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Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 14 Aug 2017 21:50:30 +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/14/t1502740271hklhfog0afcirzy.htm/, Retrieved Mon, 13 May 2024 17:06:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307256, Retrieved Mon, 13 May 2024 17:06:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-14 19:50:30] [b5765487180b26865894987d1ded8bd3] [Current]
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Dataseries X:
64 800
62 400
66 000
52 800
68 400
67 200
72 000
74 400
82 800
72 000
68 400
85 200
72 000
54 000
63 600
48 000
67 200
55 200
73 200
66 000
69 600
78 000
76 800
91 200
66 000
55 200
61 200
44 400
63 600
49 200
69 600
66 000
58 800
84 000
75 600
86 400
64 800
60 000
54 000
44 400
58 800
52 800
72 000
69 600
60 000
80 400
74 400
96 000
76 800
46 800
46 800
46 800
55 200
55 200
74 400
68 400
61 200
76 800
70 800
102 000
80 400
46 800
49 200
40 800
56 400
64 800
81 600
80 400
64 800
75 600
67 200
96 000
73 200
58 800
52 800
39 600
58 800
70 800
82 800
78 000
57 600
82 800
64 800
99 600
82 800
60 000
55 200
37 200
58 800
56 400
85 200
85 200
64 800
84 000
62 400
97 200
82 800
61 200
46 800
32 400
63 600
61 200
80 400
92 400
68 400
76 800
57 600
99 600




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=307256&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=307256&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307256&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=307256&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=307256&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307256&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')