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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationFri, 11 Oct 2013 10:18:25 -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/t1381501115dfx7nui0pbkn4w2.htm/, Retrieved Sat, 27 Apr 2024 19:24:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=214792, Retrieved Sat, 27 Apr 2024 19:24:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2013-10-11 14:18:25] [998078bdc1a977f0c7d195eebcf8b96b] [Current]
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Dataseries X:
55,7
59,2
59,8
61,6
65,8
64,2
67
62,8
65,5
75,2
80,9
83,2
83,7
86,4
85,9
80,4
81,8
87,5
83,7
87
99,7
101,4
101,9
115,7
123,2
136,9
146,8
149,6
146,5
157
147,9
133,6
128,7
100,8
91,8
89,3
96,7
91,6
93,3
93,3
101
100,4
86,9
83,9
80,3
87,7
92,7
95,5
92
87,4
86,8
83,7
85
81,7
90,9
101,5
113,8
120,1
122,1
132,5
140
149,4
144,3
154,4
151,4
145,5
136,8
146,6
145,1
133,6
131,4
127,5
130,1
131,1
132,3
128,6
125,1
128,7
156,1
163,2
159,8
157,4
156,2
152,5




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=214792&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=214792&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214792&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 Mean109.2380952380953.3320644048135332.7839087024516
Geometric Mean104.903454644329
Harmonic Mean100.557916869138
Quadratic Mean113.377606548501
Winsorized Mean ( 1 / 28 )109.2392857142863.3165772271001632.937356266478
Winsorized Mean ( 2 / 28 )109.1964285714293.3037212135183433.0525554410018
Winsorized Mean ( 3 / 28 )109.2464285714293.2898169729507933.2074487637652
Winsorized Mean ( 4 / 28 )109.2654761904763.2733229049496133.3805980538172
Winsorized Mean ( 5 / 28 )109.3428571428573.2582123109648133.5591565886874
Winsorized Mean ( 6 / 28 )109.3142857142863.2221204318030833.9261948856189
Winsorized Mean ( 7 / 28 )109.1809523809523.1917319481753334.2074316245039
Winsorized Mean ( 8 / 28 )109.1904761904763.1561642819873634.5959419202735
Winsorized Mean ( 9 / 28 )109.876190476192.9928824628051236.7124976813181
Winsorized Mean ( 10 / 28 )110.4595238095242.9086952550531737.9756262254103
Winsorized Mean ( 11 / 28 )110.276190476192.8757326483216638.3471636490791
Winsorized Mean ( 12 / 28 )110.1904761904762.8422482772950438.7687722676163
Winsorized Mean ( 13 / 28 )110.2833333333332.8222066461894939.0769873220434
Winsorized Mean ( 14 / 28 )110.2833333333332.8175922801943139.1409836364712
Winsorized Mean ( 15 / 28 )110.3547619047622.7600197709188939.9833229701907
Winsorized Mean ( 16 / 28 )110.373809523812.7371161286654240.3248544582674
Winsorized Mean ( 17 / 28 )110.2119047619052.7124843671865740.6313511315158
Winsorized Mean ( 18 / 28 )109.2904761904762.5764738492431242.41862428473
Winsorized Mean ( 19 / 28 )108.6345238095242.472359822620143.9396089580512
Winsorized Mean ( 20 / 28 )108.8726190476192.43784016923544.6594573432529
Winsorized Mean ( 21 / 28 )108.2976190476192.3031663805151547.021187858515
Winsorized Mean ( 22 / 28 )108.4285714285712.2878991279061747.392199291497
Winsorized Mean ( 23 / 28 )108.2369047619052.2355623224969548.4159639267013
Winsorized Mean ( 24 / 28 )108.2083333333332.224799724967948.6373367089905
Winsorized Mean ( 25 / 28 )107.9702380952382.1865984527000549.3781736477104
Winsorized Mean ( 26 / 28 )108.001190476192.1603581052672149.992262955327
Winsorized Mean ( 27 / 28 )107.7119047619052.1154639257697750.9164460096908
Winsorized Mean ( 28 / 28 )107.3119047619052.048675043582952.3811255953158
Trimmed Mean ( 1 / 28 )109.2329268292683.283949476475133.2626697249057
Trimmed Mean ( 2 / 28 )109.226253.2454728662848433.6549570741084
Trimmed Mean ( 3 / 28 )109.2423076923083.2078997973221634.0541521226752
Trimmed Mean ( 4 / 28 )109.2407894736843.1693400594985734.4679925230136
Trimmed Mean ( 5 / 28 )109.2337837837843.1291160391278934.9088312538989
Trimmed Mean ( 6 / 28 )109.2083333333333.0855193050516935.393825977538
Trimmed Mean ( 7 / 28 )109.1871428571433.0426811494706435.8851741255041
Trimmed Mean ( 8 / 28 )109.1882352941182.9982893347844836.4168441075304
Trimmed Mean ( 9 / 28 )109.1878787878792.9524424049509436.9822214329336
Trimmed Mean ( 10 / 28 )109.08752.9296738028780337.2353740859598
Trimmed Mean ( 11 / 28 )108.9016129032262.9156414483240237.3508247956294
Trimmed Mean ( 12 / 28 )108.7266666666672.9021518089876937.4641555034958
Trimmed Mean ( 13 / 28 )108.552.8888402104729737.575633157719
Trimmed Mean ( 14 / 28 )108.352.8727854260101137.7160086580092
Trimmed Mean ( 15 / 28 )108.1351851851852.850582783240137.9344132087523
Trimmed Mean ( 16 / 28 )107.8961538461542.829709280456938.1297664008552
Trimmed Mean ( 17 / 28 )107.6362.8039531277924638.3872322732945
Trimmed Mean ( 18 / 28 )107.3708333333332.7725317409775738.7266380926897
Trimmed Mean ( 19 / 28 )107.1760869565222.7553201674129938.8978704631451
Trimmed Mean ( 20 / 28 )107.0295454545452.7481275184704138.946353375231
Trimmed Mean ( 21 / 28 )106.8452380952382.7386937940931539.0132107231861
Trimmed Mean ( 22 / 28 )106.72.7456725858554138.8611521088403
Trimmed Mean ( 23 / 28 )106.5263157894742.7487943411910538.7538326142347
Trimmed Mean ( 24 / 28 )106.3527777777782.7543197993913538.6130825481048
Trimmed Mean ( 25 / 28 )106.1617647058822.7533483576107838.5573312626537
Trimmed Mean ( 26 / 28 )105.9718752.749725918801438.5390683032849
Trimmed Mean ( 27 / 28 )105.7533333333332.7381373538561538.6223624554114
Trimmed Mean ( 28 / 28 )105.5357142857142.7205528455327538.792010402962
Median100.9
Midrange109.45
Midmean - Weighted Average at Xnp106.337209302326
Midmean - Weighted Average at X(n+1)p106.845238095238
Midmean - Empirical Distribution Function106.337209302326
Midmean - Empirical Distribution Function - Averaging106.845238095238
Midmean - Empirical Distribution Function - Interpolation106.845238095238
Midmean - Closest Observation106.337209302326
Midmean - True Basic - Statistics Graphics Toolkit106.845238095238
Midmean - MS Excel (old versions)107.029545454545
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 109.238095238095 & 3.33206440481353 & 32.7839087024516 \tabularnewline
Geometric Mean & 104.903454644329 &  &  \tabularnewline
Harmonic Mean & 100.557916869138 &  &  \tabularnewline
Quadratic Mean & 113.377606548501 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 109.239285714286 & 3.31657722710016 & 32.937356266478 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 109.196428571429 & 3.30372121351834 & 33.0525554410018 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 109.246428571429 & 3.28981697295079 & 33.2074487637652 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 109.265476190476 & 3.27332290494961 & 33.3805980538172 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 109.342857142857 & 3.25821231096481 & 33.5591565886874 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 109.314285714286 & 3.22212043180308 & 33.9261948856189 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 109.180952380952 & 3.19173194817533 & 34.2074316245039 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 109.190476190476 & 3.15616428198736 & 34.5959419202735 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 109.87619047619 & 2.99288246280512 & 36.7124976813181 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 110.459523809524 & 2.90869525505317 & 37.9756262254103 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 110.27619047619 & 2.87573264832166 & 38.3471636490791 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 110.190476190476 & 2.84224827729504 & 38.7687722676163 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 110.283333333333 & 2.82220664618949 & 39.0769873220434 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 110.283333333333 & 2.81759228019431 & 39.1409836364712 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 110.354761904762 & 2.76001977091889 & 39.9833229701907 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 110.37380952381 & 2.73711612866542 & 40.3248544582674 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 110.211904761905 & 2.71248436718657 & 40.6313511315158 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 109.290476190476 & 2.57647384924312 & 42.41862428473 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 108.634523809524 & 2.4723598226201 & 43.9396089580512 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 108.872619047619 & 2.437840169235 & 44.6594573432529 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 108.297619047619 & 2.30316638051515 & 47.021187858515 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 108.428571428571 & 2.28789912790617 & 47.392199291497 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 108.236904761905 & 2.23556232249695 & 48.4159639267013 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 108.208333333333 & 2.2247997249679 & 48.6373367089905 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 107.970238095238 & 2.18659845270005 & 49.3781736477104 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 108.00119047619 & 2.16035810526721 & 49.992262955327 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 107.711904761905 & 2.11546392576977 & 50.9164460096908 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 107.311904761905 & 2.0486750435829 & 52.3811255953158 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 109.232926829268 & 3.2839494764751 & 33.2626697249057 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 109.22625 & 3.24547286628484 & 33.6549570741084 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 109.242307692308 & 3.20789979732216 & 34.0541521226752 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 109.240789473684 & 3.16934005949857 & 34.4679925230136 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 109.233783783784 & 3.12911603912789 & 34.9088312538989 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 109.208333333333 & 3.08551930505169 & 35.393825977538 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 109.187142857143 & 3.04268114947064 & 35.8851741255041 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 109.188235294118 & 2.99828933478448 & 36.4168441075304 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 109.187878787879 & 2.95244240495094 & 36.9822214329336 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 109.0875 & 2.92967380287803 & 37.2353740859598 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 108.901612903226 & 2.91564144832402 & 37.3508247956294 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 108.726666666667 & 2.90215180898769 & 37.4641555034958 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 108.55 & 2.88884021047297 & 37.575633157719 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 108.35 & 2.87278542601011 & 37.7160086580092 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 108.135185185185 & 2.8505827832401 & 37.9344132087523 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 107.896153846154 & 2.8297092804569 & 38.1297664008552 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 107.636 & 2.80395312779246 & 38.3872322732945 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 107.370833333333 & 2.77253174097757 & 38.7266380926897 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 107.176086956522 & 2.75532016741299 & 38.8978704631451 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 107.029545454545 & 2.74812751847041 & 38.946353375231 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 106.845238095238 & 2.73869379409315 & 39.0132107231861 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 106.7 & 2.74567258585541 & 38.8611521088403 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 106.526315789474 & 2.74879434119105 & 38.7538326142347 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 106.352777777778 & 2.75431979939135 & 38.6130825481048 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 106.161764705882 & 2.75334835761078 & 38.5573312626537 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 105.971875 & 2.7497259188014 & 38.5390683032849 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 105.753333333333 & 2.73813735385615 & 38.6223624554114 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 105.535714285714 & 2.72055284553275 & 38.792010402962 \tabularnewline
Median & 100.9 &  &  \tabularnewline
Midrange & 109.45 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 106.337209302326 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 106.845238095238 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 106.337209302326 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 106.845238095238 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 106.845238095238 &  &  \tabularnewline
Midmean - Closest Observation & 106.337209302326 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 106.845238095238 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 107.029545454545 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=214792&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]109.238095238095[/C][C]3.33206440481353[/C][C]32.7839087024516[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]104.903454644329[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]100.557916869138[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]113.377606548501[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]109.239285714286[/C][C]3.31657722710016[/C][C]32.937356266478[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]109.196428571429[/C][C]3.30372121351834[/C][C]33.0525554410018[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]109.246428571429[/C][C]3.28981697295079[/C][C]33.2074487637652[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]109.265476190476[/C][C]3.27332290494961[/C][C]33.3805980538172[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]109.342857142857[/C][C]3.25821231096481[/C][C]33.5591565886874[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]109.314285714286[/C][C]3.22212043180308[/C][C]33.9261948856189[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]109.180952380952[/C][C]3.19173194817533[/C][C]34.2074316245039[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]109.190476190476[/C][C]3.15616428198736[/C][C]34.5959419202735[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]109.87619047619[/C][C]2.99288246280512[/C][C]36.7124976813181[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]110.459523809524[/C][C]2.90869525505317[/C][C]37.9756262254103[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]110.27619047619[/C][C]2.87573264832166[/C][C]38.3471636490791[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]110.190476190476[/C][C]2.84224827729504[/C][C]38.7687722676163[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]110.283333333333[/C][C]2.82220664618949[/C][C]39.0769873220434[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]110.283333333333[/C][C]2.81759228019431[/C][C]39.1409836364712[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]110.354761904762[/C][C]2.76001977091889[/C][C]39.9833229701907[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]110.37380952381[/C][C]2.73711612866542[/C][C]40.3248544582674[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]110.211904761905[/C][C]2.71248436718657[/C][C]40.6313511315158[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]109.290476190476[/C][C]2.57647384924312[/C][C]42.41862428473[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]108.634523809524[/C][C]2.4723598226201[/C][C]43.9396089580512[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]108.872619047619[/C][C]2.437840169235[/C][C]44.6594573432529[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]108.297619047619[/C][C]2.30316638051515[/C][C]47.021187858515[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]108.428571428571[/C][C]2.28789912790617[/C][C]47.392199291497[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]108.236904761905[/C][C]2.23556232249695[/C][C]48.4159639267013[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]108.208333333333[/C][C]2.2247997249679[/C][C]48.6373367089905[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]107.970238095238[/C][C]2.18659845270005[/C][C]49.3781736477104[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]108.00119047619[/C][C]2.16035810526721[/C][C]49.992262955327[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]107.711904761905[/C][C]2.11546392576977[/C][C]50.9164460096908[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]107.311904761905[/C][C]2.0486750435829[/C][C]52.3811255953158[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]109.232926829268[/C][C]3.2839494764751[/C][C]33.2626697249057[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]109.22625[/C][C]3.24547286628484[/C][C]33.6549570741084[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]109.242307692308[/C][C]3.20789979732216[/C][C]34.0541521226752[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]109.240789473684[/C][C]3.16934005949857[/C][C]34.4679925230136[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]109.233783783784[/C][C]3.12911603912789[/C][C]34.9088312538989[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]109.208333333333[/C][C]3.08551930505169[/C][C]35.393825977538[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]109.187142857143[/C][C]3.04268114947064[/C][C]35.8851741255041[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]109.188235294118[/C][C]2.99828933478448[/C][C]36.4168441075304[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]109.187878787879[/C][C]2.95244240495094[/C][C]36.9822214329336[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]109.0875[/C][C]2.92967380287803[/C][C]37.2353740859598[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]108.901612903226[/C][C]2.91564144832402[/C][C]37.3508247956294[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]108.726666666667[/C][C]2.90215180898769[/C][C]37.4641555034958[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]108.55[/C][C]2.88884021047297[/C][C]37.575633157719[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]108.35[/C][C]2.87278542601011[/C][C]37.7160086580092[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]108.135185185185[/C][C]2.8505827832401[/C][C]37.9344132087523[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]107.896153846154[/C][C]2.8297092804569[/C][C]38.1297664008552[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]107.636[/C][C]2.80395312779246[/C][C]38.3872322732945[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]107.370833333333[/C][C]2.77253174097757[/C][C]38.7266380926897[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]107.176086956522[/C][C]2.75532016741299[/C][C]38.8978704631451[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]107.029545454545[/C][C]2.74812751847041[/C][C]38.946353375231[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]106.845238095238[/C][C]2.73869379409315[/C][C]39.0132107231861[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]106.7[/C][C]2.74567258585541[/C][C]38.8611521088403[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]106.526315789474[/C][C]2.74879434119105[/C][C]38.7538326142347[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]106.352777777778[/C][C]2.75431979939135[/C][C]38.6130825481048[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]106.161764705882[/C][C]2.75334835761078[/C][C]38.5573312626537[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]105.971875[/C][C]2.7497259188014[/C][C]38.5390683032849[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]105.753333333333[/C][C]2.73813735385615[/C][C]38.6223624554114[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]105.535714285714[/C][C]2.72055284553275[/C][C]38.792010402962[/C][/ROW]
[ROW][C]Median[/C][C]100.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]109.45[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]106.337209302326[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]106.845238095238[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]106.337209302326[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]106.845238095238[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]106.845238095238[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]106.337209302326[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]106.845238095238[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]107.029545454545[/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=214792&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=214792&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 Mean109.2380952380953.3320644048135332.7839087024516
Geometric Mean104.903454644329
Harmonic Mean100.557916869138
Quadratic Mean113.377606548501
Winsorized Mean ( 1 / 28 )109.2392857142863.3165772271001632.937356266478
Winsorized Mean ( 2 / 28 )109.1964285714293.3037212135183433.0525554410018
Winsorized Mean ( 3 / 28 )109.2464285714293.2898169729507933.2074487637652
Winsorized Mean ( 4 / 28 )109.2654761904763.2733229049496133.3805980538172
Winsorized Mean ( 5 / 28 )109.3428571428573.2582123109648133.5591565886874
Winsorized Mean ( 6 / 28 )109.3142857142863.2221204318030833.9261948856189
Winsorized Mean ( 7 / 28 )109.1809523809523.1917319481753334.2074316245039
Winsorized Mean ( 8 / 28 )109.1904761904763.1561642819873634.5959419202735
Winsorized Mean ( 9 / 28 )109.876190476192.9928824628051236.7124976813181
Winsorized Mean ( 10 / 28 )110.4595238095242.9086952550531737.9756262254103
Winsorized Mean ( 11 / 28 )110.276190476192.8757326483216638.3471636490791
Winsorized Mean ( 12 / 28 )110.1904761904762.8422482772950438.7687722676163
Winsorized Mean ( 13 / 28 )110.2833333333332.8222066461894939.0769873220434
Winsorized Mean ( 14 / 28 )110.2833333333332.8175922801943139.1409836364712
Winsorized Mean ( 15 / 28 )110.3547619047622.7600197709188939.9833229701907
Winsorized Mean ( 16 / 28 )110.373809523812.7371161286654240.3248544582674
Winsorized Mean ( 17 / 28 )110.2119047619052.7124843671865740.6313511315158
Winsorized Mean ( 18 / 28 )109.2904761904762.5764738492431242.41862428473
Winsorized Mean ( 19 / 28 )108.6345238095242.472359822620143.9396089580512
Winsorized Mean ( 20 / 28 )108.8726190476192.43784016923544.6594573432529
Winsorized Mean ( 21 / 28 )108.2976190476192.3031663805151547.021187858515
Winsorized Mean ( 22 / 28 )108.4285714285712.2878991279061747.392199291497
Winsorized Mean ( 23 / 28 )108.2369047619052.2355623224969548.4159639267013
Winsorized Mean ( 24 / 28 )108.2083333333332.224799724967948.6373367089905
Winsorized Mean ( 25 / 28 )107.9702380952382.1865984527000549.3781736477104
Winsorized Mean ( 26 / 28 )108.001190476192.1603581052672149.992262955327
Winsorized Mean ( 27 / 28 )107.7119047619052.1154639257697750.9164460096908
Winsorized Mean ( 28 / 28 )107.3119047619052.048675043582952.3811255953158
Trimmed Mean ( 1 / 28 )109.2329268292683.283949476475133.2626697249057
Trimmed Mean ( 2 / 28 )109.226253.2454728662848433.6549570741084
Trimmed Mean ( 3 / 28 )109.2423076923083.2078997973221634.0541521226752
Trimmed Mean ( 4 / 28 )109.2407894736843.1693400594985734.4679925230136
Trimmed Mean ( 5 / 28 )109.2337837837843.1291160391278934.9088312538989
Trimmed Mean ( 6 / 28 )109.2083333333333.0855193050516935.393825977538
Trimmed Mean ( 7 / 28 )109.1871428571433.0426811494706435.8851741255041
Trimmed Mean ( 8 / 28 )109.1882352941182.9982893347844836.4168441075304
Trimmed Mean ( 9 / 28 )109.1878787878792.9524424049509436.9822214329336
Trimmed Mean ( 10 / 28 )109.08752.9296738028780337.2353740859598
Trimmed Mean ( 11 / 28 )108.9016129032262.9156414483240237.3508247956294
Trimmed Mean ( 12 / 28 )108.7266666666672.9021518089876937.4641555034958
Trimmed Mean ( 13 / 28 )108.552.8888402104729737.575633157719
Trimmed Mean ( 14 / 28 )108.352.8727854260101137.7160086580092
Trimmed Mean ( 15 / 28 )108.1351851851852.850582783240137.9344132087523
Trimmed Mean ( 16 / 28 )107.8961538461542.829709280456938.1297664008552
Trimmed Mean ( 17 / 28 )107.6362.8039531277924638.3872322732945
Trimmed Mean ( 18 / 28 )107.3708333333332.7725317409775738.7266380926897
Trimmed Mean ( 19 / 28 )107.1760869565222.7553201674129938.8978704631451
Trimmed Mean ( 20 / 28 )107.0295454545452.7481275184704138.946353375231
Trimmed Mean ( 21 / 28 )106.8452380952382.7386937940931539.0132107231861
Trimmed Mean ( 22 / 28 )106.72.7456725858554138.8611521088403
Trimmed Mean ( 23 / 28 )106.5263157894742.7487943411910538.7538326142347
Trimmed Mean ( 24 / 28 )106.3527777777782.7543197993913538.6130825481048
Trimmed Mean ( 25 / 28 )106.1617647058822.7533483576107838.5573312626537
Trimmed Mean ( 26 / 28 )105.9718752.749725918801438.5390683032849
Trimmed Mean ( 27 / 28 )105.7533333333332.7381373538561538.6223624554114
Trimmed Mean ( 28 / 28 )105.5357142857142.7205528455327538.792010402962
Median100.9
Midrange109.45
Midmean - Weighted Average at Xnp106.337209302326
Midmean - Weighted Average at X(n+1)p106.845238095238
Midmean - Empirical Distribution Function106.337209302326
Midmean - Empirical Distribution Function - Averaging106.845238095238
Midmean - Empirical Distribution Function - Interpolation106.845238095238
Midmean - Closest Observation106.337209302326
Midmean - True Basic - Statistics Graphics Toolkit106.845238095238
Midmean - MS Excel (old versions)107.029545454545
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')