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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationTue, 16 Mar 2010 15:52:42 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Mar/16/t1268776427bq7agtfe3kbqyen.htm/, Retrieved Fri, 21 Jan 2022 11:31:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74488, Retrieved Fri, 21 Jan 2022 11:31:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W52
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Centrummaten witt...] [2010-03-16 21:52:42] [03859715711bd3369851d387eaa83ba4] [Current]
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Dataseries X:
1954
2302
3054
2414
2226
2725
2589
3470
2400
3180
4009
3924
2072
2434
2956
2828
2687
2629
3150
4119
3030
3055
3821
4001
2529
2472
3134
2789
2758
2993
3282
3437
2804
3076
3782
3889
2271
2452
3084
2522
2769
3438
2839
3746
2632
2851
3871
3618
2389
2344
2678
2492
2858
2246
2800
3869
3007
3023
3907
4209
2353
2570
2903
2910
3782
2759
2931
3641
2794
3070
3576
4106
2452
2206
2488
2416
2534
2521
3093
3903
2907
3025
3812
4209




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74488&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74488&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74488&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean3010.1190476190563.666121637769647.2797615150051
Geometric Mean2956.14350124694
Harmonic Mean2904.42622431556
Quadratic Mean3065.49291460995
Winsorized Mean ( 1 / 28 )3011.5238095238163.400308389617447.5001444948332
Winsorized Mean ( 2 / 28 )3012.5714285714362.393901420840548.2831071622199
Winsorized Mean ( 3 / 28 )3012.8214285714362.185064611008948.449277128162
Winsorized Mean ( 4 / 28 )3009.1547619047661.095972615045949.2529152594865
Winsorized Mean ( 5 / 28 )3010.1666666666760.781263327577449.5245821141218
Winsorized Mean ( 6 / 28 )3006.8809523809559.408811518558450.6133833605079
Winsorized Mean ( 7 / 28 )3008.9642857142958.657145946879851.2974887738183
Winsorized Mean ( 8 / 28 )3009.4404761904858.470433145851451.4694404381029
Winsorized Mean ( 9 / 28 )3011.7976190476257.683113552804252.2128129628538
Winsorized Mean ( 10 / 28 )3010.9642857142957.12289206764952.710291386306
Winsorized Mean ( 11 / 28 )3012.5357142857156.840940834169352.9993992019703
Winsorized Mean ( 12 / 28 )3005.9642857142955.576149467925354.0873074959812
Winsorized Mean ( 13 / 28 )3007.3571428571454.977118389659454.7019784038517
Winsorized Mean ( 14 / 28 )3005.3571428571453.726164558198155.9384271624607
Winsorized Mean ( 15 / 28 )3005.3571428571453.726164558198155.9384271624607
Winsorized Mean ( 16 / 28 )3002.3095238095252.068787461473657.6604463092399
Winsorized Mean ( 17 / 28 )2984.2976190476248.089220066080762.0575175672804
Winsorized Mean ( 18 / 28 )2980.2261904761947.17562295084763.1730119087422
Winsorized Mean ( 19 / 28 )2977.2857142857144.825980127440766.4187532725724
Winsorized Mean ( 20 / 28 )2952.2857142857140.833184884207772.3011374855435
Winsorized Mean ( 21 / 28 )2946.0357142857139.397529877154474.7771680984
Winsorized Mean ( 22 / 28 )2947.0833333333339.191452375242975.1970941295096
Winsorized Mean ( 23 / 28 )2914.531.742322132180091.8174791328612
Winsorized Mean ( 24 / 28 )2890.7857142857127.10572504658106.648529390674
Winsorized Mean ( 25 / 28 )2893.7619047619024.3881914834753118.654222750491
Winsorized Mean ( 26 / 28 )2889.7380952381023.6447648552999122.214710652551
Winsorized Mean ( 27 / 28 )2891.3452380952420.1085514704493143.786848214514
Winsorized Mean ( 28 / 28 )2891.3452380952419.3650314910497149.307541246787
Trimmed Mean ( 1 / 28 )3008.3780487804962.212517730065648.3564748469683
Trimmed Mean ( 2 / 28 )3005.07560.832840000022649.398893755394
Trimmed Mean ( 3 / 28 )3001.0384615384659.841322096627350.1499358034338
Trimmed Mean ( 4 / 28 )2996.6973684210558.765564626510450.9941049229565
Trimmed Mean ( 5 / 28 )2993.1621621621657.8766322782851.7162461659926
Trimmed Mean ( 6 / 28 )2989.1944444444456.910403868035352.5245691697398
Trimmed Mean ( 7 / 28 )2985.6571428571456.11608378628253.2050161274264
Trimmed Mean ( 8 / 28 )2981.5441176470655.330428267674353.8861565145153
Trimmed Mean ( 9 / 28 )2977.1060606060654.4147635629154.7113662850738
Trimmed Mean ( 10 / 28 )2972.04687553.460341839971255.5934880457098
Trimmed Mean ( 11 / 28 )2966.7741935483952.404910835934956.6125224950106
Trimmed Mean ( 12 / 28 )2960.9551.158347425414757.878140108354
Trimmed Mean ( 13 / 28 )2955.5172413793149.883216558681959.2487302398089
Trimmed Mean ( 14 / 28 )2949.5357142857148.412761038329160.9247572546114
Trimmed Mean ( 15 / 28 )2943.3333333333346.829134677539262.8526098891393
Trimmed Mean ( 16 / 28 )2936.6538461538544.827403920413265.5102368044242
Trimmed Mean ( 17 / 28 )2929.7642.646449334221668.6988024967654
Trimmed Mean ( 18 / 28 )2924.1458333333340.788635141701171.690210353319
Trimmed Mean ( 19 / 28 )2918.4565217391338.596534430817975.6144706973704
Trimmed Mean ( 20 / 28 )2912.5454545454536.29069057711580.2559942571639
Trimmed Mean ( 21 / 28 )2908.5714285714334.316338433139684.7576274560399
Trimmed Mean ( 22 / 28 )2904.82532.054798582731590.6205974903514
Trimmed Mean ( 23 / 28 )2900.5789473684228.9885107858319100.059605296664
Trimmed Mean ( 24 / 28 )2899.1666666666727.1192691993122106.904306504697
Trimmed Mean ( 25 / 28 )2900.0294117647125.8815512961254112.050061396391
Trimmed Mean ( 26 / 28 )2900.687524.9115547382295116.439440672427
Trimmed Mean ( 27 / 28 )2901.8666666666723.7068171646180122.406422022677
Trimmed Mean ( 28 / 28 )2903.0357142857123.0672172921972125.851145264397
Median2905
Midrange3081.5
Midmean - Weighted Average at Xnp2899.58139534884
Midmean - Weighted Average at X(n+1)p2908.57142857143
Midmean - Empirical Distribution Function2899.58139534884
Midmean - Empirical Distribution Function - Averaging2908.57142857143
Midmean - Empirical Distribution Function - Interpolation2908.57142857143
Midmean - Closest Observation2899.58139534884
Midmean - True Basic - Statistics Graphics Toolkit2908.57142857143
Midmean - MS Excel (old versions)2912.54545454545
Number of observations84

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 3010.11904761905 & 63.6661216377696 & 47.2797615150051 \tabularnewline
Geometric Mean & 2956.14350124694 &  &  \tabularnewline
Harmonic Mean & 2904.42622431556 &  &  \tabularnewline
Quadratic Mean & 3065.49291460995 &  &  \tabularnewline
Winsorized Mean ( 1 / 28 ) & 3011.52380952381 & 63.4003083896174 & 47.5001444948332 \tabularnewline
Winsorized Mean ( 2 / 28 ) & 3012.57142857143 & 62.3939014208405 & 48.2831071622199 \tabularnewline
Winsorized Mean ( 3 / 28 ) & 3012.82142857143 & 62.1850646110089 & 48.449277128162 \tabularnewline
Winsorized Mean ( 4 / 28 ) & 3009.15476190476 & 61.0959726150459 & 49.2529152594865 \tabularnewline
Winsorized Mean ( 5 / 28 ) & 3010.16666666667 & 60.7812633275774 & 49.5245821141218 \tabularnewline
Winsorized Mean ( 6 / 28 ) & 3006.88095238095 & 59.4088115185584 & 50.6133833605079 \tabularnewline
Winsorized Mean ( 7 / 28 ) & 3008.96428571429 & 58.6571459468798 & 51.2974887738183 \tabularnewline
Winsorized Mean ( 8 / 28 ) & 3009.44047619048 & 58.4704331458514 & 51.4694404381029 \tabularnewline
Winsorized Mean ( 9 / 28 ) & 3011.79761904762 & 57.6831135528042 & 52.2128129628538 \tabularnewline
Winsorized Mean ( 10 / 28 ) & 3010.96428571429 & 57.122892067649 & 52.710291386306 \tabularnewline
Winsorized Mean ( 11 / 28 ) & 3012.53571428571 & 56.8409408341693 & 52.9993992019703 \tabularnewline
Winsorized Mean ( 12 / 28 ) & 3005.96428571429 & 55.5761494679253 & 54.0873074959812 \tabularnewline
Winsorized Mean ( 13 / 28 ) & 3007.35714285714 & 54.9771183896594 & 54.7019784038517 \tabularnewline
Winsorized Mean ( 14 / 28 ) & 3005.35714285714 & 53.7261645581981 & 55.9384271624607 \tabularnewline
Winsorized Mean ( 15 / 28 ) & 3005.35714285714 & 53.7261645581981 & 55.9384271624607 \tabularnewline
Winsorized Mean ( 16 / 28 ) & 3002.30952380952 & 52.0687874614736 & 57.6604463092399 \tabularnewline
Winsorized Mean ( 17 / 28 ) & 2984.29761904762 & 48.0892200660807 & 62.0575175672804 \tabularnewline
Winsorized Mean ( 18 / 28 ) & 2980.22619047619 & 47.175622950847 & 63.1730119087422 \tabularnewline
Winsorized Mean ( 19 / 28 ) & 2977.28571428571 & 44.8259801274407 & 66.4187532725724 \tabularnewline
Winsorized Mean ( 20 / 28 ) & 2952.28571428571 & 40.8331848842077 & 72.3011374855435 \tabularnewline
Winsorized Mean ( 21 / 28 ) & 2946.03571428571 & 39.3975298771544 & 74.7771680984 \tabularnewline
Winsorized Mean ( 22 / 28 ) & 2947.08333333333 & 39.1914523752429 & 75.1970941295096 \tabularnewline
Winsorized Mean ( 23 / 28 ) & 2914.5 & 31.7423221321800 & 91.8174791328612 \tabularnewline
Winsorized Mean ( 24 / 28 ) & 2890.78571428571 & 27.10572504658 & 106.648529390674 \tabularnewline
Winsorized Mean ( 25 / 28 ) & 2893.76190476190 & 24.3881914834753 & 118.654222750491 \tabularnewline
Winsorized Mean ( 26 / 28 ) & 2889.73809523810 & 23.6447648552999 & 122.214710652551 \tabularnewline
Winsorized Mean ( 27 / 28 ) & 2891.34523809524 & 20.1085514704493 & 143.786848214514 \tabularnewline
Winsorized Mean ( 28 / 28 ) & 2891.34523809524 & 19.3650314910497 & 149.307541246787 \tabularnewline
Trimmed Mean ( 1 / 28 ) & 3008.37804878049 & 62.2125177300656 & 48.3564748469683 \tabularnewline
Trimmed Mean ( 2 / 28 ) & 3005.075 & 60.8328400000226 & 49.398893755394 \tabularnewline
Trimmed Mean ( 3 / 28 ) & 3001.03846153846 & 59.8413220966273 & 50.1499358034338 \tabularnewline
Trimmed Mean ( 4 / 28 ) & 2996.69736842105 & 58.7655646265104 & 50.9941049229565 \tabularnewline
Trimmed Mean ( 5 / 28 ) & 2993.16216216216 & 57.87663227828 & 51.7162461659926 \tabularnewline
Trimmed Mean ( 6 / 28 ) & 2989.19444444444 & 56.9104038680353 & 52.5245691697398 \tabularnewline
Trimmed Mean ( 7 / 28 ) & 2985.65714285714 & 56.116083786282 & 53.2050161274264 \tabularnewline
Trimmed Mean ( 8 / 28 ) & 2981.54411764706 & 55.3304282676743 & 53.8861565145153 \tabularnewline
Trimmed Mean ( 9 / 28 ) & 2977.10606060606 & 54.41476356291 & 54.7113662850738 \tabularnewline
Trimmed Mean ( 10 / 28 ) & 2972.046875 & 53.4603418399712 & 55.5934880457098 \tabularnewline
Trimmed Mean ( 11 / 28 ) & 2966.77419354839 & 52.4049108359349 & 56.6125224950106 \tabularnewline
Trimmed Mean ( 12 / 28 ) & 2960.95 & 51.1583474254147 & 57.878140108354 \tabularnewline
Trimmed Mean ( 13 / 28 ) & 2955.51724137931 & 49.8832165586819 & 59.2487302398089 \tabularnewline
Trimmed Mean ( 14 / 28 ) & 2949.53571428571 & 48.4127610383291 & 60.9247572546114 \tabularnewline
Trimmed Mean ( 15 / 28 ) & 2943.33333333333 & 46.8291346775392 & 62.8526098891393 \tabularnewline
Trimmed Mean ( 16 / 28 ) & 2936.65384615385 & 44.8274039204132 & 65.5102368044242 \tabularnewline
Trimmed Mean ( 17 / 28 ) & 2929.76 & 42.6464493342216 & 68.6988024967654 \tabularnewline
Trimmed Mean ( 18 / 28 ) & 2924.14583333333 & 40.7886351417011 & 71.690210353319 \tabularnewline
Trimmed Mean ( 19 / 28 ) & 2918.45652173913 & 38.5965344308179 & 75.6144706973704 \tabularnewline
Trimmed Mean ( 20 / 28 ) & 2912.54545454545 & 36.290690577115 & 80.2559942571639 \tabularnewline
Trimmed Mean ( 21 / 28 ) & 2908.57142857143 & 34.3163384331396 & 84.7576274560399 \tabularnewline
Trimmed Mean ( 22 / 28 ) & 2904.825 & 32.0547985827315 & 90.6205974903514 \tabularnewline
Trimmed Mean ( 23 / 28 ) & 2900.57894736842 & 28.9885107858319 & 100.059605296664 \tabularnewline
Trimmed Mean ( 24 / 28 ) & 2899.16666666667 & 27.1192691993122 & 106.904306504697 \tabularnewline
Trimmed Mean ( 25 / 28 ) & 2900.02941176471 & 25.8815512961254 & 112.050061396391 \tabularnewline
Trimmed Mean ( 26 / 28 ) & 2900.6875 & 24.9115547382295 & 116.439440672427 \tabularnewline
Trimmed Mean ( 27 / 28 ) & 2901.86666666667 & 23.7068171646180 & 122.406422022677 \tabularnewline
Trimmed Mean ( 28 / 28 ) & 2903.03571428571 & 23.0672172921972 & 125.851145264397 \tabularnewline
Median & 2905 &  &  \tabularnewline
Midrange & 3081.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 2899.58139534884 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 2908.57142857143 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 2899.58139534884 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 2908.57142857143 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 2908.57142857143 &  &  \tabularnewline
Midmean - Closest Observation & 2899.58139534884 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 2908.57142857143 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 2912.54545454545 &  &  \tabularnewline
Number of observations & 84 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74488&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]3010.11904761905[/C][C]63.6661216377696[/C][C]47.2797615150051[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]2956.14350124694[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]2904.42622431556[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]3065.49291460995[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 28 )[/C][C]3011.52380952381[/C][C]63.4003083896174[/C][C]47.5001444948332[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 28 )[/C][C]3012.57142857143[/C][C]62.3939014208405[/C][C]48.2831071622199[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 28 )[/C][C]3012.82142857143[/C][C]62.1850646110089[/C][C]48.449277128162[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 28 )[/C][C]3009.15476190476[/C][C]61.0959726150459[/C][C]49.2529152594865[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 28 )[/C][C]3010.16666666667[/C][C]60.7812633275774[/C][C]49.5245821141218[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 28 )[/C][C]3006.88095238095[/C][C]59.4088115185584[/C][C]50.6133833605079[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 28 )[/C][C]3008.96428571429[/C][C]58.6571459468798[/C][C]51.2974887738183[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 28 )[/C][C]3009.44047619048[/C][C]58.4704331458514[/C][C]51.4694404381029[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 28 )[/C][C]3011.79761904762[/C][C]57.6831135528042[/C][C]52.2128129628538[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 28 )[/C][C]3010.96428571429[/C][C]57.122892067649[/C][C]52.710291386306[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 28 )[/C][C]3012.53571428571[/C][C]56.8409408341693[/C][C]52.9993992019703[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 28 )[/C][C]3005.96428571429[/C][C]55.5761494679253[/C][C]54.0873074959812[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 28 )[/C][C]3007.35714285714[/C][C]54.9771183896594[/C][C]54.7019784038517[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 28 )[/C][C]3005.35714285714[/C][C]53.7261645581981[/C][C]55.9384271624607[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 28 )[/C][C]3005.35714285714[/C][C]53.7261645581981[/C][C]55.9384271624607[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 28 )[/C][C]3002.30952380952[/C][C]52.0687874614736[/C][C]57.6604463092399[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 28 )[/C][C]2984.29761904762[/C][C]48.0892200660807[/C][C]62.0575175672804[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 28 )[/C][C]2980.22619047619[/C][C]47.175622950847[/C][C]63.1730119087422[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 28 )[/C][C]2977.28571428571[/C][C]44.8259801274407[/C][C]66.4187532725724[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 28 )[/C][C]2952.28571428571[/C][C]40.8331848842077[/C][C]72.3011374855435[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 28 )[/C][C]2946.03571428571[/C][C]39.3975298771544[/C][C]74.7771680984[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 28 )[/C][C]2947.08333333333[/C][C]39.1914523752429[/C][C]75.1970941295096[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 28 )[/C][C]2914.5[/C][C]31.7423221321800[/C][C]91.8174791328612[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 28 )[/C][C]2890.78571428571[/C][C]27.10572504658[/C][C]106.648529390674[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 28 )[/C][C]2893.76190476190[/C][C]24.3881914834753[/C][C]118.654222750491[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 28 )[/C][C]2889.73809523810[/C][C]23.6447648552999[/C][C]122.214710652551[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 28 )[/C][C]2891.34523809524[/C][C]20.1085514704493[/C][C]143.786848214514[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 28 )[/C][C]2891.34523809524[/C][C]19.3650314910497[/C][C]149.307541246787[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 28 )[/C][C]3008.37804878049[/C][C]62.2125177300656[/C][C]48.3564748469683[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 28 )[/C][C]3005.075[/C][C]60.8328400000226[/C][C]49.398893755394[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 28 )[/C][C]3001.03846153846[/C][C]59.8413220966273[/C][C]50.1499358034338[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 28 )[/C][C]2996.69736842105[/C][C]58.7655646265104[/C][C]50.9941049229565[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 28 )[/C][C]2993.16216216216[/C][C]57.87663227828[/C][C]51.7162461659926[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 28 )[/C][C]2989.19444444444[/C][C]56.9104038680353[/C][C]52.5245691697398[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 28 )[/C][C]2985.65714285714[/C][C]56.116083786282[/C][C]53.2050161274264[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 28 )[/C][C]2981.54411764706[/C][C]55.3304282676743[/C][C]53.8861565145153[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 28 )[/C][C]2977.10606060606[/C][C]54.41476356291[/C][C]54.7113662850738[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 28 )[/C][C]2972.046875[/C][C]53.4603418399712[/C][C]55.5934880457098[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 28 )[/C][C]2966.77419354839[/C][C]52.4049108359349[/C][C]56.6125224950106[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 28 )[/C][C]2960.95[/C][C]51.1583474254147[/C][C]57.878140108354[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 28 )[/C][C]2955.51724137931[/C][C]49.8832165586819[/C][C]59.2487302398089[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 28 )[/C][C]2949.53571428571[/C][C]48.4127610383291[/C][C]60.9247572546114[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 28 )[/C][C]2943.33333333333[/C][C]46.8291346775392[/C][C]62.8526098891393[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 28 )[/C][C]2936.65384615385[/C][C]44.8274039204132[/C][C]65.5102368044242[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 28 )[/C][C]2929.76[/C][C]42.6464493342216[/C][C]68.6988024967654[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 28 )[/C][C]2924.14583333333[/C][C]40.7886351417011[/C][C]71.690210353319[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 28 )[/C][C]2918.45652173913[/C][C]38.5965344308179[/C][C]75.6144706973704[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 28 )[/C][C]2912.54545454545[/C][C]36.290690577115[/C][C]80.2559942571639[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 28 )[/C][C]2908.57142857143[/C][C]34.3163384331396[/C][C]84.7576274560399[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 28 )[/C][C]2904.825[/C][C]32.0547985827315[/C][C]90.6205974903514[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 28 )[/C][C]2900.57894736842[/C][C]28.9885107858319[/C][C]100.059605296664[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 28 )[/C][C]2899.16666666667[/C][C]27.1192691993122[/C][C]106.904306504697[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 28 )[/C][C]2900.02941176471[/C][C]25.8815512961254[/C][C]112.050061396391[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 28 )[/C][C]2900.6875[/C][C]24.9115547382295[/C][C]116.439440672427[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 28 )[/C][C]2901.86666666667[/C][C]23.7068171646180[/C][C]122.406422022677[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 28 )[/C][C]2903.03571428571[/C][C]23.0672172921972[/C][C]125.851145264397[/C][/ROW]
[ROW][C]Median[/C][C]2905[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3081.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]2899.58139534884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]2908.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]2899.58139534884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]2908.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]2908.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]2899.58139534884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]2908.57142857143[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]2912.54545454545[/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=74488&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74488&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 Mean3010.1190476190563.666121637769647.2797615150051
Geometric Mean2956.14350124694
Harmonic Mean2904.42622431556
Quadratic Mean3065.49291460995
Winsorized Mean ( 1 / 28 )3011.5238095238163.400308389617447.5001444948332
Winsorized Mean ( 2 / 28 )3012.5714285714362.393901420840548.2831071622199
Winsorized Mean ( 3 / 28 )3012.8214285714362.185064611008948.449277128162
Winsorized Mean ( 4 / 28 )3009.1547619047661.095972615045949.2529152594865
Winsorized Mean ( 5 / 28 )3010.1666666666760.781263327577449.5245821141218
Winsorized Mean ( 6 / 28 )3006.8809523809559.408811518558450.6133833605079
Winsorized Mean ( 7 / 28 )3008.9642857142958.657145946879851.2974887738183
Winsorized Mean ( 8 / 28 )3009.4404761904858.470433145851451.4694404381029
Winsorized Mean ( 9 / 28 )3011.7976190476257.683113552804252.2128129628538
Winsorized Mean ( 10 / 28 )3010.9642857142957.12289206764952.710291386306
Winsorized Mean ( 11 / 28 )3012.5357142857156.840940834169352.9993992019703
Winsorized Mean ( 12 / 28 )3005.9642857142955.576149467925354.0873074959812
Winsorized Mean ( 13 / 28 )3007.3571428571454.977118389659454.7019784038517
Winsorized Mean ( 14 / 28 )3005.3571428571453.726164558198155.9384271624607
Winsorized Mean ( 15 / 28 )3005.3571428571453.726164558198155.9384271624607
Winsorized Mean ( 16 / 28 )3002.3095238095252.068787461473657.6604463092399
Winsorized Mean ( 17 / 28 )2984.2976190476248.089220066080762.0575175672804
Winsorized Mean ( 18 / 28 )2980.2261904761947.17562295084763.1730119087422
Winsorized Mean ( 19 / 28 )2977.2857142857144.825980127440766.4187532725724
Winsorized Mean ( 20 / 28 )2952.2857142857140.833184884207772.3011374855435
Winsorized Mean ( 21 / 28 )2946.0357142857139.397529877154474.7771680984
Winsorized Mean ( 22 / 28 )2947.0833333333339.191452375242975.1970941295096
Winsorized Mean ( 23 / 28 )2914.531.742322132180091.8174791328612
Winsorized Mean ( 24 / 28 )2890.7857142857127.10572504658106.648529390674
Winsorized Mean ( 25 / 28 )2893.7619047619024.3881914834753118.654222750491
Winsorized Mean ( 26 / 28 )2889.7380952381023.6447648552999122.214710652551
Winsorized Mean ( 27 / 28 )2891.3452380952420.1085514704493143.786848214514
Winsorized Mean ( 28 / 28 )2891.3452380952419.3650314910497149.307541246787
Trimmed Mean ( 1 / 28 )3008.3780487804962.212517730065648.3564748469683
Trimmed Mean ( 2 / 28 )3005.07560.832840000022649.398893755394
Trimmed Mean ( 3 / 28 )3001.0384615384659.841322096627350.1499358034338
Trimmed Mean ( 4 / 28 )2996.6973684210558.765564626510450.9941049229565
Trimmed Mean ( 5 / 28 )2993.1621621621657.8766322782851.7162461659926
Trimmed Mean ( 6 / 28 )2989.1944444444456.910403868035352.5245691697398
Trimmed Mean ( 7 / 28 )2985.6571428571456.11608378628253.2050161274264
Trimmed Mean ( 8 / 28 )2981.5441176470655.330428267674353.8861565145153
Trimmed Mean ( 9 / 28 )2977.1060606060654.4147635629154.7113662850738
Trimmed Mean ( 10 / 28 )2972.04687553.460341839971255.5934880457098
Trimmed Mean ( 11 / 28 )2966.7741935483952.404910835934956.6125224950106
Trimmed Mean ( 12 / 28 )2960.9551.158347425414757.878140108354
Trimmed Mean ( 13 / 28 )2955.5172413793149.883216558681959.2487302398089
Trimmed Mean ( 14 / 28 )2949.5357142857148.412761038329160.9247572546114
Trimmed Mean ( 15 / 28 )2943.3333333333346.829134677539262.8526098891393
Trimmed Mean ( 16 / 28 )2936.6538461538544.827403920413265.5102368044242
Trimmed Mean ( 17 / 28 )2929.7642.646449334221668.6988024967654
Trimmed Mean ( 18 / 28 )2924.1458333333340.788635141701171.690210353319
Trimmed Mean ( 19 / 28 )2918.4565217391338.596534430817975.6144706973704
Trimmed Mean ( 20 / 28 )2912.5454545454536.29069057711580.2559942571639
Trimmed Mean ( 21 / 28 )2908.5714285714334.316338433139684.7576274560399
Trimmed Mean ( 22 / 28 )2904.82532.054798582731590.6205974903514
Trimmed Mean ( 23 / 28 )2900.5789473684228.9885107858319100.059605296664
Trimmed Mean ( 24 / 28 )2899.1666666666727.1192691993122106.904306504697
Trimmed Mean ( 25 / 28 )2900.0294117647125.8815512961254112.050061396391
Trimmed Mean ( 26 / 28 )2900.687524.9115547382295116.439440672427
Trimmed Mean ( 27 / 28 )2901.8666666666723.7068171646180122.406422022677
Trimmed Mean ( 28 / 28 )2903.0357142857123.0672172921972125.851145264397
Median2905
Midrange3081.5
Midmean - Weighted Average at Xnp2899.58139534884
Midmean - Weighted Average at X(n+1)p2908.57142857143
Midmean - Empirical Distribution Function2899.58139534884
Midmean - Empirical Distribution Function - Averaging2908.57142857143
Midmean - Empirical Distribution Function - Interpolation2908.57142857143
Midmean - Closest Observation2899.58139534884
Midmean - True Basic - Statistics Graphics Toolkit2908.57142857143
Midmean - MS Excel (old versions)2912.54545454545
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')