1009.9583333333366.146469743406315.2685145140948
Trimmed Mean ( 19 / 28 )1001.8695652173964.065452707553815.6382187727718
Trimmed Mean ( 20 / 28 )992.77272727272761.46672610624616.1513844995861
Trimmed Mean ( 21 / 28 )982.61904761904858.216893433490616.8785895238748
Trimmed Mean ( 22 / 28 )971.17554.370982168092917.8620094998013
Trimmed Mean ( 23 / 28 )967.76315789473753.084910568156718.2304754314733
Trimmed Mean ( 24 / 28 )963.66666666666751.435581532816818.7354091846289
Trimmed Mean ( 25 / 28 )958.88235294117650.304523008635619.0615534268473
Trimmed Mean ( 26 / 28 )952.2187549.075643850126319.403082166543
Trimmed Mean ( 27 / 28 )945.43333333333347.99544239218419.6983981438891
Trimmed Mean ( 28 / 28 )938.32142857142946.739711924913320.0754645231624
Median849
Midrange1651.5
Midmean - Weighted Average at Xnp969.674418604651
Midmean - Weighted Average at X(n+1)p982.619047619048
Midmean - Empirical Distribution Function969.674418604651
Midmean - Empirical Distribution Function - Averaging982.619047619048
Midmean - Empirical Distribution Function - Interpolation982.619047619048
Midmean - Closest Observation969.674418604651
Midmean - True Basic - Statistics Graphics Toolkit982.619047619048
Midmean - MS Excel (old versions)992.772727272727
Number of observations84



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
geomean <- function(x) {
return(exp(mean(log(x))))
}
harmean <- function(x) {
return(1/mean(1/x))
}
quamean <- function(x) {
return(sqrt(mean(x*x)))
}
winmean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
win <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
}
return(win)
}
trimean <- function(x) {
x <-sort(x[!is.na(x)])
n<-length(x)
denom <- 3
nodenom <- n/denom
if (nodenom>40) denom <- n/40
sqrtn = sqrt(n)
roundnodenom = floor(nodenom)
tri <- array(NA,dim=c(roundnodenom,2))
for (j in 1:roundnodenom) {
tri[j,1] <- mean(x,trim=j/n)
tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
}
return(tri)
}
midrange <- function(x) {
return((max(x)+min(x))/2)
}
q1 <- function(data,n,p,i,f) {
np <- n*p;
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q2 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
qvalue <- (1-f)*data[i] + f*data[i+1]
}
q3 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
q4 <- function(data,n,p,i,f) {
np <- n*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- (data[i]+data[i+1])/2
} else {
qvalue <- data[i+1]
}
}
q5 <- function(data,n,p,i,f) {
np <- (n-1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i+1]
} else {
qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
}
}
q6 <- function(data,n,p,i,f) {
np <- n*p+0.5
i <<- floor(np)
f <<- np - i
qvalue <- data[i]
}
q7 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
qvalue <- f*data[i] + (1-f)*data[i+1]
}
}
q8 <- function(data,n,p,i,f) {
np <- (n+1)*p
i <<- floor(np)
f <<- np - i
if (f==0) {
qvalue <- data[i]
} else {
if (f == 0.5) {
qvalue <- (data[i]+data[i+1])/2
} else {
if (f < 0.5) {
qvalue <- data[i]
} else {
qvalue <- data[i+1]
}
}
}
}
midmean <- function(x,def) {
x <-sort(x[!is.na(x)])
n<-length(x)
if (def==1) {
qvalue1 <- q1(x,n,0.25,i,f)
qvalue3 <- q1(x,n,0.75,i,f)
}
if (def==2) {
qvalue1 <- q2(x,n,0.25,i,f)
qvalue3 <- q2(x,n,0.75,i,f)
}
if (def==3) {
qvalue1 <- q3(x,n,0.25,i,f)
qvalue3 <- q3(x,n,0.75,i,f)
}
if (def==4) {
qvalue1 <- q4(x,n,0.25,i,f)
qvalue3 <- q4(x,n,0.75,i,f)
}
if (def==5) {
qvalue1 <- q5(x,n,0.25,i,f)
qvalue3 <- q5(x,n,0.75,i,f)
}
if (def==6) {
qvalue1 <- q6(x,n,0.25,i,f)
qvalue3 <- q6(x,n,0.75,i,f)
}
if (def==7) {
qvalue1 <- q7(x,n,0.25,i,f)
qvalue3 <- q7(x,n,0.75,i,f)
}
if (def==8) {
qvalue1 <- q8(x,n,0.25,i,f)
qvalue3 <- q8(x,n,0.75,i,f)
}
midm <- 0
myn <- 0
roundno4 <- round(n/4)
round3no4 <- round(3*n/4)
for (i in 1:n) {
if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
midm = midm + x[i]
myn = myn + 1
}
}
midm = midm / myn
return(midm)
}
(arm <- mean(x))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
lb <- win[,1] - 2*win[,2]
ub <- win[,1] + 2*win[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
bitmap(file='test2.png')
lb <- tri[,1] - 2*tri[,2]
ub <- tri[,1] + 2*tri[,2]
if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
lines(ub,lty=3)
lines(lb,lty=3)
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Measure',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.element(a,'S.E.',header=TRUE)
a<-table.element(a,'Value/S.E.',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
for (j in 1:length(win[,1])) {
a<-table.row.start(a)
mylabel <- paste('Winsorized Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(win[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
a<-table.row.end(a)
}
for (j in 1:length(tri[,1])) {
a<-table.row.start(a)
mylabel <- paste('Trimmed Mean (',j)
mylabel <- paste(mylabel,'/')
mylabel <- paste(mylabel,length(tri[,1]))
mylabel <- paste(mylabel,')')
a<-table.element(a,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')