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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, 15 Dec 2016 11:43:36 +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/2016/Dec/15/t1481798660s7e15g4noumsefm.htm/, Retrieved Fri, 03 May 2024 10:25:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299845, Retrieved Fri, 03 May 2024 10:25:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Mediaan Tevredenheid] [2016-12-15 10:43:36] [6fe662842930c5949e61d44eeb8a265b] [Current]
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Dataseries X:
13
16
17
16
17
17
15
16
14
16
17
16
16
16
15
16
16
13
15
17
13
17
14
14
18
17
13
16
15
15
15
13
17
11
14
13
17
16
17
16
16
16
15
12
17
14
14
16
15
16
14
15
17
10
17
20
17
18
14
17
17
16
18
18
16
15
13
16
12
16
16
16
14
15
14
15
15
16
11
18
11
18
15
19
17
14
13
17
14
19
14
16
16
15
12
17
18
15
18
15
16
16




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299845&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=299845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299845&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean15.46080.18572283.2469
Geometric Mean15.341
Harmonic Mean15.2128
Quadratic Mean15.573
Winsorized Mean ( 1 / 34 )15.46080.18095785.439
Winsorized Mean ( 2 / 34 )15.46080.18095785.439
Winsorized Mean ( 3 / 34 )15.43140.17597487.6913
Winsorized Mean ( 4 / 34 )15.47060.16702992.6223
Winsorized Mean ( 5 / 34 )15.47060.16702992.6223
Winsorized Mean ( 6 / 34 )15.47060.16702992.6223
Winsorized Mean ( 7 / 34 )15.53920.154321100.694
Winsorized Mean ( 8 / 34 )15.53920.154321100.694
Winsorized Mean ( 9 / 34 )15.53920.154321100.694
Winsorized Mean ( 10 / 34 )15.53920.154321100.694
Winsorized Mean ( 11 / 34 )15.43140.139688110.47
Winsorized Mean ( 12 / 34 )15.43140.139688110.47
Winsorized Mean ( 13 / 34 )15.43140.139688110.47
Winsorized Mean ( 14 / 34 )15.43140.139688110.47
Winsorized Mean ( 15 / 34 )15.57840.116937133.221
Winsorized Mean ( 16 / 34 )15.57840.116937133.221
Winsorized Mean ( 17 / 34 )15.57840.116937133.221
Winsorized Mean ( 18 / 34 )15.57840.116937133.221
Winsorized Mean ( 19 / 34 )15.57840.116937133.221
Winsorized Mean ( 20 / 34 )15.57840.116937133.221
Winsorized Mean ( 21 / 34 )15.57840.116937133.221
Winsorized Mean ( 22 / 34 )15.57840.116937133.221
Winsorized Mean ( 23 / 34 )15.57840.116937133.221
Winsorized Mean ( 24 / 34 )15.57840.116937133.221
Winsorized Mean ( 25 / 34 )15.57840.116937133.221
Winsorized Mean ( 26 / 34 )15.57840.116937133.221
Winsorized Mean ( 27 / 34 )15.57840.116937133.221
Winsorized Mean ( 28 / 34 )15.85290.0840596188.592
Winsorized Mean ( 29 / 34 )15.85290.0840596188.592
Winsorized Mean ( 30 / 34 )15.55880.0494064314.915
Winsorized Mean ( 31 / 34 )15.55880.0494064314.915
Winsorized Mean ( 32 / 34 )15.55880.0494064314.915
Winsorized Mean ( 33 / 34 )15.55880.0494064314.915
Winsorized Mean ( 34 / 34 )15.55880.0494064314.915
Trimmed Mean ( 1 / 34 )15.470.17549688.15
Trimmed Mean ( 2 / 34 )15.47960.16929891.434
Trimmed Mean ( 3 / 34 )15.48960.16221895.4863
Trimmed Mean ( 4 / 34 )15.51060.15627399.2538
Trimmed Mean ( 5 / 34 )15.52170.1526101.715
Trimmed Mean ( 6 / 34 )15.53330.1484104.672
Trimmed Mean ( 7 / 34 )15.54550.143575108.274
Trimmed Mean ( 8 / 34 )15.54650.140992110.265
Trimmed Mean ( 9 / 34 )15.54760.138018112.649
Trimmed Mean ( 10 / 34 )15.54880.134584115.532
Trimmed Mean ( 11 / 34 )15.550.130602119.064
Trimmed Mean ( 12 / 34 )15.56410.128504121.117
Trimmed Mean ( 13 / 34 )15.57890.126023123.62
Trimmed Mean ( 14 / 34 )15.59460.123083126.699
Trimmed Mean ( 15 / 34 )15.61110.11959130.538
Trimmed Mean ( 16 / 34 )15.61430.119164131.032
Trimmed Mean ( 17 / 34 )15.61760.118576131.71
Trimmed Mean ( 18 / 34 )15.62120.117799132.609
Trimmed Mean ( 19 / 34 )15.6250.116794133.782
Trimmed Mean ( 20 / 34 )15.6290.115517135.296
Trimmed Mean ( 21 / 34 )15.63330.11391137.243
Trimmed Mean ( 22 / 34 )15.63790.1119139.749
Trimmed Mean ( 23 / 34 )15.64290.109392142.998
Trimmed Mean ( 24 / 34 )15.64810.106259147.264
Trimmed Mean ( 25 / 34 )15.65380.102328152.977
Trimmed Mean ( 26 / 34 )15.660.0973527160.858
Trimmed Mean ( 27 / 34 )15.66670.0909628172.232
Trimmed Mean ( 28 / 34 )15.67390.0825578189.854
Trimmed Mean ( 29 / 34 )15.65910.0792618197.562
Trimmed Mean ( 30 / 34 )15.64290.0748318209.04
Trimmed Mean ( 31 / 34 )15.64290.0763763204.813
Trimmed Mean ( 32 / 34 )15.65790.0779933200.76
Trimmed Mean ( 33 / 34 )15.66670.0796819196.615
Trimmed Mean ( 34 / 34 )15.67650.0814375192.497
Median16
Midrange15
Midmean - Weighted Average at Xnp15.6842
Midmean - Weighted Average at X(n+1)p15.6842
Midmean - Empirical Distribution Function15.6842
Midmean - Empirical Distribution Function - Averaging15.6842
Midmean - Empirical Distribution Function - Interpolation15.6842
Midmean - Closest Observation15.6842
Midmean - True Basic - Statistics Graphics Toolkit15.6842
Midmean - MS Excel (old versions)15.6842
Number of observations102

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 15.4608 & 0.185722 & 83.2469 \tabularnewline
Geometric Mean & 15.341 &  &  \tabularnewline
Harmonic Mean & 15.2128 &  &  \tabularnewline
Quadratic Mean & 15.573 &  &  \tabularnewline
Winsorized Mean ( 1 / 34 ) & 15.4608 & 0.180957 & 85.439 \tabularnewline
Winsorized Mean ( 2 / 34 ) & 15.4608 & 0.180957 & 85.439 \tabularnewline
Winsorized Mean ( 3 / 34 ) & 15.4314 & 0.175974 & 87.6913 \tabularnewline
Winsorized Mean ( 4 / 34 ) & 15.4706 & 0.167029 & 92.6223 \tabularnewline
Winsorized Mean ( 5 / 34 ) & 15.4706 & 0.167029 & 92.6223 \tabularnewline
Winsorized Mean ( 6 / 34 ) & 15.4706 & 0.167029 & 92.6223 \tabularnewline
Winsorized Mean ( 7 / 34 ) & 15.5392 & 0.154321 & 100.694 \tabularnewline
Winsorized Mean ( 8 / 34 ) & 15.5392 & 0.154321 & 100.694 \tabularnewline
Winsorized Mean ( 9 / 34 ) & 15.5392 & 0.154321 & 100.694 \tabularnewline
Winsorized Mean ( 10 / 34 ) & 15.5392 & 0.154321 & 100.694 \tabularnewline
Winsorized Mean ( 11 / 34 ) & 15.4314 & 0.139688 & 110.47 \tabularnewline
Winsorized Mean ( 12 / 34 ) & 15.4314 & 0.139688 & 110.47 \tabularnewline
Winsorized Mean ( 13 / 34 ) & 15.4314 & 0.139688 & 110.47 \tabularnewline
Winsorized Mean ( 14 / 34 ) & 15.4314 & 0.139688 & 110.47 \tabularnewline
Winsorized Mean ( 15 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 16 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 17 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 18 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 19 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 20 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 21 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 22 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 23 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 24 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 25 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 26 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 27 / 34 ) & 15.5784 & 0.116937 & 133.221 \tabularnewline
Winsorized Mean ( 28 / 34 ) & 15.8529 & 0.0840596 & 188.592 \tabularnewline
Winsorized Mean ( 29 / 34 ) & 15.8529 & 0.0840596 & 188.592 \tabularnewline
Winsorized Mean ( 30 / 34 ) & 15.5588 & 0.0494064 & 314.915 \tabularnewline
Winsorized Mean ( 31 / 34 ) & 15.5588 & 0.0494064 & 314.915 \tabularnewline
Winsorized Mean ( 32 / 34 ) & 15.5588 & 0.0494064 & 314.915 \tabularnewline
Winsorized Mean ( 33 / 34 ) & 15.5588 & 0.0494064 & 314.915 \tabularnewline
Winsorized Mean ( 34 / 34 ) & 15.5588 & 0.0494064 & 314.915 \tabularnewline
Trimmed Mean ( 1 / 34 ) & 15.47 & 0.175496 & 88.15 \tabularnewline
Trimmed Mean ( 2 / 34 ) & 15.4796 & 0.169298 & 91.434 \tabularnewline
Trimmed Mean ( 3 / 34 ) & 15.4896 & 0.162218 & 95.4863 \tabularnewline
Trimmed Mean ( 4 / 34 ) & 15.5106 & 0.156273 & 99.2538 \tabularnewline
Trimmed Mean ( 5 / 34 ) & 15.5217 & 0.1526 & 101.715 \tabularnewline
Trimmed Mean ( 6 / 34 ) & 15.5333 & 0.1484 & 104.672 \tabularnewline
Trimmed Mean ( 7 / 34 ) & 15.5455 & 0.143575 & 108.274 \tabularnewline
Trimmed Mean ( 8 / 34 ) & 15.5465 & 0.140992 & 110.265 \tabularnewline
Trimmed Mean ( 9 / 34 ) & 15.5476 & 0.138018 & 112.649 \tabularnewline
Trimmed Mean ( 10 / 34 ) & 15.5488 & 0.134584 & 115.532 \tabularnewline
Trimmed Mean ( 11 / 34 ) & 15.55 & 0.130602 & 119.064 \tabularnewline
Trimmed Mean ( 12 / 34 ) & 15.5641 & 0.128504 & 121.117 \tabularnewline
Trimmed Mean ( 13 / 34 ) & 15.5789 & 0.126023 & 123.62 \tabularnewline
Trimmed Mean ( 14 / 34 ) & 15.5946 & 0.123083 & 126.699 \tabularnewline
Trimmed Mean ( 15 / 34 ) & 15.6111 & 0.11959 & 130.538 \tabularnewline
Trimmed Mean ( 16 / 34 ) & 15.6143 & 0.119164 & 131.032 \tabularnewline
Trimmed Mean ( 17 / 34 ) & 15.6176 & 0.118576 & 131.71 \tabularnewline
Trimmed Mean ( 18 / 34 ) & 15.6212 & 0.117799 & 132.609 \tabularnewline
Trimmed Mean ( 19 / 34 ) & 15.625 & 0.116794 & 133.782 \tabularnewline
Trimmed Mean ( 20 / 34 ) & 15.629 & 0.115517 & 135.296 \tabularnewline
Trimmed Mean ( 21 / 34 ) & 15.6333 & 0.11391 & 137.243 \tabularnewline
Trimmed Mean ( 22 / 34 ) & 15.6379 & 0.1119 & 139.749 \tabularnewline
Trimmed Mean ( 23 / 34 ) & 15.6429 & 0.109392 & 142.998 \tabularnewline
Trimmed Mean ( 24 / 34 ) & 15.6481 & 0.106259 & 147.264 \tabularnewline
Trimmed Mean ( 25 / 34 ) & 15.6538 & 0.102328 & 152.977 \tabularnewline
Trimmed Mean ( 26 / 34 ) & 15.66 & 0.0973527 & 160.858 \tabularnewline
Trimmed Mean ( 27 / 34 ) & 15.6667 & 0.0909628 & 172.232 \tabularnewline
Trimmed Mean ( 28 / 34 ) & 15.6739 & 0.0825578 & 189.854 \tabularnewline
Trimmed Mean ( 29 / 34 ) & 15.6591 & 0.0792618 & 197.562 \tabularnewline
Trimmed Mean ( 30 / 34 ) & 15.6429 & 0.0748318 & 209.04 \tabularnewline
Trimmed Mean ( 31 / 34 ) & 15.6429 & 0.0763763 & 204.813 \tabularnewline
Trimmed Mean ( 32 / 34 ) & 15.6579 & 0.0779933 & 200.76 \tabularnewline
Trimmed Mean ( 33 / 34 ) & 15.6667 & 0.0796819 & 196.615 \tabularnewline
Trimmed Mean ( 34 / 34 ) & 15.6765 & 0.0814375 & 192.497 \tabularnewline
Median & 16 &  &  \tabularnewline
Midrange & 15 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 15.6842 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 15.6842 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 15.6842 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 15.6842 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 15.6842 &  &  \tabularnewline
Midmean - Closest Observation & 15.6842 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 15.6842 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 15.6842 &  &  \tabularnewline
Number of observations & 102 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299845&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]15.4608[/C][C]0.185722[/C][C]83.2469[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]15.341[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]15.2128[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]15.573[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 34 )[/C][C]15.4608[/C][C]0.180957[/C][C]85.439[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 34 )[/C][C]15.4608[/C][C]0.180957[/C][C]85.439[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 34 )[/C][C]15.4314[/C][C]0.175974[/C][C]87.6913[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 34 )[/C][C]15.4706[/C][C]0.167029[/C][C]92.6223[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 34 )[/C][C]15.4706[/C][C]0.167029[/C][C]92.6223[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 34 )[/C][C]15.4706[/C][C]0.167029[/C][C]92.6223[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 34 )[/C][C]15.5392[/C][C]0.154321[/C][C]100.694[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 34 )[/C][C]15.5392[/C][C]0.154321[/C][C]100.694[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 34 )[/C][C]15.5392[/C][C]0.154321[/C][C]100.694[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 34 )[/C][C]15.5392[/C][C]0.154321[/C][C]100.694[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 34 )[/C][C]15.4314[/C][C]0.139688[/C][C]110.47[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 34 )[/C][C]15.4314[/C][C]0.139688[/C][C]110.47[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 34 )[/C][C]15.4314[/C][C]0.139688[/C][C]110.47[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 34 )[/C][C]15.4314[/C][C]0.139688[/C][C]110.47[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 34 )[/C][C]15.5784[/C][C]0.116937[/C][C]133.221[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 34 )[/C][C]15.8529[/C][C]0.0840596[/C][C]188.592[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 34 )[/C][C]15.8529[/C][C]0.0840596[/C][C]188.592[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 34 )[/C][C]15.5588[/C][C]0.0494064[/C][C]314.915[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 34 )[/C][C]15.5588[/C][C]0.0494064[/C][C]314.915[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 34 )[/C][C]15.5588[/C][C]0.0494064[/C][C]314.915[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 34 )[/C][C]15.5588[/C][C]0.0494064[/C][C]314.915[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 34 )[/C][C]15.5588[/C][C]0.0494064[/C][C]314.915[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 34 )[/C][C]15.47[/C][C]0.175496[/C][C]88.15[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 34 )[/C][C]15.4796[/C][C]0.169298[/C][C]91.434[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 34 )[/C][C]15.4896[/C][C]0.162218[/C][C]95.4863[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 34 )[/C][C]15.5106[/C][C]0.156273[/C][C]99.2538[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 34 )[/C][C]15.5217[/C][C]0.1526[/C][C]101.715[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 34 )[/C][C]15.5333[/C][C]0.1484[/C][C]104.672[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 34 )[/C][C]15.5455[/C][C]0.143575[/C][C]108.274[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 34 )[/C][C]15.5465[/C][C]0.140992[/C][C]110.265[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 34 )[/C][C]15.5476[/C][C]0.138018[/C][C]112.649[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 34 )[/C][C]15.5488[/C][C]0.134584[/C][C]115.532[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 34 )[/C][C]15.55[/C][C]0.130602[/C][C]119.064[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 34 )[/C][C]15.5641[/C][C]0.128504[/C][C]121.117[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 34 )[/C][C]15.5789[/C][C]0.126023[/C][C]123.62[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 34 )[/C][C]15.5946[/C][C]0.123083[/C][C]126.699[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 34 )[/C][C]15.6111[/C][C]0.11959[/C][C]130.538[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 34 )[/C][C]15.6143[/C][C]0.119164[/C][C]131.032[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 34 )[/C][C]15.6176[/C][C]0.118576[/C][C]131.71[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 34 )[/C][C]15.6212[/C][C]0.117799[/C][C]132.609[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 34 )[/C][C]15.625[/C][C]0.116794[/C][C]133.782[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 34 )[/C][C]15.629[/C][C]0.115517[/C][C]135.296[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 34 )[/C][C]15.6333[/C][C]0.11391[/C][C]137.243[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 34 )[/C][C]15.6379[/C][C]0.1119[/C][C]139.749[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 34 )[/C][C]15.6429[/C][C]0.109392[/C][C]142.998[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 34 )[/C][C]15.6481[/C][C]0.106259[/C][C]147.264[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 34 )[/C][C]15.6538[/C][C]0.102328[/C][C]152.977[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 34 )[/C][C]15.66[/C][C]0.0973527[/C][C]160.858[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 34 )[/C][C]15.6667[/C][C]0.0909628[/C][C]172.232[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 34 )[/C][C]15.6739[/C][C]0.0825578[/C][C]189.854[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 34 )[/C][C]15.6591[/C][C]0.0792618[/C][C]197.562[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 34 )[/C][C]15.6429[/C][C]0.0748318[/C][C]209.04[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 34 )[/C][C]15.6429[/C][C]0.0763763[/C][C]204.813[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 34 )[/C][C]15.6579[/C][C]0.0779933[/C][C]200.76[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 34 )[/C][C]15.6667[/C][C]0.0796819[/C][C]196.615[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 34 )[/C][C]15.6765[/C][C]0.0814375[/C][C]192.497[/C][/ROW]
[ROW][C]Median[/C][C]16[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]15[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]15.6842[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]102[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299845&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 Mean15.46080.18572283.2469
Geometric Mean15.341
Harmonic Mean15.2128
Quadratic Mean15.573
Winsorized Mean ( 1 / 34 )15.46080.18095785.439
Winsorized Mean ( 2 / 34 )15.46080.18095785.439
Winsorized Mean ( 3 / 34 )15.43140.17597487.6913
Winsorized Mean ( 4 / 34 )15.47060.16702992.6223
Winsorized Mean ( 5 / 34 )15.47060.16702992.6223
Winsorized Mean ( 6 / 34 )15.47060.16702992.6223
Winsorized Mean ( 7 / 34 )15.53920.154321100.694
Winsorized Mean ( 8 / 34 )15.53920.154321100.694
Winsorized Mean ( 9 / 34 )15.53920.154321100.694
Winsorized Mean ( 10 / 34 )15.53920.154321100.694
Winsorized Mean ( 11 / 34 )15.43140.139688110.47
Winsorized Mean ( 12 / 34 )15.43140.139688110.47
Winsorized Mean ( 13 / 34 )15.43140.139688110.47
Winsorized Mean ( 14 / 34 )15.43140.139688110.47
Winsorized Mean ( 15 / 34 )15.57840.116937133.221
Winsorized Mean ( 16 / 34 )15.57840.116937133.221
Winsorized Mean ( 17 / 34 )15.57840.116937133.221
Winsorized Mean ( 18 / 34 )15.57840.116937133.221
Winsorized Mean ( 19 / 34 )15.57840.116937133.221
Winsorized Mean ( 20 / 34 )15.57840.116937133.221
Winsorized Mean ( 21 / 34 )15.57840.116937133.221
Winsorized Mean ( 22 / 34 )15.57840.116937133.221
Winsorized Mean ( 23 / 34 )15.57840.116937133.221
Winsorized Mean ( 24 / 34 )15.57840.116937133.221
Winsorized Mean ( 25 / 34 )15.57840.116937133.221
Winsorized Mean ( 26 / 34 )15.57840.116937133.221
Winsorized Mean ( 27 / 34 )15.57840.116937133.221
Winsorized Mean ( 28 / 34 )15.85290.0840596188.592
Winsorized Mean ( 29 / 34 )15.85290.0840596188.592
Winsorized Mean ( 30 / 34 )15.55880.0494064314.915
Winsorized Mean ( 31 / 34 )15.55880.0494064314.915
Winsorized Mean ( 32 / 34 )15.55880.0494064314.915
Winsorized Mean ( 33 / 34 )15.55880.0494064314.915
Winsorized Mean ( 34 / 34 )15.55880.0494064314.915
Trimmed Mean ( 1 / 34 )15.470.17549688.15
Trimmed Mean ( 2 / 34 )15.47960.16929891.434
Trimmed Mean ( 3 / 34 )15.48960.16221895.4863
Trimmed Mean ( 4 / 34 )15.51060.15627399.2538
Trimmed Mean ( 5 / 34 )15.52170.1526101.715
Trimmed Mean ( 6 / 34 )15.53330.1484104.672
Trimmed Mean ( 7 / 34 )15.54550.143575108.274
Trimmed Mean ( 8 / 34 )15.54650.140992110.265
Trimmed Mean ( 9 / 34 )15.54760.138018112.649
Trimmed Mean ( 10 / 34 )15.54880.134584115.532
Trimmed Mean ( 11 / 34 )15.550.130602119.064
Trimmed Mean ( 12 / 34 )15.56410.128504121.117
Trimmed Mean ( 13 / 34 )15.57890.126023123.62
Trimmed Mean ( 14 / 34 )15.59460.123083126.699
Trimmed Mean ( 15 / 34 )15.61110.11959130.538
Trimmed Mean ( 16 / 34 )15.61430.119164131.032
Trimmed Mean ( 17 / 34 )15.61760.118576131.71
Trimmed Mean ( 18 / 34 )15.62120.117799132.609
Trimmed Mean ( 19 / 34 )15.6250.116794133.782
Trimmed Mean ( 20 / 34 )15.6290.115517135.296
Trimmed Mean ( 21 / 34 )15.63330.11391137.243
Trimmed Mean ( 22 / 34 )15.63790.1119139.749
Trimmed Mean ( 23 / 34 )15.64290.109392142.998
Trimmed Mean ( 24 / 34 )15.64810.106259147.264
Trimmed Mean ( 25 / 34 )15.65380.102328152.977
Trimmed Mean ( 26 / 34 )15.660.0973527160.858
Trimmed Mean ( 27 / 34 )15.66670.0909628172.232
Trimmed Mean ( 28 / 34 )15.67390.0825578189.854
Trimmed Mean ( 29 / 34 )15.65910.0792618197.562
Trimmed Mean ( 30 / 34 )15.64290.0748318209.04
Trimmed Mean ( 31 / 34 )15.64290.0763763204.813
Trimmed Mean ( 32 / 34 )15.65790.0779933200.76
Trimmed Mean ( 33 / 34 )15.66670.0796819196.615
Trimmed Mean ( 34 / 34 )15.67650.0814375192.497
Median16
Midrange15
Midmean - Weighted Average at Xnp15.6842
Midmean - Weighted Average at X(n+1)p15.6842
Midmean - Empirical Distribution Function15.6842
Midmean - Empirical Distribution Function - Averaging15.6842
Midmean - Empirical Distribution Function - Interpolation15.6842
Midmean - Closest Observation15.6842
Midmean - True Basic - Statistics Graphics Toolkit15.6842
Midmean - MS Excel (old versions)15.6842
Number of observations102



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')