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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, 14 Dec 2017 11:35:50 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/14/t1513249350s286nivzzpz6e22.htm/, Retrieved Tue, 14 May 2024 03:51:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309454, Retrieved Tue, 14 May 2024 03:51:27 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2017-12-14 10:35:50] [8329b9b38c877eb1bcf8703660df8d0b] [Current]
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Dataseries X:
51,7
77
60,2
77,3
82,3
81,6
73,4
81,1
74
59
81,9
75,7
75,9
57,7
73
62,6
81,9
80,8
67
68,8
73
74
74,9
82,5
82,3
59
85,3
64,3
66,3
75,2
76,1
77,1
53,7
68,2
71
81,4
55,9
53,8
70,7
68,1
74
69,4
77,8
79,4
75,4
71
75,5
63,8
82,5
81,8
76,9
64,4
82,1
82,6
80,2
62,6
74,9
75
55,9
72,1
80,8
80
74
76
73,7
65,9




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=309454&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=309454&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309454&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 Mean72.47581.0545668.7262
Geometric Mean71.9395
Harmonic Mean71.3641
Quadratic Mean72.9727
Winsorized Mean ( 1 / 22 )72.46521.0388569.7551
Winsorized Mean ( 2 / 22 )72.46521.0375669.8421
Winsorized Mean ( 3 / 22 )72.56061.0122571.6826
Winsorized Mean ( 4 / 22 )72.54851.0104371.7994
Winsorized Mean ( 5 / 22 )72.68480.97704274.3927
Winsorized Mean ( 6 / 22 )72.78480.94710576.8498
Winsorized Mean ( 7 / 22 )72.76360.94392177.0866
Winsorized Mean ( 8 / 22 )72.90910.91200279.944
Winsorized Mean ( 9 / 22 )73.22270.84296386.8635
Winsorized Mean ( 10 / 22 )73.19240.83825387.3154
Winsorized Mean ( 11 / 22 )73.35910.79512892.2607
Winsorized Mean ( 12 / 22 )73.39550.77001695.3168
Winsorized Mean ( 13 / 22 )73.35610.75741996.85
Winsorized Mean ( 14 / 22 )73.67420.701275105.058
Winsorized Mean ( 15 / 22 )73.62880.664777110.757
Winsorized Mean ( 16 / 22 )73.750.628975117.254
Winsorized Mean ( 17 / 22 )73.87880.559472132.051
Winsorized Mean ( 18 / 22 )73.46970.492176149.275
Winsorized Mean ( 19 / 22 )73.49850.444681165.284
Winsorized Mean ( 20 / 22 )73.61970.407438180.689
Winsorized Mean ( 21 / 22 )74.00150.339075218.245
Winsorized Mean ( 22 / 22 )74.06820.31966231.709
Trimmed Mean ( 1 / 22 )72.61.0174371.3561
Trimmed Mean ( 2 / 22 )72.74350.99114473.3935
Trimmed Mean ( 3 / 22 )72.89670.95961775.9644
Trimmed Mean ( 4 / 22 )73.02410.93299578.2685
Trimmed Mean ( 5 / 22 )73.16430.90047481.2509
Trimmed Mean ( 6 / 22 )73.28150.87157284.0797
Trimmed Mean ( 7 / 22 )73.38650.84459586.8896
Trimmed Mean ( 8 / 22 )73.5040.81105690.6275
Trimmed Mean ( 9 / 22 )73.60620.77746694.6745
Trimmed Mean ( 10 / 22 )73.66740.75347997.7697
Trimmed Mean ( 11 / 22 )73.73860.723205101.961
Trimmed Mean ( 12 / 22 )73.79290.695083106.164
Trimmed Mean ( 13 / 22 )73.84750.664262111.172
Trimmed Mean ( 14 / 22 )73.91320.625776118.114
Trimmed Mean ( 15 / 22 )73.94440.590204125.286
Trimmed Mean ( 16 / 22 )73.98530.551519134.148
Trimmed Mean ( 17 / 22 )74.01560.50828145.62
Trimmed Mean ( 18 / 22 )74.03330.470127157.475
Trimmed Mean ( 19 / 22 )74.10710.436312169.849
Trimmed Mean ( 20 / 22 )74.18850.402658184.247
Trimmed Mean ( 21 / 22 )74.26670.365727203.066
Trimmed Mean ( 22 / 22 )74.30450.340643218.13
Median74.45
Midrange68.5
Midmean - Weighted Average at Xnp73.803
Midmean - Weighted Average at X(n+1)p73.9853
Midmean - Empirical Distribution Function73.9853
Midmean - Empirical Distribution Function - Averaging73.9853
Midmean - Empirical Distribution Function - Interpolation74.0156
Midmean - Closest Observation73.9853
Midmean - True Basic - Statistics Graphics Toolkit73.9853
Midmean - MS Excel (old versions)73.9853
Number of observations66

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 72.4758 & 1.05456 & 68.7262 \tabularnewline
Geometric Mean & 71.9395 &  &  \tabularnewline
Harmonic Mean & 71.3641 &  &  \tabularnewline
Quadratic Mean & 72.9727 &  &  \tabularnewline
Winsorized Mean ( 1 / 22 ) & 72.4652 & 1.03885 & 69.7551 \tabularnewline
Winsorized Mean ( 2 / 22 ) & 72.4652 & 1.03756 & 69.8421 \tabularnewline
Winsorized Mean ( 3 / 22 ) & 72.5606 & 1.01225 & 71.6826 \tabularnewline
Winsorized Mean ( 4 / 22 ) & 72.5485 & 1.01043 & 71.7994 \tabularnewline
Winsorized Mean ( 5 / 22 ) & 72.6848 & 0.977042 & 74.3927 \tabularnewline
Winsorized Mean ( 6 / 22 ) & 72.7848 & 0.947105 & 76.8498 \tabularnewline
Winsorized Mean ( 7 / 22 ) & 72.7636 & 0.943921 & 77.0866 \tabularnewline
Winsorized Mean ( 8 / 22 ) & 72.9091 & 0.912002 & 79.944 \tabularnewline
Winsorized Mean ( 9 / 22 ) & 73.2227 & 0.842963 & 86.8635 \tabularnewline
Winsorized Mean ( 10 / 22 ) & 73.1924 & 0.838253 & 87.3154 \tabularnewline
Winsorized Mean ( 11 / 22 ) & 73.3591 & 0.795128 & 92.2607 \tabularnewline
Winsorized Mean ( 12 / 22 ) & 73.3955 & 0.770016 & 95.3168 \tabularnewline
Winsorized Mean ( 13 / 22 ) & 73.3561 & 0.757419 & 96.85 \tabularnewline
Winsorized Mean ( 14 / 22 ) & 73.6742 & 0.701275 & 105.058 \tabularnewline
Winsorized Mean ( 15 / 22 ) & 73.6288 & 0.664777 & 110.757 \tabularnewline
Winsorized Mean ( 16 / 22 ) & 73.75 & 0.628975 & 117.254 \tabularnewline
Winsorized Mean ( 17 / 22 ) & 73.8788 & 0.559472 & 132.051 \tabularnewline
Winsorized Mean ( 18 / 22 ) & 73.4697 & 0.492176 & 149.275 \tabularnewline
Winsorized Mean ( 19 / 22 ) & 73.4985 & 0.444681 & 165.284 \tabularnewline
Winsorized Mean ( 20 / 22 ) & 73.6197 & 0.407438 & 180.689 \tabularnewline
Winsorized Mean ( 21 / 22 ) & 74.0015 & 0.339075 & 218.245 \tabularnewline
Winsorized Mean ( 22 / 22 ) & 74.0682 & 0.31966 & 231.709 \tabularnewline
Trimmed Mean ( 1 / 22 ) & 72.6 & 1.01743 & 71.3561 \tabularnewline
Trimmed Mean ( 2 / 22 ) & 72.7435 & 0.991144 & 73.3935 \tabularnewline
Trimmed Mean ( 3 / 22 ) & 72.8967 & 0.959617 & 75.9644 \tabularnewline
Trimmed Mean ( 4 / 22 ) & 73.0241 & 0.932995 & 78.2685 \tabularnewline
Trimmed Mean ( 5 / 22 ) & 73.1643 & 0.900474 & 81.2509 \tabularnewline
Trimmed Mean ( 6 / 22 ) & 73.2815 & 0.871572 & 84.0797 \tabularnewline
Trimmed Mean ( 7 / 22 ) & 73.3865 & 0.844595 & 86.8896 \tabularnewline
Trimmed Mean ( 8 / 22 ) & 73.504 & 0.811056 & 90.6275 \tabularnewline
Trimmed Mean ( 9 / 22 ) & 73.6062 & 0.777466 & 94.6745 \tabularnewline
Trimmed Mean ( 10 / 22 ) & 73.6674 & 0.753479 & 97.7697 \tabularnewline
Trimmed Mean ( 11 / 22 ) & 73.7386 & 0.723205 & 101.961 \tabularnewline
Trimmed Mean ( 12 / 22 ) & 73.7929 & 0.695083 & 106.164 \tabularnewline
Trimmed Mean ( 13 / 22 ) & 73.8475 & 0.664262 & 111.172 \tabularnewline
Trimmed Mean ( 14 / 22 ) & 73.9132 & 0.625776 & 118.114 \tabularnewline
Trimmed Mean ( 15 / 22 ) & 73.9444 & 0.590204 & 125.286 \tabularnewline
Trimmed Mean ( 16 / 22 ) & 73.9853 & 0.551519 & 134.148 \tabularnewline
Trimmed Mean ( 17 / 22 ) & 74.0156 & 0.50828 & 145.62 \tabularnewline
Trimmed Mean ( 18 / 22 ) & 74.0333 & 0.470127 & 157.475 \tabularnewline
Trimmed Mean ( 19 / 22 ) & 74.1071 & 0.436312 & 169.849 \tabularnewline
Trimmed Mean ( 20 / 22 ) & 74.1885 & 0.402658 & 184.247 \tabularnewline
Trimmed Mean ( 21 / 22 ) & 74.2667 & 0.365727 & 203.066 \tabularnewline
Trimmed Mean ( 22 / 22 ) & 74.3045 & 0.340643 & 218.13 \tabularnewline
Median & 74.45 &  &  \tabularnewline
Midrange & 68.5 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 73.803 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 73.9853 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 73.9853 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 73.9853 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 74.0156 &  &  \tabularnewline
Midmean - Closest Observation & 73.9853 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 73.9853 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 73.9853 &  &  \tabularnewline
Number of observations & 66 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309454&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]72.4758[/C][C]1.05456[/C][C]68.7262[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]71.9395[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]71.3641[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]72.9727[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 22 )[/C][C]72.4652[/C][C]1.03885[/C][C]69.7551[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 22 )[/C][C]72.4652[/C][C]1.03756[/C][C]69.8421[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 22 )[/C][C]72.5606[/C][C]1.01225[/C][C]71.6826[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 22 )[/C][C]72.5485[/C][C]1.01043[/C][C]71.7994[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 22 )[/C][C]72.6848[/C][C]0.977042[/C][C]74.3927[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 22 )[/C][C]72.7848[/C][C]0.947105[/C][C]76.8498[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 22 )[/C][C]72.7636[/C][C]0.943921[/C][C]77.0866[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 22 )[/C][C]72.9091[/C][C]0.912002[/C][C]79.944[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 22 )[/C][C]73.2227[/C][C]0.842963[/C][C]86.8635[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 22 )[/C][C]73.1924[/C][C]0.838253[/C][C]87.3154[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 22 )[/C][C]73.3591[/C][C]0.795128[/C][C]92.2607[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 22 )[/C][C]73.3955[/C][C]0.770016[/C][C]95.3168[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 22 )[/C][C]73.3561[/C][C]0.757419[/C][C]96.85[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 22 )[/C][C]73.6742[/C][C]0.701275[/C][C]105.058[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 22 )[/C][C]73.6288[/C][C]0.664777[/C][C]110.757[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 22 )[/C][C]73.75[/C][C]0.628975[/C][C]117.254[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 22 )[/C][C]73.8788[/C][C]0.559472[/C][C]132.051[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 22 )[/C][C]73.4697[/C][C]0.492176[/C][C]149.275[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 22 )[/C][C]73.4985[/C][C]0.444681[/C][C]165.284[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 22 )[/C][C]73.6197[/C][C]0.407438[/C][C]180.689[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 22 )[/C][C]74.0015[/C][C]0.339075[/C][C]218.245[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 22 )[/C][C]74.0682[/C][C]0.31966[/C][C]231.709[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 22 )[/C][C]72.6[/C][C]1.01743[/C][C]71.3561[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 22 )[/C][C]72.7435[/C][C]0.991144[/C][C]73.3935[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 22 )[/C][C]72.8967[/C][C]0.959617[/C][C]75.9644[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 22 )[/C][C]73.0241[/C][C]0.932995[/C][C]78.2685[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 22 )[/C][C]73.1643[/C][C]0.900474[/C][C]81.2509[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 22 )[/C][C]73.2815[/C][C]0.871572[/C][C]84.0797[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 22 )[/C][C]73.3865[/C][C]0.844595[/C][C]86.8896[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 22 )[/C][C]73.504[/C][C]0.811056[/C][C]90.6275[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 22 )[/C][C]73.6062[/C][C]0.777466[/C][C]94.6745[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 22 )[/C][C]73.6674[/C][C]0.753479[/C][C]97.7697[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 22 )[/C][C]73.7386[/C][C]0.723205[/C][C]101.961[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 22 )[/C][C]73.7929[/C][C]0.695083[/C][C]106.164[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 22 )[/C][C]73.8475[/C][C]0.664262[/C][C]111.172[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 22 )[/C][C]73.9132[/C][C]0.625776[/C][C]118.114[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 22 )[/C][C]73.9444[/C][C]0.590204[/C][C]125.286[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 22 )[/C][C]73.9853[/C][C]0.551519[/C][C]134.148[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 22 )[/C][C]74.0156[/C][C]0.50828[/C][C]145.62[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 22 )[/C][C]74.0333[/C][C]0.470127[/C][C]157.475[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 22 )[/C][C]74.1071[/C][C]0.436312[/C][C]169.849[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 22 )[/C][C]74.1885[/C][C]0.402658[/C][C]184.247[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 22 )[/C][C]74.2667[/C][C]0.365727[/C][C]203.066[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 22 )[/C][C]74.3045[/C][C]0.340643[/C][C]218.13[/C][/ROW]
[ROW][C]Median[/C][C]74.45[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]68.5[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]73.803[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]73.9853[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]73.9853[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]73.9853[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]74.0156[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]73.9853[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]73.9853[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]73.9853[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]66[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309454&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309454&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 Mean72.47581.0545668.7262
Geometric Mean71.9395
Harmonic Mean71.3641
Quadratic Mean72.9727
Winsorized Mean ( 1 / 22 )72.46521.0388569.7551
Winsorized Mean ( 2 / 22 )72.46521.0375669.8421
Winsorized Mean ( 3 / 22 )72.56061.0122571.6826
Winsorized Mean ( 4 / 22 )72.54851.0104371.7994
Winsorized Mean ( 5 / 22 )72.68480.97704274.3927
Winsorized Mean ( 6 / 22 )72.78480.94710576.8498
Winsorized Mean ( 7 / 22 )72.76360.94392177.0866
Winsorized Mean ( 8 / 22 )72.90910.91200279.944
Winsorized Mean ( 9 / 22 )73.22270.84296386.8635
Winsorized Mean ( 10 / 22 )73.19240.83825387.3154
Winsorized Mean ( 11 / 22 )73.35910.79512892.2607
Winsorized Mean ( 12 / 22 )73.39550.77001695.3168
Winsorized Mean ( 13 / 22 )73.35610.75741996.85
Winsorized Mean ( 14 / 22 )73.67420.701275105.058
Winsorized Mean ( 15 / 22 )73.62880.664777110.757
Winsorized Mean ( 16 / 22 )73.750.628975117.254
Winsorized Mean ( 17 / 22 )73.87880.559472132.051
Winsorized Mean ( 18 / 22 )73.46970.492176149.275
Winsorized Mean ( 19 / 22 )73.49850.444681165.284
Winsorized Mean ( 20 / 22 )73.61970.407438180.689
Winsorized Mean ( 21 / 22 )74.00150.339075218.245
Winsorized Mean ( 22 / 22 )74.06820.31966231.709
Trimmed Mean ( 1 / 22 )72.61.0174371.3561
Trimmed Mean ( 2 / 22 )72.74350.99114473.3935
Trimmed Mean ( 3 / 22 )72.89670.95961775.9644
Trimmed Mean ( 4 / 22 )73.02410.93299578.2685
Trimmed Mean ( 5 / 22 )73.16430.90047481.2509
Trimmed Mean ( 6 / 22 )73.28150.87157284.0797
Trimmed Mean ( 7 / 22 )73.38650.84459586.8896
Trimmed Mean ( 8 / 22 )73.5040.81105690.6275
Trimmed Mean ( 9 / 22 )73.60620.77746694.6745
Trimmed Mean ( 10 / 22 )73.66740.75347997.7697
Trimmed Mean ( 11 / 22 )73.73860.723205101.961
Trimmed Mean ( 12 / 22 )73.79290.695083106.164
Trimmed Mean ( 13 / 22 )73.84750.664262111.172
Trimmed Mean ( 14 / 22 )73.91320.625776118.114
Trimmed Mean ( 15 / 22 )73.94440.590204125.286
Trimmed Mean ( 16 / 22 )73.98530.551519134.148
Trimmed Mean ( 17 / 22 )74.01560.50828145.62
Trimmed Mean ( 18 / 22 )74.03330.470127157.475
Trimmed Mean ( 19 / 22 )74.10710.436312169.849
Trimmed Mean ( 20 / 22 )74.18850.402658184.247
Trimmed Mean ( 21 / 22 )74.26670.365727203.066
Trimmed Mean ( 22 / 22 )74.30450.340643218.13
Median74.45
Midrange68.5
Midmean - Weighted Average at Xnp73.803
Midmean - Weighted Average at X(n+1)p73.9853
Midmean - Empirical Distribution Function73.9853
Midmean - Empirical Distribution Function - Averaging73.9853
Midmean - Empirical Distribution Function - Interpolation74.0156
Midmean - Closest Observation73.9853
Midmean - True Basic - Statistics Graphics Toolkit73.9853
Midmean - MS Excel (old versions)73.9853
Number of observations66



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')