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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationMon, 18 Dec 2017 15:55:48 +0100
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/Dec/18/t1513609065f28fxiuy59u0y54.htm/, Retrieved Tue, 14 May 2024 14:31:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310190, Retrieved Tue, 14 May 2024 14:31:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper
Estimated Impact55
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Central tendancy] [2017-12-18 14:55:48] [2fb711e06e7eb81d34c9e51edb934d8a] [Current]
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Dataseries X:
10
10.5
10
9.5
8.5
5
5.5
6.5
6
10.5
11
8.5
4
7
10
11
8
9
9.5
10
8.5
9.5
9.5
10.5
13
10.5
12
7.5
9.5
7.5
12
6
12
11
12.5
8
8.5
10
11.5
8
11
8.5
5.5
11.5
9.5
8.5
9.5
13
10.5
9.5
9.5
9.5
11
8
8.5
6
9.5
5
9.5
10
9
9
9.5
8
9.5
11
14
12
10.5
10
8
9.5
10.5
9
10
10
17
12
11
10.5
11
9.5
8.5
8.5
12
12
13.5
11.5
11
9
5
8
10.5
10
10
9
10
9
8.5
10
5
8.5
12.5
11
11.5
8
11
9
10
10
14
8
7
9.5
11
14
10
10
10.5
7.5




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=310190&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=310190&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310190&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 Mean9.629170.19105550.4
Geometric Mean9.38185
Harmonic Mean9.10045
Quadratic Mean9.85214
Winsorized Mean ( 1 / 40 )9.61250.18252352.6647
Winsorized Mean ( 2 / 40 )9.61250.18252352.6647
Winsorized Mean ( 3 / 40 )9.61250.18252352.6647
Winsorized Mean ( 4 / 40 )9.595830.17931353.5144
Winsorized Mean ( 5 / 40 )9.595830.17132556.0097
Winsorized Mean ( 6 / 40 )9.595830.17132556.0097
Winsorized Mean ( 7 / 40 )9.595830.16099959.6018
Winsorized Mean ( 8 / 40 )9.595830.16099959.6018
Winsorized Mean ( 9 / 40 )9.558330.1556861.3975
Winsorized Mean ( 10 / 40 )9.60.14800364.8637
Winsorized Mean ( 11 / 40 )9.645830.14032768.7381
Winsorized Mean ( 12 / 40 )9.645830.14032768.7381
Winsorized Mean ( 13 / 40 )9.70.13223573.3545
Winsorized Mean ( 14 / 40 )9.70.13223573.3545
Winsorized Mean ( 15 / 40 )9.70.13223573.3545
Winsorized Mean ( 16 / 40 )9.70.11403685.0609
Winsorized Mean ( 17 / 40 )9.70.11403685.0609
Winsorized Mean ( 18 / 40 )9.70.11403685.0609
Winsorized Mean ( 19 / 40 )9.70.11403685.0609
Winsorized Mean ( 20 / 40 )9.616670.10380392.6438
Winsorized Mean ( 21 / 40 )9.616670.10380392.6438
Winsorized Mean ( 22 / 40 )9.616670.10380392.6438
Winsorized Mean ( 23 / 40 )9.616670.10380392.6438
Winsorized Mean ( 24 / 40 )9.616670.10380392.6438
Winsorized Mean ( 25 / 40 )9.720830.0910559106.757
Winsorized Mean ( 26 / 40 )9.720830.0910559106.757
Winsorized Mean ( 27 / 40 )9.720830.0910559106.757
Winsorized Mean ( 28 / 40 )9.720830.0910559106.757
Winsorized Mean ( 29 / 40 )9.720830.0910559106.757
Winsorized Mean ( 30 / 40 )9.720830.0910559106.757
Winsorized Mean ( 31 / 40 )9.720830.0910559106.757
Winsorized Mean ( 32 / 40 )9.58750.0763906125.506
Winsorized Mean ( 33 / 40 )9.58750.0763906125.506
Winsorized Mean ( 34 / 40 )9.58750.0763906125.506
Winsorized Mean ( 35 / 40 )9.58750.0763906125.506
Winsorized Mean ( 36 / 40 )9.73750.0594567163.775
Winsorized Mean ( 37 / 40 )9.73750.0594567163.775
Winsorized Mean ( 38 / 40 )9.73750.0594567163.775
Winsorized Mean ( 39 / 40 )9.73750.0594567163.775
Winsorized Mean ( 40 / 40 )9.73750.0594567163.775
Trimmed Mean ( 1 / 40 )9.614410.17754754.1513
Trimmed Mean ( 2 / 40 )9.616380.17200655.9072
Trimmed Mean ( 3 / 40 )9.618420.16580758.0098
Trimmed Mean ( 4 / 40 )9.620540.1588360.5712
Trimmed Mean ( 5 / 40 )9.627270.15205563.3143
Trimmed Mean ( 6 / 40 )9.634260.14673265.659
Trimmed Mean ( 7 / 40 )9.641510.14071468.5187
Trimmed Mean ( 8 / 40 )9.649040.13627870.8041
Trimmed Mean ( 9 / 40 )9.656860.13125873.5715
Trimmed Mean ( 10 / 40 )9.670.12657576.3974
Trimmed Mean ( 11 / 40 )9.678570.12270478.8774
Trimmed Mean ( 12 / 40 )9.682290.11964980.9228
Trimmed Mean ( 13 / 40 )9.686170.11617783.3741
Trimmed Mean ( 14 / 40 )9.684780.11350485.3251
Trimmed Mean ( 15 / 40 )9.683330.11045587.6674
Trimmed Mean ( 16 / 40 )9.681820.10696290.5166
Trimmed Mean ( 17 / 40 )9.680230.10556191.7026
Trimmed Mean ( 18 / 40 )9.678570.10393993.1174
Trimmed Mean ( 19 / 40 )9.676830.10206194.8142
Trimmed Mean ( 20 / 40 )9.6750.099881396.865
Trimmed Mean ( 21 / 40 )9.679490.098681998.0877
Trimmed Mean ( 22 / 40 )9.684210.097261799.5686
Trimmed Mean ( 23 / 40 )9.689190.0955811101.371
Trimmed Mean ( 24 / 40 )9.694440.0935914103.583
Trimmed Mean ( 25 / 40 )9.70.0912304106.324
Trimmed Mean ( 26 / 40 )9.698530.0902025107.52
Trimmed Mean ( 27 / 40 )9.696970.0889454109.022
Trimmed Mean ( 28 / 40 )9.695310.0874129110.914
Trimmed Mean ( 29 / 40 )9.693550.0855465113.313
Trimmed Mean ( 30 / 40 )9.691670.0832697116.389
Trimmed Mean ( 31 / 40 )9.689660.0804814120.396
Trimmed Mean ( 32 / 40 )9.68750.077042125.743
Trimmed Mean ( 33 / 40 )9.694440.0752548128.822
Trimmed Mean ( 34 / 40 )9.701920.072993132.916
Trimmed Mean ( 35 / 40 )9.710.0701165138.484
Trimmed Mean ( 36 / 40 )9.718750.0664217146.319
Trimmed Mean ( 37 / 40 )9.717390.0652979148.816
Trimmed Mean ( 38 / 40 )9.715910.06379152.311
Trimmed Mean ( 39 / 40 )9.714290.0617751157.252
Trimmed Mean ( 40 / 40 )9.71250.0590727164.416
Median9.5
Midrange10.5
Midmean - Weighted Average at Xnp9.78667
Midmean - Weighted Average at X(n+1)p9.78667
Midmean - Empirical Distribution Function9.78667
Midmean - Empirical Distribution Function - Averaging9.78667
Midmean - Empirical Distribution Function - Interpolation9.78667
Midmean - Closest Observation9.78667
Midmean - True Basic - Statistics Graphics Toolkit9.78667
Midmean - MS Excel (old versions)9.78667
Number of observations120

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 9.62917 & 0.191055 & 50.4 \tabularnewline
Geometric Mean & 9.38185 &  &  \tabularnewline
Harmonic Mean & 9.10045 &  &  \tabularnewline
Quadratic Mean & 9.85214 &  &  \tabularnewline
Winsorized Mean ( 1 / 40 ) & 9.6125 & 0.182523 & 52.6647 \tabularnewline
Winsorized Mean ( 2 / 40 ) & 9.6125 & 0.182523 & 52.6647 \tabularnewline
Winsorized Mean ( 3 / 40 ) & 9.6125 & 0.182523 & 52.6647 \tabularnewline
Winsorized Mean ( 4 / 40 ) & 9.59583 & 0.179313 & 53.5144 \tabularnewline
Winsorized Mean ( 5 / 40 ) & 9.59583 & 0.171325 & 56.0097 \tabularnewline
Winsorized Mean ( 6 / 40 ) & 9.59583 & 0.171325 & 56.0097 \tabularnewline
Winsorized Mean ( 7 / 40 ) & 9.59583 & 0.160999 & 59.6018 \tabularnewline
Winsorized Mean ( 8 / 40 ) & 9.59583 & 0.160999 & 59.6018 \tabularnewline
Winsorized Mean ( 9 / 40 ) & 9.55833 & 0.15568 & 61.3975 \tabularnewline
Winsorized Mean ( 10 / 40 ) & 9.6 & 0.148003 & 64.8637 \tabularnewline
Winsorized Mean ( 11 / 40 ) & 9.64583 & 0.140327 & 68.7381 \tabularnewline
Winsorized Mean ( 12 / 40 ) & 9.64583 & 0.140327 & 68.7381 \tabularnewline
Winsorized Mean ( 13 / 40 ) & 9.7 & 0.132235 & 73.3545 \tabularnewline
Winsorized Mean ( 14 / 40 ) & 9.7 & 0.132235 & 73.3545 \tabularnewline
Winsorized Mean ( 15 / 40 ) & 9.7 & 0.132235 & 73.3545 \tabularnewline
Winsorized Mean ( 16 / 40 ) & 9.7 & 0.114036 & 85.0609 \tabularnewline
Winsorized Mean ( 17 / 40 ) & 9.7 & 0.114036 & 85.0609 \tabularnewline
Winsorized Mean ( 18 / 40 ) & 9.7 & 0.114036 & 85.0609 \tabularnewline
Winsorized Mean ( 19 / 40 ) & 9.7 & 0.114036 & 85.0609 \tabularnewline
Winsorized Mean ( 20 / 40 ) & 9.61667 & 0.103803 & 92.6438 \tabularnewline
Winsorized Mean ( 21 / 40 ) & 9.61667 & 0.103803 & 92.6438 \tabularnewline
Winsorized Mean ( 22 / 40 ) & 9.61667 & 0.103803 & 92.6438 \tabularnewline
Winsorized Mean ( 23 / 40 ) & 9.61667 & 0.103803 & 92.6438 \tabularnewline
Winsorized Mean ( 24 / 40 ) & 9.61667 & 0.103803 & 92.6438 \tabularnewline
Winsorized Mean ( 25 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 26 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 27 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 28 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 29 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 30 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 31 / 40 ) & 9.72083 & 0.0910559 & 106.757 \tabularnewline
Winsorized Mean ( 32 / 40 ) & 9.5875 & 0.0763906 & 125.506 \tabularnewline
Winsorized Mean ( 33 / 40 ) & 9.5875 & 0.0763906 & 125.506 \tabularnewline
Winsorized Mean ( 34 / 40 ) & 9.5875 & 0.0763906 & 125.506 \tabularnewline
Winsorized Mean ( 35 / 40 ) & 9.5875 & 0.0763906 & 125.506 \tabularnewline
Winsorized Mean ( 36 / 40 ) & 9.7375 & 0.0594567 & 163.775 \tabularnewline
Winsorized Mean ( 37 / 40 ) & 9.7375 & 0.0594567 & 163.775 \tabularnewline
Winsorized Mean ( 38 / 40 ) & 9.7375 & 0.0594567 & 163.775 \tabularnewline
Winsorized Mean ( 39 / 40 ) & 9.7375 & 0.0594567 & 163.775 \tabularnewline
Winsorized Mean ( 40 / 40 ) & 9.7375 & 0.0594567 & 163.775 \tabularnewline
Trimmed Mean ( 1 / 40 ) & 9.61441 & 0.177547 & 54.1513 \tabularnewline
Trimmed Mean ( 2 / 40 ) & 9.61638 & 0.172006 & 55.9072 \tabularnewline
Trimmed Mean ( 3 / 40 ) & 9.61842 & 0.165807 & 58.0098 \tabularnewline
Trimmed Mean ( 4 / 40 ) & 9.62054 & 0.15883 & 60.5712 \tabularnewline
Trimmed Mean ( 5 / 40 ) & 9.62727 & 0.152055 & 63.3143 \tabularnewline
Trimmed Mean ( 6 / 40 ) & 9.63426 & 0.146732 & 65.659 \tabularnewline
Trimmed Mean ( 7 / 40 ) & 9.64151 & 0.140714 & 68.5187 \tabularnewline
Trimmed Mean ( 8 / 40 ) & 9.64904 & 0.136278 & 70.8041 \tabularnewline
Trimmed Mean ( 9 / 40 ) & 9.65686 & 0.131258 & 73.5715 \tabularnewline
Trimmed Mean ( 10 / 40 ) & 9.67 & 0.126575 & 76.3974 \tabularnewline
Trimmed Mean ( 11 / 40 ) & 9.67857 & 0.122704 & 78.8774 \tabularnewline
Trimmed Mean ( 12 / 40 ) & 9.68229 & 0.119649 & 80.9228 \tabularnewline
Trimmed Mean ( 13 / 40 ) & 9.68617 & 0.116177 & 83.3741 \tabularnewline
Trimmed Mean ( 14 / 40 ) & 9.68478 & 0.113504 & 85.3251 \tabularnewline
Trimmed Mean ( 15 / 40 ) & 9.68333 & 0.110455 & 87.6674 \tabularnewline
Trimmed Mean ( 16 / 40 ) & 9.68182 & 0.106962 & 90.5166 \tabularnewline
Trimmed Mean ( 17 / 40 ) & 9.68023 & 0.105561 & 91.7026 \tabularnewline
Trimmed Mean ( 18 / 40 ) & 9.67857 & 0.103939 & 93.1174 \tabularnewline
Trimmed Mean ( 19 / 40 ) & 9.67683 & 0.102061 & 94.8142 \tabularnewline
Trimmed Mean ( 20 / 40 ) & 9.675 & 0.0998813 & 96.865 \tabularnewline
Trimmed Mean ( 21 / 40 ) & 9.67949 & 0.0986819 & 98.0877 \tabularnewline
Trimmed Mean ( 22 / 40 ) & 9.68421 & 0.0972617 & 99.5686 \tabularnewline
Trimmed Mean ( 23 / 40 ) & 9.68919 & 0.0955811 & 101.371 \tabularnewline
Trimmed Mean ( 24 / 40 ) & 9.69444 & 0.0935914 & 103.583 \tabularnewline
Trimmed Mean ( 25 / 40 ) & 9.7 & 0.0912304 & 106.324 \tabularnewline
Trimmed Mean ( 26 / 40 ) & 9.69853 & 0.0902025 & 107.52 \tabularnewline
Trimmed Mean ( 27 / 40 ) & 9.69697 & 0.0889454 & 109.022 \tabularnewline
Trimmed Mean ( 28 / 40 ) & 9.69531 & 0.0874129 & 110.914 \tabularnewline
Trimmed Mean ( 29 / 40 ) & 9.69355 & 0.0855465 & 113.313 \tabularnewline
Trimmed Mean ( 30 / 40 ) & 9.69167 & 0.0832697 & 116.389 \tabularnewline
Trimmed Mean ( 31 / 40 ) & 9.68966 & 0.0804814 & 120.396 \tabularnewline
Trimmed Mean ( 32 / 40 ) & 9.6875 & 0.077042 & 125.743 \tabularnewline
Trimmed Mean ( 33 / 40 ) & 9.69444 & 0.0752548 & 128.822 \tabularnewline
Trimmed Mean ( 34 / 40 ) & 9.70192 & 0.072993 & 132.916 \tabularnewline
Trimmed Mean ( 35 / 40 ) & 9.71 & 0.0701165 & 138.484 \tabularnewline
Trimmed Mean ( 36 / 40 ) & 9.71875 & 0.0664217 & 146.319 \tabularnewline
Trimmed Mean ( 37 / 40 ) & 9.71739 & 0.0652979 & 148.816 \tabularnewline
Trimmed Mean ( 38 / 40 ) & 9.71591 & 0.06379 & 152.311 \tabularnewline
Trimmed Mean ( 39 / 40 ) & 9.71429 & 0.0617751 & 157.252 \tabularnewline
Trimmed Mean ( 40 / 40 ) & 9.7125 & 0.0590727 & 164.416 \tabularnewline
Median & 9.5 &  &  \tabularnewline
Midrange & 10.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 9.78667 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 9.78667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 9.78667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 9.78667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 9.78667 &  &  \tabularnewline
Midmean - Closest Observation & 9.78667 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 9.78667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 9.78667 &  &  \tabularnewline
Number of observations & 120 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310190&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]9.62917[/C][C]0.191055[/C][C]50.4[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]9.38185[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]9.10045[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]9.85214[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 40 )[/C][C]9.6125[/C][C]0.182523[/C][C]52.6647[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 40 )[/C][C]9.6125[/C][C]0.182523[/C][C]52.6647[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 40 )[/C][C]9.6125[/C][C]0.182523[/C][C]52.6647[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 40 )[/C][C]9.59583[/C][C]0.179313[/C][C]53.5144[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 40 )[/C][C]9.59583[/C][C]0.171325[/C][C]56.0097[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 40 )[/C][C]9.59583[/C][C]0.171325[/C][C]56.0097[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 40 )[/C][C]9.59583[/C][C]0.160999[/C][C]59.6018[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 40 )[/C][C]9.59583[/C][C]0.160999[/C][C]59.6018[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 40 )[/C][C]9.55833[/C][C]0.15568[/C][C]61.3975[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 40 )[/C][C]9.6[/C][C]0.148003[/C][C]64.8637[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 40 )[/C][C]9.64583[/C][C]0.140327[/C][C]68.7381[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 40 )[/C][C]9.64583[/C][C]0.140327[/C][C]68.7381[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 40 )[/C][C]9.7[/C][C]0.132235[/C][C]73.3545[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 40 )[/C][C]9.7[/C][C]0.132235[/C][C]73.3545[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 40 )[/C][C]9.7[/C][C]0.132235[/C][C]73.3545[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 40 )[/C][C]9.7[/C][C]0.114036[/C][C]85.0609[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 40 )[/C][C]9.7[/C][C]0.114036[/C][C]85.0609[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 40 )[/C][C]9.7[/C][C]0.114036[/C][C]85.0609[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 40 )[/C][C]9.7[/C][C]0.114036[/C][C]85.0609[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 40 )[/C][C]9.61667[/C][C]0.103803[/C][C]92.6438[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 40 )[/C][C]9.61667[/C][C]0.103803[/C][C]92.6438[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 40 )[/C][C]9.61667[/C][C]0.103803[/C][C]92.6438[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 40 )[/C][C]9.61667[/C][C]0.103803[/C][C]92.6438[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 40 )[/C][C]9.61667[/C][C]0.103803[/C][C]92.6438[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 40 )[/C][C]9.72083[/C][C]0.0910559[/C][C]106.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 40 )[/C][C]9.5875[/C][C]0.0763906[/C][C]125.506[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 40 )[/C][C]9.5875[/C][C]0.0763906[/C][C]125.506[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 40 )[/C][C]9.5875[/C][C]0.0763906[/C][C]125.506[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 40 )[/C][C]9.5875[/C][C]0.0763906[/C][C]125.506[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 40 )[/C][C]9.7375[/C][C]0.0594567[/C][C]163.775[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 40 )[/C][C]9.7375[/C][C]0.0594567[/C][C]163.775[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 40 )[/C][C]9.7375[/C][C]0.0594567[/C][C]163.775[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 40 )[/C][C]9.7375[/C][C]0.0594567[/C][C]163.775[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 40 )[/C][C]9.7375[/C][C]0.0594567[/C][C]163.775[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 40 )[/C][C]9.61441[/C][C]0.177547[/C][C]54.1513[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 40 )[/C][C]9.61638[/C][C]0.172006[/C][C]55.9072[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 40 )[/C][C]9.61842[/C][C]0.165807[/C][C]58.0098[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 40 )[/C][C]9.62054[/C][C]0.15883[/C][C]60.5712[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 40 )[/C][C]9.62727[/C][C]0.152055[/C][C]63.3143[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 40 )[/C][C]9.63426[/C][C]0.146732[/C][C]65.659[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 40 )[/C][C]9.64151[/C][C]0.140714[/C][C]68.5187[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 40 )[/C][C]9.64904[/C][C]0.136278[/C][C]70.8041[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 40 )[/C][C]9.65686[/C][C]0.131258[/C][C]73.5715[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 40 )[/C][C]9.67[/C][C]0.126575[/C][C]76.3974[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 40 )[/C][C]9.67857[/C][C]0.122704[/C][C]78.8774[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 40 )[/C][C]9.68229[/C][C]0.119649[/C][C]80.9228[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 40 )[/C][C]9.68617[/C][C]0.116177[/C][C]83.3741[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 40 )[/C][C]9.68478[/C][C]0.113504[/C][C]85.3251[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 40 )[/C][C]9.68333[/C][C]0.110455[/C][C]87.6674[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 40 )[/C][C]9.68182[/C][C]0.106962[/C][C]90.5166[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 40 )[/C][C]9.68023[/C][C]0.105561[/C][C]91.7026[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 40 )[/C][C]9.67857[/C][C]0.103939[/C][C]93.1174[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 40 )[/C][C]9.67683[/C][C]0.102061[/C][C]94.8142[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 40 )[/C][C]9.675[/C][C]0.0998813[/C][C]96.865[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 40 )[/C][C]9.67949[/C][C]0.0986819[/C][C]98.0877[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 40 )[/C][C]9.68421[/C][C]0.0972617[/C][C]99.5686[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 40 )[/C][C]9.68919[/C][C]0.0955811[/C][C]101.371[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 40 )[/C][C]9.69444[/C][C]0.0935914[/C][C]103.583[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 40 )[/C][C]9.7[/C][C]0.0912304[/C][C]106.324[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 40 )[/C][C]9.69853[/C][C]0.0902025[/C][C]107.52[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 40 )[/C][C]9.69697[/C][C]0.0889454[/C][C]109.022[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 40 )[/C][C]9.69531[/C][C]0.0874129[/C][C]110.914[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 40 )[/C][C]9.69355[/C][C]0.0855465[/C][C]113.313[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 40 )[/C][C]9.69167[/C][C]0.0832697[/C][C]116.389[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 40 )[/C][C]9.68966[/C][C]0.0804814[/C][C]120.396[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 40 )[/C][C]9.6875[/C][C]0.077042[/C][C]125.743[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 40 )[/C][C]9.69444[/C][C]0.0752548[/C][C]128.822[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 40 )[/C][C]9.70192[/C][C]0.072993[/C][C]132.916[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 40 )[/C][C]9.71[/C][C]0.0701165[/C][C]138.484[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 40 )[/C][C]9.71875[/C][C]0.0664217[/C][C]146.319[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 40 )[/C][C]9.71739[/C][C]0.0652979[/C][C]148.816[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 40 )[/C][C]9.71591[/C][C]0.06379[/C][C]152.311[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 40 )[/C][C]9.71429[/C][C]0.0617751[/C][C]157.252[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 40 )[/C][C]9.7125[/C][C]0.0590727[/C][C]164.416[/C][/ROW]
[ROW][C]Median[/C][C]9.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]10.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]9.78667[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]120[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310190&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310190&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 Mean9.629170.19105550.4
Geometric Mean9.38185
Harmonic Mean9.10045
Quadratic Mean9.85214
Winsorized Mean ( 1 / 40 )9.61250.18252352.6647
Winsorized Mean ( 2 / 40 )9.61250.18252352.6647
Winsorized Mean ( 3 / 40 )9.61250.18252352.6647
Winsorized Mean ( 4 / 40 )9.595830.17931353.5144
Winsorized Mean ( 5 / 40 )9.595830.17132556.0097
Winsorized Mean ( 6 / 40 )9.595830.17132556.0097
Winsorized Mean ( 7 / 40 )9.595830.16099959.6018
Winsorized Mean ( 8 / 40 )9.595830.16099959.6018
Winsorized Mean ( 9 / 40 )9.558330.1556861.3975
Winsorized Mean ( 10 / 40 )9.60.14800364.8637
Winsorized Mean ( 11 / 40 )9.645830.14032768.7381
Winsorized Mean ( 12 / 40 )9.645830.14032768.7381
Winsorized Mean ( 13 / 40 )9.70.13223573.3545
Winsorized Mean ( 14 / 40 )9.70.13223573.3545
Winsorized Mean ( 15 / 40 )9.70.13223573.3545
Winsorized Mean ( 16 / 40 )9.70.11403685.0609
Winsorized Mean ( 17 / 40 )9.70.11403685.0609
Winsorized Mean ( 18 / 40 )9.70.11403685.0609
Winsorized Mean ( 19 / 40 )9.70.11403685.0609
Winsorized Mean ( 20 / 40 )9.616670.10380392.6438
Winsorized Mean ( 21 / 40 )9.616670.10380392.6438
Winsorized Mean ( 22 / 40 )9.616670.10380392.6438
Winsorized Mean ( 23 / 40 )9.616670.10380392.6438
Winsorized Mean ( 24 / 40 )9.616670.10380392.6438
Winsorized Mean ( 25 / 40 )9.720830.0910559106.757
Winsorized Mean ( 26 / 40 )9.720830.0910559106.757
Winsorized Mean ( 27 / 40 )9.720830.0910559106.757
Winsorized Mean ( 28 / 40 )9.720830.0910559106.757
Winsorized Mean ( 29 / 40 )9.720830.0910559106.757
Winsorized Mean ( 30 / 40 )9.720830.0910559106.757
Winsorized Mean ( 31 / 40 )9.720830.0910559106.757
Winsorized Mean ( 32 / 40 )9.58750.0763906125.506
Winsorized Mean ( 33 / 40 )9.58750.0763906125.506
Winsorized Mean ( 34 / 40 )9.58750.0763906125.506
Winsorized Mean ( 35 / 40 )9.58750.0763906125.506
Winsorized Mean ( 36 / 40 )9.73750.0594567163.775
Winsorized Mean ( 37 / 40 )9.73750.0594567163.775
Winsorized Mean ( 38 / 40 )9.73750.0594567163.775
Winsorized Mean ( 39 / 40 )9.73750.0594567163.775
Winsorized Mean ( 40 / 40 )9.73750.0594567163.775
Trimmed Mean ( 1 / 40 )9.614410.17754754.1513
Trimmed Mean ( 2 / 40 )9.616380.17200655.9072
Trimmed Mean ( 3 / 40 )9.618420.16580758.0098
Trimmed Mean ( 4 / 40 )9.620540.1588360.5712
Trimmed Mean ( 5 / 40 )9.627270.15205563.3143
Trimmed Mean ( 6 / 40 )9.634260.14673265.659
Trimmed Mean ( 7 / 40 )9.641510.14071468.5187
Trimmed Mean ( 8 / 40 )9.649040.13627870.8041
Trimmed Mean ( 9 / 40 )9.656860.13125873.5715
Trimmed Mean ( 10 / 40 )9.670.12657576.3974
Trimmed Mean ( 11 / 40 )9.678570.12270478.8774
Trimmed Mean ( 12 / 40 )9.682290.11964980.9228
Trimmed Mean ( 13 / 40 )9.686170.11617783.3741
Trimmed Mean ( 14 / 40 )9.684780.11350485.3251
Trimmed Mean ( 15 / 40 )9.683330.11045587.6674
Trimmed Mean ( 16 / 40 )9.681820.10696290.5166
Trimmed Mean ( 17 / 40 )9.680230.10556191.7026
Trimmed Mean ( 18 / 40 )9.678570.10393993.1174
Trimmed Mean ( 19 / 40 )9.676830.10206194.8142
Trimmed Mean ( 20 / 40 )9.6750.099881396.865
Trimmed Mean ( 21 / 40 )9.679490.098681998.0877
Trimmed Mean ( 22 / 40 )9.684210.097261799.5686
Trimmed Mean ( 23 / 40 )9.689190.0955811101.371
Trimmed Mean ( 24 / 40 )9.694440.0935914103.583
Trimmed Mean ( 25 / 40 )9.70.0912304106.324
Trimmed Mean ( 26 / 40 )9.698530.0902025107.52
Trimmed Mean ( 27 / 40 )9.696970.0889454109.022
Trimmed Mean ( 28 / 40 )9.695310.0874129110.914
Trimmed Mean ( 29 / 40 )9.693550.0855465113.313
Trimmed Mean ( 30 / 40 )9.691670.0832697116.389
Trimmed Mean ( 31 / 40 )9.689660.0804814120.396
Trimmed Mean ( 32 / 40 )9.68750.077042125.743
Trimmed Mean ( 33 / 40 )9.694440.0752548128.822
Trimmed Mean ( 34 / 40 )9.701920.072993132.916
Trimmed Mean ( 35 / 40 )9.710.0701165138.484
Trimmed Mean ( 36 / 40 )9.718750.0664217146.319
Trimmed Mean ( 37 / 40 )9.717390.0652979148.816
Trimmed Mean ( 38 / 40 )9.715910.06379152.311
Trimmed Mean ( 39 / 40 )9.714290.0617751157.252
Trimmed Mean ( 40 / 40 )9.71250.0590727164.416
Median9.5
Midrange10.5
Midmean - Weighted Average at Xnp9.78667
Midmean - Weighted Average at X(n+1)p9.78667
Midmean - Empirical Distribution Function9.78667
Midmean - Empirical Distribution Function - Averaging9.78667
Midmean - Empirical Distribution Function - Interpolation9.78667
Midmean - Closest Observation9.78667
Midmean - True Basic - Statistics Graphics Toolkit9.78667
Midmean - MS Excel (old versions)9.78667
Number of observations120



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')