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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 computationThu, 31 Jan 2019 14:04:54 +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/2019/Jan/31/t154893991203og3fuuhvxq41r.htm/, Retrieved Sun, 05 May 2024 15:06:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=317172, Retrieved Sun, 05 May 2024 15:06:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact27
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2019-01-31 13:04:54] [21684ad9fc05505f2c2196f825276d48] [Current]
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Dataseries X:
13
16
17
NA
NA
16
NA
NA
NA
17
17
15
16
14
16
17
NA
NA
NA
NA
16
NA
16
NA
NA
NA
16
15
16
16
13
15
17
NA
13
17
NA
14
14
18
NA
17
13
16
15
15
NA
15
13
NA
17
NA
NA
11
14
13
NA
17
16
NA
17
16
16
16
15
12
17
14
14
16
NA
NA
NA
NA
NA
15
16
14
15
17
NA
10
NA
17
NA
20
17
18
NA
17
14
NA
17
NA
17
NA
16
18
18
16
NA
NA
15
13
NA
NA
NA
NA
NA
16
NA
NA
NA
12
NA
16
16
NA
16
14
15
14
NA
15
NA
15
16
NA
NA
NA
11
NA
18
NA
11
NA
18
NA
15
19
17
NA
14
NA
13
17
14
19
14
NA
NA
16
16
15
12
NA
17
NA
NA
18
15
18
15
NA
NA
NA
16
NA
16




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=317172&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=317172&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=317172&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 MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 34 )15.47570.17981386.0655
Winsorized Mean ( 2 / 34 )15.47570.17981386.0655
Winsorized Mean ( 3 / 34 )15.44660.17492188.3061
Winsorized Mean ( 4 / 34 )15.48540.16606493.2496
Winsorized Mean ( 5 / 34 )15.48540.16606493.2496
Winsorized Mean ( 6 / 34 )15.48540.16606493.2496
Winsorized Mean ( 7 / 34 )15.55340.153473101.343
Winsorized Mean ( 8 / 34 )15.55340.153473101.343
Winsorized Mean ( 9 / 34 )15.55340.153473101.343
Winsorized Mean ( 10 / 34 )15.55340.153473101.343
Winsorized Mean ( 11 / 34 )15.44660.139161110.998
Winsorized Mean ( 12 / 34 )15.44660.139161110.998
Winsorized Mean ( 13 / 34 )15.44660.139161110.998
Winsorized Mean ( 14 / 34 )15.44660.139161110.998
Winsorized Mean ( 15 / 34 )15.59220.116616133.706
Winsorized Mean ( 16 / 34 )15.59220.116616133.706
Winsorized Mean ( 17 / 34 )15.59220.116616133.706
Winsorized Mean ( 18 / 34 )15.59220.116616133.706
Winsorized Mean ( 19 / 34 )15.59220.116616133.706
Winsorized Mean ( 20 / 34 )15.59220.116616133.706
Winsorized Mean ( 21 / 34 )15.59220.116616133.706
Winsorized Mean ( 22 / 34 )15.59220.116616133.706
Winsorized Mean ( 23 / 34 )15.59220.116616133.706
Winsorized Mean ( 24 / 34 )15.59220.116616133.706
Winsorized Mean ( 25 / 34 )15.59220.116616133.706
Winsorized Mean ( 26 / 34 )15.59220.116616133.706
Winsorized Mean ( 27 / 34 )15.59220.116616133.706
Winsorized Mean ( 28 / 34 )15.86410.0839812188.9
Winsorized Mean ( 29 / 34 )15.86410.0839812188.9
Winsorized Mean ( 30 / 34 )15.86410.0839812188.9
Winsorized Mean ( 31 / 34 )15.56310.0491115316.894
Winsorized Mean ( 32 / 34 )15.56310.0491115316.894
Winsorized Mean ( 33 / 34 )15.56310.0491115316.894
Winsorized Mean ( 34 / 34 )15.56310.0491115316.894
Trimmed Mean ( 1 / 34 )15.47570.17440988.7323
Trimmed Mean ( 2 / 34 )15.48510.16828192.0193
Trimmed Mean ( 3 / 34 )15.50520.1612996.132
Trimmed Mean ( 4 / 34 )15.50520.15541299.7683
Trimmed Mean ( 5 / 34 )15.53760.151785102.366
Trimmed Mean ( 6 / 34 )15.54950.147642105.318
Trimmed Mean ( 7 / 34 )15.56180.14289108.908
Trimmed Mean ( 8 / 34 )15.56180.14036110.871
Trimmed Mean ( 9 / 34 )15.56470.137451113.238
Trimmed Mean ( 10 / 34 )15.56630.134097116.082
Trimmed Mean ( 11 / 34 )15.56790.130216119.554
Trimmed Mean ( 12 / 34 )15.58230.128163121.582
Trimmed Mean ( 13 / 34 )15.59740.125737124.047
Trimmed Mean ( 14 / 34 )15.61330.122869127.073
Trimmed Mean ( 15 / 34 )15.61330.119466130.693
Trimmed Mean ( 16 / 34 )15.63010.119083131.254
Trimmed Mean ( 17 / 34 )15.63770.11855131.908
Trimmed Mean ( 18 / 34 )15.64180.117838132.74
Trimmed Mean ( 19 / 34 )15.64620.116913133.827
Trimmed Mean ( 20 / 34 )15.65080.115733135.232
Trimmed Mean ( 21 / 34 )15.65570.114246137.036
Trimmed Mean ( 22 / 34 )15.6610.112384139.353
Trimmed Mean ( 23 / 34 )15.66670.110062142.344
Trimmed Mean ( 24 / 34 )15.67270.107166146.247
Trimmed Mean ( 25 / 34 )15.67920.103542151.428
Trimmed Mean ( 26 / 34 )15.68630.0989759158.486
Trimmed Mean ( 27 / 34 )15.69390.0931501168.479
Trimmed Mean ( 28 / 34 )15.70210.0855677183.505
Trimmed Mean ( 29 / 34 )15.68890.0830129188.993
Trimmed Mean ( 30 / 34 )15.68890.0795957197.107
Trimmed Mean ( 31 / 34 )15.67440.0749777209.054
Trimmed Mean ( 32 / 34 )15.65850.0764719204.762
Trimmed Mean ( 33 / 34 )15.67570.0780203200.918
Trimmed Mean ( 34 / 34 )15.68570.0796149197.02
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp15.7013
Midmean - Weighted Average at X(n+1)p15.7013
Midmean - Empirical Distribution Function15.7013
Midmean - Empirical Distribution Function - Averaging15.7013
Midmean - Empirical Distribution Function - Interpolation15.7013
Midmean - Closest Observation15.7013
Midmean - True Basic - Statistics Graphics Toolkit15.7013
Midmean - MS Excel (old versions)15.7013
Number of observations169

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & NA & NA & NA \tabularnewline
Geometric Mean & NA &  &  \tabularnewline
Harmonic Mean & NA &  &  \tabularnewline
Quadratic Mean & NA &  &  \tabularnewline
Winsorized Mean ( 1 / 34 ) & 15.4757 & 0.179813 & 86.0655 \tabularnewline
Winsorized Mean ( 2 / 34 ) & 15.4757 & 0.179813 & 86.0655 \tabularnewline
Winsorized Mean ( 3 / 34 ) & 15.4466 & 0.174921 & 88.3061 \tabularnewline
Winsorized Mean ( 4 / 34 ) & 15.4854 & 0.166064 & 93.2496 \tabularnewline
Winsorized Mean ( 5 / 34 ) & 15.4854 & 0.166064 & 93.2496 \tabularnewline
Winsorized Mean ( 6 / 34 ) & 15.4854 & 0.166064 & 93.2496 \tabularnewline
Winsorized Mean ( 7 / 34 ) & 15.5534 & 0.153473 & 101.343 \tabularnewline
Winsorized Mean ( 8 / 34 ) & 15.5534 & 0.153473 & 101.343 \tabularnewline
Winsorized Mean ( 9 / 34 ) & 15.5534 & 0.153473 & 101.343 \tabularnewline
Winsorized Mean ( 10 / 34 ) & 15.5534 & 0.153473 & 101.343 \tabularnewline
Winsorized Mean ( 11 / 34 ) & 15.4466 & 0.139161 & 110.998 \tabularnewline
Winsorized Mean ( 12 / 34 ) & 15.4466 & 0.139161 & 110.998 \tabularnewline
Winsorized Mean ( 13 / 34 ) & 15.4466 & 0.139161 & 110.998 \tabularnewline
Winsorized Mean ( 14 / 34 ) & 15.4466 & 0.139161 & 110.998 \tabularnewline
Winsorized Mean ( 15 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 16 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 17 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 18 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 19 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 20 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 21 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 22 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 23 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 24 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 25 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 26 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 27 / 34 ) & 15.5922 & 0.116616 & 133.706 \tabularnewline
Winsorized Mean ( 28 / 34 ) & 15.8641 & 0.0839812 & 188.9 \tabularnewline
Winsorized Mean ( 29 / 34 ) & 15.8641 & 0.0839812 & 188.9 \tabularnewline
Winsorized Mean ( 30 / 34 ) & 15.8641 & 0.0839812 & 188.9 \tabularnewline
Winsorized Mean ( 31 / 34 ) & 15.5631 & 0.0491115 & 316.894 \tabularnewline
Winsorized Mean ( 32 / 34 ) & 15.5631 & 0.0491115 & 316.894 \tabularnewline
Winsorized Mean ( 33 / 34 ) & 15.5631 & 0.0491115 & 316.894 \tabularnewline
Winsorized Mean ( 34 / 34 ) & 15.5631 & 0.0491115 & 316.894 \tabularnewline
Trimmed Mean ( 1 / 34 ) & 15.4757 & 0.174409 & 88.7323 \tabularnewline
Trimmed Mean ( 2 / 34 ) & 15.4851 & 0.168281 & 92.0193 \tabularnewline
Trimmed Mean ( 3 / 34 ) & 15.5052 & 0.16129 & 96.132 \tabularnewline
Trimmed Mean ( 4 / 34 ) & 15.5052 & 0.155412 & 99.7683 \tabularnewline
Trimmed Mean ( 5 / 34 ) & 15.5376 & 0.151785 & 102.366 \tabularnewline
Trimmed Mean ( 6 / 34 ) & 15.5495 & 0.147642 & 105.318 \tabularnewline
Trimmed Mean ( 7 / 34 ) & 15.5618 & 0.14289 & 108.908 \tabularnewline
Trimmed Mean ( 8 / 34 ) & 15.5618 & 0.14036 & 110.871 \tabularnewline
Trimmed Mean ( 9 / 34 ) & 15.5647 & 0.137451 & 113.238 \tabularnewline
Trimmed Mean ( 10 / 34 ) & 15.5663 & 0.134097 & 116.082 \tabularnewline
Trimmed Mean ( 11 / 34 ) & 15.5679 & 0.130216 & 119.554 \tabularnewline
Trimmed Mean ( 12 / 34 ) & 15.5823 & 0.128163 & 121.582 \tabularnewline
Trimmed Mean ( 13 / 34 ) & 15.5974 & 0.125737 & 124.047 \tabularnewline
Trimmed Mean ( 14 / 34 ) & 15.6133 & 0.122869 & 127.073 \tabularnewline
Trimmed Mean ( 15 / 34 ) & 15.6133 & 0.119466 & 130.693 \tabularnewline
Trimmed Mean ( 16 / 34 ) & 15.6301 & 0.119083 & 131.254 \tabularnewline
Trimmed Mean ( 17 / 34 ) & 15.6377 & 0.11855 & 131.908 \tabularnewline
Trimmed Mean ( 18 / 34 ) & 15.6418 & 0.117838 & 132.74 \tabularnewline
Trimmed Mean ( 19 / 34 ) & 15.6462 & 0.116913 & 133.827 \tabularnewline
Trimmed Mean ( 20 / 34 ) & 15.6508 & 0.115733 & 135.232 \tabularnewline
Trimmed Mean ( 21 / 34 ) & 15.6557 & 0.114246 & 137.036 \tabularnewline
Trimmed Mean ( 22 / 34 ) & 15.661 & 0.112384 & 139.353 \tabularnewline
Trimmed Mean ( 23 / 34 ) & 15.6667 & 0.110062 & 142.344 \tabularnewline
Trimmed Mean ( 24 / 34 ) & 15.6727 & 0.107166 & 146.247 \tabularnewline
Trimmed Mean ( 25 / 34 ) & 15.6792 & 0.103542 & 151.428 \tabularnewline
Trimmed Mean ( 26 / 34 ) & 15.6863 & 0.0989759 & 158.486 \tabularnewline
Trimmed Mean ( 27 / 34 ) & 15.6939 & 0.0931501 & 168.479 \tabularnewline
Trimmed Mean ( 28 / 34 ) & 15.7021 & 0.0855677 & 183.505 \tabularnewline
Trimmed Mean ( 29 / 34 ) & 15.6889 & 0.0830129 & 188.993 \tabularnewline
Trimmed Mean ( 30 / 34 ) & 15.6889 & 0.0795957 & 197.107 \tabularnewline
Trimmed Mean ( 31 / 34 ) & 15.6744 & 0.0749777 & 209.054 \tabularnewline
Trimmed Mean ( 32 / 34 ) & 15.6585 & 0.0764719 & 204.762 \tabularnewline
Trimmed Mean ( 33 / 34 ) & 15.6757 & 0.0780203 & 200.918 \tabularnewline
Trimmed Mean ( 34 / 34 ) & 15.6857 & 0.0796149 & 197.02 \tabularnewline
Median & NA &  &  \tabularnewline
Midrange & NA &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 15.7013 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 15.7013 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 15.7013 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 15.7013 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 15.7013 &  &  \tabularnewline
Midmean - Closest Observation & 15.7013 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 15.7013 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 15.7013 &  &  \tabularnewline
Number of observations & 169 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=317172&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]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 34 )[/C][C]15.4757[/C][C]0.179813[/C][C]86.0655[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 34 )[/C][C]15.4757[/C][C]0.179813[/C][C]86.0655[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 34 )[/C][C]15.4466[/C][C]0.174921[/C][C]88.3061[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 34 )[/C][C]15.4854[/C][C]0.166064[/C][C]93.2496[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 34 )[/C][C]15.4854[/C][C]0.166064[/C][C]93.2496[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 34 )[/C][C]15.4854[/C][C]0.166064[/C][C]93.2496[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 34 )[/C][C]15.5534[/C][C]0.153473[/C][C]101.343[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 34 )[/C][C]15.5534[/C][C]0.153473[/C][C]101.343[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 34 )[/C][C]15.5534[/C][C]0.153473[/C][C]101.343[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 34 )[/C][C]15.5534[/C][C]0.153473[/C][C]101.343[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 34 )[/C][C]15.4466[/C][C]0.139161[/C][C]110.998[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 34 )[/C][C]15.4466[/C][C]0.139161[/C][C]110.998[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 34 )[/C][C]15.4466[/C][C]0.139161[/C][C]110.998[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 34 )[/C][C]15.4466[/C][C]0.139161[/C][C]110.998[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 34 )[/C][C]15.5922[/C][C]0.116616[/C][C]133.706[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 34 )[/C][C]15.8641[/C][C]0.0839812[/C][C]188.9[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 34 )[/C][C]15.8641[/C][C]0.0839812[/C][C]188.9[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 34 )[/C][C]15.8641[/C][C]0.0839812[/C][C]188.9[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 34 )[/C][C]15.5631[/C][C]0.0491115[/C][C]316.894[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 34 )[/C][C]15.5631[/C][C]0.0491115[/C][C]316.894[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 34 )[/C][C]15.5631[/C][C]0.0491115[/C][C]316.894[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 34 )[/C][C]15.5631[/C][C]0.0491115[/C][C]316.894[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 34 )[/C][C]15.4757[/C][C]0.174409[/C][C]88.7323[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 34 )[/C][C]15.4851[/C][C]0.168281[/C][C]92.0193[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 34 )[/C][C]15.5052[/C][C]0.16129[/C][C]96.132[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 34 )[/C][C]15.5052[/C][C]0.155412[/C][C]99.7683[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 34 )[/C][C]15.5376[/C][C]0.151785[/C][C]102.366[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 34 )[/C][C]15.5495[/C][C]0.147642[/C][C]105.318[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 34 )[/C][C]15.5618[/C][C]0.14289[/C][C]108.908[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 34 )[/C][C]15.5618[/C][C]0.14036[/C][C]110.871[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 34 )[/C][C]15.5647[/C][C]0.137451[/C][C]113.238[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 34 )[/C][C]15.5663[/C][C]0.134097[/C][C]116.082[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 34 )[/C][C]15.5679[/C][C]0.130216[/C][C]119.554[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 34 )[/C][C]15.5823[/C][C]0.128163[/C][C]121.582[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 34 )[/C][C]15.5974[/C][C]0.125737[/C][C]124.047[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 34 )[/C][C]15.6133[/C][C]0.122869[/C][C]127.073[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 34 )[/C][C]15.6133[/C][C]0.119466[/C][C]130.693[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 34 )[/C][C]15.6301[/C][C]0.119083[/C][C]131.254[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 34 )[/C][C]15.6377[/C][C]0.11855[/C][C]131.908[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 34 )[/C][C]15.6418[/C][C]0.117838[/C][C]132.74[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 34 )[/C][C]15.6462[/C][C]0.116913[/C][C]133.827[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 34 )[/C][C]15.6508[/C][C]0.115733[/C][C]135.232[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 34 )[/C][C]15.6557[/C][C]0.114246[/C][C]137.036[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 34 )[/C][C]15.661[/C][C]0.112384[/C][C]139.353[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 34 )[/C][C]15.6667[/C][C]0.110062[/C][C]142.344[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 34 )[/C][C]15.6727[/C][C]0.107166[/C][C]146.247[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 34 )[/C][C]15.6792[/C][C]0.103542[/C][C]151.428[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 34 )[/C][C]15.6863[/C][C]0.0989759[/C][C]158.486[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 34 )[/C][C]15.6939[/C][C]0.0931501[/C][C]168.479[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 34 )[/C][C]15.7021[/C][C]0.0855677[/C][C]183.505[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 34 )[/C][C]15.6889[/C][C]0.0830129[/C][C]188.993[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 34 )[/C][C]15.6889[/C][C]0.0795957[/C][C]197.107[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 34 )[/C][C]15.6744[/C][C]0.0749777[/C][C]209.054[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 34 )[/C][C]15.6585[/C][C]0.0764719[/C][C]204.762[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 34 )[/C][C]15.6757[/C][C]0.0780203[/C][C]200.918[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 34 )[/C][C]15.6857[/C][C]0.0796149[/C][C]197.02[/C][/ROW]
[ROW][C]Median[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]NA[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]15.7013[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]169[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=317172&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=317172&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 MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 34 )15.47570.17981386.0655
Winsorized Mean ( 2 / 34 )15.47570.17981386.0655
Winsorized Mean ( 3 / 34 )15.44660.17492188.3061
Winsorized Mean ( 4 / 34 )15.48540.16606493.2496
Winsorized Mean ( 5 / 34 )15.48540.16606493.2496
Winsorized Mean ( 6 / 34 )15.48540.16606493.2496
Winsorized Mean ( 7 / 34 )15.55340.153473101.343
Winsorized Mean ( 8 / 34 )15.55340.153473101.343
Winsorized Mean ( 9 / 34 )15.55340.153473101.343
Winsorized Mean ( 10 / 34 )15.55340.153473101.343
Winsorized Mean ( 11 / 34 )15.44660.139161110.998
Winsorized Mean ( 12 / 34 )15.44660.139161110.998
Winsorized Mean ( 13 / 34 )15.44660.139161110.998
Winsorized Mean ( 14 / 34 )15.44660.139161110.998
Winsorized Mean ( 15 / 34 )15.59220.116616133.706
Winsorized Mean ( 16 / 34 )15.59220.116616133.706
Winsorized Mean ( 17 / 34 )15.59220.116616133.706
Winsorized Mean ( 18 / 34 )15.59220.116616133.706
Winsorized Mean ( 19 / 34 )15.59220.116616133.706
Winsorized Mean ( 20 / 34 )15.59220.116616133.706
Winsorized Mean ( 21 / 34 )15.59220.116616133.706
Winsorized Mean ( 22 / 34 )15.59220.116616133.706
Winsorized Mean ( 23 / 34 )15.59220.116616133.706
Winsorized Mean ( 24 / 34 )15.59220.116616133.706
Winsorized Mean ( 25 / 34 )15.59220.116616133.706
Winsorized Mean ( 26 / 34 )15.59220.116616133.706
Winsorized Mean ( 27 / 34 )15.59220.116616133.706
Winsorized Mean ( 28 / 34 )15.86410.0839812188.9
Winsorized Mean ( 29 / 34 )15.86410.0839812188.9
Winsorized Mean ( 30 / 34 )15.86410.0839812188.9
Winsorized Mean ( 31 / 34 )15.56310.0491115316.894
Winsorized Mean ( 32 / 34 )15.56310.0491115316.894
Winsorized Mean ( 33 / 34 )15.56310.0491115316.894
Winsorized Mean ( 34 / 34 )15.56310.0491115316.894
Trimmed Mean ( 1 / 34 )15.47570.17440988.7323
Trimmed Mean ( 2 / 34 )15.48510.16828192.0193
Trimmed Mean ( 3 / 34 )15.50520.1612996.132
Trimmed Mean ( 4 / 34 )15.50520.15541299.7683
Trimmed Mean ( 5 / 34 )15.53760.151785102.366
Trimmed Mean ( 6 / 34 )15.54950.147642105.318
Trimmed Mean ( 7 / 34 )15.56180.14289108.908
Trimmed Mean ( 8 / 34 )15.56180.14036110.871
Trimmed Mean ( 9 / 34 )15.56470.137451113.238
Trimmed Mean ( 10 / 34 )15.56630.134097116.082
Trimmed Mean ( 11 / 34 )15.56790.130216119.554
Trimmed Mean ( 12 / 34 )15.58230.128163121.582
Trimmed Mean ( 13 / 34 )15.59740.125737124.047
Trimmed Mean ( 14 / 34 )15.61330.122869127.073
Trimmed Mean ( 15 / 34 )15.61330.119466130.693
Trimmed Mean ( 16 / 34 )15.63010.119083131.254
Trimmed Mean ( 17 / 34 )15.63770.11855131.908
Trimmed Mean ( 18 / 34 )15.64180.117838132.74
Trimmed Mean ( 19 / 34 )15.64620.116913133.827
Trimmed Mean ( 20 / 34 )15.65080.115733135.232
Trimmed Mean ( 21 / 34 )15.65570.114246137.036
Trimmed Mean ( 22 / 34 )15.6610.112384139.353
Trimmed Mean ( 23 / 34 )15.66670.110062142.344
Trimmed Mean ( 24 / 34 )15.67270.107166146.247
Trimmed Mean ( 25 / 34 )15.67920.103542151.428
Trimmed Mean ( 26 / 34 )15.68630.0989759158.486
Trimmed Mean ( 27 / 34 )15.69390.0931501168.479
Trimmed Mean ( 28 / 34 )15.70210.0855677183.505
Trimmed Mean ( 29 / 34 )15.68890.0830129188.993
Trimmed Mean ( 30 / 34 )15.68890.0795957197.107
Trimmed Mean ( 31 / 34 )15.67440.0749777209.054
Trimmed Mean ( 32 / 34 )15.65850.0764719204.762
Trimmed Mean ( 33 / 34 )15.67570.0780203200.918
Trimmed Mean ( 34 / 34 )15.68570.0796149197.02
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp15.7013
Midmean - Weighted Average at X(n+1)p15.7013
Midmean - Empirical Distribution Function15.7013
Midmean - Empirical Distribution Function - Averaging15.7013
Midmean - Empirical Distribution Function - Interpolation15.7013
Midmean - Closest Observation15.7013
Midmean - True Basic - Statistics Graphics Toolkit15.7013
Midmean - MS Excel (old versions)15.7013
Number of observations169



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')