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Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 07 Oct 2013 14:43:06 -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/07/t1381171452hrcba56vn8mb27z.htm/, Retrieved Fri, 03 May 2024 05:58:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=213742, Retrieved Fri, 03 May 2024 05:58:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2013-10-07 18:43:06] [62756545679af31f2a2b14ff700a18b9] [Current]
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Dataseries X:
78,7
75,7
77,1
86,1
86,8
86,3
91,5
90,7
78,2
73
73,7
77,3
67,5
72,7
76,6
82,4
82,3
86,3
93
88,8
96,9
103,9
115,7
112,8
114,7
118
129,3
137
156
166,2
167,8
144,3
126
90,4
67,5
52,4
54,6
52,9
59,1
63,3
73,8
87,6
81,8
90,7
86,3
93,6
98
94,3
97,6
94,2
100,2
106,7
95,7
94,6
94,7
96,2
96,3
103,3
106,8
113,7
117,4
123,6
137,6
147,4
137,2
133,8
136,7
127,3
128,7
127
133,7
132
135,1
142,6
149,3
143,5
131,4
114,7
122,3
133,4
134,6
130,9
127,9
128




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213742&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=213742&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213742&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'Sir Maurice George Kendall' @ kendall.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean105.1869047619053.0094500137787434.952201990499
Geometric Mean101.496231287771
Harmonic Mean97.7107298982924
Quadratic Mean108.70141881494
Winsorized Mean ( 1 / 28 )105.173809523813.0034781515804835.0173379714666
Winsorized Mean ( 2 / 28 )104.9714285714292.9398900398550335.7059029924142
Winsorized Mean ( 3 / 28 )104.8928571428572.8603516476534436.671315301008
Winsorized Mean ( 4 / 28 )105.0023809523812.8064489990880237.4146763352915
Winsorized Mean ( 5 / 28 )105.0678571428572.7305517173892938.4786182491038
Winsorized Mean ( 6 / 28 )105.0107142857142.7207359211332638.5964376292626
Winsorized Mean ( 7 / 28 )105.3690476190482.6396177161273539.9182983866456
Winsorized Mean ( 8 / 28 )104.9214285714292.5581751506945441.0141692381551
Winsorized Mean ( 9 / 28 )104.9535714285712.5404035431151441.3137399815909
Winsorized Mean ( 10 / 28 )104.9416666666672.5350057560881941.3970131683661
Winsorized Mean ( 11 / 28 )105.151190476192.4928914968472742.1804120272278
Winsorized Mean ( 12 / 28 )105.051190476192.4403241875056543.0480470644219
Winsorized Mean ( 13 / 28 )105.051190476192.418064363683943.4443317778961
Winsorized Mean ( 14 / 28 )104.951190476192.393928477883643.8405706126086
Winsorized Mean ( 15 / 28 )105.0940476190482.3691592438320344.3592164151287
Winsorized Mean ( 16 / 28 )105.1321428571432.347886441494244.7773542191575
Winsorized Mean ( 17 / 28 )105.476190476192.2241339241828847.4234889047615
Winsorized Mean ( 18 / 28 )105.4547619047622.1920404471062148.1080365300634
Winsorized Mean ( 19 / 28 )105.3642857142862.1730912139497448.485901115388
Winsorized Mean ( 20 / 28 )105.8642857142862.0109800738214152.643130129636
Winsorized Mean ( 21 / 28 )105.7642857142861.984088052783153.3062459430312
Winsorized Mean ( 22 / 28 )105.5809523809521.9586791978785553.9041577075548
Winsorized Mean ( 23 / 28 )105.5535714285711.9549057452547753.9941998148946
Winsorized Mean ( 24 / 28 )105.5251.9144608337579355.1199576085675
Winsorized Mean ( 25 / 28 )105.673809523811.8743620976825656.3785458820702
Winsorized Mean ( 26 / 28 )105.7357142857141.7892637700874759.0945371238055
Winsorized Mean ( 27 / 28 )105.4785714285711.6267539379769164.839905388364
Winsorized Mean ( 28 / 28 )105.1452380952381.5577498637044467.4981526528239
Trimmed Mean ( 1 / 28 )105.0670731707322.9149311160395936.0444446157213
Trimmed Mean ( 2 / 28 )104.9552.8120518770985837.323280148121
Trimmed Mean ( 3 / 28 )104.9461538461542.7322226483991438.4105423866696
Trimmed Mean ( 4 / 28 )104.9657894736842.6743049942398239.2497451486534
Trimmed Mean ( 5 / 28 )104.9554054054052.6252117856011439.9797860047211
Trimmed Mean ( 6 / 28 )104.9291666666672.5894864155508540.5212269261299
Trimmed Mean ( 7 / 28 )104.9128571428572.5492879868445341.1537879142154
Trimmed Mean ( 8 / 28 )104.8323529411762.5199427934129941.6010844433466
Trimmed Mean ( 9 / 28 )104.8181818181822.5014717431029941.9026047794402
Trimmed Mean ( 10 / 28 )104.79843752.4814355286156642.2329882406676
Trimmed Mean ( 11 / 28 )104.7790322580652.4568869920451142.6470702955884
Trimmed Mean ( 12 / 28 )104.7316666666672.4335571737460343.036452069647
Trimmed Mean ( 13 / 28 )104.6931034482762.4130917657117243.3854629715657
Trimmed Mean ( 14 / 28 )104.6517857142862.3901162704308143.7852279443386
Trimmed Mean ( 15 / 28 )104.6185185185192.3642147426206544.2508527810602
Trimmed Mean ( 16 / 28 )104.5673076923082.3345214403833844.7917529834874
Trimmed Mean ( 17 / 28 )104.5082.2993128343494545.4518404102106
Trimmed Mean ( 18 / 28 )104.4083333333332.2754487386392545.8847222353913
Trimmed Mean ( 19 / 28 )104.3021739130432.2482381489084146.392849424642
Trimmed Mean ( 20 / 28 )104.1954545454552.2141338093824647.0592400982828
Trimmed Mean ( 21 / 28 )104.0285714285712.1976211553236847.3368993452601
Trimmed Mean ( 22 / 28 )103.8552.1768418372990247.7090242481103
Trimmed Mean ( 23 / 28 )103.6815789473682.150122743736248.2212372523459
Trimmed Mean ( 24 / 28 )103.4916666666672.1100717470687549.0465155085054
Trimmed Mean ( 25 / 28 )103.2823529411762.0603829083074750.1277468982788
Trimmed Mean ( 26 / 28 )103.031251.9961173880852151.6158271126696
Trimmed Mean ( 27 / 28 )102.741.9238287973152253.4039204233651
Trimmed Mean ( 28 / 28 )102.4357142857141.8651511299938454.9208654668388
Median97.8
Midrange110.1
Midmean - Weighted Average at Xnp103.611627906977
Midmean - Weighted Average at X(n+1)p104.028571428571
Midmean - Empirical Distribution Function103.611627906977
Midmean - Empirical Distribution Function - Averaging104.028571428571
Midmean - Empirical Distribution Function - Interpolation104.028571428571
Midmean - Closest Observation103.611627906977
Midmean - True Basic - Statistics Graphics Toolkit104.028571428571
Midmean - MS Excel (old versions)104.195454545455
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 105.186904761905 & 3.00945001377874 & 34.952201990499 \tabularnewline
Geometric Mean & 101.496231287771 &  &  \tabularnewline
Harmonic Mean & 97.7107298982924 &  &  \tabularnewline
Quadratic Mean & 108.70141881494 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 105.17380952381 & 3.00347815158048 & 35.0173379714666 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 104.971428571429 & 2.93989003985503 & 35.7059029924142 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 104.892857142857 & 2.86035164765344 & 36.671315301008 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 105.002380952381 & 2.80644899908802 & 37.4146763352915 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 105.067857142857 & 2.73055171738929 & 38.4786182491038 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 105.010714285714 & 2.72073592113326 & 38.5964376292626 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 105.369047619048 & 2.63961771612735 & 39.9182983866456 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 104.921428571429 & 2.55817515069454 & 41.0141692381551 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 104.953571428571 & 2.54040354311514 & 41.3137399815909 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 104.941666666667 & 2.53500575608819 & 41.3970131683661 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 105.15119047619 & 2.49289149684727 & 42.1804120272278 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 105.05119047619 & 2.44032418750565 & 43.0480470644219 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 105.05119047619 & 2.4180643636839 & 43.4443317778961 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 104.95119047619 & 2.3939284778836 & 43.8405706126086 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 105.094047619048 & 2.36915924383203 & 44.3592164151287 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 105.132142857143 & 2.3478864414942 & 44.7773542191575 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 105.47619047619 & 2.22413392418288 & 47.4234889047615 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 105.454761904762 & 2.19204044710621 & 48.1080365300634 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 105.364285714286 & 2.17309121394974 & 48.485901115388 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 105.864285714286 & 2.01098007382141 & 52.643130129636 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 105.764285714286 & 1.9840880527831 & 53.3062459430312 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 105.580952380952 & 1.95867919787855 & 53.9041577075548 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 105.553571428571 & 1.95490574525477 & 53.9941998148946 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 105.525 & 1.91446083375793 & 55.1199576085675 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 105.67380952381 & 1.87436209768256 & 56.3785458820702 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 105.735714285714 & 1.78926377008747 & 59.0945371238055 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 105.478571428571 & 1.62675393797691 & 64.839905388364 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 105.145238095238 & 1.55774986370444 & 67.4981526528239 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 105.067073170732 & 2.91493111603959 & 36.0444446157213 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 104.955 & 2.81205187709858 & 37.323280148121 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 104.946153846154 & 2.73222264839914 & 38.4105423866696 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 104.965789473684 & 2.67430499423982 & 39.2497451486534 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 104.955405405405 & 2.62521178560114 & 39.9797860047211 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 104.929166666667 & 2.58948641555085 & 40.5212269261299 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 104.912857142857 & 2.54928798684453 & 41.1537879142154 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 104.832352941176 & 2.51994279341299 & 41.6010844433466 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 104.818181818182 & 2.50147174310299 & 41.9026047794402 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 104.7984375 & 2.48143552861566 & 42.2329882406676 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 104.779032258065 & 2.45688699204511 & 42.6470702955884 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 104.731666666667 & 2.43355717374603 & 43.036452069647 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 104.693103448276 & 2.41309176571172 & 43.3854629715657 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 104.651785714286 & 2.39011627043081 & 43.7852279443386 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 104.618518518519 & 2.36421474262065 & 44.2508527810602 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 104.567307692308 & 2.33452144038338 & 44.7917529834874 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 104.508 & 2.29931283434945 & 45.4518404102106 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 104.408333333333 & 2.27544873863925 & 45.8847222353913 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 104.302173913043 & 2.24823814890841 & 46.392849424642 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 104.195454545455 & 2.21413380938246 & 47.0592400982828 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 104.028571428571 & 2.19762115532368 & 47.3368993452601 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 103.855 & 2.17684183729902 & 47.7090242481103 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 103.681578947368 & 2.1501227437362 & 48.2212372523459 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 103.491666666667 & 2.11007174706875 & 49.0465155085054 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 103.282352941176 & 2.06038290830747 & 50.1277468982788 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 103.03125 & 1.99611738808521 & 51.6158271126696 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 102.74 & 1.92382879731522 & 53.4039204233651 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 102.435714285714 & 1.86515112999384 & 54.9208654668388 \tabularnewline
Median & 97.8 &  &  \tabularnewline
Midrange & 110.1 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 103.611627906977 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 104.028571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 103.611627906977 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 104.028571428571 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 104.028571428571 &  &  \tabularnewline
Midmean - Closest Observation & 103.611627906977 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 104.028571428571 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 104.195454545455 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=213742&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]105.186904761905[/C][C]3.00945001377874[/C][C]34.952201990499[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]101.496231287771[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]97.7107298982924[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]108.70141881494[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]105.17380952381[/C][C]3.00347815158048[/C][C]35.0173379714666[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]104.971428571429[/C][C]2.93989003985503[/C][C]35.7059029924142[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]104.892857142857[/C][C]2.86035164765344[/C][C]36.671315301008[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]105.002380952381[/C][C]2.80644899908802[/C][C]37.4146763352915[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]105.067857142857[/C][C]2.73055171738929[/C][C]38.4786182491038[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]105.010714285714[/C][C]2.72073592113326[/C][C]38.5964376292626[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]105.369047619048[/C][C]2.63961771612735[/C][C]39.9182983866456[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]104.921428571429[/C][C]2.55817515069454[/C][C]41.0141692381551[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]104.953571428571[/C][C]2.54040354311514[/C][C]41.3137399815909[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]104.941666666667[/C][C]2.53500575608819[/C][C]41.3970131683661[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]105.15119047619[/C][C]2.49289149684727[/C][C]42.1804120272278[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]105.05119047619[/C][C]2.44032418750565[/C][C]43.0480470644219[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]105.05119047619[/C][C]2.4180643636839[/C][C]43.4443317778961[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]104.95119047619[/C][C]2.3939284778836[/C][C]43.8405706126086[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]105.094047619048[/C][C]2.36915924383203[/C][C]44.3592164151287[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]105.132142857143[/C][C]2.3478864414942[/C][C]44.7773542191575[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]105.47619047619[/C][C]2.22413392418288[/C][C]47.4234889047615[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]105.454761904762[/C][C]2.19204044710621[/C][C]48.1080365300634[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]105.364285714286[/C][C]2.17309121394974[/C][C]48.485901115388[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]105.864285714286[/C][C]2.01098007382141[/C][C]52.643130129636[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]105.764285714286[/C][C]1.9840880527831[/C][C]53.3062459430312[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]105.580952380952[/C][C]1.95867919787855[/C][C]53.9041577075548[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]105.553571428571[/C][C]1.95490574525477[/C][C]53.9941998148946[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]105.525[/C][C]1.91446083375793[/C][C]55.1199576085675[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]105.67380952381[/C][C]1.87436209768256[/C][C]56.3785458820702[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]105.735714285714[/C][C]1.78926377008747[/C][C]59.0945371238055[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]105.478571428571[/C][C]1.62675393797691[/C][C]64.839905388364[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]105.145238095238[/C][C]1.55774986370444[/C][C]67.4981526528239[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]105.067073170732[/C][C]2.91493111603959[/C][C]36.0444446157213[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]104.955[/C][C]2.81205187709858[/C][C]37.323280148121[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]104.946153846154[/C][C]2.73222264839914[/C][C]38.4105423866696[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]104.965789473684[/C][C]2.67430499423982[/C][C]39.2497451486534[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]104.955405405405[/C][C]2.62521178560114[/C][C]39.9797860047211[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]104.929166666667[/C][C]2.58948641555085[/C][C]40.5212269261299[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]104.912857142857[/C][C]2.54928798684453[/C][C]41.1537879142154[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]104.832352941176[/C][C]2.51994279341299[/C][C]41.6010844433466[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]104.818181818182[/C][C]2.50147174310299[/C][C]41.9026047794402[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]104.7984375[/C][C]2.48143552861566[/C][C]42.2329882406676[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]104.779032258065[/C][C]2.45688699204511[/C][C]42.6470702955884[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]104.731666666667[/C][C]2.43355717374603[/C][C]43.036452069647[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]104.693103448276[/C][C]2.41309176571172[/C][C]43.3854629715657[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]104.651785714286[/C][C]2.39011627043081[/C][C]43.7852279443386[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]104.618518518519[/C][C]2.36421474262065[/C][C]44.2508527810602[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]104.567307692308[/C][C]2.33452144038338[/C][C]44.7917529834874[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]104.508[/C][C]2.29931283434945[/C][C]45.4518404102106[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]104.408333333333[/C][C]2.27544873863925[/C][C]45.8847222353913[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]104.302173913043[/C][C]2.24823814890841[/C][C]46.392849424642[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]104.195454545455[/C][C]2.21413380938246[/C][C]47.0592400982828[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]104.028571428571[/C][C]2.19762115532368[/C][C]47.3368993452601[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]103.855[/C][C]2.17684183729902[/C][C]47.7090242481103[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]103.681578947368[/C][C]2.1501227437362[/C][C]48.2212372523459[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]103.491666666667[/C][C]2.11007174706875[/C][C]49.0465155085054[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]103.282352941176[/C][C]2.06038290830747[/C][C]50.1277468982788[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]103.03125[/C][C]1.99611738808521[/C][C]51.6158271126696[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]102.74[/C][C]1.92382879731522[/C][C]53.4039204233651[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]102.435714285714[/C][C]1.86515112999384[/C][C]54.9208654668388[/C][/ROW]
[ROW][C]Median[/C][C]97.8[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]110.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]103.611627906977[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]104.028571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]103.611627906977[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]104.028571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]104.028571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]103.611627906977[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]104.028571428571[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]104.195454545455[/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=213742&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=213742&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 Mean105.1869047619053.0094500137787434.952201990499
Geometric Mean101.496231287771
Harmonic Mean97.7107298982924
Quadratic Mean108.70141881494
Winsorized Mean ( 1 / 28 )105.173809523813.0034781515804835.0173379714666
Winsorized Mean ( 2 / 28 )104.9714285714292.9398900398550335.7059029924142
Winsorized Mean ( 3 / 28 )104.8928571428572.8603516476534436.671315301008
Winsorized Mean ( 4 / 28 )105.0023809523812.8064489990880237.4146763352915
Winsorized Mean ( 5 / 28 )105.0678571428572.7305517173892938.4786182491038
Winsorized Mean ( 6 / 28 )105.0107142857142.7207359211332638.5964376292626
Winsorized Mean ( 7 / 28 )105.3690476190482.6396177161273539.9182983866456
Winsorized Mean ( 8 / 28 )104.9214285714292.5581751506945441.0141692381551
Winsorized Mean ( 9 / 28 )104.9535714285712.5404035431151441.3137399815909
Winsorized Mean ( 10 / 28 )104.9416666666672.5350057560881941.3970131683661
Winsorized Mean ( 11 / 28 )105.151190476192.4928914968472742.1804120272278
Winsorized Mean ( 12 / 28 )105.051190476192.4403241875056543.0480470644219
Winsorized Mean ( 13 / 28 )105.051190476192.418064363683943.4443317778961
Winsorized Mean ( 14 / 28 )104.951190476192.393928477883643.8405706126086
Winsorized Mean ( 15 / 28 )105.0940476190482.3691592438320344.3592164151287
Winsorized Mean ( 16 / 28 )105.1321428571432.347886441494244.7773542191575
Winsorized Mean ( 17 / 28 )105.476190476192.2241339241828847.4234889047615
Winsorized Mean ( 18 / 28 )105.4547619047622.1920404471062148.1080365300634
Winsorized Mean ( 19 / 28 )105.3642857142862.1730912139497448.485901115388
Winsorized Mean ( 20 / 28 )105.8642857142862.0109800738214152.643130129636
Winsorized Mean ( 21 / 28 )105.7642857142861.984088052783153.3062459430312
Winsorized Mean ( 22 / 28 )105.5809523809521.9586791978785553.9041577075548
Winsorized Mean ( 23 / 28 )105.5535714285711.9549057452547753.9941998148946
Winsorized Mean ( 24 / 28 )105.5251.9144608337579355.1199576085675
Winsorized Mean ( 25 / 28 )105.673809523811.8743620976825656.3785458820702
Winsorized Mean ( 26 / 28 )105.7357142857141.7892637700874759.0945371238055
Winsorized Mean ( 27 / 28 )105.4785714285711.6267539379769164.839905388364
Winsorized Mean ( 28 / 28 )105.1452380952381.5577498637044467.4981526528239
Trimmed Mean ( 1 / 28 )105.0670731707322.9149311160395936.0444446157213
Trimmed Mean ( 2 / 28 )104.9552.8120518770985837.323280148121
Trimmed Mean ( 3 / 28 )104.9461538461542.7322226483991438.4105423866696
Trimmed Mean ( 4 / 28 )104.9657894736842.6743049942398239.2497451486534
Trimmed Mean ( 5 / 28 )104.9554054054052.6252117856011439.9797860047211
Trimmed Mean ( 6 / 28 )104.9291666666672.5894864155508540.5212269261299
Trimmed Mean ( 7 / 28 )104.9128571428572.5492879868445341.1537879142154
Trimmed Mean ( 8 / 28 )104.8323529411762.5199427934129941.6010844433466
Trimmed Mean ( 9 / 28 )104.8181818181822.5014717431029941.9026047794402
Trimmed Mean ( 10 / 28 )104.79843752.4814355286156642.2329882406676
Trimmed Mean ( 11 / 28 )104.7790322580652.4568869920451142.6470702955884
Trimmed Mean ( 12 / 28 )104.7316666666672.4335571737460343.036452069647
Trimmed Mean ( 13 / 28 )104.6931034482762.4130917657117243.3854629715657
Trimmed Mean ( 14 / 28 )104.6517857142862.3901162704308143.7852279443386
Trimmed Mean ( 15 / 28 )104.6185185185192.3642147426206544.2508527810602
Trimmed Mean ( 16 / 28 )104.5673076923082.3345214403833844.7917529834874
Trimmed Mean ( 17 / 28 )104.5082.2993128343494545.4518404102106
Trimmed Mean ( 18 / 28 )104.4083333333332.2754487386392545.8847222353913
Trimmed Mean ( 19 / 28 )104.3021739130432.2482381489084146.392849424642
Trimmed Mean ( 20 / 28 )104.1954545454552.2141338093824647.0592400982828
Trimmed Mean ( 21 / 28 )104.0285714285712.1976211553236847.3368993452601
Trimmed Mean ( 22 / 28 )103.8552.1768418372990247.7090242481103
Trimmed Mean ( 23 / 28 )103.6815789473682.150122743736248.2212372523459
Trimmed Mean ( 24 / 28 )103.4916666666672.1100717470687549.0465155085054
Trimmed Mean ( 25 / 28 )103.2823529411762.0603829083074750.1277468982788
Trimmed Mean ( 26 / 28 )103.031251.9961173880852151.6158271126696
Trimmed Mean ( 27 / 28 )102.741.9238287973152253.4039204233651
Trimmed Mean ( 28 / 28 )102.4357142857141.8651511299938454.9208654668388
Median97.8
Midrange110.1
Midmean - Weighted Average at Xnp103.611627906977
Midmean - Weighted Average at X(n+1)p104.028571428571
Midmean - Empirical Distribution Function103.611627906977
Midmean - Empirical Distribution Function - Averaging104.028571428571
Midmean - Empirical Distribution Function - Interpolation104.028571428571
Midmean - Closest Observation103.611627906977
Midmean - True Basic - Statistics Graphics Toolkit104.028571428571
Midmean - MS Excel (old versions)104.195454545455
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')