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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 21 Dec 2016 13:30:27 +0100
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/Dec/21/t14823234558jcrf1fn10m5kdx.htm/, Retrieved Mon, 06 May 2024 21:07:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302226, Retrieved Mon, 06 May 2024 21:07:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact53
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [n1787.] [2016-12-21 12:30:27] [b7f10b15eba379294ac5bdad7f2e1205] [Current]
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Dataseries X:
3560
2900
3380
3560
3100
2800
2780
4380
3480
3220
3840
4580
3660
5040
4320
4240
3160
4420
3280
5040
5580
4920
5200
4140
4360
4360
4480
4140
2620
4240
3920
4180
8140
8060
6780
5180
4820
3600
6480
5500
4080
3800
4560
7140
4740
5820
6800
4720
6220
3420
7600
2540
4220
5420
2040
4480
5340
4720
4220
3680
4940
2460
3900
5160
2500
3560
3340
6380
2900
7940
4640
3000
5500
4000
3340
2220
2060
3520
2560
2100
3720
4600
2800
2720
2920
2940
2900
2140
2020
3040
3900
2020
3280
3040
3060
2360
3120
3900
1960
2760
1760
2520
2160
2980
2800
3700
3660
2920




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302226&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302226&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean3969.63135.9429.2014
Geometric Mean3741.73
Harmonic Mean3531.92
Quadratic Mean4211.33
Winsorized Mean ( 1 / 36 )3970.74135.4629.313
Winsorized Mean ( 2 / 36 )3969.63134.68829.4727
Winsorized Mean ( 3 / 36 )3960.19132.17129.9626
Winsorized Mean ( 4 / 36 )3943.89127.88330.8398
Winsorized Mean ( 5 / 36 )3929.07124.21331.6316
Winsorized Mean ( 6 / 36 )3930.19123.66431.7812
Winsorized Mean ( 7 / 36 )3913.33119.25232.8156
Winsorized Mean ( 8 / 36 )3907.41117.57333.2338
Winsorized Mean ( 9 / 36 )3899.07114.30734.1106
Winsorized Mean ( 10 / 36 )3875105.84236.6112
Winsorized Mean ( 11 / 36 )3860.74100.43838.4389
Winsorized Mean ( 12 / 36 )3856.398.457939.167
Winsorized Mean ( 13 / 36 )3858.798.149539.3146
Winsorized Mean ( 14 / 36 )3850.9396.218340.0228
Winsorized Mean ( 15 / 36 )3842.5994.192440.7951
Winsorized Mean ( 16 / 36 )3830.7490.052342.5391
Winsorized Mean ( 17 / 36 )3843.3387.672343.8375
Winsorized Mean ( 18 / 36 )3846.6786.407144.518
Winsorized Mean ( 19 / 36 )3829.0783.053746.1036
Winsorized Mean ( 20 / 36 )3832.7882.618746.3912
Winsorized Mean ( 21 / 36 )3813.3380.010847.6602
Winsorized Mean ( 22 / 36 )3809.2679.476747.9293
Winsorized Mean ( 23 / 36 )3809.2674.245951.306
Winsorized Mean ( 24 / 36 )3791.4872.020352.6446
Winsorized Mean ( 25 / 36 )3786.8571.452952.9979
Winsorized Mean ( 26 / 36 )3791.6770.89753.4813
Winsorized Mean ( 27 / 36 )3771.6768.487755.0708
Winsorized Mean ( 28 / 36 )3766.4866.665556.4982
Winsorized Mean ( 29 / 36 )3771.8564.803258.2048
Winsorized Mean ( 30 / 36 )3771.8563.524659.3762
Winsorized Mean ( 31 / 36 )3760.3759.59663.0977
Winsorized Mean ( 32 / 36 )3760.3759.59663.0977
Winsorized Mean ( 33 / 36 )3748.1556.857965.9214
Winsorized Mean ( 34 / 36 )3748.1554.056669.3374
Winsorized Mean ( 35 / 36 )3748.1552.625871.2227
Winsorized Mean ( 36 / 36 )3761.4851.149373.5393
Trimmed Mean ( 1 / 36 )3951.13131.08230.1425
Trimmed Mean ( 2 / 36 )3930.77126.10631.1704
Trimmed Mean ( 3 / 36 )3910.2120.932.3425
Trimmed Mean ( 4 / 36 )3892.2116.06433.5349
Trimmed Mean ( 5 / 36 )3877.96112.05634.6073
Trimmed Mean ( 6 / 36 )3866.46108.57335.6117
Trimmed Mean ( 7 / 36 )3854.26104.72936.8022
Trimmed Mean ( 8 / 36 )3844.35101.37737.9213
Trimmed Mean ( 9 / 36 )3834.8997.897339.1726
Trimmed Mean ( 10 / 36 )3826.1494.564640.4606
Trimmed Mean ( 11 / 36 )382092.343941.3671
Trimmed Mean ( 12 / 36 )3815.2490.724542.053
Trimmed Mean ( 13 / 36 )3810.7389.173142.7341
Trimmed Mean ( 14 / 36 )3805.7587.415943.5361
Trimmed Mean ( 15 / 36 )3801.2885.674844.3687
Trimmed Mean ( 16 / 36 )3797.3783.954345.2314
Trimmed Mean ( 17 / 36 )3794.3282.560445.9582
Trimmed Mean ( 18 / 36 )379081.248146.6473
Trimmed Mean ( 19 / 36 )3785.1479.862947.3955
Trimmed Mean ( 20 / 36 )3781.4778.702548.0476
Trimmed Mean ( 21 / 36 )3777.2777.357148.829
Trimmed Mean ( 22 / 36 )3774.3876.123249.5825
Trimmed Mean ( 23 / 36 )3771.6174.696750.4924
Trimmed Mean ( 24 / 36 )3768.6773.727851.1159
Trimmed Mean ( 25 / 36 )3766.972.848151.7089
Trimmed Mean ( 26 / 36 )3765.3671.814152.432
Trimmed Mean ( 27 / 36 )3763.3370.582653.3182
Trimmed Mean ( 28 / 36 )3762.6969.414854.2059
Trimmed Mean ( 29 / 36 )3762.468.214955.1551
Trimmed Mean ( 30 / 36 )3761.6766.975856.1646
Trimmed Mean ( 31 / 36 )3760.8765.579457.3483
Trimmed Mean ( 32 / 36 )3760.9164.476958.3295
Trimmed Mean ( 33 / 36 )3760.9562.97359.7232
Trimmed Mean ( 34 / 36 )376261.514261.1566
Trimmed Mean ( 35 / 36 )3763.1660.125662.5882
Trimmed Mean ( 36 / 36 )3764.4458.505864.3431
Median3710
Midrange4950
Midmean - Weighted Average at Xnp3748
Midmean - Weighted Average at X(n+1)p3748
Midmean - Empirical Distribution Function3748
Midmean - Empirical Distribution Function - Averaging3748
Midmean - Empirical Distribution Function - Interpolation3748
Midmean - Closest Observation3748
Midmean - True Basic - Statistics Graphics Toolkit3748
Midmean - MS Excel (old versions)3782.11
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 3969.63 & 135.94 & 29.2014 \tabularnewline
Geometric Mean & 3741.73 &  &  \tabularnewline
Harmonic Mean & 3531.92 &  &  \tabularnewline
Quadratic Mean & 4211.33 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 3970.74 & 135.46 & 29.313 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 3969.63 & 134.688 & 29.4727 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 3960.19 & 132.171 & 29.9626 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 3943.89 & 127.883 & 30.8398 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 3929.07 & 124.213 & 31.6316 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 3930.19 & 123.664 & 31.7812 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 3913.33 & 119.252 & 32.8156 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 3907.41 & 117.573 & 33.2338 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 3899.07 & 114.307 & 34.1106 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 3875 & 105.842 & 36.6112 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 3860.74 & 100.438 & 38.4389 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 3856.3 & 98.4579 & 39.167 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 3858.7 & 98.1495 & 39.3146 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 3850.93 & 96.2183 & 40.0228 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 3842.59 & 94.1924 & 40.7951 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 3830.74 & 90.0523 & 42.5391 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 3843.33 & 87.6723 & 43.8375 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 3846.67 & 86.4071 & 44.518 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 3829.07 & 83.0537 & 46.1036 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 3832.78 & 82.6187 & 46.3912 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 3813.33 & 80.0108 & 47.6602 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 3809.26 & 79.4767 & 47.9293 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 3809.26 & 74.2459 & 51.306 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 3791.48 & 72.0203 & 52.6446 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 3786.85 & 71.4529 & 52.9979 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 3791.67 & 70.897 & 53.4813 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 3771.67 & 68.4877 & 55.0708 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 3766.48 & 66.6655 & 56.4982 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 3771.85 & 64.8032 & 58.2048 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 3771.85 & 63.5246 & 59.3762 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 3760.37 & 59.596 & 63.0977 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 3760.37 & 59.596 & 63.0977 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 3748.15 & 56.8579 & 65.9214 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 3748.15 & 54.0566 & 69.3374 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 3748.15 & 52.6258 & 71.2227 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 3761.48 & 51.1493 & 73.5393 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 3951.13 & 131.082 & 30.1425 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 3930.77 & 126.106 & 31.1704 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 3910.2 & 120.9 & 32.3425 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 3892.2 & 116.064 & 33.5349 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 3877.96 & 112.056 & 34.6073 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 3866.46 & 108.573 & 35.6117 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 3854.26 & 104.729 & 36.8022 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 3844.35 & 101.377 & 37.9213 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 3834.89 & 97.8973 & 39.1726 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 3826.14 & 94.5646 & 40.4606 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 3820 & 92.3439 & 41.3671 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 3815.24 & 90.7245 & 42.053 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 3810.73 & 89.1731 & 42.7341 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 3805.75 & 87.4159 & 43.5361 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 3801.28 & 85.6748 & 44.3687 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 3797.37 & 83.9543 & 45.2314 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 3794.32 & 82.5604 & 45.9582 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 3790 & 81.2481 & 46.6473 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 3785.14 & 79.8629 & 47.3955 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 3781.47 & 78.7025 & 48.0476 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 3777.27 & 77.3571 & 48.829 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 3774.38 & 76.1232 & 49.5825 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 3771.61 & 74.6967 & 50.4924 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 3768.67 & 73.7278 & 51.1159 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 3766.9 & 72.8481 & 51.7089 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 3765.36 & 71.8141 & 52.432 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 3763.33 & 70.5826 & 53.3182 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 3762.69 & 69.4148 & 54.2059 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 3762.4 & 68.2149 & 55.1551 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 3761.67 & 66.9758 & 56.1646 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 3760.87 & 65.5794 & 57.3483 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 3760.91 & 64.4769 & 58.3295 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 3760.95 & 62.973 & 59.7232 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 3762 & 61.5142 & 61.1566 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 3763.16 & 60.1256 & 62.5882 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 3764.44 & 58.5058 & 64.3431 \tabularnewline
Median & 3710 &  &  \tabularnewline
Midrange & 4950 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 3748 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 3748 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 3748 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 3748 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 3748 &  &  \tabularnewline
Midmean - Closest Observation & 3748 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 3748 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 3782.11 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302226&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]3969.63[/C][C]135.94[/C][C]29.2014[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]3741.73[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3531.92[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]4211.33[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]3970.74[/C][C]135.46[/C][C]29.313[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]3969.63[/C][C]134.688[/C][C]29.4727[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]3960.19[/C][C]132.171[/C][C]29.9626[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]3943.89[/C][C]127.883[/C][C]30.8398[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]3929.07[/C][C]124.213[/C][C]31.6316[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]3930.19[/C][C]123.664[/C][C]31.7812[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]3913.33[/C][C]119.252[/C][C]32.8156[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]3907.41[/C][C]117.573[/C][C]33.2338[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]3899.07[/C][C]114.307[/C][C]34.1106[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]3875[/C][C]105.842[/C][C]36.6112[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]3860.74[/C][C]100.438[/C][C]38.4389[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]3856.3[/C][C]98.4579[/C][C]39.167[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]3858.7[/C][C]98.1495[/C][C]39.3146[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]3850.93[/C][C]96.2183[/C][C]40.0228[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]3842.59[/C][C]94.1924[/C][C]40.7951[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]3830.74[/C][C]90.0523[/C][C]42.5391[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]3843.33[/C][C]87.6723[/C][C]43.8375[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]3846.67[/C][C]86.4071[/C][C]44.518[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]3829.07[/C][C]83.0537[/C][C]46.1036[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]3832.78[/C][C]82.6187[/C][C]46.3912[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]3813.33[/C][C]80.0108[/C][C]47.6602[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]3809.26[/C][C]79.4767[/C][C]47.9293[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]3809.26[/C][C]74.2459[/C][C]51.306[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]3791.48[/C][C]72.0203[/C][C]52.6446[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]3786.85[/C][C]71.4529[/C][C]52.9979[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]3791.67[/C][C]70.897[/C][C]53.4813[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]3771.67[/C][C]68.4877[/C][C]55.0708[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]3766.48[/C][C]66.6655[/C][C]56.4982[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]3771.85[/C][C]64.8032[/C][C]58.2048[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]3771.85[/C][C]63.5246[/C][C]59.3762[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]3760.37[/C][C]59.596[/C][C]63.0977[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]3760.37[/C][C]59.596[/C][C]63.0977[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]3748.15[/C][C]56.8579[/C][C]65.9214[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]3748.15[/C][C]54.0566[/C][C]69.3374[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]3748.15[/C][C]52.6258[/C][C]71.2227[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]3761.48[/C][C]51.1493[/C][C]73.5393[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]3951.13[/C][C]131.082[/C][C]30.1425[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]3930.77[/C][C]126.106[/C][C]31.1704[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]3910.2[/C][C]120.9[/C][C]32.3425[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]3892.2[/C][C]116.064[/C][C]33.5349[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]3877.96[/C][C]112.056[/C][C]34.6073[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]3866.46[/C][C]108.573[/C][C]35.6117[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]3854.26[/C][C]104.729[/C][C]36.8022[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]3844.35[/C][C]101.377[/C][C]37.9213[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]3834.89[/C][C]97.8973[/C][C]39.1726[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]3826.14[/C][C]94.5646[/C][C]40.4606[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]3820[/C][C]92.3439[/C][C]41.3671[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]3815.24[/C][C]90.7245[/C][C]42.053[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]3810.73[/C][C]89.1731[/C][C]42.7341[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]3805.75[/C][C]87.4159[/C][C]43.5361[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]3801.28[/C][C]85.6748[/C][C]44.3687[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]3797.37[/C][C]83.9543[/C][C]45.2314[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]3794.32[/C][C]82.5604[/C][C]45.9582[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]3790[/C][C]81.2481[/C][C]46.6473[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]3785.14[/C][C]79.8629[/C][C]47.3955[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]3781.47[/C][C]78.7025[/C][C]48.0476[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]3777.27[/C][C]77.3571[/C][C]48.829[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]3774.38[/C][C]76.1232[/C][C]49.5825[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]3771.61[/C][C]74.6967[/C][C]50.4924[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]3768.67[/C][C]73.7278[/C][C]51.1159[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]3766.9[/C][C]72.8481[/C][C]51.7089[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]3765.36[/C][C]71.8141[/C][C]52.432[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]3763.33[/C][C]70.5826[/C][C]53.3182[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]3762.69[/C][C]69.4148[/C][C]54.2059[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]3762.4[/C][C]68.2149[/C][C]55.1551[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]3761.67[/C][C]66.9758[/C][C]56.1646[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]3760.87[/C][C]65.5794[/C][C]57.3483[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]3760.91[/C][C]64.4769[/C][C]58.3295[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]3760.95[/C][C]62.973[/C][C]59.7232[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]3762[/C][C]61.5142[/C][C]61.1566[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]3763.16[/C][C]60.1256[/C][C]62.5882[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]3764.44[/C][C]58.5058[/C][C]64.3431[/C][/ROW]
[ROW][C]Median[/C][C]3710[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]4950[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]3748[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]3782.11[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302226&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 Mean3969.63135.9429.2014
Geometric Mean3741.73
Harmonic Mean3531.92
Quadratic Mean4211.33
Winsorized Mean ( 1 / 36 )3970.74135.4629.313
Winsorized Mean ( 2 / 36 )3969.63134.68829.4727
Winsorized Mean ( 3 / 36 )3960.19132.17129.9626
Winsorized Mean ( 4 / 36 )3943.89127.88330.8398
Winsorized Mean ( 5 / 36 )3929.07124.21331.6316
Winsorized Mean ( 6 / 36 )3930.19123.66431.7812
Winsorized Mean ( 7 / 36 )3913.33119.25232.8156
Winsorized Mean ( 8 / 36 )3907.41117.57333.2338
Winsorized Mean ( 9 / 36 )3899.07114.30734.1106
Winsorized Mean ( 10 / 36 )3875105.84236.6112
Winsorized Mean ( 11 / 36 )3860.74100.43838.4389
Winsorized Mean ( 12 / 36 )3856.398.457939.167
Winsorized Mean ( 13 / 36 )3858.798.149539.3146
Winsorized Mean ( 14 / 36 )3850.9396.218340.0228
Winsorized Mean ( 15 / 36 )3842.5994.192440.7951
Winsorized Mean ( 16 / 36 )3830.7490.052342.5391
Winsorized Mean ( 17 / 36 )3843.3387.672343.8375
Winsorized Mean ( 18 / 36 )3846.6786.407144.518
Winsorized Mean ( 19 / 36 )3829.0783.053746.1036
Winsorized Mean ( 20 / 36 )3832.7882.618746.3912
Winsorized Mean ( 21 / 36 )3813.3380.010847.6602
Winsorized Mean ( 22 / 36 )3809.2679.476747.9293
Winsorized Mean ( 23 / 36 )3809.2674.245951.306
Winsorized Mean ( 24 / 36 )3791.4872.020352.6446
Winsorized Mean ( 25 / 36 )3786.8571.452952.9979
Winsorized Mean ( 26 / 36 )3791.6770.89753.4813
Winsorized Mean ( 27 / 36 )3771.6768.487755.0708
Winsorized Mean ( 28 / 36 )3766.4866.665556.4982
Winsorized Mean ( 29 / 36 )3771.8564.803258.2048
Winsorized Mean ( 30 / 36 )3771.8563.524659.3762
Winsorized Mean ( 31 / 36 )3760.3759.59663.0977
Winsorized Mean ( 32 / 36 )3760.3759.59663.0977
Winsorized Mean ( 33 / 36 )3748.1556.857965.9214
Winsorized Mean ( 34 / 36 )3748.1554.056669.3374
Winsorized Mean ( 35 / 36 )3748.1552.625871.2227
Winsorized Mean ( 36 / 36 )3761.4851.149373.5393
Trimmed Mean ( 1 / 36 )3951.13131.08230.1425
Trimmed Mean ( 2 / 36 )3930.77126.10631.1704
Trimmed Mean ( 3 / 36 )3910.2120.932.3425
Trimmed Mean ( 4 / 36 )3892.2116.06433.5349
Trimmed Mean ( 5 / 36 )3877.96112.05634.6073
Trimmed Mean ( 6 / 36 )3866.46108.57335.6117
Trimmed Mean ( 7 / 36 )3854.26104.72936.8022
Trimmed Mean ( 8 / 36 )3844.35101.37737.9213
Trimmed Mean ( 9 / 36 )3834.8997.897339.1726
Trimmed Mean ( 10 / 36 )3826.1494.564640.4606
Trimmed Mean ( 11 / 36 )382092.343941.3671
Trimmed Mean ( 12 / 36 )3815.2490.724542.053
Trimmed Mean ( 13 / 36 )3810.7389.173142.7341
Trimmed Mean ( 14 / 36 )3805.7587.415943.5361
Trimmed Mean ( 15 / 36 )3801.2885.674844.3687
Trimmed Mean ( 16 / 36 )3797.3783.954345.2314
Trimmed Mean ( 17 / 36 )3794.3282.560445.9582
Trimmed Mean ( 18 / 36 )379081.248146.6473
Trimmed Mean ( 19 / 36 )3785.1479.862947.3955
Trimmed Mean ( 20 / 36 )3781.4778.702548.0476
Trimmed Mean ( 21 / 36 )3777.2777.357148.829
Trimmed Mean ( 22 / 36 )3774.3876.123249.5825
Trimmed Mean ( 23 / 36 )3771.6174.696750.4924
Trimmed Mean ( 24 / 36 )3768.6773.727851.1159
Trimmed Mean ( 25 / 36 )3766.972.848151.7089
Trimmed Mean ( 26 / 36 )3765.3671.814152.432
Trimmed Mean ( 27 / 36 )3763.3370.582653.3182
Trimmed Mean ( 28 / 36 )3762.6969.414854.2059
Trimmed Mean ( 29 / 36 )3762.468.214955.1551
Trimmed Mean ( 30 / 36 )3761.6766.975856.1646
Trimmed Mean ( 31 / 36 )3760.8765.579457.3483
Trimmed Mean ( 32 / 36 )3760.9164.476958.3295
Trimmed Mean ( 33 / 36 )3760.9562.97359.7232
Trimmed Mean ( 34 / 36 )376261.514261.1566
Trimmed Mean ( 35 / 36 )3763.1660.125662.5882
Trimmed Mean ( 36 / 36 )3764.4458.505864.3431
Median3710
Midrange4950
Midmean - Weighted Average at Xnp3748
Midmean - Weighted Average at X(n+1)p3748
Midmean - Empirical Distribution Function3748
Midmean - Empirical Distribution Function - Averaging3748
Midmean - Empirical Distribution Function - Interpolation3748
Midmean - Closest Observation3748
Midmean - True Basic - Statistics Graphics Toolkit3748
Midmean - MS Excel (old versions)3782.11
Number of observations108



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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- 'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')