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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 01 Mar 2016 11:24:52 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/01/t14568317481gugv8wz3vn8zb7.htm/, Retrieved Tue, 07 May 2024 22:41:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293118, Retrieved Tue, 07 May 2024 22:41:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2016-03-01 11:24:52] [c1931050b1d666e3090788e81f04199e] [Current]
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Dataseries X:
4736
4840
4413
4571
4106
4801
3956
3829
4453
4027
4121
4798
3233
3554
3952
3951
3685
4312
3867
4140
4114
3818
3377
3453
3502
4017
5410
5184
5529
6434
4962
2980
2937
3023
2731
3163
3146
3173
3724
3224
4114
3450
2957
3882
4284
4181
3760
4457
4167
3962
5247
5157
3697
3514
3786
3297
3571
3871
3492
3051
3735
3645
4852
4232
3804
4464
4259
3373
4134
4488
3333
4772
4929
5555
7183
9266
4003
3051
3507
3273
3942
3216
3232
3593




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=293118&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=293118&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293118&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 Mean4083.14285714286106.40727183508338.3727802313283
Geometric Mean3990.78783028765
Harmonic Mean3913.18532407216
Quadratic Mean4196.64433974166
Winsorized Mean ( 1 / 28 )4060.7976190476293.63801558775943.3669764737995
Winsorized Mean ( 2 / 28 )4043.4404761904887.011081968390446.4704079609008
Winsorized Mean ( 3 / 28 )4012.8690476190577.862081053775151.538168429477
Winsorized Mean ( 4 / 28 )4013.6785714285777.246197894343351.9595615167811
Winsorized Mean ( 5 / 28 )4008.261904761975.358569357641253.189198506931
Winsorized Mean ( 6 / 28 )3996.6190476190572.848383298170554.8621515903897
Winsorized Mean ( 7 / 28 )3999.2857142857170.578166306701856.6646304879411
Winsorized Mean ( 8 / 28 )3998.3333333333369.826484259175957.2609859389836
Winsorized Mean ( 9 / 28 )3978.511904761965.691178199976760.5638689056625
Winsorized Mean ( 10 / 28 )3979.7023809523864.242246239389561.9483690860153
Winsorized Mean ( 11 / 28 )3970.6666666666762.334633401692463.6992062033826
Winsorized Mean ( 12 / 28 )3970.0952380952461.878850550511764.1591626666441
Winsorized Mean ( 13 / 28 )3964.2142857142960.845237098995565.152417423643
Winsorized Mean ( 14 / 28 )3970.3809523809559.811117172756666.3819895039417
Winsorized Mean ( 15 / 28 )3970.0238095238158.441871754097267.9311543310638
Winsorized Mean ( 16 / 28 )3970.0238095238156.370941192740370.4267788602239
Winsorized Mean ( 17 / 28 )3944.7261904761949.996549941758478.899967999221
Winsorized Mean ( 18 / 28 )3927.7976190476247.263281515589883.1046320334748
Winsorized Mean ( 19 / 28 )3938.8809523809544.226696573836189.0611611881304
Winsorized Mean ( 20 / 28 )3937.9285714285743.893650440256189.7152214940179
Winsorized Mean ( 21 / 28 )3946.6785714285742.472613297237792.922904079586
Winsorized Mean ( 22 / 28 )3938.8214285714340.645219839327196.9073717436347
Winsorized Mean ( 23 / 28 )3912.5357142857136.7021881599479106.602246635403
Winsorized Mean ( 24 / 28 )3906.5357142857135.3968260909322110.364011288754
Winsorized Mean ( 25 / 28 )391132.8693627654363118.986182601404
Winsorized Mean ( 26 / 28 )3907.9047619047631.1244546136847125.557373146277
Winsorized Mean ( 27 / 28 )3898.5833333333328.181630636223138.337748573084
Winsorized Mean ( 28 / 28 )3911.2525.3875349166703154.061826515963
Trimmed Mean ( 1 / 28 )4036.4268292682986.825013481835946.4892162684516
Trimmed Mean ( 2 / 28 )4010.837578.463509304172451.1172331644198
Trimmed Mean ( 3 / 28 )3993.2820512820572.882348999486554.7907978557358
Trimmed Mean ( 4 / 28 )3986.0657894736870.627799644621656.4376323420863
Trimmed Mean ( 5 / 28 )3978.2297297297368.192598481853358.3381454629329
Trimmed Mean ( 6 / 28 )3971.2222222222265.910156703940260.2520525032345
Trimmed Mean ( 7 / 28 )3966.1428571428663.914838156156362.0535539408361
Trimmed Mean ( 8 / 28 )3960.2941176470662.105520880217563.7671830381272
Trimmed Mean ( 9 / 28 )3954.2424242424260.113971244163265.7790916554421
Trimmed Mean ( 10 / 28 )3950.70312558.664052632541267.3445312369799
Trimmed Mean ( 11 / 28 )3946.7741935483957.209479987141868.9881151591564
Trimmed Mean ( 12 / 28 )3943.7333333333355.834222271361870.6329052846167
Trimmed Mean ( 13 / 28 )3940.5517241379354.237731347860972.6533287106845
Trimmed Mean ( 14 / 28 )3937.8214285714352.483597358138575.0295640312239
Trimmed Mean ( 15 / 28 )3934.203703703750.508749127111577.8915291250392
Trimmed Mean ( 16 / 28 )3930.3461538461548.322695177756581.3354085360565
Trimmed Mean ( 17 / 28 )3926.1846.007414575461385.337983806073
Trimmed Mean ( 18 / 28 )3924.2708333333344.482323164361688.2209056130725
Trimmed Mean ( 19 / 28 )3923.9130434782643.10751446073691.0261956080142
Trimmed Mean ( 20 / 28 )3922.4090909090941.954159497421993.4927344009865
Trimmed Mean ( 21 / 28 )3920.8571428571440.496147297120496.820497863409
Trimmed Mean ( 22 / 28 )3918.27538.8670644881123100.812218560999
Trimmed Mean ( 23 / 28 )3916.2105263157937.1304677165759105.471618515796
Trimmed Mean ( 24 / 28 )3916.5833333333335.7937738445075109.420799001174
Trimmed Mean ( 25 / 28 )3917.6176470588234.2633196111669114.338531453386
Trimmed Mean ( 26 / 28 )3918.312532.8183059379532119.394112158258
Trimmed Mean ( 27 / 28 )3919.4333333333331.2454385943003125.440176539826
Trimmed Mean ( 28 / 28 )3921.7529.8637835644292131.321270512796
Median3946.5
Midrange5998.5
Midmean - Weighted Average at Xnp3909.97674418605
Midmean - Weighted Average at X(n+1)p3920.85714285714
Midmean - Empirical Distribution Function3909.97674418605
Midmean - Empirical Distribution Function - Averaging3920.85714285714
Midmean - Empirical Distribution Function - Interpolation3920.85714285714
Midmean - Closest Observation3909.97674418605
Midmean - True Basic - Statistics Graphics Toolkit3920.85714285714
Midmean - MS Excel (old versions)3922.40909090909
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4083.14285714286 & 106.407271835083 & 38.3727802313283 \tabularnewline
Geometric Mean & 3990.78783028765 &  &  \tabularnewline
Harmonic Mean & 3913.18532407216 &  &  \tabularnewline
Quadratic Mean & 4196.64433974166 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 4060.79761904762 & 93.638015587759 & 43.3669764737995 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 4043.44047619048 & 87.0110819683904 & 46.4704079609008 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 4012.86904761905 & 77.8620810537751 & 51.538168429477 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 4013.67857142857 & 77.2461978943433 & 51.9595615167811 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 4008.2619047619 & 75.3585693576412 & 53.189198506931 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 3996.61904761905 & 72.8483832981705 & 54.8621515903897 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 3999.28571428571 & 70.5781663067018 & 56.6646304879411 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 3998.33333333333 & 69.8264842591759 & 57.2609859389836 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 3978.5119047619 & 65.6911781999767 & 60.5638689056625 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 3979.70238095238 & 64.2422462393895 & 61.9483690860153 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 3970.66666666667 & 62.3346334016924 & 63.6992062033826 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 3970.09523809524 & 61.8788505505117 & 64.1591626666441 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 3964.21428571429 & 60.8452370989955 & 65.152417423643 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 3970.38095238095 & 59.8111171727566 & 66.3819895039417 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 3970.02380952381 & 58.4418717540972 & 67.9311543310638 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 3970.02380952381 & 56.3709411927403 & 70.4267788602239 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 3944.72619047619 & 49.9965499417584 & 78.899967999221 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 3927.79761904762 & 47.2632815155898 & 83.1046320334748 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 3938.88095238095 & 44.2266965738361 & 89.0611611881304 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 3937.92857142857 & 43.8936504402561 & 89.7152214940179 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 3946.67857142857 & 42.4726132972377 & 92.922904079586 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 3938.82142857143 & 40.6452198393271 & 96.9073717436347 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 3912.53571428571 & 36.7021881599479 & 106.602246635403 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 3906.53571428571 & 35.3968260909322 & 110.364011288754 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 3911 & 32.8693627654363 & 118.986182601404 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 3907.90476190476 & 31.1244546136847 & 125.557373146277 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 3898.58333333333 & 28.181630636223 & 138.337748573084 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 3911.25 & 25.3875349166703 & 154.061826515963 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 4036.42682926829 & 86.8250134818359 & 46.4892162684516 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 4010.8375 & 78.4635093041724 & 51.1172331644198 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 3993.28205128205 & 72.8823489994865 & 54.7907978557358 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 3986.06578947368 & 70.6277996446216 & 56.4376323420863 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 3978.22972972973 & 68.1925984818533 & 58.3381454629329 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 3971.22222222222 & 65.9101567039402 & 60.2520525032345 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 3966.14285714286 & 63.9148381561563 & 62.0535539408361 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 3960.29411764706 & 62.1055208802175 & 63.7671830381272 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 3954.24242424242 & 60.1139712441632 & 65.7790916554421 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 3950.703125 & 58.6640526325412 & 67.3445312369799 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 3946.77419354839 & 57.2094799871418 & 68.9881151591564 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 3943.73333333333 & 55.8342222713618 & 70.6329052846167 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 3940.55172413793 & 54.2377313478609 & 72.6533287106845 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 3937.82142857143 & 52.4835973581385 & 75.0295640312239 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 3934.2037037037 & 50.5087491271115 & 77.8915291250392 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 3930.34615384615 & 48.3226951777565 & 81.3354085360565 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 3926.18 & 46.0074145754613 & 85.337983806073 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 3924.27083333333 & 44.4823231643616 & 88.2209056130725 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 3923.91304347826 & 43.107514460736 & 91.0261956080142 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 3922.40909090909 & 41.9541594974219 & 93.4927344009865 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 3920.85714285714 & 40.4961472971204 & 96.820497863409 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 3918.275 & 38.8670644881123 & 100.812218560999 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 3916.21052631579 & 37.1304677165759 & 105.471618515796 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 3916.58333333333 & 35.7937738445075 & 109.420799001174 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 3917.61764705882 & 34.2633196111669 & 114.338531453386 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 3918.3125 & 32.8183059379532 & 119.394112158258 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 3919.43333333333 & 31.2454385943003 & 125.440176539826 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 3921.75 & 29.8637835644292 & 131.321270512796 \tabularnewline
Median & 3946.5 &  &  \tabularnewline
Midrange & 5998.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 3909.97674418605 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 3920.85714285714 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 3909.97674418605 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 3920.85714285714 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 3920.85714285714 &  &  \tabularnewline
Midmean - Closest Observation & 3909.97674418605 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 3920.85714285714 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 3922.40909090909 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293118&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]4083.14285714286[/C][C]106.407271835083[/C][C]38.3727802313283[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]3990.78783028765[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3913.18532407216[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4196.64433974166[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]4060.79761904762[/C][C]93.638015587759[/C][C]43.3669764737995[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]4043.44047619048[/C][C]87.0110819683904[/C][C]46.4704079609008[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]4012.86904761905[/C][C]77.8620810537751[/C][C]51.538168429477[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]4013.67857142857[/C][C]77.2461978943433[/C][C]51.9595615167811[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]4008.2619047619[/C][C]75.3585693576412[/C][C]53.189198506931[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]3996.61904761905[/C][C]72.8483832981705[/C][C]54.8621515903897[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]3999.28571428571[/C][C]70.5781663067018[/C][C]56.6646304879411[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]3998.33333333333[/C][C]69.8264842591759[/C][C]57.2609859389836[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]3978.5119047619[/C][C]65.6911781999767[/C][C]60.5638689056625[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]3979.70238095238[/C][C]64.2422462393895[/C][C]61.9483690860153[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]3970.66666666667[/C][C]62.3346334016924[/C][C]63.6992062033826[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]3970.09523809524[/C][C]61.8788505505117[/C][C]64.1591626666441[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]3964.21428571429[/C][C]60.8452370989955[/C][C]65.152417423643[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]3970.38095238095[/C][C]59.8111171727566[/C][C]66.3819895039417[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]3970.02380952381[/C][C]58.4418717540972[/C][C]67.9311543310638[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]3970.02380952381[/C][C]56.3709411927403[/C][C]70.4267788602239[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]3944.72619047619[/C][C]49.9965499417584[/C][C]78.899967999221[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]3927.79761904762[/C][C]47.2632815155898[/C][C]83.1046320334748[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]3938.88095238095[/C][C]44.2266965738361[/C][C]89.0611611881304[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]3937.92857142857[/C][C]43.8936504402561[/C][C]89.7152214940179[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]3946.67857142857[/C][C]42.4726132972377[/C][C]92.922904079586[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]3938.82142857143[/C][C]40.6452198393271[/C][C]96.9073717436347[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]3912.53571428571[/C][C]36.7021881599479[/C][C]106.602246635403[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]3906.53571428571[/C][C]35.3968260909322[/C][C]110.364011288754[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]3911[/C][C]32.8693627654363[/C][C]118.986182601404[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]3907.90476190476[/C][C]31.1244546136847[/C][C]125.557373146277[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]3898.58333333333[/C][C]28.181630636223[/C][C]138.337748573084[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]3911.25[/C][C]25.3875349166703[/C][C]154.061826515963[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]4036.42682926829[/C][C]86.8250134818359[/C][C]46.4892162684516[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]4010.8375[/C][C]78.4635093041724[/C][C]51.1172331644198[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]3993.28205128205[/C][C]72.8823489994865[/C][C]54.7907978557358[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]3986.06578947368[/C][C]70.6277996446216[/C][C]56.4376323420863[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]3978.22972972973[/C][C]68.1925984818533[/C][C]58.3381454629329[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]3971.22222222222[/C][C]65.9101567039402[/C][C]60.2520525032345[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]3966.14285714286[/C][C]63.9148381561563[/C][C]62.0535539408361[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]3960.29411764706[/C][C]62.1055208802175[/C][C]63.7671830381272[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]3954.24242424242[/C][C]60.1139712441632[/C][C]65.7790916554421[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]3950.703125[/C][C]58.6640526325412[/C][C]67.3445312369799[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]3946.77419354839[/C][C]57.2094799871418[/C][C]68.9881151591564[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]3943.73333333333[/C][C]55.8342222713618[/C][C]70.6329052846167[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]3940.55172413793[/C][C]54.2377313478609[/C][C]72.6533287106845[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]3937.82142857143[/C][C]52.4835973581385[/C][C]75.0295640312239[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]3934.2037037037[/C][C]50.5087491271115[/C][C]77.8915291250392[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]3930.34615384615[/C][C]48.3226951777565[/C][C]81.3354085360565[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]3926.18[/C][C]46.0074145754613[/C][C]85.337983806073[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]3924.27083333333[/C][C]44.4823231643616[/C][C]88.2209056130725[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]3923.91304347826[/C][C]43.107514460736[/C][C]91.0261956080142[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]3922.40909090909[/C][C]41.9541594974219[/C][C]93.4927344009865[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]3920.85714285714[/C][C]40.4961472971204[/C][C]96.820497863409[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]3918.275[/C][C]38.8670644881123[/C][C]100.812218560999[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]3916.21052631579[/C][C]37.1304677165759[/C][C]105.471618515796[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]3916.58333333333[/C][C]35.7937738445075[/C][C]109.420799001174[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]3917.61764705882[/C][C]34.2633196111669[/C][C]114.338531453386[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]3918.3125[/C][C]32.8183059379532[/C][C]119.394112158258[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]3919.43333333333[/C][C]31.2454385943003[/C][C]125.440176539826[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]3921.75[/C][C]29.8637835644292[/C][C]131.321270512796[/C][/ROW]
[ROW][C]Median[/C][C]3946.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]5998.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]3909.97674418605[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]3920.85714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]3909.97674418605[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]3920.85714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]3920.85714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]3909.97674418605[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]3920.85714285714[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]3922.40909090909[/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=293118&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293118&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 Mean4083.14285714286106.40727183508338.3727802313283
Geometric Mean3990.78783028765
Harmonic Mean3913.18532407216
Quadratic Mean4196.64433974166
Winsorized Mean ( 1 / 28 )4060.7976190476293.63801558775943.3669764737995
Winsorized Mean ( 2 / 28 )4043.4404761904887.011081968390446.4704079609008
Winsorized Mean ( 3 / 28 )4012.8690476190577.862081053775151.538168429477
Winsorized Mean ( 4 / 28 )4013.6785714285777.246197894343351.9595615167811
Winsorized Mean ( 5 / 28 )4008.261904761975.358569357641253.189198506931
Winsorized Mean ( 6 / 28 )3996.6190476190572.848383298170554.8621515903897
Winsorized Mean ( 7 / 28 )3999.2857142857170.578166306701856.6646304879411
Winsorized Mean ( 8 / 28 )3998.3333333333369.826484259175957.2609859389836
Winsorized Mean ( 9 / 28 )3978.511904761965.691178199976760.5638689056625
Winsorized Mean ( 10 / 28 )3979.7023809523864.242246239389561.9483690860153
Winsorized Mean ( 11 / 28 )3970.6666666666762.334633401692463.6992062033826
Winsorized Mean ( 12 / 28 )3970.0952380952461.878850550511764.1591626666441
Winsorized Mean ( 13 / 28 )3964.2142857142960.845237098995565.152417423643
Winsorized Mean ( 14 / 28 )3970.3809523809559.811117172756666.3819895039417
Winsorized Mean ( 15 / 28 )3970.0238095238158.441871754097267.9311543310638
Winsorized Mean ( 16 / 28 )3970.0238095238156.370941192740370.4267788602239
Winsorized Mean ( 17 / 28 )3944.7261904761949.996549941758478.899967999221
Winsorized Mean ( 18 / 28 )3927.7976190476247.263281515589883.1046320334748
Winsorized Mean ( 19 / 28 )3938.8809523809544.226696573836189.0611611881304
Winsorized Mean ( 20 / 28 )3937.9285714285743.893650440256189.7152214940179
Winsorized Mean ( 21 / 28 )3946.6785714285742.472613297237792.922904079586
Winsorized Mean ( 22 / 28 )3938.8214285714340.645219839327196.9073717436347
Winsorized Mean ( 23 / 28 )3912.5357142857136.7021881599479106.602246635403
Winsorized Mean ( 24 / 28 )3906.5357142857135.3968260909322110.364011288754
Winsorized Mean ( 25 / 28 )391132.8693627654363118.986182601404
Winsorized Mean ( 26 / 28 )3907.9047619047631.1244546136847125.557373146277
Winsorized Mean ( 27 / 28 )3898.5833333333328.181630636223138.337748573084
Winsorized Mean ( 28 / 28 )3911.2525.3875349166703154.061826515963
Trimmed Mean ( 1 / 28 )4036.4268292682986.825013481835946.4892162684516
Trimmed Mean ( 2 / 28 )4010.837578.463509304172451.1172331644198
Trimmed Mean ( 3 / 28 )3993.2820512820572.882348999486554.7907978557358
Trimmed Mean ( 4 / 28 )3986.0657894736870.627799644621656.4376323420863
Trimmed Mean ( 5 / 28 )3978.2297297297368.192598481853358.3381454629329
Trimmed Mean ( 6 / 28 )3971.2222222222265.910156703940260.2520525032345
Trimmed Mean ( 7 / 28 )3966.1428571428663.914838156156362.0535539408361
Trimmed Mean ( 8 / 28 )3960.2941176470662.105520880217563.7671830381272
Trimmed Mean ( 9 / 28 )3954.2424242424260.113971244163265.7790916554421
Trimmed Mean ( 10 / 28 )3950.70312558.664052632541267.3445312369799
Trimmed Mean ( 11 / 28 )3946.7741935483957.209479987141868.9881151591564
Trimmed Mean ( 12 / 28 )3943.7333333333355.834222271361870.6329052846167
Trimmed Mean ( 13 / 28 )3940.5517241379354.237731347860972.6533287106845
Trimmed Mean ( 14 / 28 )3937.8214285714352.483597358138575.0295640312239
Trimmed Mean ( 15 / 28 )3934.203703703750.508749127111577.8915291250392
Trimmed Mean ( 16 / 28 )3930.3461538461548.322695177756581.3354085360565
Trimmed Mean ( 17 / 28 )3926.1846.007414575461385.337983806073
Trimmed Mean ( 18 / 28 )3924.2708333333344.482323164361688.2209056130725
Trimmed Mean ( 19 / 28 )3923.9130434782643.10751446073691.0261956080142
Trimmed Mean ( 20 / 28 )3922.4090909090941.954159497421993.4927344009865
Trimmed Mean ( 21 / 28 )3920.8571428571440.496147297120496.820497863409
Trimmed Mean ( 22 / 28 )3918.27538.8670644881123100.812218560999
Trimmed Mean ( 23 / 28 )3916.2105263157937.1304677165759105.471618515796
Trimmed Mean ( 24 / 28 )3916.5833333333335.7937738445075109.420799001174
Trimmed Mean ( 25 / 28 )3917.6176470588234.2633196111669114.338531453386
Trimmed Mean ( 26 / 28 )3918.312532.8183059379532119.394112158258
Trimmed Mean ( 27 / 28 )3919.4333333333331.2454385943003125.440176539826
Trimmed Mean ( 28 / 28 )3921.7529.8637835644292131.321270512796
Median3946.5
Midrange5998.5
Midmean - Weighted Average at Xnp3909.97674418605
Midmean - Weighted Average at X(n+1)p3920.85714285714
Midmean - Empirical Distribution Function3909.97674418605
Midmean - Empirical Distribution Function - Averaging3920.85714285714
Midmean - Empirical Distribution Function - Interpolation3920.85714285714
Midmean - Closest Observation3909.97674418605
Midmean - True Basic - Statistics Graphics Toolkit3920.85714285714
Midmean - MS Excel (old versions)3922.40909090909
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')