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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 computationWed, 16 Aug 2017 22:48:45 +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/16/t15029165429srnyhkglsd2sfc.htm/, Retrieved Sun, 12 May 2024 10:08:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307513, Retrieved Sun, 12 May 2024 10:08:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-16 20:48:45] [a0ce0558b0177aac41d3fe22da4ea7eb] [Current]
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Dataseries X:
59400
57200
60500
48400
62700
61600
66000
68200
75900
66000
62700
78100
66000
49500
58300
44000
61600
50600
67100
60500
63800
71500
70400
83600
60500
50600
56100
40700
58300
45100
63800
60500
53900
77000
69300
79200
59400
55000
49500
40700
53900
48400
66000
63800
55000
73700
68200
88000
70400
42900
42900
42900
50600
50600
68200
62700
56100
70400
64900
93500
73700
42900
45100
37400
51700
59400
74800
73700
59400
69300
61600
88000
67100
53900
48400
36300
53900
64900
75900
71500
52800
75900
59400
91300
75900
55000
50600
34100
53900
51700
78100
78100
59400
77000
57200
89100
75900
56100
42900
29700
58300
56100
73700
84700
62700
70400
52800
91300




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=307513&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=307513&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307513&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 Mean61752.81287.8147.9518
Geometric Mean60269
Harmonic Mean58720.9
Quadratic Mean63173.3
Winsorized Mean ( 1 / 36 )61773.11274.3848.4731
Winsorized Mean ( 2 / 36 )61813.91266.4148.8103
Winsorized Mean ( 3 / 36 )61783.31247.8449.5122
Winsorized Mean ( 4 / 36 )61864.81218.4950.7716
Winsorized Mean ( 5 / 36 )61864.81218.4950.7716
Winsorized Mean ( 6 / 36 )61803.71164.0253.095
Winsorized Mean ( 7 / 36 )61732.41151.1453.6273
Winsorized Mean ( 8 / 36 )61406.51097.4155.9558
Winsorized Mean ( 9 / 36 )61314.81083.8356.5724
Winsorized Mean ( 10 / 36 )61314.81083.8356.5724
Winsorized Mean ( 11 / 36 )61426.91066.3857.6034
Winsorized Mean ( 12 / 36 )61426.91030.4259.6133
Winsorized Mean ( 13 / 36 )61426.91030.4259.6133
Winsorized Mean ( 14 / 36 )61712950.58664.92
Winsorized Mean ( 15 / 36 )61712950.58664.92
Winsorized Mean ( 16 / 36 )61712950.58664.92
Winsorized Mean ( 17 / 36 )61885.2928.45666.6539
Winsorized Mean ( 18 / 36 )61885.2928.45666.6539
Winsorized Mean ( 19 / 36 )61885.2877.7970.5011
Winsorized Mean ( 20 / 36 )61681.5850.32272.5389
Winsorized Mean ( 21 / 36 )61681.5850.32272.5389
Winsorized Mean ( 22 / 36 )61681.5850.32272.5389
Winsorized Mean ( 23 / 36 )61681.5850.32272.5389
Winsorized Mean ( 24 / 36 )61437758.02181.0492
Winsorized Mean ( 25 / 36 )61437758.02181.0492
Winsorized Mean ( 26 / 36 )61437694.28788.4894
Winsorized Mean ( 27 / 36 )61437694.28788.4894
Winsorized Mean ( 28 / 36 )61722.2661.94193.2443
Winsorized Mean ( 29 / 36 )61722.2661.94193.2443
Winsorized Mean ( 30 / 36 )61416.7625.19898.2355
Winsorized Mean ( 31 / 36 )61416.7625.19898.2355
Winsorized Mean ( 32 / 36 )61090.7587.542103.977
Winsorized Mean ( 33 / 36 )61426.9549.936111.698
Winsorized Mean ( 34 / 36 )61426.9549.936111.698
Winsorized Mean ( 35 / 36 )61070.4509.682119.821
Winsorized Mean ( 36 / 36 )61437469.771130.781
Trimmed Mean ( 1 / 36 )61755.71240.5949.7792
Trimmed Mean ( 2 / 36 )61737.51202.651.3369
Trimmed Mean ( 3 / 36 )61697.11164.5352.9801
Trimmed Mean ( 4 / 36 )616661129.4754.5971
Trimmed Mean ( 5 / 36 )61611.21099.7156.025
Trimmed Mean ( 6 / 36 )61554.21065.9357.7468
Trimmed Mean ( 7 / 36 )61506.41041.2659.0691
Trimmed Mean ( 8 / 36 )61468.51016.1160.4941
Trimmed Mean ( 9 / 36 )61477.8998.41761.5753
Trimmed Mean ( 10 / 36 )61500980.6962.7109
Trimmed Mean ( 11 / 36 )61523.3960.33664.0643
Trimmed Mean ( 12 / 36 )61534.5939.94665.466
Trimmed Mean ( 13 / 36 )61546.3922.34366.7282
Trimmed Mean ( 14 / 36 )61558.8901.92868.2524
Trimmed Mean ( 15 / 36 )61543.6890.46469.1141
Trimmed Mean ( 16 / 36 )61527.6876.9470.1618
Trimmed Mean ( 17 / 36 )61510.8860.98971.4421
Trimmed Mean ( 18 / 36 )61477.8845.3572.7246
Trimmed Mean ( 19 / 36 )61442.9826.77474.3164
Trimmed Mean ( 20 / 36 )61405.9812.20675.6038
Trimmed Mean ( 21 / 36 )61383.3798.82776.8419
Trimmed Mean ( 22 / 36 )61359.4782.61378.4032
Trimmed Mean ( 23 / 36 )61333.9762.94480.3911
Trimmed Mean ( 24 / 36 )61306.7738.99882.9592
Trimmed Mean ( 25 / 36 )61296.6724.86384.563
Trimmed Mean ( 26 / 36 )61285.7707.30286.6472
Trimmed Mean ( 27 / 36 )61274.1695.84188.0576
Trimmed Mean ( 28 / 36 )61261.5681.21389.9301
Trimmed Mean ( 29 / 36 )61226667.89291.6705
Trimmed Mean ( 30 / 36 )61187.5650.62594.0443
Trimmed Mean ( 31 / 36 )61169.6635.52596.2504
Trimmed Mean ( 32 / 36 )61150615.63999.3277
Trimmed Mean ( 33 / 36 )61154.8597.529102.346
Trimmed Mean ( 34 / 36 )61132.5581.382105.15
Trimmed Mean ( 35 / 36 )61107.9559.229109.272
Trimmed Mean ( 36 / 36 )61111.1539.323113.311
Median60500
Midrange61600
Midmean - Weighted Average at Xnp61285.7
Midmean - Weighted Average at X(n+1)p61285.7
Midmean - Empirical Distribution Function61285.7
Midmean - Empirical Distribution Function - Averaging61285.7
Midmean - Empirical Distribution Function - Interpolation61285.7
Midmean - Closest Observation61285.7
Midmean - True Basic - Statistics Graphics Toolkit61285.7
Midmean - MS Excel (old versions)61285.7
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 61752.8 & 1287.81 & 47.9518 \tabularnewline
Geometric Mean & 60269 &  &  \tabularnewline
Harmonic Mean & 58720.9 &  &  \tabularnewline
Quadratic Mean & 63173.3 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 61773.1 & 1274.38 & 48.4731 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 61813.9 & 1266.41 & 48.8103 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 61783.3 & 1247.84 & 49.5122 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 61864.8 & 1218.49 & 50.7716 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 61864.8 & 1218.49 & 50.7716 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 61803.7 & 1164.02 & 53.095 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 61732.4 & 1151.14 & 53.6273 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 61406.5 & 1097.41 & 55.9558 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 61314.8 & 1083.83 & 56.5724 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 61314.8 & 1083.83 & 56.5724 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 61426.9 & 1066.38 & 57.6034 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 61426.9 & 1030.42 & 59.6133 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 61426.9 & 1030.42 & 59.6133 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 61712 & 950.586 & 64.92 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 61712 & 950.586 & 64.92 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 61712 & 950.586 & 64.92 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 61885.2 & 928.456 & 66.6539 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 61885.2 & 928.456 & 66.6539 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 61885.2 & 877.79 & 70.5011 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 61681.5 & 850.322 & 72.5389 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 61681.5 & 850.322 & 72.5389 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 61681.5 & 850.322 & 72.5389 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 61681.5 & 850.322 & 72.5389 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 61437 & 758.021 & 81.0492 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 61437 & 758.021 & 81.0492 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 61437 & 694.287 & 88.4894 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 61437 & 694.287 & 88.4894 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 61722.2 & 661.941 & 93.2443 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 61722.2 & 661.941 & 93.2443 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 61416.7 & 625.198 & 98.2355 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 61416.7 & 625.198 & 98.2355 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 61090.7 & 587.542 & 103.977 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 61426.9 & 549.936 & 111.698 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 61426.9 & 549.936 & 111.698 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 61070.4 & 509.682 & 119.821 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 61437 & 469.771 & 130.781 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 61755.7 & 1240.59 & 49.7792 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 61737.5 & 1202.6 & 51.3369 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 61697.1 & 1164.53 & 52.9801 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 61666 & 1129.47 & 54.5971 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 61611.2 & 1099.71 & 56.025 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 61554.2 & 1065.93 & 57.7468 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 61506.4 & 1041.26 & 59.0691 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 61468.5 & 1016.11 & 60.4941 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 61477.8 & 998.417 & 61.5753 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 61500 & 980.69 & 62.7109 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 61523.3 & 960.336 & 64.0643 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 61534.5 & 939.946 & 65.466 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 61546.3 & 922.343 & 66.7282 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 61558.8 & 901.928 & 68.2524 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 61543.6 & 890.464 & 69.1141 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 61527.6 & 876.94 & 70.1618 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 61510.8 & 860.989 & 71.4421 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 61477.8 & 845.35 & 72.7246 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 61442.9 & 826.774 & 74.3164 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 61405.9 & 812.206 & 75.6038 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 61383.3 & 798.827 & 76.8419 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 61359.4 & 782.613 & 78.4032 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 61333.9 & 762.944 & 80.3911 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 61306.7 & 738.998 & 82.9592 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 61296.6 & 724.863 & 84.563 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 61285.7 & 707.302 & 86.6472 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 61274.1 & 695.841 & 88.0576 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 61261.5 & 681.213 & 89.9301 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 61226 & 667.892 & 91.6705 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 61187.5 & 650.625 & 94.0443 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 61169.6 & 635.525 & 96.2504 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 61150 & 615.639 & 99.3277 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 61154.8 & 597.529 & 102.346 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 61132.5 & 581.382 & 105.15 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 61107.9 & 559.229 & 109.272 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 61111.1 & 539.323 & 113.311 \tabularnewline
Median & 60500 &  &  \tabularnewline
Midrange & 61600 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 61285.7 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 61285.7 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 61285.7 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 61285.7 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 61285.7 &  &  \tabularnewline
Midmean - Closest Observation & 61285.7 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 61285.7 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 61285.7 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307513&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]61752.8[/C][C]1287.81[/C][C]47.9518[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]60269[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]58720.9[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]63173.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]61773.1[/C][C]1274.38[/C][C]48.4731[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]61813.9[/C][C]1266.41[/C][C]48.8103[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]61783.3[/C][C]1247.84[/C][C]49.5122[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]61864.8[/C][C]1218.49[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]61864.8[/C][C]1218.49[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]61803.7[/C][C]1164.02[/C][C]53.095[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]61732.4[/C][C]1151.14[/C][C]53.6273[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]61406.5[/C][C]1097.41[/C][C]55.9558[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]61314.8[/C][C]1083.83[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]61314.8[/C][C]1083.83[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]61426.9[/C][C]1066.38[/C][C]57.6034[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]61426.9[/C][C]1030.42[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]61426.9[/C][C]1030.42[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]61712[/C][C]950.586[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]61712[/C][C]950.586[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]61712[/C][C]950.586[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]61885.2[/C][C]928.456[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]61885.2[/C][C]928.456[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]61885.2[/C][C]877.79[/C][C]70.5011[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]61681.5[/C][C]850.322[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]61681.5[/C][C]850.322[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]61681.5[/C][C]850.322[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]61681.5[/C][C]850.322[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]61437[/C][C]758.021[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]61437[/C][C]758.021[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]61437[/C][C]694.287[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]61437[/C][C]694.287[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]61722.2[/C][C]661.941[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]61722.2[/C][C]661.941[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]61416.7[/C][C]625.198[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]61416.7[/C][C]625.198[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]61090.7[/C][C]587.542[/C][C]103.977[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]61426.9[/C][C]549.936[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]61426.9[/C][C]549.936[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]61070.4[/C][C]509.682[/C][C]119.821[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]61437[/C][C]469.771[/C][C]130.781[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]61755.7[/C][C]1240.59[/C][C]49.7792[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]61737.5[/C][C]1202.6[/C][C]51.3369[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]61697.1[/C][C]1164.53[/C][C]52.9801[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]61666[/C][C]1129.47[/C][C]54.5971[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]61611.2[/C][C]1099.71[/C][C]56.025[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]61554.2[/C][C]1065.93[/C][C]57.7468[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]61506.4[/C][C]1041.26[/C][C]59.0691[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]61468.5[/C][C]1016.11[/C][C]60.4941[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]61477.8[/C][C]998.417[/C][C]61.5753[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]61500[/C][C]980.69[/C][C]62.7109[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]61523.3[/C][C]960.336[/C][C]64.0643[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]61534.5[/C][C]939.946[/C][C]65.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]61546.3[/C][C]922.343[/C][C]66.7282[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]61558.8[/C][C]901.928[/C][C]68.2524[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]61543.6[/C][C]890.464[/C][C]69.1141[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]61527.6[/C][C]876.94[/C][C]70.1618[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]61510.8[/C][C]860.989[/C][C]71.4421[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]61477.8[/C][C]845.35[/C][C]72.7246[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]61442.9[/C][C]826.774[/C][C]74.3164[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]61405.9[/C][C]812.206[/C][C]75.6038[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]61383.3[/C][C]798.827[/C][C]76.8419[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]61359.4[/C][C]782.613[/C][C]78.4032[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]61333.9[/C][C]762.944[/C][C]80.3911[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]61306.7[/C][C]738.998[/C][C]82.9592[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]61296.6[/C][C]724.863[/C][C]84.563[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]61285.7[/C][C]707.302[/C][C]86.6472[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]61274.1[/C][C]695.841[/C][C]88.0576[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]61261.5[/C][C]681.213[/C][C]89.9301[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]61226[/C][C]667.892[/C][C]91.6705[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]61187.5[/C][C]650.625[/C][C]94.0443[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]61169.6[/C][C]635.525[/C][C]96.2504[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]61150[/C][C]615.639[/C][C]99.3277[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]61154.8[/C][C]597.529[/C][C]102.346[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]61132.5[/C][C]581.382[/C][C]105.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]61107.9[/C][C]559.229[/C][C]109.272[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]61111.1[/C][C]539.323[/C][C]113.311[/C][/ROW]
[ROW][C]Median[/C][C]60500[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]61600[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]61285.7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]61285.7[/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=307513&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307513&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 Mean61752.81287.8147.9518
Geometric Mean60269
Harmonic Mean58720.9
Quadratic Mean63173.3
Winsorized Mean ( 1 / 36 )61773.11274.3848.4731
Winsorized Mean ( 2 / 36 )61813.91266.4148.8103
Winsorized Mean ( 3 / 36 )61783.31247.8449.5122
Winsorized Mean ( 4 / 36 )61864.81218.4950.7716
Winsorized Mean ( 5 / 36 )61864.81218.4950.7716
Winsorized Mean ( 6 / 36 )61803.71164.0253.095
Winsorized Mean ( 7 / 36 )61732.41151.1453.6273
Winsorized Mean ( 8 / 36 )61406.51097.4155.9558
Winsorized Mean ( 9 / 36 )61314.81083.8356.5724
Winsorized Mean ( 10 / 36 )61314.81083.8356.5724
Winsorized Mean ( 11 / 36 )61426.91066.3857.6034
Winsorized Mean ( 12 / 36 )61426.91030.4259.6133
Winsorized Mean ( 13 / 36 )61426.91030.4259.6133
Winsorized Mean ( 14 / 36 )61712950.58664.92
Winsorized Mean ( 15 / 36 )61712950.58664.92
Winsorized Mean ( 16 / 36 )61712950.58664.92
Winsorized Mean ( 17 / 36 )61885.2928.45666.6539
Winsorized Mean ( 18 / 36 )61885.2928.45666.6539
Winsorized Mean ( 19 / 36 )61885.2877.7970.5011
Winsorized Mean ( 20 / 36 )61681.5850.32272.5389
Winsorized Mean ( 21 / 36 )61681.5850.32272.5389
Winsorized Mean ( 22 / 36 )61681.5850.32272.5389
Winsorized Mean ( 23 / 36 )61681.5850.32272.5389
Winsorized Mean ( 24 / 36 )61437758.02181.0492
Winsorized Mean ( 25 / 36 )61437758.02181.0492
Winsorized Mean ( 26 / 36 )61437694.28788.4894
Winsorized Mean ( 27 / 36 )61437694.28788.4894
Winsorized Mean ( 28 / 36 )61722.2661.94193.2443
Winsorized Mean ( 29 / 36 )61722.2661.94193.2443
Winsorized Mean ( 30 / 36 )61416.7625.19898.2355
Winsorized Mean ( 31 / 36 )61416.7625.19898.2355
Winsorized Mean ( 32 / 36 )61090.7587.542103.977
Winsorized Mean ( 33 / 36 )61426.9549.936111.698
Winsorized Mean ( 34 / 36 )61426.9549.936111.698
Winsorized Mean ( 35 / 36 )61070.4509.682119.821
Winsorized Mean ( 36 / 36 )61437469.771130.781
Trimmed Mean ( 1 / 36 )61755.71240.5949.7792
Trimmed Mean ( 2 / 36 )61737.51202.651.3369
Trimmed Mean ( 3 / 36 )61697.11164.5352.9801
Trimmed Mean ( 4 / 36 )616661129.4754.5971
Trimmed Mean ( 5 / 36 )61611.21099.7156.025
Trimmed Mean ( 6 / 36 )61554.21065.9357.7468
Trimmed Mean ( 7 / 36 )61506.41041.2659.0691
Trimmed Mean ( 8 / 36 )61468.51016.1160.4941
Trimmed Mean ( 9 / 36 )61477.8998.41761.5753
Trimmed Mean ( 10 / 36 )61500980.6962.7109
Trimmed Mean ( 11 / 36 )61523.3960.33664.0643
Trimmed Mean ( 12 / 36 )61534.5939.94665.466
Trimmed Mean ( 13 / 36 )61546.3922.34366.7282
Trimmed Mean ( 14 / 36 )61558.8901.92868.2524
Trimmed Mean ( 15 / 36 )61543.6890.46469.1141
Trimmed Mean ( 16 / 36 )61527.6876.9470.1618
Trimmed Mean ( 17 / 36 )61510.8860.98971.4421
Trimmed Mean ( 18 / 36 )61477.8845.3572.7246
Trimmed Mean ( 19 / 36 )61442.9826.77474.3164
Trimmed Mean ( 20 / 36 )61405.9812.20675.6038
Trimmed Mean ( 21 / 36 )61383.3798.82776.8419
Trimmed Mean ( 22 / 36 )61359.4782.61378.4032
Trimmed Mean ( 23 / 36 )61333.9762.94480.3911
Trimmed Mean ( 24 / 36 )61306.7738.99882.9592
Trimmed Mean ( 25 / 36 )61296.6724.86384.563
Trimmed Mean ( 26 / 36 )61285.7707.30286.6472
Trimmed Mean ( 27 / 36 )61274.1695.84188.0576
Trimmed Mean ( 28 / 36 )61261.5681.21389.9301
Trimmed Mean ( 29 / 36 )61226667.89291.6705
Trimmed Mean ( 30 / 36 )61187.5650.62594.0443
Trimmed Mean ( 31 / 36 )61169.6635.52596.2504
Trimmed Mean ( 32 / 36 )61150615.63999.3277
Trimmed Mean ( 33 / 36 )61154.8597.529102.346
Trimmed Mean ( 34 / 36 )61132.5581.382105.15
Trimmed Mean ( 35 / 36 )61107.9559.229109.272
Trimmed Mean ( 36 / 36 )61111.1539.323113.311
Median60500
Midrange61600
Midmean - Weighted Average at Xnp61285.7
Midmean - Weighted Average at X(n+1)p61285.7
Midmean - Empirical Distribution Function61285.7
Midmean - Empirical Distribution Function - Averaging61285.7
Midmean - Empirical Distribution Function - Interpolation61285.7
Midmean - Closest Observation61285.7
Midmean - True Basic - Statistics Graphics Toolkit61285.7
Midmean - MS Excel (old versions)61285.7
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')