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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 09:28:19 +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/t1485160114aqr6wnjluv35ux4.htm/, Retrieved Wed, 15 May 2024 07:54:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=303845, Retrieved Wed, 15 May 2024 07:54:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [] [2015-08-02 10:20:32] [32b17a345b130fdf5cc88718ed94a974]
- RMPD  [Two-Way ANOVA] [] [2015-11-22 17:26:16] [32b17a345b130fdf5cc88718ed94a974]
- R PD    [Two-Way ANOVA] [] [2015-12-10 12:41:44] [32b17a345b130fdf5cc88718ed94a974]
- RMPD        [Central Tendency] [] [2017-01-23 08:28:19] [6b5df91e566a166559c1ed571e5d94be] [Current]
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Dataseries X:
4
5
3
4
5
3
7
5
6
3
2
4
5
2
3
6
4
4
6
2
3
5
4
2
7
1
4
4
7
4
3
3
3
3
2
5
5
3
6
2
8
9
10
7
8
9
10
6
6
7
8
9
8
7
5
11
7
8
10
9
3
5
4
2
6
1
4
4
5
4
3
3
4
3
2
5
4
3
6
2




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=303845&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=303845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=303845&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 Mean4.9250.26491918.5906
Geometric Mean4.35266
Harmonic Mean3.76582
Quadratic Mean5.45894
Winsorized Mean ( 1 / 26 )4.91250.26156418.7813
Winsorized Mean ( 2 / 26 )4.93750.25738719.1832
Winsorized Mean ( 3 / 26 )4.93750.25738719.1832
Winsorized Mean ( 4 / 26 )4.88750.24584819.8802
Winsorized Mean ( 5 / 26 )4.88750.24584819.8802
Winsorized Mean ( 6 / 26 )4.88750.24584819.8802
Winsorized Mean ( 7 / 26 )4.88750.24584819.8802
Winsorized Mean ( 8 / 26 )4.78750.22620521.1644
Winsorized Mean ( 9 / 26 )4.78750.22620521.1644
Winsorized Mean ( 10 / 26 )4.78750.22620521.1644
Winsorized Mean ( 11 / 26 )4.9250.20728423.7596
Winsorized Mean ( 12 / 26 )4.9250.20728423.7596
Winsorized Mean ( 13 / 26 )4.76250.17899526.6069
Winsorized Mean ( 14 / 26 )4.76250.17899526.6069
Winsorized Mean ( 15 / 26 )4.76250.17899526.6069
Winsorized Mean ( 16 / 26 )4.76250.17899526.6069
Winsorized Mean ( 17 / 26 )4.76250.17899526.6069
Winsorized Mean ( 18 / 26 )4.76250.17899526.6069
Winsorized Mean ( 19 / 26 )4.76250.17899526.6069
Winsorized Mean ( 20 / 26 )4.51250.14230731.7097
Winsorized Mean ( 21 / 26 )4.51250.14230731.7097
Winsorized Mean ( 22 / 26 )4.51250.14230731.7097
Winsorized Mean ( 23 / 26 )4.51250.14230731.7097
Winsorized Mean ( 24 / 26 )4.51250.14230731.7097
Winsorized Mean ( 25 / 26 )4.51250.14230731.7097
Winsorized Mean ( 26 / 26 )4.83750.10287647.0226
Trimmed Mean ( 1 / 26 )4.897440.25520919.1899
Trimmed Mean ( 2 / 26 )4.881580.24777419.7017
Trimmed Mean ( 3 / 26 )4.851350.24161820.0786
Trimmed Mean ( 4 / 26 )4.819440.23430920.5687
Trimmed Mean ( 5 / 26 )4.80.22986220.8821
Trimmed Mean ( 6 / 26 )4.779410.22453321.286
Trimmed Mean ( 7 / 26 )4.757580.2181321.8107
Trimmed Mean ( 8 / 26 )4.734380.21039722.5021
Trimmed Mean ( 9 / 26 )4.725810.20590122.9518
Trimmed Mean ( 10 / 26 )4.716670.20041223.5349
Trimmed Mean ( 11 / 26 )4.70690.19368224.3022
Trimmed Mean ( 12 / 26 )4.678570.18916624.7326
Trimmed Mean ( 13 / 26 )4.648150.18344725.3378
Trimmed Mean ( 14 / 26 )4.634620.1822225.4341
Trimmed Mean ( 15 / 26 )4.620.18045325.6022
Trimmed Mean ( 16 / 26 )4.604170.17825.8661
Trimmed Mean ( 17 / 26 )4.586960.17466626.2613
Trimmed Mean ( 18 / 26 )4.568180.17018126.843
Trimmed Mean ( 19 / 26 )4.547620.16415927.7025
Trimmed Mean ( 20 / 26 )4.5250.15602229.0023
Trimmed Mean ( 21 / 26 )4.526320.15429829.335
Trimmed Mean ( 22 / 26 )4.527780.15163729.8593
Trimmed Mean ( 23 / 26 )4.529410.14768130.6702
Trimmed Mean ( 24 / 26 )4.531250.14187931.9373
Trimmed Mean ( 25 / 26 )4.533330.13333334
Trimmed Mean ( 26 / 26 )4.535710.12042837.6631
Median4
Midrange6
Midmean - Weighted Average at Xnp4.2449
Midmean - Weighted Average at X(n+1)p4.2449
Midmean - Empirical Distribution Function4.2449
Midmean - Empirical Distribution Function - Averaging4.2449
Midmean - Empirical Distribution Function - Interpolation4.2449
Midmean - Closest Observation4.2449
Midmean - True Basic - Statistics Graphics Toolkit4.2449
Midmean - MS Excel (old versions)4.58929
Number of observations80

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 4.925 & 0.264919 & 18.5906 \tabularnewline
Geometric Mean & 4.35266 &  &  \tabularnewline
Harmonic Mean & 3.76582 &  &  \tabularnewline
Quadratic Mean & 5.45894 &  &  \tabularnewline
Winsorized Mean ( 1 / 26 ) & 4.9125 & 0.261564 & 18.7813 \tabularnewline
Winsorized Mean ( 2 / 26 ) & 4.9375 & 0.257387 & 19.1832 \tabularnewline
Winsorized Mean ( 3 / 26 ) & 4.9375 & 0.257387 & 19.1832 \tabularnewline
Winsorized Mean ( 4 / 26 ) & 4.8875 & 0.245848 & 19.8802 \tabularnewline
Winsorized Mean ( 5 / 26 ) & 4.8875 & 0.245848 & 19.8802 \tabularnewline
Winsorized Mean ( 6 / 26 ) & 4.8875 & 0.245848 & 19.8802 \tabularnewline
Winsorized Mean ( 7 / 26 ) & 4.8875 & 0.245848 & 19.8802 \tabularnewline
Winsorized Mean ( 8 / 26 ) & 4.7875 & 0.226205 & 21.1644 \tabularnewline
Winsorized Mean ( 9 / 26 ) & 4.7875 & 0.226205 & 21.1644 \tabularnewline
Winsorized Mean ( 10 / 26 ) & 4.7875 & 0.226205 & 21.1644 \tabularnewline
Winsorized Mean ( 11 / 26 ) & 4.925 & 0.207284 & 23.7596 \tabularnewline
Winsorized Mean ( 12 / 26 ) & 4.925 & 0.207284 & 23.7596 \tabularnewline
Winsorized Mean ( 13 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 14 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 15 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 16 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 17 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 18 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 19 / 26 ) & 4.7625 & 0.178995 & 26.6069 \tabularnewline
Winsorized Mean ( 20 / 26 ) & 4.5125 & 0.142307 & 31.7097 \tabularnewline
Winsorized Mean ( 21 / 26 ) & 4.5125 & 0.142307 & 31.7097 \tabularnewline
Winsorized Mean ( 22 / 26 ) & 4.5125 & 0.142307 & 31.7097 \tabularnewline
Winsorized Mean ( 23 / 26 ) & 4.5125 & 0.142307 & 31.7097 \tabularnewline
Winsorized Mean ( 24 / 26 ) & 4.5125 & 0.142307 & 31.7097 \tabularnewline
Winsorized Mean ( 25 / 26 ) & 4.5125 & 0.142307 & 31.7097 \tabularnewline
Winsorized Mean ( 26 / 26 ) & 4.8375 & 0.102876 & 47.0226 \tabularnewline
Trimmed Mean ( 1 / 26 ) & 4.89744 & 0.255209 & 19.1899 \tabularnewline
Trimmed Mean ( 2 / 26 ) & 4.88158 & 0.247774 & 19.7017 \tabularnewline
Trimmed Mean ( 3 / 26 ) & 4.85135 & 0.241618 & 20.0786 \tabularnewline
Trimmed Mean ( 4 / 26 ) & 4.81944 & 0.234309 & 20.5687 \tabularnewline
Trimmed Mean ( 5 / 26 ) & 4.8 & 0.229862 & 20.8821 \tabularnewline
Trimmed Mean ( 6 / 26 ) & 4.77941 & 0.224533 & 21.286 \tabularnewline
Trimmed Mean ( 7 / 26 ) & 4.75758 & 0.21813 & 21.8107 \tabularnewline
Trimmed Mean ( 8 / 26 ) & 4.73438 & 0.210397 & 22.5021 \tabularnewline
Trimmed Mean ( 9 / 26 ) & 4.72581 & 0.205901 & 22.9518 \tabularnewline
Trimmed Mean ( 10 / 26 ) & 4.71667 & 0.200412 & 23.5349 \tabularnewline
Trimmed Mean ( 11 / 26 ) & 4.7069 & 0.193682 & 24.3022 \tabularnewline
Trimmed Mean ( 12 / 26 ) & 4.67857 & 0.189166 & 24.7326 \tabularnewline
Trimmed Mean ( 13 / 26 ) & 4.64815 & 0.183447 & 25.3378 \tabularnewline
Trimmed Mean ( 14 / 26 ) & 4.63462 & 0.18222 & 25.4341 \tabularnewline
Trimmed Mean ( 15 / 26 ) & 4.62 & 0.180453 & 25.6022 \tabularnewline
Trimmed Mean ( 16 / 26 ) & 4.60417 & 0.178 & 25.8661 \tabularnewline
Trimmed Mean ( 17 / 26 ) & 4.58696 & 0.174666 & 26.2613 \tabularnewline
Trimmed Mean ( 18 / 26 ) & 4.56818 & 0.170181 & 26.843 \tabularnewline
Trimmed Mean ( 19 / 26 ) & 4.54762 & 0.164159 & 27.7025 \tabularnewline
Trimmed Mean ( 20 / 26 ) & 4.525 & 0.156022 & 29.0023 \tabularnewline
Trimmed Mean ( 21 / 26 ) & 4.52632 & 0.154298 & 29.335 \tabularnewline
Trimmed Mean ( 22 / 26 ) & 4.52778 & 0.151637 & 29.8593 \tabularnewline
Trimmed Mean ( 23 / 26 ) & 4.52941 & 0.147681 & 30.6702 \tabularnewline
Trimmed Mean ( 24 / 26 ) & 4.53125 & 0.141879 & 31.9373 \tabularnewline
Trimmed Mean ( 25 / 26 ) & 4.53333 & 0.133333 & 34 \tabularnewline
Trimmed Mean ( 26 / 26 ) & 4.53571 & 0.120428 & 37.6631 \tabularnewline
Median & 4 &  &  \tabularnewline
Midrange & 6 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 4.2449 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 4.2449 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 4.2449 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 4.2449 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 4.2449 &  &  \tabularnewline
Midmean - Closest Observation & 4.2449 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 4.2449 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 4.58929 &  &  \tabularnewline
Number of observations & 80 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=303845&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]4.925[/C][C]0.264919[/C][C]18.5906[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]4.35266[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]3.76582[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]5.45894[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 26 )[/C][C]4.9125[/C][C]0.261564[/C][C]18.7813[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 26 )[/C][C]4.9375[/C][C]0.257387[/C][C]19.1832[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 26 )[/C][C]4.9375[/C][C]0.257387[/C][C]19.1832[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 26 )[/C][C]4.8875[/C][C]0.245848[/C][C]19.8802[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 26 )[/C][C]4.8875[/C][C]0.245848[/C][C]19.8802[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 26 )[/C][C]4.8875[/C][C]0.245848[/C][C]19.8802[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 26 )[/C][C]4.8875[/C][C]0.245848[/C][C]19.8802[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 26 )[/C][C]4.7875[/C][C]0.226205[/C][C]21.1644[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 26 )[/C][C]4.7875[/C][C]0.226205[/C][C]21.1644[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 26 )[/C][C]4.7875[/C][C]0.226205[/C][C]21.1644[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 26 )[/C][C]4.925[/C][C]0.207284[/C][C]23.7596[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 26 )[/C][C]4.925[/C][C]0.207284[/C][C]23.7596[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 26 )[/C][C]4.7625[/C][C]0.178995[/C][C]26.6069[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 26 )[/C][C]4.5125[/C][C]0.142307[/C][C]31.7097[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 26 )[/C][C]4.5125[/C][C]0.142307[/C][C]31.7097[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 26 )[/C][C]4.5125[/C][C]0.142307[/C][C]31.7097[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 26 )[/C][C]4.5125[/C][C]0.142307[/C][C]31.7097[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 26 )[/C][C]4.5125[/C][C]0.142307[/C][C]31.7097[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 26 )[/C][C]4.5125[/C][C]0.142307[/C][C]31.7097[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 26 )[/C][C]4.8375[/C][C]0.102876[/C][C]47.0226[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 26 )[/C][C]4.89744[/C][C]0.255209[/C][C]19.1899[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 26 )[/C][C]4.88158[/C][C]0.247774[/C][C]19.7017[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 26 )[/C][C]4.85135[/C][C]0.241618[/C][C]20.0786[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 26 )[/C][C]4.81944[/C][C]0.234309[/C][C]20.5687[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 26 )[/C][C]4.8[/C][C]0.229862[/C][C]20.8821[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 26 )[/C][C]4.77941[/C][C]0.224533[/C][C]21.286[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 26 )[/C][C]4.75758[/C][C]0.21813[/C][C]21.8107[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 26 )[/C][C]4.73438[/C][C]0.210397[/C][C]22.5021[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 26 )[/C][C]4.72581[/C][C]0.205901[/C][C]22.9518[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 26 )[/C][C]4.71667[/C][C]0.200412[/C][C]23.5349[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 26 )[/C][C]4.7069[/C][C]0.193682[/C][C]24.3022[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 26 )[/C][C]4.67857[/C][C]0.189166[/C][C]24.7326[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 26 )[/C][C]4.64815[/C][C]0.183447[/C][C]25.3378[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 26 )[/C][C]4.63462[/C][C]0.18222[/C][C]25.4341[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 26 )[/C][C]4.62[/C][C]0.180453[/C][C]25.6022[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 26 )[/C][C]4.60417[/C][C]0.178[/C][C]25.8661[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 26 )[/C][C]4.58696[/C][C]0.174666[/C][C]26.2613[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 26 )[/C][C]4.56818[/C][C]0.170181[/C][C]26.843[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 26 )[/C][C]4.54762[/C][C]0.164159[/C][C]27.7025[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 26 )[/C][C]4.525[/C][C]0.156022[/C][C]29.0023[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 26 )[/C][C]4.52632[/C][C]0.154298[/C][C]29.335[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 26 )[/C][C]4.52778[/C][C]0.151637[/C][C]29.8593[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 26 )[/C][C]4.52941[/C][C]0.147681[/C][C]30.6702[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 26 )[/C][C]4.53125[/C][C]0.141879[/C][C]31.9373[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 26 )[/C][C]4.53333[/C][C]0.133333[/C][C]34[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 26 )[/C][C]4.53571[/C][C]0.120428[/C][C]37.6631[/C][/ROW]
[ROW][C]Median[/C][C]4[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]6[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]4.2449[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]4.58929[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]80[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=303845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=303845&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 Mean4.9250.26491918.5906
Geometric Mean4.35266
Harmonic Mean3.76582
Quadratic Mean5.45894
Winsorized Mean ( 1 / 26 )4.91250.26156418.7813
Winsorized Mean ( 2 / 26 )4.93750.25738719.1832
Winsorized Mean ( 3 / 26 )4.93750.25738719.1832
Winsorized Mean ( 4 / 26 )4.88750.24584819.8802
Winsorized Mean ( 5 / 26 )4.88750.24584819.8802
Winsorized Mean ( 6 / 26 )4.88750.24584819.8802
Winsorized Mean ( 7 / 26 )4.88750.24584819.8802
Winsorized Mean ( 8 / 26 )4.78750.22620521.1644
Winsorized Mean ( 9 / 26 )4.78750.22620521.1644
Winsorized Mean ( 10 / 26 )4.78750.22620521.1644
Winsorized Mean ( 11 / 26 )4.9250.20728423.7596
Winsorized Mean ( 12 / 26 )4.9250.20728423.7596
Winsorized Mean ( 13 / 26 )4.76250.17899526.6069
Winsorized Mean ( 14 / 26 )4.76250.17899526.6069
Winsorized Mean ( 15 / 26 )4.76250.17899526.6069
Winsorized Mean ( 16 / 26 )4.76250.17899526.6069
Winsorized Mean ( 17 / 26 )4.76250.17899526.6069
Winsorized Mean ( 18 / 26 )4.76250.17899526.6069
Winsorized Mean ( 19 / 26 )4.76250.17899526.6069
Winsorized Mean ( 20 / 26 )4.51250.14230731.7097
Winsorized Mean ( 21 / 26 )4.51250.14230731.7097
Winsorized Mean ( 22 / 26 )4.51250.14230731.7097
Winsorized Mean ( 23 / 26 )4.51250.14230731.7097
Winsorized Mean ( 24 / 26 )4.51250.14230731.7097
Winsorized Mean ( 25 / 26 )4.51250.14230731.7097
Winsorized Mean ( 26 / 26 )4.83750.10287647.0226
Trimmed Mean ( 1 / 26 )4.897440.25520919.1899
Trimmed Mean ( 2 / 26 )4.881580.24777419.7017
Trimmed Mean ( 3 / 26 )4.851350.24161820.0786
Trimmed Mean ( 4 / 26 )4.819440.23430920.5687
Trimmed Mean ( 5 / 26 )4.80.22986220.8821
Trimmed Mean ( 6 / 26 )4.779410.22453321.286
Trimmed Mean ( 7 / 26 )4.757580.2181321.8107
Trimmed Mean ( 8 / 26 )4.734380.21039722.5021
Trimmed Mean ( 9 / 26 )4.725810.20590122.9518
Trimmed Mean ( 10 / 26 )4.716670.20041223.5349
Trimmed Mean ( 11 / 26 )4.70690.19368224.3022
Trimmed Mean ( 12 / 26 )4.678570.18916624.7326
Trimmed Mean ( 13 / 26 )4.648150.18344725.3378
Trimmed Mean ( 14 / 26 )4.634620.1822225.4341
Trimmed Mean ( 15 / 26 )4.620.18045325.6022
Trimmed Mean ( 16 / 26 )4.604170.17825.8661
Trimmed Mean ( 17 / 26 )4.586960.17466626.2613
Trimmed Mean ( 18 / 26 )4.568180.17018126.843
Trimmed Mean ( 19 / 26 )4.547620.16415927.7025
Trimmed Mean ( 20 / 26 )4.5250.15602229.0023
Trimmed Mean ( 21 / 26 )4.526320.15429829.335
Trimmed Mean ( 22 / 26 )4.527780.15163729.8593
Trimmed Mean ( 23 / 26 )4.529410.14768130.6702
Trimmed Mean ( 24 / 26 )4.531250.14187931.9373
Trimmed Mean ( 25 / 26 )4.533330.13333334
Trimmed Mean ( 26 / 26 )4.535710.12042837.6631
Median4
Midrange6
Midmean - Weighted Average at Xnp4.2449
Midmean - Weighted Average at X(n+1)p4.2449
Midmean - Empirical Distribution Function4.2449
Midmean - Empirical Distribution Function - Averaging4.2449
Midmean - Empirical Distribution Function - Interpolation4.2449
Midmean - Closest Observation4.2449
Midmean - True Basic - Statistics Graphics Toolkit4.2449
Midmean - MS Excel (old versions)4.58929
Number of observations80



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')