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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 computationThu, 03 Aug 2017 22:23:36 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/03/t15017918279q97vlkuaqrngr4.htm/, Retrieved Thu, 09 May 2024 22:50:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=306895, Retrieved Thu, 09 May 2024 22:50:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-03 20:23:36] [1a8cec710a8245ea2c14b5d40c333c7c] [Current]
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Dataseries X:
70200
67600
71500
57200
74100
72800
78000
80600
89700
78000
74100
92300
78000
58500
68900
52000
72800
59800
79300
71500
75400
84500
83200
98800
71500
59800
66300
48100
68900
53300
75400
71500
63700
91000
81900
93600
70200
65000
58500
48100
63700
57200
78000
75400
65000
87100
80600
104000
83200
50700
50700
50700
59800
59800
80600
74100
66300
83200
76700
110500
87100
50700
53300
44200
61100
70200
88400
87100
70200
81900
72800
104000
79300
63700
57200
42900
63700
76700
89700
84500
62400
89700
70200
107900
89700
65000
59800
40300
63700
61100
92300
92300
70200
91000
67600
105300
89700
66300
50700
35100
68900
66300
87100
100100
74100
83200
62400
107900




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=306895&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=306895&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306895&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 Mean72980.61521.9647.9518
Geometric Mean71227
Harmonic Mean69397.4
Quadratic Mean74659.3
Winsorized Mean ( 1 / 36 )73004.61506.0948.4731
Winsorized Mean ( 2 / 36 )73052.81496.6748.8103
Winsorized Mean ( 3 / 36 )73016.71474.7249.5122
Winsorized Mean ( 4 / 36 )731131440.0450.7716
Winsorized Mean ( 5 / 36 )731131440.0450.7716
Winsorized Mean ( 6 / 36 )73040.71375.6653.095
Winsorized Mean ( 7 / 36 )72956.51360.4453.6273
Winsorized Mean ( 8 / 36 )72571.31296.9455.9558
Winsorized Mean ( 9 / 36 )724631280.8956.5724
Winsorized Mean ( 10 / 36 )724631280.8956.5724
Winsorized Mean ( 11 / 36 )72595.41260.2657.6034
Winsorized Mean ( 12 / 36 )72595.41217.7759.6133
Winsorized Mean ( 13 / 36 )72595.41217.7759.6133
Winsorized Mean ( 14 / 36 )72932.41123.4264.92
Winsorized Mean ( 15 / 36 )72932.41123.4264.92
Winsorized Mean ( 16 / 36 )72932.41123.4264.92
Winsorized Mean ( 17 / 36 )731371097.2766.6539
Winsorized Mean ( 18 / 36 )731371097.2766.6539
Winsorized Mean ( 19 / 36 )731371037.3970.5011
Winsorized Mean ( 20 / 36 )72896.31004.9372.5389
Winsorized Mean ( 21 / 36 )72896.31004.9372.5389
Winsorized Mean ( 22 / 36 )72896.31004.9372.5389
Winsorized Mean ( 23 / 36 )72896.31004.9372.5389
Winsorized Mean ( 24 / 36 )72607.4895.84381.0492
Winsorized Mean ( 25 / 36 )72607.4895.84381.0492
Winsorized Mean ( 26 / 36 )72607.4820.52188.4894
Winsorized Mean ( 27 / 36 )72607.4820.52188.4894
Winsorized Mean ( 28 / 36 )72944.4782.29493.2443
Winsorized Mean ( 29 / 36 )72944.4782.29493.2443
Winsorized Mean ( 30 / 36 )72583.3738.87198.2355
Winsorized Mean ( 31 / 36 )72583.3738.87198.2355
Winsorized Mean ( 32 / 36 )72198.1694.367103.977
Winsorized Mean ( 33 / 36 )72595.4649.924111.698
Winsorized Mean ( 34 / 36 )72595.4649.924111.698
Winsorized Mean ( 35 / 36 )72174.1602.351119.821
Winsorized Mean ( 36 / 36 )72607.4555.184130.781
Trimmed Mean ( 1 / 36 )729841466.1549.7792
Trimmed Mean ( 2 / 36 )72962.51421.2551.3369
Trimmed Mean ( 3 / 36 )72914.71376.2752.9801
Trimmed Mean ( 4 / 36 )728781334.8354.5971
Trimmed Mean ( 5 / 36 )72813.31299.6656.025
Trimmed Mean ( 6 / 36 )72745.81259.7457.7468
Trimmed Mean ( 7 / 36 )72689.41230.5859.0691
Trimmed Mean ( 8 / 36 )72644.61200.8560.4941
Trimmed Mean ( 9 / 36 )72655.61179.9561.5753
Trimmed Mean ( 10 / 36 )72681.8115962.7109
Trimmed Mean ( 11 / 36 )72709.31134.9464.0643
Trimmed Mean ( 12 / 36 )72722.61110.8565.466
Trimmed Mean ( 13 / 36 )72736.61090.0466.7282
Trimmed Mean ( 14 / 36 )72751.21065.9168.2524
Trimmed Mean ( 15 / 36 )72733.31052.3769.1141
Trimmed Mean ( 16 / 36 )72714.51036.3870.1618
Trimmed Mean ( 17 / 36 )72694.61017.5371.4421
Trimmed Mean ( 18 / 36 )72655.6999.05172.7246
Trimmed Mean ( 19 / 36 )72614.3977.09674.3164
Trimmed Mean ( 20 / 36 )72570.6959.8875.6038
Trimmed Mean ( 21 / 36 )72543.9944.06876.8419
Trimmed Mean ( 22 / 36 )72515.6924.90778.4032
Trimmed Mean ( 23 / 36 )72485.5901.66180.3911
Trimmed Mean ( 24 / 36 )72453.3873.36182.9592
Trimmed Mean ( 25 / 36 )72441.4856.65684.563
Trimmed Mean ( 26 / 36 )72428.6835.90286.6472
Trimmed Mean ( 27 / 36 )72414.8822.35788.0576
Trimmed Mean ( 28 / 36 )72400805.0789.9301
Trimmed Mean ( 29 / 36 )72358789.32791.6705
Trimmed Mean ( 30 / 36 )72312.5768.9294.0443
Trimmed Mean ( 31 / 36 )72291.3751.07596.2504
Trimmed Mean ( 32 / 36 )72268.2727.57499.3277
Trimmed Mean ( 33 / 36 )72273.8706.17102.346
Trimmed Mean ( 34 / 36 )72247.5687.088105.15
Trimmed Mean ( 35 / 36 )72218.4660.906109.272
Trimmed Mean ( 36 / 36 )72222.2637.382113.311
Median71500
Midrange72800
Midmean - Weighted Average at Xnp72428.6
Midmean - Weighted Average at X(n+1)p72428.6
Midmean - Empirical Distribution Function72428.6
Midmean - Empirical Distribution Function - Averaging72428.6
Midmean - Empirical Distribution Function - Interpolation72428.6
Midmean - Closest Observation72428.6
Midmean - True Basic - Statistics Graphics Toolkit72428.6
Midmean - MS Excel (old versions)72428.6
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 72980.6 & 1521.96 & 47.9518 \tabularnewline
Geometric Mean & 71227 &  &  \tabularnewline
Harmonic Mean & 69397.4 &  &  \tabularnewline
Quadratic Mean & 74659.3 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 73004.6 & 1506.09 & 48.4731 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 73052.8 & 1496.67 & 48.8103 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 73016.7 & 1474.72 & 49.5122 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 73113 & 1440.04 & 50.7716 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 73113 & 1440.04 & 50.7716 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 73040.7 & 1375.66 & 53.095 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 72956.5 & 1360.44 & 53.6273 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 72571.3 & 1296.94 & 55.9558 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 72463 & 1280.89 & 56.5724 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 72463 & 1280.89 & 56.5724 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 72595.4 & 1260.26 & 57.6034 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 72595.4 & 1217.77 & 59.6133 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 72595.4 & 1217.77 & 59.6133 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 72932.4 & 1123.42 & 64.92 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 72932.4 & 1123.42 & 64.92 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 72932.4 & 1123.42 & 64.92 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 73137 & 1097.27 & 66.6539 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 73137 & 1097.27 & 66.6539 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 73137 & 1037.39 & 70.5011 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 72896.3 & 1004.93 & 72.5389 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 72896.3 & 1004.93 & 72.5389 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 72896.3 & 1004.93 & 72.5389 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 72896.3 & 1004.93 & 72.5389 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 72607.4 & 895.843 & 81.0492 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 72607.4 & 895.843 & 81.0492 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 72607.4 & 820.521 & 88.4894 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 72607.4 & 820.521 & 88.4894 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 72944.4 & 782.294 & 93.2443 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 72944.4 & 782.294 & 93.2443 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 72583.3 & 738.871 & 98.2355 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 72583.3 & 738.871 & 98.2355 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 72198.1 & 694.367 & 103.977 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 72595.4 & 649.924 & 111.698 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 72595.4 & 649.924 & 111.698 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 72174.1 & 602.351 & 119.821 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 72607.4 & 555.184 & 130.781 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 72984 & 1466.15 & 49.7792 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 72962.5 & 1421.25 & 51.3369 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 72914.7 & 1376.27 & 52.9801 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 72878 & 1334.83 & 54.5971 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 72813.3 & 1299.66 & 56.025 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 72745.8 & 1259.74 & 57.7468 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 72689.4 & 1230.58 & 59.0691 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 72644.6 & 1200.85 & 60.4941 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 72655.6 & 1179.95 & 61.5753 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 72681.8 & 1159 & 62.7109 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 72709.3 & 1134.94 & 64.0643 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 72722.6 & 1110.85 & 65.466 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 72736.6 & 1090.04 & 66.7282 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 72751.2 & 1065.91 & 68.2524 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 72733.3 & 1052.37 & 69.1141 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 72714.5 & 1036.38 & 70.1618 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 72694.6 & 1017.53 & 71.4421 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 72655.6 & 999.051 & 72.7246 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 72614.3 & 977.096 & 74.3164 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 72570.6 & 959.88 & 75.6038 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 72543.9 & 944.068 & 76.8419 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 72515.6 & 924.907 & 78.4032 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 72485.5 & 901.661 & 80.3911 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 72453.3 & 873.361 & 82.9592 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 72441.4 & 856.656 & 84.563 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 72428.6 & 835.902 & 86.6472 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 72414.8 & 822.357 & 88.0576 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 72400 & 805.07 & 89.9301 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 72358 & 789.327 & 91.6705 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 72312.5 & 768.92 & 94.0443 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 72291.3 & 751.075 & 96.2504 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 72268.2 & 727.574 & 99.3277 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 72273.8 & 706.17 & 102.346 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 72247.5 & 687.088 & 105.15 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 72218.4 & 660.906 & 109.272 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 72222.2 & 637.382 & 113.311 \tabularnewline
Median & 71500 &  &  \tabularnewline
Midrange & 72800 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 72428.6 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 72428.6 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 72428.6 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 72428.6 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 72428.6 &  &  \tabularnewline
Midmean - Closest Observation & 72428.6 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 72428.6 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 72428.6 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=306895&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]72980.6[/C][C]1521.96[/C][C]47.9518[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]71227[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]69397.4[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]74659.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]73004.6[/C][C]1506.09[/C][C]48.4731[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]73052.8[/C][C]1496.67[/C][C]48.8103[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]73016.7[/C][C]1474.72[/C][C]49.5122[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]73113[/C][C]1440.04[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]73113[/C][C]1440.04[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]73040.7[/C][C]1375.66[/C][C]53.095[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]72956.5[/C][C]1360.44[/C][C]53.6273[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]72571.3[/C][C]1296.94[/C][C]55.9558[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]72463[/C][C]1280.89[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]72463[/C][C]1280.89[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]72595.4[/C][C]1260.26[/C][C]57.6034[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]72595.4[/C][C]1217.77[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]72595.4[/C][C]1217.77[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]72932.4[/C][C]1123.42[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]72932.4[/C][C]1123.42[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]72932.4[/C][C]1123.42[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]73137[/C][C]1097.27[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]73137[/C][C]1097.27[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]73137[/C][C]1037.39[/C][C]70.5011[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]72896.3[/C][C]1004.93[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]72896.3[/C][C]1004.93[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]72896.3[/C][C]1004.93[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]72896.3[/C][C]1004.93[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]72607.4[/C][C]895.843[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]72607.4[/C][C]895.843[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]72607.4[/C][C]820.521[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]72607.4[/C][C]820.521[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]72944.4[/C][C]782.294[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]72944.4[/C][C]782.294[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]72583.3[/C][C]738.871[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]72583.3[/C][C]738.871[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]72198.1[/C][C]694.367[/C][C]103.977[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]72595.4[/C][C]649.924[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]72595.4[/C][C]649.924[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]72174.1[/C][C]602.351[/C][C]119.821[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]72607.4[/C][C]555.184[/C][C]130.781[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]72984[/C][C]1466.15[/C][C]49.7792[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]72962.5[/C][C]1421.25[/C][C]51.3369[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]72914.7[/C][C]1376.27[/C][C]52.9801[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]72878[/C][C]1334.83[/C][C]54.5971[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]72813.3[/C][C]1299.66[/C][C]56.025[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]72745.8[/C][C]1259.74[/C][C]57.7468[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]72689.4[/C][C]1230.58[/C][C]59.0691[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]72644.6[/C][C]1200.85[/C][C]60.4941[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]72655.6[/C][C]1179.95[/C][C]61.5753[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]72681.8[/C][C]1159[/C][C]62.7109[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]72709.3[/C][C]1134.94[/C][C]64.0643[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]72722.6[/C][C]1110.85[/C][C]65.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]72736.6[/C][C]1090.04[/C][C]66.7282[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]72751.2[/C][C]1065.91[/C][C]68.2524[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]72733.3[/C][C]1052.37[/C][C]69.1141[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]72714.5[/C][C]1036.38[/C][C]70.1618[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]72694.6[/C][C]1017.53[/C][C]71.4421[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]72655.6[/C][C]999.051[/C][C]72.7246[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]72614.3[/C][C]977.096[/C][C]74.3164[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]72570.6[/C][C]959.88[/C][C]75.6038[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]72543.9[/C][C]944.068[/C][C]76.8419[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]72515.6[/C][C]924.907[/C][C]78.4032[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]72485.5[/C][C]901.661[/C][C]80.3911[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]72453.3[/C][C]873.361[/C][C]82.9592[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]72441.4[/C][C]856.656[/C][C]84.563[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]72428.6[/C][C]835.902[/C][C]86.6472[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]72414.8[/C][C]822.357[/C][C]88.0576[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]72400[/C][C]805.07[/C][C]89.9301[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]72358[/C][C]789.327[/C][C]91.6705[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]72312.5[/C][C]768.92[/C][C]94.0443[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]72291.3[/C][C]751.075[/C][C]96.2504[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]72268.2[/C][C]727.574[/C][C]99.3277[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]72273.8[/C][C]706.17[/C][C]102.346[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]72247.5[/C][C]687.088[/C][C]105.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]72218.4[/C][C]660.906[/C][C]109.272[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]72222.2[/C][C]637.382[/C][C]113.311[/C][/ROW]
[ROW][C]Median[/C][C]71500[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]72800[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]72428.6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]72428.6[/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=306895&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=306895&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 Mean72980.61521.9647.9518
Geometric Mean71227
Harmonic Mean69397.4
Quadratic Mean74659.3
Winsorized Mean ( 1 / 36 )73004.61506.0948.4731
Winsorized Mean ( 2 / 36 )73052.81496.6748.8103
Winsorized Mean ( 3 / 36 )73016.71474.7249.5122
Winsorized Mean ( 4 / 36 )731131440.0450.7716
Winsorized Mean ( 5 / 36 )731131440.0450.7716
Winsorized Mean ( 6 / 36 )73040.71375.6653.095
Winsorized Mean ( 7 / 36 )72956.51360.4453.6273
Winsorized Mean ( 8 / 36 )72571.31296.9455.9558
Winsorized Mean ( 9 / 36 )724631280.8956.5724
Winsorized Mean ( 10 / 36 )724631280.8956.5724
Winsorized Mean ( 11 / 36 )72595.41260.2657.6034
Winsorized Mean ( 12 / 36 )72595.41217.7759.6133
Winsorized Mean ( 13 / 36 )72595.41217.7759.6133
Winsorized Mean ( 14 / 36 )72932.41123.4264.92
Winsorized Mean ( 15 / 36 )72932.41123.4264.92
Winsorized Mean ( 16 / 36 )72932.41123.4264.92
Winsorized Mean ( 17 / 36 )731371097.2766.6539
Winsorized Mean ( 18 / 36 )731371097.2766.6539
Winsorized Mean ( 19 / 36 )731371037.3970.5011
Winsorized Mean ( 20 / 36 )72896.31004.9372.5389
Winsorized Mean ( 21 / 36 )72896.31004.9372.5389
Winsorized Mean ( 22 / 36 )72896.31004.9372.5389
Winsorized Mean ( 23 / 36 )72896.31004.9372.5389
Winsorized Mean ( 24 / 36 )72607.4895.84381.0492
Winsorized Mean ( 25 / 36 )72607.4895.84381.0492
Winsorized Mean ( 26 / 36 )72607.4820.52188.4894
Winsorized Mean ( 27 / 36 )72607.4820.52188.4894
Winsorized Mean ( 28 / 36 )72944.4782.29493.2443
Winsorized Mean ( 29 / 36 )72944.4782.29493.2443
Winsorized Mean ( 30 / 36 )72583.3738.87198.2355
Winsorized Mean ( 31 / 36 )72583.3738.87198.2355
Winsorized Mean ( 32 / 36 )72198.1694.367103.977
Winsorized Mean ( 33 / 36 )72595.4649.924111.698
Winsorized Mean ( 34 / 36 )72595.4649.924111.698
Winsorized Mean ( 35 / 36 )72174.1602.351119.821
Winsorized Mean ( 36 / 36 )72607.4555.184130.781
Trimmed Mean ( 1 / 36 )729841466.1549.7792
Trimmed Mean ( 2 / 36 )72962.51421.2551.3369
Trimmed Mean ( 3 / 36 )72914.71376.2752.9801
Trimmed Mean ( 4 / 36 )728781334.8354.5971
Trimmed Mean ( 5 / 36 )72813.31299.6656.025
Trimmed Mean ( 6 / 36 )72745.81259.7457.7468
Trimmed Mean ( 7 / 36 )72689.41230.5859.0691
Trimmed Mean ( 8 / 36 )72644.61200.8560.4941
Trimmed Mean ( 9 / 36 )72655.61179.9561.5753
Trimmed Mean ( 10 / 36 )72681.8115962.7109
Trimmed Mean ( 11 / 36 )72709.31134.9464.0643
Trimmed Mean ( 12 / 36 )72722.61110.8565.466
Trimmed Mean ( 13 / 36 )72736.61090.0466.7282
Trimmed Mean ( 14 / 36 )72751.21065.9168.2524
Trimmed Mean ( 15 / 36 )72733.31052.3769.1141
Trimmed Mean ( 16 / 36 )72714.51036.3870.1618
Trimmed Mean ( 17 / 36 )72694.61017.5371.4421
Trimmed Mean ( 18 / 36 )72655.6999.05172.7246
Trimmed Mean ( 19 / 36 )72614.3977.09674.3164
Trimmed Mean ( 20 / 36 )72570.6959.8875.6038
Trimmed Mean ( 21 / 36 )72543.9944.06876.8419
Trimmed Mean ( 22 / 36 )72515.6924.90778.4032
Trimmed Mean ( 23 / 36 )72485.5901.66180.3911
Trimmed Mean ( 24 / 36 )72453.3873.36182.9592
Trimmed Mean ( 25 / 36 )72441.4856.65684.563
Trimmed Mean ( 26 / 36 )72428.6835.90286.6472
Trimmed Mean ( 27 / 36 )72414.8822.35788.0576
Trimmed Mean ( 28 / 36 )72400805.0789.9301
Trimmed Mean ( 29 / 36 )72358789.32791.6705
Trimmed Mean ( 30 / 36 )72312.5768.9294.0443
Trimmed Mean ( 31 / 36 )72291.3751.07596.2504
Trimmed Mean ( 32 / 36 )72268.2727.57499.3277
Trimmed Mean ( 33 / 36 )72273.8706.17102.346
Trimmed Mean ( 34 / 36 )72247.5687.088105.15
Trimmed Mean ( 35 / 36 )72218.4660.906109.272
Trimmed Mean ( 36 / 36 )72222.2637.382113.311
Median71500
Midrange72800
Midmean - Weighted Average at Xnp72428.6
Midmean - Weighted Average at X(n+1)p72428.6
Midmean - Empirical Distribution Function72428.6
Midmean - Empirical Distribution Function - Averaging72428.6
Midmean - Empirical Distribution Function - Interpolation72428.6
Midmean - Closest Observation72428.6
Midmean - True Basic - Statistics Graphics Toolkit72428.6
Midmean - MS Excel (old versions)72428.6
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')