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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, 23 Jan 2017 09:50:57 +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/Jan/23/t1485161512f6913buxa51pavc.htm/, Retrieved Wed, 15 May 2024 06:34:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=304115, Retrieved Wed, 15 May 2024 06:34:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [vraag 11] [2017-01-23 08:50:57] [cedc5386ad7644fa02c81dc221bdf6b7] [Current]
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Dataseries X:
14
19
17
17
15
20
15
19
15
15
19
NA
20
18
15
14
20
NA
16
16
16
10
19
19
16
15
18
17
19
17
NA
19
20
5
19
16
15
16
18
16
15
17
NA
20
19
7
13
16
16
NA
18
18
16
17
19
16
19
13
16
13
12
17
17
17
16
16
14
16
13
16
14
20
12
13
18
14
19
18
14
18
19
15
14
17
19
13
19
18
20
15
15
15
20
15
19
18
18
15
20
17
12
18
19
20
NA
17
15
16
18
18
14
15
12
17
14
18
17
17
20
16
14
15
18
20
17
17
17
17
15
17
18
17
20
15
16
15
18
11
15
18
20
19
14
16
15
17
18
20
17
18
15
16
11
15
18
17
16
12
19
18
15
17
19
18
19
16
16
16
14




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=304115&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=304115&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304115&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 MeanNANANA
Geometric MeanNA
Harmonic MeanNA
Quadratic MeanNA
Winsorized Mean ( 1 / 54 )16.46010.1917185.8596
Winsorized Mean ( 2 / 54 )16.49690.18200890.6385
Winsorized Mean ( 3 / 54 )16.51530.17821992.6686
Winsorized Mean ( 4 / 54 )16.51530.17821992.6686
Winsorized Mean ( 5 / 54 )16.5460.17279295.7569
Winsorized Mean ( 6 / 54 )16.5460.17279295.7569
Winsorized Mean ( 7 / 54 )16.5460.17279295.7569
Winsorized Mean ( 8 / 54 )16.5460.17279295.7569
Winsorized Mean ( 9 / 54 )16.5460.17279295.7569
Winsorized Mean ( 10 / 54 )16.60740.163613101.504
Winsorized Mean ( 11 / 54 )16.60740.163613101.504
Winsorized Mean ( 12 / 54 )16.60740.163613101.504
Winsorized Mean ( 13 / 54 )16.60740.163613101.504
Winsorized Mean ( 14 / 54 )16.60740.163613101.504
Winsorized Mean ( 15 / 54 )16.51530.153071107.893
Winsorized Mean ( 16 / 54 )16.61350.140418118.315
Winsorized Mean ( 17 / 54 )16.61350.140418118.315
Winsorized Mean ( 18 / 54 )16.61350.140418118.315
Winsorized Mean ( 19 / 54 )16.61350.140418118.315
Winsorized Mean ( 20 / 54 )16.61350.140418118.315
Winsorized Mean ( 21 / 54 )16.61350.140418118.315
Winsorized Mean ( 22 / 54 )16.61350.140418118.315
Winsorized Mean ( 23 / 54 )16.61350.140418118.315
Winsorized Mean ( 24 / 54 )16.61350.140418118.315
Winsorized Mean ( 25 / 54 )16.61350.140418118.315
Winsorized Mean ( 26 / 54 )16.61350.140418118.315
Winsorized Mean ( 27 / 54 )16.61350.140418118.315
Winsorized Mean ( 28 / 54 )16.78530.12269136.811
Winsorized Mean ( 29 / 54 )16.78530.12269136.811
Winsorized Mean ( 30 / 54 )16.78530.12269136.811
Winsorized Mean ( 31 / 54 )16.78530.12269136.811
Winsorized Mean ( 32 / 54 )16.78530.12269136.811
Winsorized Mean ( 33 / 54 )16.78530.12269136.811
Winsorized Mean ( 34 / 54 )16.78530.12269136.811
Winsorized Mean ( 35 / 54 )16.78530.12269136.811
Winsorized Mean ( 36 / 54 )16.56440.100381165.016
Winsorized Mean ( 37 / 54 )16.56440.100381165.016
Winsorized Mean ( 38 / 54 )16.56440.100381165.016
Winsorized Mean ( 39 / 54 )16.56440.100381165.016
Winsorized Mean ( 40 / 54 )16.56440.100381165.016
Winsorized Mean ( 41 / 54 )16.56440.100381165.016
Winsorized Mean ( 42 / 54 )16.56440.100381165.016
Winsorized Mean ( 43 / 54 )16.56440.100381165.016
Winsorized Mean ( 44 / 54 )16.56440.100381165.016
Winsorized Mean ( 45 / 54 )16.56440.100381165.016
Winsorized Mean ( 46 / 54 )16.56440.100381165.016
Winsorized Mean ( 47 / 54 )16.56440.100381165.016
Winsorized Mean ( 48 / 54 )16.56440.100381165.016
Winsorized Mean ( 49 / 54 )16.56440.100381165.016
Winsorized Mean ( 50 / 54 )16.56440.100381165.016
Winsorized Mean ( 51 / 54 )16.56440.100381165.016
Winsorized Mean ( 52 / 54 )16.56440.100381165.016
Winsorized Mean ( 53 / 54 )16.88960.0717691235.332
Winsorized Mean ( 54 / 54 )16.88960.0717691235.332
Trimmed Mean ( 1 / 54 )16.49690.1835989.8572
Trimmed Mean ( 2 / 54 )16.53460.17456794.7177
Trimmed Mean ( 3 / 54 )16.55410.17035697.1736
Trimmed Mean ( 4 / 54 )16.56770.16729299.035
Trimmed Mean ( 5 / 54 )16.58170.163965101.129
Trimmed Mean ( 6 / 54 )16.58940.161743102.566
Trimmed Mean ( 7 / 54 )16.59730.159334104.167
Trimmed Mean ( 8 / 54 )16.60540.156718105.958
Trimmed Mean ( 9 / 54 )16.61380.153873107.971
Trimmed Mean ( 10 / 54 )16.62240.150773110.247
Trimmed Mean ( 11 / 54 )16.62410.148801111.72
Trimmed Mean ( 12 / 54 )16.62590.146653113.369
Trimmed Mean ( 13 / 54 )16.62770.144309115.223
Trimmed Mean ( 14 / 54 )16.62960.14175117.317
Trimmed Mean ( 15 / 54 )16.63160.138948119.696
Trimmed Mean ( 16 / 54 )16.64120.137107121.374
Trimmed Mean ( 17 / 54 )16.64340.136487121.941
Trimmed Mean ( 18 / 54 )16.64570.135789122.585
Trimmed Mean ( 19 / 54 )16.6480.135006123.313
Trimmed Mean ( 20 / 54 )16.65040.134129124.137
Trimmed Mean ( 21 / 54 )16.65290.133149125.069
Trimmed Mean ( 22 / 54 )16.65550.132056126.125
Trimmed Mean ( 23 / 54 )16.65810.130836127.321
Trimmed Mean ( 24 / 54 )16.66090.129475128.68
Trimmed Mean ( 25 / 54 )16.66370.127958130.228
Trimmed Mean ( 26 / 54 )16.66670.126266131.996
Trimmed Mean ( 27 / 54 )16.66670.124378134.001
Trimmed Mean ( 28 / 54 )16.67290.122266136.366
Trimmed Mean ( 29 / 54 )16.66670.121549137.119
Trimmed Mean ( 30 / 54 )16.66020.12072138.007
Trimmed Mean ( 31 / 54 )16.65350.119765139.051
Trimmed Mean ( 32 / 54 )16.64650.118669140.277
Trimmed Mean ( 33 / 54 )16.63920.117412141.716
Trimmed Mean ( 34 / 54 )16.63160.115973143.41
Trimmed Mean ( 35 / 54 )16.62370.114325145.407
Trimmed Mean ( 36 / 54 )16.61540.112437147.775
Trimmed Mean ( 37 / 54 )16.6180.112436147.799
Trimmed Mean ( 38 / 54 )16.62070.112374147.905
Trimmed Mean ( 39 / 54 )16.62350.112243148.103
Trimmed Mean ( 40 / 54 )16.62650.112031148.41
Trimmed Mean ( 41 / 54 )16.62960.111727148.842
Trimmed Mean ( 42 / 54 )16.63290.111316149.421
Trimmed Mean ( 43 / 54 )16.63290.110781150.142
Trimmed Mean ( 44 / 54 )16.640.110102151.132
Trimmed Mean ( 45 / 54 )16.64380.109256152.339
Trimmed Mean ( 46 / 54 )16.64790.108211153.846
Trimmed Mean ( 47 / 54 )16.65220.106934155.724
Trimmed Mean ( 48 / 54 )16.65670.105378158.066
Trimmed Mean ( 49 / 54 )16.66150.103489160.998
Trimmed Mean ( 50 / 54 )16.66670.101196164.697
Trimmed Mean ( 51 / 54 )16.67210.0984062169.422
Trimmed Mean ( 52 / 54 )16.6780.0949966175.564
Trimmed Mean ( 53 / 54 )16.68420.0907981183.751
Trimmed Mean ( 54 / 54 )16.68420.0900974185.18
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp16.4848
Midmean - Weighted Average at X(n+1)p16.4848
Midmean - Empirical Distribution Function16.4848
Midmean - Empirical Distribution Function - Averaging16.4848
Midmean - Empirical Distribution Function - Interpolation16.4848
Midmean - Closest Observation16.4848
Midmean - True Basic - Statistics Graphics Toolkit16.4848
Midmean - MS Excel (old versions)16.4848
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 / 54 ) & 16.4601 & 0.19171 & 85.8596 \tabularnewline
Winsorized Mean ( 2 / 54 ) & 16.4969 & 0.182008 & 90.6385 \tabularnewline
Winsorized Mean ( 3 / 54 ) & 16.5153 & 0.178219 & 92.6686 \tabularnewline
Winsorized Mean ( 4 / 54 ) & 16.5153 & 0.178219 & 92.6686 \tabularnewline
Winsorized Mean ( 5 / 54 ) & 16.546 & 0.172792 & 95.7569 \tabularnewline
Winsorized Mean ( 6 / 54 ) & 16.546 & 0.172792 & 95.7569 \tabularnewline
Winsorized Mean ( 7 / 54 ) & 16.546 & 0.172792 & 95.7569 \tabularnewline
Winsorized Mean ( 8 / 54 ) & 16.546 & 0.172792 & 95.7569 \tabularnewline
Winsorized Mean ( 9 / 54 ) & 16.546 & 0.172792 & 95.7569 \tabularnewline
Winsorized Mean ( 10 / 54 ) & 16.6074 & 0.163613 & 101.504 \tabularnewline
Winsorized Mean ( 11 / 54 ) & 16.6074 & 0.163613 & 101.504 \tabularnewline
Winsorized Mean ( 12 / 54 ) & 16.6074 & 0.163613 & 101.504 \tabularnewline
Winsorized Mean ( 13 / 54 ) & 16.6074 & 0.163613 & 101.504 \tabularnewline
Winsorized Mean ( 14 / 54 ) & 16.6074 & 0.163613 & 101.504 \tabularnewline
Winsorized Mean ( 15 / 54 ) & 16.5153 & 0.153071 & 107.893 \tabularnewline
Winsorized Mean ( 16 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 17 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 18 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 19 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 20 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 21 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 22 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 23 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 24 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 25 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 26 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 27 / 54 ) & 16.6135 & 0.140418 & 118.315 \tabularnewline
Winsorized Mean ( 28 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 29 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 30 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 31 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 32 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 33 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 34 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 35 / 54 ) & 16.7853 & 0.12269 & 136.811 \tabularnewline
Winsorized Mean ( 36 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 37 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 38 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 39 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 40 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 41 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 42 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 43 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 44 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 45 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 46 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 47 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 48 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 49 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 50 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 51 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 52 / 54 ) & 16.5644 & 0.100381 & 165.016 \tabularnewline
Winsorized Mean ( 53 / 54 ) & 16.8896 & 0.0717691 & 235.332 \tabularnewline
Winsorized Mean ( 54 / 54 ) & 16.8896 & 0.0717691 & 235.332 \tabularnewline
Trimmed Mean ( 1 / 54 ) & 16.4969 & 0.18359 & 89.8572 \tabularnewline
Trimmed Mean ( 2 / 54 ) & 16.5346 & 0.174567 & 94.7177 \tabularnewline
Trimmed Mean ( 3 / 54 ) & 16.5541 & 0.170356 & 97.1736 \tabularnewline
Trimmed Mean ( 4 / 54 ) & 16.5677 & 0.167292 & 99.035 \tabularnewline
Trimmed Mean ( 5 / 54 ) & 16.5817 & 0.163965 & 101.129 \tabularnewline
Trimmed Mean ( 6 / 54 ) & 16.5894 & 0.161743 & 102.566 \tabularnewline
Trimmed Mean ( 7 / 54 ) & 16.5973 & 0.159334 & 104.167 \tabularnewline
Trimmed Mean ( 8 / 54 ) & 16.6054 & 0.156718 & 105.958 \tabularnewline
Trimmed Mean ( 9 / 54 ) & 16.6138 & 0.153873 & 107.971 \tabularnewline
Trimmed Mean ( 10 / 54 ) & 16.6224 & 0.150773 & 110.247 \tabularnewline
Trimmed Mean ( 11 / 54 ) & 16.6241 & 0.148801 & 111.72 \tabularnewline
Trimmed Mean ( 12 / 54 ) & 16.6259 & 0.146653 & 113.369 \tabularnewline
Trimmed Mean ( 13 / 54 ) & 16.6277 & 0.144309 & 115.223 \tabularnewline
Trimmed Mean ( 14 / 54 ) & 16.6296 & 0.14175 & 117.317 \tabularnewline
Trimmed Mean ( 15 / 54 ) & 16.6316 & 0.138948 & 119.696 \tabularnewline
Trimmed Mean ( 16 / 54 ) & 16.6412 & 0.137107 & 121.374 \tabularnewline
Trimmed Mean ( 17 / 54 ) & 16.6434 & 0.136487 & 121.941 \tabularnewline
Trimmed Mean ( 18 / 54 ) & 16.6457 & 0.135789 & 122.585 \tabularnewline
Trimmed Mean ( 19 / 54 ) & 16.648 & 0.135006 & 123.313 \tabularnewline
Trimmed Mean ( 20 / 54 ) & 16.6504 & 0.134129 & 124.137 \tabularnewline
Trimmed Mean ( 21 / 54 ) & 16.6529 & 0.133149 & 125.069 \tabularnewline
Trimmed Mean ( 22 / 54 ) & 16.6555 & 0.132056 & 126.125 \tabularnewline
Trimmed Mean ( 23 / 54 ) & 16.6581 & 0.130836 & 127.321 \tabularnewline
Trimmed Mean ( 24 / 54 ) & 16.6609 & 0.129475 & 128.68 \tabularnewline
Trimmed Mean ( 25 / 54 ) & 16.6637 & 0.127958 & 130.228 \tabularnewline
Trimmed Mean ( 26 / 54 ) & 16.6667 & 0.126266 & 131.996 \tabularnewline
Trimmed Mean ( 27 / 54 ) & 16.6667 & 0.124378 & 134.001 \tabularnewline
Trimmed Mean ( 28 / 54 ) & 16.6729 & 0.122266 & 136.366 \tabularnewline
Trimmed Mean ( 29 / 54 ) & 16.6667 & 0.121549 & 137.119 \tabularnewline
Trimmed Mean ( 30 / 54 ) & 16.6602 & 0.12072 & 138.007 \tabularnewline
Trimmed Mean ( 31 / 54 ) & 16.6535 & 0.119765 & 139.051 \tabularnewline
Trimmed Mean ( 32 / 54 ) & 16.6465 & 0.118669 & 140.277 \tabularnewline
Trimmed Mean ( 33 / 54 ) & 16.6392 & 0.117412 & 141.716 \tabularnewline
Trimmed Mean ( 34 / 54 ) & 16.6316 & 0.115973 & 143.41 \tabularnewline
Trimmed Mean ( 35 / 54 ) & 16.6237 & 0.114325 & 145.407 \tabularnewline
Trimmed Mean ( 36 / 54 ) & 16.6154 & 0.112437 & 147.775 \tabularnewline
Trimmed Mean ( 37 / 54 ) & 16.618 & 0.112436 & 147.799 \tabularnewline
Trimmed Mean ( 38 / 54 ) & 16.6207 & 0.112374 & 147.905 \tabularnewline
Trimmed Mean ( 39 / 54 ) & 16.6235 & 0.112243 & 148.103 \tabularnewline
Trimmed Mean ( 40 / 54 ) & 16.6265 & 0.112031 & 148.41 \tabularnewline
Trimmed Mean ( 41 / 54 ) & 16.6296 & 0.111727 & 148.842 \tabularnewline
Trimmed Mean ( 42 / 54 ) & 16.6329 & 0.111316 & 149.421 \tabularnewline
Trimmed Mean ( 43 / 54 ) & 16.6329 & 0.110781 & 150.142 \tabularnewline
Trimmed Mean ( 44 / 54 ) & 16.64 & 0.110102 & 151.132 \tabularnewline
Trimmed Mean ( 45 / 54 ) & 16.6438 & 0.109256 & 152.339 \tabularnewline
Trimmed Mean ( 46 / 54 ) & 16.6479 & 0.108211 & 153.846 \tabularnewline
Trimmed Mean ( 47 / 54 ) & 16.6522 & 0.106934 & 155.724 \tabularnewline
Trimmed Mean ( 48 / 54 ) & 16.6567 & 0.105378 & 158.066 \tabularnewline
Trimmed Mean ( 49 / 54 ) & 16.6615 & 0.103489 & 160.998 \tabularnewline
Trimmed Mean ( 50 / 54 ) & 16.6667 & 0.101196 & 164.697 \tabularnewline
Trimmed Mean ( 51 / 54 ) & 16.6721 & 0.0984062 & 169.422 \tabularnewline
Trimmed Mean ( 52 / 54 ) & 16.678 & 0.0949966 & 175.564 \tabularnewline
Trimmed Mean ( 53 / 54 ) & 16.6842 & 0.0907981 & 183.751 \tabularnewline
Trimmed Mean ( 54 / 54 ) & 16.6842 & 0.0900974 & 185.18 \tabularnewline
Median & NA &  &  \tabularnewline
Midrange & NA &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 16.4848 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 16.4848 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 16.4848 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 16.4848 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 16.4848 &  &  \tabularnewline
Midmean - Closest Observation & 16.4848 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 16.4848 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 16.4848 &  &  \tabularnewline
Number of observations & 169 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304115&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 / 54 )[/C][C]16.4601[/C][C]0.19171[/C][C]85.8596[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 54 )[/C][C]16.4969[/C][C]0.182008[/C][C]90.6385[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 54 )[/C][C]16.5153[/C][C]0.178219[/C][C]92.6686[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 54 )[/C][C]16.5153[/C][C]0.178219[/C][C]92.6686[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 54 )[/C][C]16.546[/C][C]0.172792[/C][C]95.7569[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 54 )[/C][C]16.546[/C][C]0.172792[/C][C]95.7569[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 54 )[/C][C]16.546[/C][C]0.172792[/C][C]95.7569[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 54 )[/C][C]16.546[/C][C]0.172792[/C][C]95.7569[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 54 )[/C][C]16.546[/C][C]0.172792[/C][C]95.7569[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 54 )[/C][C]16.6074[/C][C]0.163613[/C][C]101.504[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 54 )[/C][C]16.6074[/C][C]0.163613[/C][C]101.504[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 54 )[/C][C]16.6074[/C][C]0.163613[/C][C]101.504[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 54 )[/C][C]16.6074[/C][C]0.163613[/C][C]101.504[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 54 )[/C][C]16.6074[/C][C]0.163613[/C][C]101.504[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 54 )[/C][C]16.5153[/C][C]0.153071[/C][C]107.893[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 54 )[/C][C]16.6135[/C][C]0.140418[/C][C]118.315[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 54 )[/C][C]16.7853[/C][C]0.12269[/C][C]136.811[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 37 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 38 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 39 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 40 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 41 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 42 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 43 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 44 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 45 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 46 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 47 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 48 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 49 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 50 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 51 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 52 / 54 )[/C][C]16.5644[/C][C]0.100381[/C][C]165.016[/C][/ROW]
[ROW][C]Winsorized Mean ( 53 / 54 )[/C][C]16.8896[/C][C]0.0717691[/C][C]235.332[/C][/ROW]
[ROW][C]Winsorized Mean ( 54 / 54 )[/C][C]16.8896[/C][C]0.0717691[/C][C]235.332[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 54 )[/C][C]16.4969[/C][C]0.18359[/C][C]89.8572[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 54 )[/C][C]16.5346[/C][C]0.174567[/C][C]94.7177[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 54 )[/C][C]16.5541[/C][C]0.170356[/C][C]97.1736[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 54 )[/C][C]16.5677[/C][C]0.167292[/C][C]99.035[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 54 )[/C][C]16.5817[/C][C]0.163965[/C][C]101.129[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 54 )[/C][C]16.5894[/C][C]0.161743[/C][C]102.566[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 54 )[/C][C]16.5973[/C][C]0.159334[/C][C]104.167[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 54 )[/C][C]16.6054[/C][C]0.156718[/C][C]105.958[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 54 )[/C][C]16.6138[/C][C]0.153873[/C][C]107.971[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 54 )[/C][C]16.6224[/C][C]0.150773[/C][C]110.247[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 54 )[/C][C]16.6241[/C][C]0.148801[/C][C]111.72[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 54 )[/C][C]16.6259[/C][C]0.146653[/C][C]113.369[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 54 )[/C][C]16.6277[/C][C]0.144309[/C][C]115.223[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 54 )[/C][C]16.6296[/C][C]0.14175[/C][C]117.317[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 54 )[/C][C]16.6316[/C][C]0.138948[/C][C]119.696[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 54 )[/C][C]16.6412[/C][C]0.137107[/C][C]121.374[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 54 )[/C][C]16.6434[/C][C]0.136487[/C][C]121.941[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 54 )[/C][C]16.6457[/C][C]0.135789[/C][C]122.585[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 54 )[/C][C]16.648[/C][C]0.135006[/C][C]123.313[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 54 )[/C][C]16.6504[/C][C]0.134129[/C][C]124.137[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 54 )[/C][C]16.6529[/C][C]0.133149[/C][C]125.069[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 54 )[/C][C]16.6555[/C][C]0.132056[/C][C]126.125[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 54 )[/C][C]16.6581[/C][C]0.130836[/C][C]127.321[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 54 )[/C][C]16.6609[/C][C]0.129475[/C][C]128.68[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 54 )[/C][C]16.6637[/C][C]0.127958[/C][C]130.228[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 54 )[/C][C]16.6667[/C][C]0.126266[/C][C]131.996[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 54 )[/C][C]16.6667[/C][C]0.124378[/C][C]134.001[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 54 )[/C][C]16.6729[/C][C]0.122266[/C][C]136.366[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 54 )[/C][C]16.6667[/C][C]0.121549[/C][C]137.119[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 54 )[/C][C]16.6602[/C][C]0.12072[/C][C]138.007[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 54 )[/C][C]16.6535[/C][C]0.119765[/C][C]139.051[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 54 )[/C][C]16.6465[/C][C]0.118669[/C][C]140.277[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 54 )[/C][C]16.6392[/C][C]0.117412[/C][C]141.716[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 54 )[/C][C]16.6316[/C][C]0.115973[/C][C]143.41[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 54 )[/C][C]16.6237[/C][C]0.114325[/C][C]145.407[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 54 )[/C][C]16.6154[/C][C]0.112437[/C][C]147.775[/C][/ROW]
[ROW][C]Trimmed Mean ( 37 / 54 )[/C][C]16.618[/C][C]0.112436[/C][C]147.799[/C][/ROW]
[ROW][C]Trimmed Mean ( 38 / 54 )[/C][C]16.6207[/C][C]0.112374[/C][C]147.905[/C][/ROW]
[ROW][C]Trimmed Mean ( 39 / 54 )[/C][C]16.6235[/C][C]0.112243[/C][C]148.103[/C][/ROW]
[ROW][C]Trimmed Mean ( 40 / 54 )[/C][C]16.6265[/C][C]0.112031[/C][C]148.41[/C][/ROW]
[ROW][C]Trimmed Mean ( 41 / 54 )[/C][C]16.6296[/C][C]0.111727[/C][C]148.842[/C][/ROW]
[ROW][C]Trimmed Mean ( 42 / 54 )[/C][C]16.6329[/C][C]0.111316[/C][C]149.421[/C][/ROW]
[ROW][C]Trimmed Mean ( 43 / 54 )[/C][C]16.6329[/C][C]0.110781[/C][C]150.142[/C][/ROW]
[ROW][C]Trimmed Mean ( 44 / 54 )[/C][C]16.64[/C][C]0.110102[/C][C]151.132[/C][/ROW]
[ROW][C]Trimmed Mean ( 45 / 54 )[/C][C]16.6438[/C][C]0.109256[/C][C]152.339[/C][/ROW]
[ROW][C]Trimmed Mean ( 46 / 54 )[/C][C]16.6479[/C][C]0.108211[/C][C]153.846[/C][/ROW]
[ROW][C]Trimmed Mean ( 47 / 54 )[/C][C]16.6522[/C][C]0.106934[/C][C]155.724[/C][/ROW]
[ROW][C]Trimmed Mean ( 48 / 54 )[/C][C]16.6567[/C][C]0.105378[/C][C]158.066[/C][/ROW]
[ROW][C]Trimmed Mean ( 49 / 54 )[/C][C]16.6615[/C][C]0.103489[/C][C]160.998[/C][/ROW]
[ROW][C]Trimmed Mean ( 50 / 54 )[/C][C]16.6667[/C][C]0.101196[/C][C]164.697[/C][/ROW]
[ROW][C]Trimmed Mean ( 51 / 54 )[/C][C]16.6721[/C][C]0.0984062[/C][C]169.422[/C][/ROW]
[ROW][C]Trimmed Mean ( 52 / 54 )[/C][C]16.678[/C][C]0.0949966[/C][C]175.564[/C][/ROW]
[ROW][C]Trimmed Mean ( 53 / 54 )[/C][C]16.6842[/C][C]0.0907981[/C][C]183.751[/C][/ROW]
[ROW][C]Trimmed Mean ( 54 / 54 )[/C][C]16.6842[/C][C]0.0900974[/C][C]185.18[/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]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]16.4848[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]16.4848[/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=304115&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304115&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 / 54 )16.46010.1917185.8596
Winsorized Mean ( 2 / 54 )16.49690.18200890.6385
Winsorized Mean ( 3 / 54 )16.51530.17821992.6686
Winsorized Mean ( 4 / 54 )16.51530.17821992.6686
Winsorized Mean ( 5 / 54 )16.5460.17279295.7569
Winsorized Mean ( 6 / 54 )16.5460.17279295.7569
Winsorized Mean ( 7 / 54 )16.5460.17279295.7569
Winsorized Mean ( 8 / 54 )16.5460.17279295.7569
Winsorized Mean ( 9 / 54 )16.5460.17279295.7569
Winsorized Mean ( 10 / 54 )16.60740.163613101.504
Winsorized Mean ( 11 / 54 )16.60740.163613101.504
Winsorized Mean ( 12 / 54 )16.60740.163613101.504
Winsorized Mean ( 13 / 54 )16.60740.163613101.504
Winsorized Mean ( 14 / 54 )16.60740.163613101.504
Winsorized Mean ( 15 / 54 )16.51530.153071107.893
Winsorized Mean ( 16 / 54 )16.61350.140418118.315
Winsorized Mean ( 17 / 54 )16.61350.140418118.315
Winsorized Mean ( 18 / 54 )16.61350.140418118.315
Winsorized Mean ( 19 / 54 )16.61350.140418118.315
Winsorized Mean ( 20 / 54 )16.61350.140418118.315
Winsorized Mean ( 21 / 54 )16.61350.140418118.315
Winsorized Mean ( 22 / 54 )16.61350.140418118.315
Winsorized Mean ( 23 / 54 )16.61350.140418118.315
Winsorized Mean ( 24 / 54 )16.61350.140418118.315
Winsorized Mean ( 25 / 54 )16.61350.140418118.315
Winsorized Mean ( 26 / 54 )16.61350.140418118.315
Winsorized Mean ( 27 / 54 )16.61350.140418118.315
Winsorized Mean ( 28 / 54 )16.78530.12269136.811
Winsorized Mean ( 29 / 54 )16.78530.12269136.811
Winsorized Mean ( 30 / 54 )16.78530.12269136.811
Winsorized Mean ( 31 / 54 )16.78530.12269136.811
Winsorized Mean ( 32 / 54 )16.78530.12269136.811
Winsorized Mean ( 33 / 54 )16.78530.12269136.811
Winsorized Mean ( 34 / 54 )16.78530.12269136.811
Winsorized Mean ( 35 / 54 )16.78530.12269136.811
Winsorized Mean ( 36 / 54 )16.56440.100381165.016
Winsorized Mean ( 37 / 54 )16.56440.100381165.016
Winsorized Mean ( 38 / 54 )16.56440.100381165.016
Winsorized Mean ( 39 / 54 )16.56440.100381165.016
Winsorized Mean ( 40 / 54 )16.56440.100381165.016
Winsorized Mean ( 41 / 54 )16.56440.100381165.016
Winsorized Mean ( 42 / 54 )16.56440.100381165.016
Winsorized Mean ( 43 / 54 )16.56440.100381165.016
Winsorized Mean ( 44 / 54 )16.56440.100381165.016
Winsorized Mean ( 45 / 54 )16.56440.100381165.016
Winsorized Mean ( 46 / 54 )16.56440.100381165.016
Winsorized Mean ( 47 / 54 )16.56440.100381165.016
Winsorized Mean ( 48 / 54 )16.56440.100381165.016
Winsorized Mean ( 49 / 54 )16.56440.100381165.016
Winsorized Mean ( 50 / 54 )16.56440.100381165.016
Winsorized Mean ( 51 / 54 )16.56440.100381165.016
Winsorized Mean ( 52 / 54 )16.56440.100381165.016
Winsorized Mean ( 53 / 54 )16.88960.0717691235.332
Winsorized Mean ( 54 / 54 )16.88960.0717691235.332
Trimmed Mean ( 1 / 54 )16.49690.1835989.8572
Trimmed Mean ( 2 / 54 )16.53460.17456794.7177
Trimmed Mean ( 3 / 54 )16.55410.17035697.1736
Trimmed Mean ( 4 / 54 )16.56770.16729299.035
Trimmed Mean ( 5 / 54 )16.58170.163965101.129
Trimmed Mean ( 6 / 54 )16.58940.161743102.566
Trimmed Mean ( 7 / 54 )16.59730.159334104.167
Trimmed Mean ( 8 / 54 )16.60540.156718105.958
Trimmed Mean ( 9 / 54 )16.61380.153873107.971
Trimmed Mean ( 10 / 54 )16.62240.150773110.247
Trimmed Mean ( 11 / 54 )16.62410.148801111.72
Trimmed Mean ( 12 / 54 )16.62590.146653113.369
Trimmed Mean ( 13 / 54 )16.62770.144309115.223
Trimmed Mean ( 14 / 54 )16.62960.14175117.317
Trimmed Mean ( 15 / 54 )16.63160.138948119.696
Trimmed Mean ( 16 / 54 )16.64120.137107121.374
Trimmed Mean ( 17 / 54 )16.64340.136487121.941
Trimmed Mean ( 18 / 54 )16.64570.135789122.585
Trimmed Mean ( 19 / 54 )16.6480.135006123.313
Trimmed Mean ( 20 / 54 )16.65040.134129124.137
Trimmed Mean ( 21 / 54 )16.65290.133149125.069
Trimmed Mean ( 22 / 54 )16.65550.132056126.125
Trimmed Mean ( 23 / 54 )16.65810.130836127.321
Trimmed Mean ( 24 / 54 )16.66090.129475128.68
Trimmed Mean ( 25 / 54 )16.66370.127958130.228
Trimmed Mean ( 26 / 54 )16.66670.126266131.996
Trimmed Mean ( 27 / 54 )16.66670.124378134.001
Trimmed Mean ( 28 / 54 )16.67290.122266136.366
Trimmed Mean ( 29 / 54 )16.66670.121549137.119
Trimmed Mean ( 30 / 54 )16.66020.12072138.007
Trimmed Mean ( 31 / 54 )16.65350.119765139.051
Trimmed Mean ( 32 / 54 )16.64650.118669140.277
Trimmed Mean ( 33 / 54 )16.63920.117412141.716
Trimmed Mean ( 34 / 54 )16.63160.115973143.41
Trimmed Mean ( 35 / 54 )16.62370.114325145.407
Trimmed Mean ( 36 / 54 )16.61540.112437147.775
Trimmed Mean ( 37 / 54 )16.6180.112436147.799
Trimmed Mean ( 38 / 54 )16.62070.112374147.905
Trimmed Mean ( 39 / 54 )16.62350.112243148.103
Trimmed Mean ( 40 / 54 )16.62650.112031148.41
Trimmed Mean ( 41 / 54 )16.62960.111727148.842
Trimmed Mean ( 42 / 54 )16.63290.111316149.421
Trimmed Mean ( 43 / 54 )16.63290.110781150.142
Trimmed Mean ( 44 / 54 )16.640.110102151.132
Trimmed Mean ( 45 / 54 )16.64380.109256152.339
Trimmed Mean ( 46 / 54 )16.64790.108211153.846
Trimmed Mean ( 47 / 54 )16.65220.106934155.724
Trimmed Mean ( 48 / 54 )16.65670.105378158.066
Trimmed Mean ( 49 / 54 )16.66150.103489160.998
Trimmed Mean ( 50 / 54 )16.66670.101196164.697
Trimmed Mean ( 51 / 54 )16.67210.0984062169.422
Trimmed Mean ( 52 / 54 )16.6780.0949966175.564
Trimmed Mean ( 53 / 54 )16.68420.0907981183.751
Trimmed Mean ( 54 / 54 )16.68420.0900974185.18
MedianNA
MidrangeNA
Midmean - Weighted Average at Xnp16.4848
Midmean - Weighted Average at X(n+1)p16.4848
Midmean - Empirical Distribution Function16.4848
Midmean - Empirical Distribution Function - Averaging16.4848
Midmean - Empirical Distribution Function - Interpolation16.4848
Midmean - Closest Observation16.4848
Midmean - True Basic - Statistics Graphics Toolkit16.4848
Midmean - MS Excel (old versions)16.4848
Number of observations169



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Exact Pearson Chi-Squared by Simulation ;
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')