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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 16:19:28 +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/t15028932474jva7m0bg5qfq5s.htm/, Retrieved Mon, 20 May 2024 01:53:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307407, Retrieved Mon, 20 May 2024 01:53:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [centrummaten - re...] [2017-08-16 14:19:28] [7f8e680169e3605c7c9c65666ad372ce] [Current]
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Dataseries X:
64800
62400
66000
52800
68400
67200
72000
74400
82800
72000
68400
85200
72000
54000
63600
48000
67200
55200
73200
66000
69600
78000
76800
91200
66000
55200
61200
44400
63600
49200
69600
66000
58800
84000
75600
86400
64800
60000
54000
44400
58800
52800
72000
69600
60000
80400
74400
96000
76800
46800
46800
46800
55200
55200
74400
68400
61200
76800
70800
102000
80400
46800
49200
40800
56400
64800
81600
80400
64800
75600
67200
96000
73200
58800
52800
39600
58800
70800
82800
78000
57600
82800
64800
99600
82800
60000
55200
37200
58800
56400
85200
85200
64800
84000
62400
97200
82800
61200
46800
32400
63600
61200
80400
92400
68400
76800
57600
99600




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=307407&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=307407&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307407&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 Mean67366.71404.8847.9518
Geometric Mean65748
Harmonic Mean64059.2
Quadratic Mean68916.3
Winsorized Mean ( 1 / 36 )67388.91390.2348.4731
Winsorized Mean ( 2 / 36 )67433.31381.5448.8103
Winsorized Mean ( 3 / 36 )674001361.2849.5122
Winsorized Mean ( 4 / 36 )67488.91329.2750.7716
Winsorized Mean ( 5 / 36 )67488.91329.2750.7716
Winsorized Mean ( 6 / 36 )67422.21269.8453.095
Winsorized Mean ( 7 / 36 )67344.41255.7953.6273
Winsorized Mean ( 8 / 36 )66988.91197.1855.9558
Winsorized Mean ( 9 / 36 )66888.91182.3656.5724
Winsorized Mean ( 10 / 36 )66888.91182.3656.5724
Winsorized Mean ( 11 / 36 )67011.11163.3257.6034
Winsorized Mean ( 12 / 36 )67011.11124.159.6133
Winsorized Mean ( 13 / 36 )67011.11124.159.6133
Winsorized Mean ( 14 / 36 )67322.2103764.92
Winsorized Mean ( 15 / 36 )67322.2103764.92
Winsorized Mean ( 16 / 36 )67322.2103764.92
Winsorized Mean ( 17 / 36 )67511.11012.8666.6539
Winsorized Mean ( 18 / 36 )67511.11012.8666.6539
Winsorized Mean ( 19 / 36 )67511.1957.58970.5011
Winsorized Mean ( 20 / 36 )67288.9927.62472.5389
Winsorized Mean ( 21 / 36 )67288.9927.62472.5389
Winsorized Mean ( 22 / 36 )67288.9927.62472.5389
Winsorized Mean ( 23 / 36 )67288.9927.62472.5389
Winsorized Mean ( 24 / 36 )67022.2826.93281.0492
Winsorized Mean ( 25 / 36 )67022.2826.93281.0492
Winsorized Mean ( 26 / 36 )67022.2757.40488.4894
Winsorized Mean ( 27 / 36 )67022.2757.40488.4894
Winsorized Mean ( 28 / 36 )67333.3722.11893.2443
Winsorized Mean ( 29 / 36 )67333.3722.11893.2443
Winsorized Mean ( 30 / 36 )67000682.03598.2355
Winsorized Mean ( 31 / 36 )67000682.03598.2355
Winsorized Mean ( 32 / 36 )66644.4640.954103.977
Winsorized Mean ( 33 / 36 )67011.1599.93111.698
Winsorized Mean ( 34 / 36 )67011.1599.93111.698
Winsorized Mean ( 35 / 36 )66622.2556.016119.821
Winsorized Mean ( 36 / 36 )67022.2512.477130.781
Trimmed Mean ( 1 / 36 )67369.81353.3749.7792
Trimmed Mean ( 2 / 36 )673501311.9251.3369
Trimmed Mean ( 3 / 36 )67305.91270.452.9801
Trimmed Mean ( 4 / 36 )672721232.1554.5971
Trimmed Mean ( 5 / 36 )67212.21199.6856.025
Trimmed Mean ( 6 / 36 )671501162.8357.7468
Trimmed Mean ( 7 / 36 )67097.91135.9259.0691
Trimmed Mean ( 8 / 36 )67056.51108.4860.4941
Trimmed Mean ( 9 / 36 )67066.71089.1861.5753
Trimmed Mean ( 10 / 36 )67090.91069.8462.7109
Trimmed Mean ( 11 / 36 )67116.31047.6464.0643
Trimmed Mean ( 12 / 36 )67128.61025.465.466
Trimmed Mean ( 13 / 36 )67141.51006.1966.7282
Trimmed Mean ( 14 / 36 )67155983.92168.2524
Trimmed Mean ( 15 / 36 )67138.5971.41569.1141
Trimmed Mean ( 16 / 36 )67121.1956.66170.1618
Trimmed Mean ( 17 / 36 )67102.7939.2671.4421
Trimmed Mean ( 18 / 36 )67066.7922.20172.7246
Trimmed Mean ( 19 / 36 )67028.6901.93574.3164
Trimmed Mean ( 20 / 36 )66988.2886.04375.6038
Trimmed Mean ( 21 / 36 )66963.6871.44776.8419
Trimmed Mean ( 22 / 36 )66937.5853.7678.4032
Trimmed Mean ( 23 / 36 )66909.7832.30280.3911
Trimmed Mean ( 24 / 36 )66880806.1882.9592
Trimmed Mean ( 25 / 36 )66869790.7684.563
Trimmed Mean ( 26 / 36 )66857.1771.60286.6472
Trimmed Mean ( 27 / 36 )66844.4759.09988.0576
Trimmed Mean ( 28 / 36 )66830.8743.14189.9301
Trimmed Mean ( 29 / 36 )66792728.6191.6705
Trimmed Mean ( 30 / 36 )66750709.77294.0443
Trimmed Mean ( 31 / 36 )66730.4693.396.2504
Trimmed Mean ( 32 / 36 )66709.1671.60699.3277
Trimmed Mean ( 33 / 36 )66714.3651.85102.346
Trimmed Mean ( 34 / 36 )66690634.235105.15
Trimmed Mean ( 35 / 36 )66663.2610.068109.272
Trimmed Mean ( 36 / 36 )66666.7588.353113.311
Median66000
Midrange67200
Midmean - Weighted Average at Xnp66857.1
Midmean - Weighted Average at X(n+1)p66857.1
Midmean - Empirical Distribution Function66857.1
Midmean - Empirical Distribution Function - Averaging66857.1
Midmean - Empirical Distribution Function - Interpolation66857.1
Midmean - Closest Observation66857.1
Midmean - True Basic - Statistics Graphics Toolkit66857.1
Midmean - MS Excel (old versions)66857.1
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 67366.7 & 1404.88 & 47.9518 \tabularnewline
Geometric Mean & 65748 &  &  \tabularnewline
Harmonic Mean & 64059.2 &  &  \tabularnewline
Quadratic Mean & 68916.3 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 67388.9 & 1390.23 & 48.4731 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 67433.3 & 1381.54 & 48.8103 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 67400 & 1361.28 & 49.5122 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 67488.9 & 1329.27 & 50.7716 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 67488.9 & 1329.27 & 50.7716 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 67422.2 & 1269.84 & 53.095 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 67344.4 & 1255.79 & 53.6273 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 66988.9 & 1197.18 & 55.9558 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 66888.9 & 1182.36 & 56.5724 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 66888.9 & 1182.36 & 56.5724 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 67011.1 & 1163.32 & 57.6034 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 67011.1 & 1124.1 & 59.6133 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 67011.1 & 1124.1 & 59.6133 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 67322.2 & 1037 & 64.92 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 67322.2 & 1037 & 64.92 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 67322.2 & 1037 & 64.92 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 67511.1 & 1012.86 & 66.6539 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 67511.1 & 1012.86 & 66.6539 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 67511.1 & 957.589 & 70.5011 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 67288.9 & 927.624 & 72.5389 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 67288.9 & 927.624 & 72.5389 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 67288.9 & 927.624 & 72.5389 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 67288.9 & 927.624 & 72.5389 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 67022.2 & 826.932 & 81.0492 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 67022.2 & 826.932 & 81.0492 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 67022.2 & 757.404 & 88.4894 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 67022.2 & 757.404 & 88.4894 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 67333.3 & 722.118 & 93.2443 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 67333.3 & 722.118 & 93.2443 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 67000 & 682.035 & 98.2355 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 67000 & 682.035 & 98.2355 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 66644.4 & 640.954 & 103.977 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 67011.1 & 599.93 & 111.698 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 67011.1 & 599.93 & 111.698 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 66622.2 & 556.016 & 119.821 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 67022.2 & 512.477 & 130.781 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 67369.8 & 1353.37 & 49.7792 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 67350 & 1311.92 & 51.3369 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 67305.9 & 1270.4 & 52.9801 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 67272 & 1232.15 & 54.5971 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 67212.2 & 1199.68 & 56.025 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 67150 & 1162.83 & 57.7468 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 67097.9 & 1135.92 & 59.0691 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 67056.5 & 1108.48 & 60.4941 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 67066.7 & 1089.18 & 61.5753 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 67090.9 & 1069.84 & 62.7109 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 67116.3 & 1047.64 & 64.0643 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 67128.6 & 1025.4 & 65.466 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 67141.5 & 1006.19 & 66.7282 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 67155 & 983.921 & 68.2524 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 67138.5 & 971.415 & 69.1141 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 67121.1 & 956.661 & 70.1618 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 67102.7 & 939.26 & 71.4421 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 67066.7 & 922.201 & 72.7246 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 67028.6 & 901.935 & 74.3164 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 66988.2 & 886.043 & 75.6038 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 66963.6 & 871.447 & 76.8419 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 66937.5 & 853.76 & 78.4032 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 66909.7 & 832.302 & 80.3911 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 66880 & 806.18 & 82.9592 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 66869 & 790.76 & 84.563 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 66857.1 & 771.602 & 86.6472 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 66844.4 & 759.099 & 88.0576 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 66830.8 & 743.141 & 89.9301 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 66792 & 728.61 & 91.6705 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 66750 & 709.772 & 94.0443 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 66730.4 & 693.3 & 96.2504 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 66709.1 & 671.606 & 99.3277 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 66714.3 & 651.85 & 102.346 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 66690 & 634.235 & 105.15 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 66663.2 & 610.068 & 109.272 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 66666.7 & 588.353 & 113.311 \tabularnewline
Median & 66000 &  &  \tabularnewline
Midrange & 67200 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 66857.1 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 66857.1 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 66857.1 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 66857.1 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 66857.1 &  &  \tabularnewline
Midmean - Closest Observation & 66857.1 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 66857.1 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 66857.1 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307407&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]67366.7[/C][C]1404.88[/C][C]47.9518[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]65748[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]64059.2[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]68916.3[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]67388.9[/C][C]1390.23[/C][C]48.4731[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]67433.3[/C][C]1381.54[/C][C]48.8103[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]67400[/C][C]1361.28[/C][C]49.5122[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]67488.9[/C][C]1329.27[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]67488.9[/C][C]1329.27[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]67422.2[/C][C]1269.84[/C][C]53.095[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]67344.4[/C][C]1255.79[/C][C]53.6273[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]66988.9[/C][C]1197.18[/C][C]55.9558[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]66888.9[/C][C]1182.36[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]66888.9[/C][C]1182.36[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]67011.1[/C][C]1163.32[/C][C]57.6034[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]67011.1[/C][C]1124.1[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]67011.1[/C][C]1124.1[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]67322.2[/C][C]1037[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]67322.2[/C][C]1037[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]67322.2[/C][C]1037[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]67511.1[/C][C]1012.86[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]67511.1[/C][C]1012.86[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]67511.1[/C][C]957.589[/C][C]70.5011[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]67288.9[/C][C]927.624[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]67288.9[/C][C]927.624[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]67288.9[/C][C]927.624[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]67288.9[/C][C]927.624[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]67022.2[/C][C]826.932[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]67022.2[/C][C]826.932[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]67022.2[/C][C]757.404[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]67022.2[/C][C]757.404[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]67333.3[/C][C]722.118[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]67333.3[/C][C]722.118[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]67000[/C][C]682.035[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]67000[/C][C]682.035[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]66644.4[/C][C]640.954[/C][C]103.977[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]67011.1[/C][C]599.93[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]67011.1[/C][C]599.93[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]66622.2[/C][C]556.016[/C][C]119.821[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]67022.2[/C][C]512.477[/C][C]130.781[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]67369.8[/C][C]1353.37[/C][C]49.7792[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]67350[/C][C]1311.92[/C][C]51.3369[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]67305.9[/C][C]1270.4[/C][C]52.9801[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]67272[/C][C]1232.15[/C][C]54.5971[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]67212.2[/C][C]1199.68[/C][C]56.025[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]67150[/C][C]1162.83[/C][C]57.7468[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]67097.9[/C][C]1135.92[/C][C]59.0691[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]67056.5[/C][C]1108.48[/C][C]60.4941[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]67066.7[/C][C]1089.18[/C][C]61.5753[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]67090.9[/C][C]1069.84[/C][C]62.7109[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]67116.3[/C][C]1047.64[/C][C]64.0643[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]67128.6[/C][C]1025.4[/C][C]65.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]67141.5[/C][C]1006.19[/C][C]66.7282[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]67155[/C][C]983.921[/C][C]68.2524[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]67138.5[/C][C]971.415[/C][C]69.1141[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]67121.1[/C][C]956.661[/C][C]70.1618[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]67102.7[/C][C]939.26[/C][C]71.4421[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]67066.7[/C][C]922.201[/C][C]72.7246[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]67028.6[/C][C]901.935[/C][C]74.3164[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]66988.2[/C][C]886.043[/C][C]75.6038[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]66963.6[/C][C]871.447[/C][C]76.8419[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]66937.5[/C][C]853.76[/C][C]78.4032[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]66909.7[/C][C]832.302[/C][C]80.3911[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]66880[/C][C]806.18[/C][C]82.9592[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]66869[/C][C]790.76[/C][C]84.563[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]66857.1[/C][C]771.602[/C][C]86.6472[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]66844.4[/C][C]759.099[/C][C]88.0576[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]66830.8[/C][C]743.141[/C][C]89.9301[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]66792[/C][C]728.61[/C][C]91.6705[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]66750[/C][C]709.772[/C][C]94.0443[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]66730.4[/C][C]693.3[/C][C]96.2504[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]66709.1[/C][C]671.606[/C][C]99.3277[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]66714.3[/C][C]651.85[/C][C]102.346[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]66690[/C][C]634.235[/C][C]105.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]66663.2[/C][C]610.068[/C][C]109.272[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]66666.7[/C][C]588.353[/C][C]113.311[/C][/ROW]
[ROW][C]Median[/C][C]66000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]67200[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]66857.1[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]66857.1[/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=307407&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307407&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 Mean67366.71404.8847.9518
Geometric Mean65748
Harmonic Mean64059.2
Quadratic Mean68916.3
Winsorized Mean ( 1 / 36 )67388.91390.2348.4731
Winsorized Mean ( 2 / 36 )67433.31381.5448.8103
Winsorized Mean ( 3 / 36 )674001361.2849.5122
Winsorized Mean ( 4 / 36 )67488.91329.2750.7716
Winsorized Mean ( 5 / 36 )67488.91329.2750.7716
Winsorized Mean ( 6 / 36 )67422.21269.8453.095
Winsorized Mean ( 7 / 36 )67344.41255.7953.6273
Winsorized Mean ( 8 / 36 )66988.91197.1855.9558
Winsorized Mean ( 9 / 36 )66888.91182.3656.5724
Winsorized Mean ( 10 / 36 )66888.91182.3656.5724
Winsorized Mean ( 11 / 36 )67011.11163.3257.6034
Winsorized Mean ( 12 / 36 )67011.11124.159.6133
Winsorized Mean ( 13 / 36 )67011.11124.159.6133
Winsorized Mean ( 14 / 36 )67322.2103764.92
Winsorized Mean ( 15 / 36 )67322.2103764.92
Winsorized Mean ( 16 / 36 )67322.2103764.92
Winsorized Mean ( 17 / 36 )67511.11012.8666.6539
Winsorized Mean ( 18 / 36 )67511.11012.8666.6539
Winsorized Mean ( 19 / 36 )67511.1957.58970.5011
Winsorized Mean ( 20 / 36 )67288.9927.62472.5389
Winsorized Mean ( 21 / 36 )67288.9927.62472.5389
Winsorized Mean ( 22 / 36 )67288.9927.62472.5389
Winsorized Mean ( 23 / 36 )67288.9927.62472.5389
Winsorized Mean ( 24 / 36 )67022.2826.93281.0492
Winsorized Mean ( 25 / 36 )67022.2826.93281.0492
Winsorized Mean ( 26 / 36 )67022.2757.40488.4894
Winsorized Mean ( 27 / 36 )67022.2757.40488.4894
Winsorized Mean ( 28 / 36 )67333.3722.11893.2443
Winsorized Mean ( 29 / 36 )67333.3722.11893.2443
Winsorized Mean ( 30 / 36 )67000682.03598.2355
Winsorized Mean ( 31 / 36 )67000682.03598.2355
Winsorized Mean ( 32 / 36 )66644.4640.954103.977
Winsorized Mean ( 33 / 36 )67011.1599.93111.698
Winsorized Mean ( 34 / 36 )67011.1599.93111.698
Winsorized Mean ( 35 / 36 )66622.2556.016119.821
Winsorized Mean ( 36 / 36 )67022.2512.477130.781
Trimmed Mean ( 1 / 36 )67369.81353.3749.7792
Trimmed Mean ( 2 / 36 )673501311.9251.3369
Trimmed Mean ( 3 / 36 )67305.91270.452.9801
Trimmed Mean ( 4 / 36 )672721232.1554.5971
Trimmed Mean ( 5 / 36 )67212.21199.6856.025
Trimmed Mean ( 6 / 36 )671501162.8357.7468
Trimmed Mean ( 7 / 36 )67097.91135.9259.0691
Trimmed Mean ( 8 / 36 )67056.51108.4860.4941
Trimmed Mean ( 9 / 36 )67066.71089.1861.5753
Trimmed Mean ( 10 / 36 )67090.91069.8462.7109
Trimmed Mean ( 11 / 36 )67116.31047.6464.0643
Trimmed Mean ( 12 / 36 )67128.61025.465.466
Trimmed Mean ( 13 / 36 )67141.51006.1966.7282
Trimmed Mean ( 14 / 36 )67155983.92168.2524
Trimmed Mean ( 15 / 36 )67138.5971.41569.1141
Trimmed Mean ( 16 / 36 )67121.1956.66170.1618
Trimmed Mean ( 17 / 36 )67102.7939.2671.4421
Trimmed Mean ( 18 / 36 )67066.7922.20172.7246
Trimmed Mean ( 19 / 36 )67028.6901.93574.3164
Trimmed Mean ( 20 / 36 )66988.2886.04375.6038
Trimmed Mean ( 21 / 36 )66963.6871.44776.8419
Trimmed Mean ( 22 / 36 )66937.5853.7678.4032
Trimmed Mean ( 23 / 36 )66909.7832.30280.3911
Trimmed Mean ( 24 / 36 )66880806.1882.9592
Trimmed Mean ( 25 / 36 )66869790.7684.563
Trimmed Mean ( 26 / 36 )66857.1771.60286.6472
Trimmed Mean ( 27 / 36 )66844.4759.09988.0576
Trimmed Mean ( 28 / 36 )66830.8743.14189.9301
Trimmed Mean ( 29 / 36 )66792728.6191.6705
Trimmed Mean ( 30 / 36 )66750709.77294.0443
Trimmed Mean ( 31 / 36 )66730.4693.396.2504
Trimmed Mean ( 32 / 36 )66709.1671.60699.3277
Trimmed Mean ( 33 / 36 )66714.3651.85102.346
Trimmed Mean ( 34 / 36 )66690634.235105.15
Trimmed Mean ( 35 / 36 )66663.2610.068109.272
Trimmed Mean ( 36 / 36 )66666.7588.353113.311
Median66000
Midrange67200
Midmean - Weighted Average at Xnp66857.1
Midmean - Weighted Average at X(n+1)p66857.1
Midmean - Empirical Distribution Function66857.1
Midmean - Empirical Distribution Function - Averaging66857.1
Midmean - Empirical Distribution Function - Interpolation66857.1
Midmean - Closest Observation66857.1
Midmean - True Basic - Statistics Graphics Toolkit66857.1
Midmean - MS Excel (old versions)66857.1
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')