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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 computationTue, 15 Aug 2017 19:18:40 +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/15/t1502817847fjxlyns1f4avpv4.htm/, Retrieved Sun, 19 May 2024 22:26:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307300, Retrieved Sun, 19 May 2024 22:26:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-08-15 17:18:40] [f8975010d6e80ebfdd11eb899305ce74] [Current]
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Dataseries X:
1474200
1419600
1501500
1201200
1556100
1528800
1638000
1692600
1883700
1638000
1556100
1938300
1638000
1228500
1446900
1092000
1528800
1255800
1665300
1501500
1583400
1774500
1747200
2074800
1501500
1255800
1392300
1010100
1446900
1119300
1583400
1501500
1337700
1911000
1719900
1965600
1474200
1365000
1228500
1010100
1337700
1201200
1638000
1583400
1365000
1829100
1692600
2184000
1747200
1064700
1064700
1064700
1255800
1255800
1692600
1556100
1392300
1747200
1610700
2320500
1829100
1064700
1119300
928200
1283100
1474200
1856400
1829100
1474200
1719900
1528800
2184000
1665300
1337700
1201200
900900
1337700
1610700
1883700
1774500
1310400
1883700
1474200
2265900
1883700
1365000
1255800
846300
1337700
1283100
1938300
1938300
1474200
1911000
1419600
2211300
1883700
1392300
1064700
737100
1446900
1392300
1829100
2102100
1556100
1747200
1310400
2265900




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=307300&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=307300&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307300&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 Mean153259031961.147.9518
Geometric Mean1495770
Harmonic Mean1457350
Quadratic Mean1567850
Winsorized Mean ( 1 / 36 )153310031627.848.4731
Winsorized Mean ( 2 / 36 )15341103143048.8103
Winsorized Mean ( 3 / 36 )153335030969.149.5122
Winsorized Mean ( 4 / 36 )153537030240.850.7716
Winsorized Mean ( 5 / 36 )153537030240.850.7716
Winsorized Mean ( 6 / 36 )153386028888.953.095
Winsorized Mean ( 7 / 36 )153209028569.253.6273
Winsorized Mean ( 8 / 36 )152400027235.755.9558
Winsorized Mean ( 9 / 36 )152172026898.756.5724
Winsorized Mean ( 10 / 36 )152172026898.756.5724
Winsorized Mean ( 11 / 36 )152450026465.557.6034
Winsorized Mean ( 12 / 36 )152450025573.259.6133
Winsorized Mean ( 13 / 36 )152450025573.259.6133
Winsorized Mean ( 14 / 36 )153158023591.864.92
Winsorized Mean ( 15 / 36 )153158023591.864.92
Winsorized Mean ( 16 / 36 )153158023591.864.92
Winsorized Mean ( 17 / 36 )153588023042.666.6539
Winsorized Mean ( 18 / 36 )153588023042.666.6539
Winsorized Mean ( 19 / 36 )153588021785.270.5011
Winsorized Mean ( 20 / 36 )153082021103.572.5389
Winsorized Mean ( 21 / 36 )153082021103.572.5389
Winsorized Mean ( 22 / 36 )153082021103.572.5389
Winsorized Mean ( 23 / 36 )153082021103.572.5389
Winsorized Mean ( 24 / 36 )152476018812.781.0492
Winsorized Mean ( 25 / 36 )152476018812.781.0492
Winsorized Mean ( 26 / 36 )152476017230.988.4894
Winsorized Mean ( 27 / 36 )152476017230.988.4894
Winsorized Mean ( 28 / 36 )153183016428.293.2443
Winsorized Mean ( 29 / 36 )153183016428.293.2443
Winsorized Mean ( 30 / 36 )152425015516.398.2355
Winsorized Mean ( 31 / 36 )152425015516.398.2355
Winsorized Mean ( 32 / 36 )151616014581.7103.977
Winsorized Mean ( 33 / 36 )152450013648.4111.698
Winsorized Mean ( 34 / 36 )152450013648.4111.698
Winsorized Mean ( 35 / 36 )151566012649.4119.821
Winsorized Mean ( 36 / 36 )152476011658.9130.781
Trimmed Mean ( 1 / 36 )153266030789.249.7792
Trimmed Mean ( 2 / 36 )153221029846.251.3369
Trimmed Mean ( 3 / 36 )153121028901.652.9801
Trimmed Mean ( 4 / 36 )153044028031.554.5971
Trimmed Mean ( 5 / 36 )152908027292.856.025
Trimmed Mean ( 6 / 36 )152766026454.557.7468
Trimmed Mean ( 7 / 36 )152648025842.259.0691
Trimmed Mean ( 8 / 36 )152554025217.960.4941
Trimmed Mean ( 9 / 36 )152577024778.961.5753
Trimmed Mean ( 10 / 36 )152632024338.962.7109
Trimmed Mean ( 11 / 36 )152690023833.864.0643
Trimmed Mean ( 12 / 36 )152718023327.765.466
Trimmed Mean ( 13 / 36 )152747022890.966.7282
Trimmed Mean ( 14 / 36 )152778022384.268.2524
Trimmed Mean ( 15 / 36 )152740022099.769.1141
Trimmed Mean ( 16 / 36 )15270002176470.1618
Trimmed Mean ( 17 / 36 )152659021368.271.4421
Trimmed Mean ( 18 / 36 )152577020980.172.7246
Trimmed Mean ( 19 / 36 )15249002051974.3164
Trimmed Mean ( 20 / 36 )152398020157.575.6038
Trimmed Mean ( 21 / 36 )152342019825.476.8419
Trimmed Mean ( 22 / 36 )15228301942378.4032
Trimmed Mean ( 23 / 36 )152220018934.980.3911
Trimmed Mean ( 24 / 36 )152152018340.682.9592
Trimmed Mean ( 25 / 36 )152127017989.884.563
Trimmed Mean ( 26 / 36 )152100017553.986.6472
Trimmed Mean ( 27 / 36 )152071017269.588.0576
Trimmed Mean ( 28 / 36 )152040016906.589.9301
Trimmed Mean ( 29 / 36 )151952016575.991.6705
Trimmed Mean ( 30 / 36 )151856016147.394.0443
Trimmed Mean ( 31 / 36 )151812015772.696.2504
Trimmed Mean ( 32 / 36 )15176301527999.3277
Trimmed Mean ( 33 / 36 )151775014829.6102.346
Trimmed Mean ( 34 / 36 )151720014428.8105.15
Trimmed Mean ( 35 / 36 )151659013879109.272
Trimmed Mean ( 36 / 36 )151667013385113.311
Median1501500
Midrange1528800
Midmean - Weighted Average at Xnp1521000
Midmean - Weighted Average at X(n+1)p1521000
Midmean - Empirical Distribution Function1521000
Midmean - Empirical Distribution Function - Averaging1521000
Midmean - Empirical Distribution Function - Interpolation1521000
Midmean - Closest Observation1521000
Midmean - True Basic - Statistics Graphics Toolkit1521000
Midmean - MS Excel (old versions)1521000
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1532590 & 31961.1 & 47.9518 \tabularnewline
Geometric Mean & 1495770 &  &  \tabularnewline
Harmonic Mean & 1457350 &  &  \tabularnewline
Quadratic Mean & 1567850 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 1533100 & 31627.8 & 48.4731 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 1534110 & 31430 & 48.8103 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 1533350 & 30969.1 & 49.5122 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 1535370 & 30240.8 & 50.7716 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 1535370 & 30240.8 & 50.7716 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 1533860 & 28888.9 & 53.095 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 1532090 & 28569.2 & 53.6273 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 1524000 & 27235.7 & 55.9558 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 1521720 & 26898.7 & 56.5724 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 1521720 & 26898.7 & 56.5724 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 1524500 & 26465.5 & 57.6034 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 1524500 & 25573.2 & 59.6133 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 1524500 & 25573.2 & 59.6133 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 1531580 & 23591.8 & 64.92 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 1531580 & 23591.8 & 64.92 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 1531580 & 23591.8 & 64.92 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 1535880 & 23042.6 & 66.6539 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 1535880 & 23042.6 & 66.6539 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 1535880 & 21785.2 & 70.5011 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 1530820 & 21103.5 & 72.5389 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 1530820 & 21103.5 & 72.5389 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 1530820 & 21103.5 & 72.5389 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 1530820 & 21103.5 & 72.5389 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 1524760 & 18812.7 & 81.0492 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 1524760 & 18812.7 & 81.0492 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 1524760 & 17230.9 & 88.4894 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 1524760 & 17230.9 & 88.4894 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 1531830 & 16428.2 & 93.2443 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 1531830 & 16428.2 & 93.2443 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 1524250 & 15516.3 & 98.2355 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 1524250 & 15516.3 & 98.2355 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 1516160 & 14581.7 & 103.977 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 1524500 & 13648.4 & 111.698 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 1524500 & 13648.4 & 111.698 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 1515660 & 12649.4 & 119.821 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 1524760 & 11658.9 & 130.781 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 1532660 & 30789.2 & 49.7792 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 1532210 & 29846.2 & 51.3369 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 1531210 & 28901.6 & 52.9801 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 1530440 & 28031.5 & 54.5971 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 1529080 & 27292.8 & 56.025 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 1527660 & 26454.5 & 57.7468 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 1526480 & 25842.2 & 59.0691 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 1525540 & 25217.9 & 60.4941 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 1525770 & 24778.9 & 61.5753 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 1526320 & 24338.9 & 62.7109 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 1526900 & 23833.8 & 64.0643 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 1527180 & 23327.7 & 65.466 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 1527470 & 22890.9 & 66.7282 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 1527780 & 22384.2 & 68.2524 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 1527400 & 22099.7 & 69.1141 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 1527000 & 21764 & 70.1618 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 1526590 & 21368.2 & 71.4421 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 1525770 & 20980.1 & 72.7246 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 1524900 & 20519 & 74.3164 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 1523980 & 20157.5 & 75.6038 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 1523420 & 19825.4 & 76.8419 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 1522830 & 19423 & 78.4032 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 1522200 & 18934.9 & 80.3911 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 1521520 & 18340.6 & 82.9592 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 1521270 & 17989.8 & 84.563 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 1521000 & 17553.9 & 86.6472 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 1520710 & 17269.5 & 88.0576 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 1520400 & 16906.5 & 89.9301 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 1519520 & 16575.9 & 91.6705 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 1518560 & 16147.3 & 94.0443 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 1518120 & 15772.6 & 96.2504 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 1517630 & 15279 & 99.3277 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 1517750 & 14829.6 & 102.346 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 1517200 & 14428.8 & 105.15 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 1516590 & 13879 & 109.272 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 1516670 & 13385 & 113.311 \tabularnewline
Median & 1501500 &  &  \tabularnewline
Midrange & 1528800 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 1521000 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 1521000 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 1521000 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 1521000 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 1521000 &  &  \tabularnewline
Midmean - Closest Observation & 1521000 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 1521000 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 1521000 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307300&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]1532590[/C][C]31961.1[/C][C]47.9518[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]1495770[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]1457350[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]1567850[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]1533100[/C][C]31627.8[/C][C]48.4731[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]1534110[/C][C]31430[/C][C]48.8103[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]1533350[/C][C]30969.1[/C][C]49.5122[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]1535370[/C][C]30240.8[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]1535370[/C][C]30240.8[/C][C]50.7716[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]1533860[/C][C]28888.9[/C][C]53.095[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]1532090[/C][C]28569.2[/C][C]53.6273[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]1524000[/C][C]27235.7[/C][C]55.9558[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]1521720[/C][C]26898.7[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]1521720[/C][C]26898.7[/C][C]56.5724[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]1524500[/C][C]26465.5[/C][C]57.6034[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]1524500[/C][C]25573.2[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]1524500[/C][C]25573.2[/C][C]59.6133[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]1531580[/C][C]23591.8[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]1531580[/C][C]23591.8[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]1531580[/C][C]23591.8[/C][C]64.92[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]1535880[/C][C]23042.6[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]1535880[/C][C]23042.6[/C][C]66.6539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]1535880[/C][C]21785.2[/C][C]70.5011[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]1530820[/C][C]21103.5[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]1530820[/C][C]21103.5[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]1530820[/C][C]21103.5[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]1530820[/C][C]21103.5[/C][C]72.5389[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]1524760[/C][C]18812.7[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]1524760[/C][C]18812.7[/C][C]81.0492[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]1524760[/C][C]17230.9[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]1524760[/C][C]17230.9[/C][C]88.4894[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]1531830[/C][C]16428.2[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]1531830[/C][C]16428.2[/C][C]93.2443[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]1524250[/C][C]15516.3[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]1524250[/C][C]15516.3[/C][C]98.2355[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]1516160[/C][C]14581.7[/C][C]103.977[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]1524500[/C][C]13648.4[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]1524500[/C][C]13648.4[/C][C]111.698[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]1515660[/C][C]12649.4[/C][C]119.821[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]1524760[/C][C]11658.9[/C][C]130.781[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]1532660[/C][C]30789.2[/C][C]49.7792[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]1532210[/C][C]29846.2[/C][C]51.3369[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]1531210[/C][C]28901.6[/C][C]52.9801[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]1530440[/C][C]28031.5[/C][C]54.5971[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]1529080[/C][C]27292.8[/C][C]56.025[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]1527660[/C][C]26454.5[/C][C]57.7468[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]1526480[/C][C]25842.2[/C][C]59.0691[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]1525540[/C][C]25217.9[/C][C]60.4941[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]1525770[/C][C]24778.9[/C][C]61.5753[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]1526320[/C][C]24338.9[/C][C]62.7109[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]1526900[/C][C]23833.8[/C][C]64.0643[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]1527180[/C][C]23327.7[/C][C]65.466[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]1527470[/C][C]22890.9[/C][C]66.7282[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]1527780[/C][C]22384.2[/C][C]68.2524[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]1527400[/C][C]22099.7[/C][C]69.1141[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]1527000[/C][C]21764[/C][C]70.1618[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]1526590[/C][C]21368.2[/C][C]71.4421[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]1525770[/C][C]20980.1[/C][C]72.7246[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]1524900[/C][C]20519[/C][C]74.3164[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]1523980[/C][C]20157.5[/C][C]75.6038[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]1523420[/C][C]19825.4[/C][C]76.8419[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]1522830[/C][C]19423[/C][C]78.4032[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]1522200[/C][C]18934.9[/C][C]80.3911[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]1521520[/C][C]18340.6[/C][C]82.9592[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]1521270[/C][C]17989.8[/C][C]84.563[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]1521000[/C][C]17553.9[/C][C]86.6472[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]1520710[/C][C]17269.5[/C][C]88.0576[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]1520400[/C][C]16906.5[/C][C]89.9301[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]1519520[/C][C]16575.9[/C][C]91.6705[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]1518560[/C][C]16147.3[/C][C]94.0443[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]1518120[/C][C]15772.6[/C][C]96.2504[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]1517630[/C][C]15279[/C][C]99.3277[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]1517750[/C][C]14829.6[/C][C]102.346[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]1517200[/C][C]14428.8[/C][C]105.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]1516590[/C][C]13879[/C][C]109.272[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]1516670[/C][C]13385[/C][C]113.311[/C][/ROW]
[ROW][C]Median[/C][C]1501500[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]1528800[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]1521000[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]1521000[/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=307300&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307300&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 Mean153259031961.147.9518
Geometric Mean1495770
Harmonic Mean1457350
Quadratic Mean1567850
Winsorized Mean ( 1 / 36 )153310031627.848.4731
Winsorized Mean ( 2 / 36 )15341103143048.8103
Winsorized Mean ( 3 / 36 )153335030969.149.5122
Winsorized Mean ( 4 / 36 )153537030240.850.7716
Winsorized Mean ( 5 / 36 )153537030240.850.7716
Winsorized Mean ( 6 / 36 )153386028888.953.095
Winsorized Mean ( 7 / 36 )153209028569.253.6273
Winsorized Mean ( 8 / 36 )152400027235.755.9558
Winsorized Mean ( 9 / 36 )152172026898.756.5724
Winsorized Mean ( 10 / 36 )152172026898.756.5724
Winsorized Mean ( 11 / 36 )152450026465.557.6034
Winsorized Mean ( 12 / 36 )152450025573.259.6133
Winsorized Mean ( 13 / 36 )152450025573.259.6133
Winsorized Mean ( 14 / 36 )153158023591.864.92
Winsorized Mean ( 15 / 36 )153158023591.864.92
Winsorized Mean ( 16 / 36 )153158023591.864.92
Winsorized Mean ( 17 / 36 )153588023042.666.6539
Winsorized Mean ( 18 / 36 )153588023042.666.6539
Winsorized Mean ( 19 / 36 )153588021785.270.5011
Winsorized Mean ( 20 / 36 )153082021103.572.5389
Winsorized Mean ( 21 / 36 )153082021103.572.5389
Winsorized Mean ( 22 / 36 )153082021103.572.5389
Winsorized Mean ( 23 / 36 )153082021103.572.5389
Winsorized Mean ( 24 / 36 )152476018812.781.0492
Winsorized Mean ( 25 / 36 )152476018812.781.0492
Winsorized Mean ( 26 / 36 )152476017230.988.4894
Winsorized Mean ( 27 / 36 )152476017230.988.4894
Winsorized Mean ( 28 / 36 )153183016428.293.2443
Winsorized Mean ( 29 / 36 )153183016428.293.2443
Winsorized Mean ( 30 / 36 )152425015516.398.2355
Winsorized Mean ( 31 / 36 )152425015516.398.2355
Winsorized Mean ( 32 / 36 )151616014581.7103.977
Winsorized Mean ( 33 / 36 )152450013648.4111.698
Winsorized Mean ( 34 / 36 )152450013648.4111.698
Winsorized Mean ( 35 / 36 )151566012649.4119.821
Winsorized Mean ( 36 / 36 )152476011658.9130.781
Trimmed Mean ( 1 / 36 )153266030789.249.7792
Trimmed Mean ( 2 / 36 )153221029846.251.3369
Trimmed Mean ( 3 / 36 )153121028901.652.9801
Trimmed Mean ( 4 / 36 )153044028031.554.5971
Trimmed Mean ( 5 / 36 )152908027292.856.025
Trimmed Mean ( 6 / 36 )152766026454.557.7468
Trimmed Mean ( 7 / 36 )152648025842.259.0691
Trimmed Mean ( 8 / 36 )152554025217.960.4941
Trimmed Mean ( 9 / 36 )152577024778.961.5753
Trimmed Mean ( 10 / 36 )152632024338.962.7109
Trimmed Mean ( 11 / 36 )152690023833.864.0643
Trimmed Mean ( 12 / 36 )152718023327.765.466
Trimmed Mean ( 13 / 36 )152747022890.966.7282
Trimmed Mean ( 14 / 36 )152778022384.268.2524
Trimmed Mean ( 15 / 36 )152740022099.769.1141
Trimmed Mean ( 16 / 36 )15270002176470.1618
Trimmed Mean ( 17 / 36 )152659021368.271.4421
Trimmed Mean ( 18 / 36 )152577020980.172.7246
Trimmed Mean ( 19 / 36 )15249002051974.3164
Trimmed Mean ( 20 / 36 )152398020157.575.6038
Trimmed Mean ( 21 / 36 )152342019825.476.8419
Trimmed Mean ( 22 / 36 )15228301942378.4032
Trimmed Mean ( 23 / 36 )152220018934.980.3911
Trimmed Mean ( 24 / 36 )152152018340.682.9592
Trimmed Mean ( 25 / 36 )152127017989.884.563
Trimmed Mean ( 26 / 36 )152100017553.986.6472
Trimmed Mean ( 27 / 36 )152071017269.588.0576
Trimmed Mean ( 28 / 36 )152040016906.589.9301
Trimmed Mean ( 29 / 36 )151952016575.991.6705
Trimmed Mean ( 30 / 36 )151856016147.394.0443
Trimmed Mean ( 31 / 36 )151812015772.696.2504
Trimmed Mean ( 32 / 36 )15176301527999.3277
Trimmed Mean ( 33 / 36 )151775014829.6102.346
Trimmed Mean ( 34 / 36 )151720014428.8105.15
Trimmed Mean ( 35 / 36 )151659013879109.272
Trimmed Mean ( 36 / 36 )151667013385113.311
Median1501500
Midrange1528800
Midmean - Weighted Average at Xnp1521000
Midmean - Weighted Average at X(n+1)p1521000
Midmean - Empirical Distribution Function1521000
Midmean - Empirical Distribution Function - Averaging1521000
Midmean - Empirical Distribution Function - Interpolation1521000
Midmean - Closest Observation1521000
Midmean - True Basic - Statistics Graphics Toolkit1521000
Midmean - MS Excel (old versions)1521000
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')