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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 computationSun, 03 Dec 2017 18:02:54 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/03/t15123206354z3qmnucktzxw90.htm/, Retrieved Tue, 14 May 2024 02:17:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308467, Retrieved Tue, 14 May 2024 02:17:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [dataset 2 -winsor...] [2017-12-03 17:02:54] [083af55ff76165a8ad7082d446c84c48] [Current]
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Dataseries X:
0
5
10
5
15
8
3
2
0
20
16
1
8
4
1
46
54
10
313
7
121
14
34
5
9
74
3
2
2
19
0
472
2
0
0
3
4
151
154
5
1
18
3
1 302
17
6
50
205
2
95
13
0
65
10
5
47
1
5
2
39
3
69
6
0
2
93
12
28
58
22
4
0
2
0
47




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=308467&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=308467&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308467&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 Mean51.1218.87762.70797
Geometric Mean0
Harmonic Mean0
Quadratic Mean170.247
Winsorized Mean ( 1 / 25 )40.053310.23223.91446
Winsorized Mean ( 2 / 25 )35.81338.004094.47438
Winsorized Mean ( 3 / 25 )31.49336.144495.12546
Winsorized Mean ( 4 / 25 )28.77335.174395.56073
Winsorized Mean ( 5 / 25 )28.57335.10935.59242
Winsorized Mean ( 6 / 25 )26.17334.365655.99529
Winsorized Mean ( 7 / 25 )23.74673.689536.43623
Winsorized Mean ( 8 / 25 )23.53333.634146.47563
Winsorized Mean ( 9 / 25 )21.37333.061696.98088
Winsorized Mean ( 10 / 25 )20.70672.909437.11709
Winsorized Mean ( 11 / 25 )20.122.779597.23848
Winsorized Mean ( 12 / 25 )192.540987.47743
Winsorized Mean ( 13 / 25 )18.482.382777.75567
Winsorized Mean ( 14 / 25 )17.73332.234647.93564
Winsorized Mean ( 15 / 25 )17.13332.118938.08586
Winsorized Mean ( 16 / 25 )17.13332.118938.08586
Winsorized Mean ( 17 / 25 )16.90672.075878.14436
Winsorized Mean ( 18 / 25 )15.22671.763258.63559
Winsorized Mean ( 19 / 25 )13.961.535939.08896
Winsorized Mean ( 20 / 25 )12.361.260019.80947
Winsorized Mean ( 21 / 25 )10.960.95529611.4729
Winsorized Mean ( 22 / 25 )10.37330.86530211.9881
Winsorized Mean ( 23 / 25 )10.06670.81965312.2816
Winsorized Mean ( 24 / 25 )9.746670.77298812.6091
Winsorized Mean ( 25 / 25 )9.413330.72536912.9773
Trimmed Mean ( 1 / 25 )34.68498.622624.02255
Trimmed Mean ( 2 / 25 )29.01416.280674.61958
Trimmed Mean ( 3 / 25 )25.31884.920925.14514
Trimmed Mean ( 4 / 25 )23.01494.262345.39959
Trimmed Mean ( 5 / 25 )21.35383.875185.51041
Trimmed Mean ( 6 / 25 )19.63493.3955.78349
Trimmed Mean ( 7 / 25 )18.29513.05915.98054
Trimmed Mean ( 8 / 25 )17.30512.859186.05247
Trimmed Mean ( 9 / 25 )16.28072.618476.21765
Trimmed Mean ( 10 / 25 )15.50912.481436.25006
Trimmed Mean ( 11 / 25 )14.77362.347476.2934
Trimmed Mean ( 12 / 25 )14.05882.20956.3629
Trimmed Mean ( 13 / 25 )13.42862.095516.40826
Trimmed Mean ( 14 / 25 )12.80851.986696.44716
Trimmed Mean ( 15 / 25 )12.22221.882646.49207
Trimmed Mean ( 16 / 25 )11.65121.774966.56419
Trimmed Mean ( 17 / 25 )11.02441.625076.78397
Trimmed Mean ( 18 / 25 )10.3591.42497.26995
Trimmed Mean ( 19 / 25 )9.810811.257917.79929
Trimmed Mean ( 20 / 25 )9.342861.105338.45256
Trimmed Mean ( 21 / 25 )90.9962059.03429
Trimmed Mean ( 22 / 25 )8.774190.9511859.22449
Trimmed Mean ( 23 / 25 )8.586210.9158129.37551
Trimmed Mean ( 24 / 25 )8.407410.8774799.58132
Trimmed Mean ( 25 / 25 )8.240.8352259.86561
Median7
Midrange651
Midmean - Weighted Average at Xnp8.72093
Midmean - Weighted Average at X(n+1)p9.40909
Midmean - Empirical Distribution Function9.40909
Midmean - Empirical Distribution Function - Averaging9.40909
Midmean - Empirical Distribution Function - Interpolation8.72093
Midmean - Closest Observation8.72093
Midmean - True Basic - Statistics Graphics Toolkit9.40909
Midmean - MS Excel (old versions)9.40909
Number of observations75

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 51.12 & 18.8776 & 2.70797 \tabularnewline
Geometric Mean & 0 &  &  \tabularnewline
Harmonic Mean & 0 &  &  \tabularnewline
Quadratic Mean & 170.247 &  &  \tabularnewline
Winsorized Mean ( 1 / 25 ) & 40.0533 & 10.2322 & 3.91446 \tabularnewline
Winsorized Mean ( 2 / 25 ) & 35.8133 & 8.00409 & 4.47438 \tabularnewline
Winsorized Mean ( 3 / 25 ) & 31.4933 & 6.14449 & 5.12546 \tabularnewline
Winsorized Mean ( 4 / 25 ) & 28.7733 & 5.17439 & 5.56073 \tabularnewline
Winsorized Mean ( 5 / 25 ) & 28.5733 & 5.1093 & 5.59242 \tabularnewline
Winsorized Mean ( 6 / 25 ) & 26.1733 & 4.36565 & 5.99529 \tabularnewline
Winsorized Mean ( 7 / 25 ) & 23.7467 & 3.68953 & 6.43623 \tabularnewline
Winsorized Mean ( 8 / 25 ) & 23.5333 & 3.63414 & 6.47563 \tabularnewline
Winsorized Mean ( 9 / 25 ) & 21.3733 & 3.06169 & 6.98088 \tabularnewline
Winsorized Mean ( 10 / 25 ) & 20.7067 & 2.90943 & 7.11709 \tabularnewline
Winsorized Mean ( 11 / 25 ) & 20.12 & 2.77959 & 7.23848 \tabularnewline
Winsorized Mean ( 12 / 25 ) & 19 & 2.54098 & 7.47743 \tabularnewline
Winsorized Mean ( 13 / 25 ) & 18.48 & 2.38277 & 7.75567 \tabularnewline
Winsorized Mean ( 14 / 25 ) & 17.7333 & 2.23464 & 7.93564 \tabularnewline
Winsorized Mean ( 15 / 25 ) & 17.1333 & 2.11893 & 8.08586 \tabularnewline
Winsorized Mean ( 16 / 25 ) & 17.1333 & 2.11893 & 8.08586 \tabularnewline
Winsorized Mean ( 17 / 25 ) & 16.9067 & 2.07587 & 8.14436 \tabularnewline
Winsorized Mean ( 18 / 25 ) & 15.2267 & 1.76325 & 8.63559 \tabularnewline
Winsorized Mean ( 19 / 25 ) & 13.96 & 1.53593 & 9.08896 \tabularnewline
Winsorized Mean ( 20 / 25 ) & 12.36 & 1.26001 & 9.80947 \tabularnewline
Winsorized Mean ( 21 / 25 ) & 10.96 & 0.955296 & 11.4729 \tabularnewline
Winsorized Mean ( 22 / 25 ) & 10.3733 & 0.865302 & 11.9881 \tabularnewline
Winsorized Mean ( 23 / 25 ) & 10.0667 & 0.819653 & 12.2816 \tabularnewline
Winsorized Mean ( 24 / 25 ) & 9.74667 & 0.772988 & 12.6091 \tabularnewline
Winsorized Mean ( 25 / 25 ) & 9.41333 & 0.725369 & 12.9773 \tabularnewline
Trimmed Mean ( 1 / 25 ) & 34.6849 & 8.62262 & 4.02255 \tabularnewline
Trimmed Mean ( 2 / 25 ) & 29.0141 & 6.28067 & 4.61958 \tabularnewline
Trimmed Mean ( 3 / 25 ) & 25.3188 & 4.92092 & 5.14514 \tabularnewline
Trimmed Mean ( 4 / 25 ) & 23.0149 & 4.26234 & 5.39959 \tabularnewline
Trimmed Mean ( 5 / 25 ) & 21.3538 & 3.87518 & 5.51041 \tabularnewline
Trimmed Mean ( 6 / 25 ) & 19.6349 & 3.395 & 5.78349 \tabularnewline
Trimmed Mean ( 7 / 25 ) & 18.2951 & 3.0591 & 5.98054 \tabularnewline
Trimmed Mean ( 8 / 25 ) & 17.3051 & 2.85918 & 6.05247 \tabularnewline
Trimmed Mean ( 9 / 25 ) & 16.2807 & 2.61847 & 6.21765 \tabularnewline
Trimmed Mean ( 10 / 25 ) & 15.5091 & 2.48143 & 6.25006 \tabularnewline
Trimmed Mean ( 11 / 25 ) & 14.7736 & 2.34747 & 6.2934 \tabularnewline
Trimmed Mean ( 12 / 25 ) & 14.0588 & 2.2095 & 6.3629 \tabularnewline
Trimmed Mean ( 13 / 25 ) & 13.4286 & 2.09551 & 6.40826 \tabularnewline
Trimmed Mean ( 14 / 25 ) & 12.8085 & 1.98669 & 6.44716 \tabularnewline
Trimmed Mean ( 15 / 25 ) & 12.2222 & 1.88264 & 6.49207 \tabularnewline
Trimmed Mean ( 16 / 25 ) & 11.6512 & 1.77496 & 6.56419 \tabularnewline
Trimmed Mean ( 17 / 25 ) & 11.0244 & 1.62507 & 6.78397 \tabularnewline
Trimmed Mean ( 18 / 25 ) & 10.359 & 1.4249 & 7.26995 \tabularnewline
Trimmed Mean ( 19 / 25 ) & 9.81081 & 1.25791 & 7.79929 \tabularnewline
Trimmed Mean ( 20 / 25 ) & 9.34286 & 1.10533 & 8.45256 \tabularnewline
Trimmed Mean ( 21 / 25 ) & 9 & 0.996205 & 9.03429 \tabularnewline
Trimmed Mean ( 22 / 25 ) & 8.77419 & 0.951185 & 9.22449 \tabularnewline
Trimmed Mean ( 23 / 25 ) & 8.58621 & 0.915812 & 9.37551 \tabularnewline
Trimmed Mean ( 24 / 25 ) & 8.40741 & 0.877479 & 9.58132 \tabularnewline
Trimmed Mean ( 25 / 25 ) & 8.24 & 0.835225 & 9.86561 \tabularnewline
Median & 7 &  &  \tabularnewline
Midrange & 651 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 8.72093 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 9.40909 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 9.40909 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 9.40909 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 8.72093 &  &  \tabularnewline
Midmean - Closest Observation & 8.72093 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 9.40909 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 9.40909 &  &  \tabularnewline
Number of observations & 75 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308467&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]51.12[/C][C]18.8776[/C][C]2.70797[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]0[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]170.247[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 25 )[/C][C]40.0533[/C][C]10.2322[/C][C]3.91446[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 25 )[/C][C]35.8133[/C][C]8.00409[/C][C]4.47438[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 25 )[/C][C]31.4933[/C][C]6.14449[/C][C]5.12546[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 25 )[/C][C]28.7733[/C][C]5.17439[/C][C]5.56073[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 25 )[/C][C]28.5733[/C][C]5.1093[/C][C]5.59242[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 25 )[/C][C]26.1733[/C][C]4.36565[/C][C]5.99529[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 25 )[/C][C]23.7467[/C][C]3.68953[/C][C]6.43623[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 25 )[/C][C]23.5333[/C][C]3.63414[/C][C]6.47563[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 25 )[/C][C]21.3733[/C][C]3.06169[/C][C]6.98088[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 25 )[/C][C]20.7067[/C][C]2.90943[/C][C]7.11709[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 25 )[/C][C]20.12[/C][C]2.77959[/C][C]7.23848[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 25 )[/C][C]19[/C][C]2.54098[/C][C]7.47743[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 25 )[/C][C]18.48[/C][C]2.38277[/C][C]7.75567[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 25 )[/C][C]17.7333[/C][C]2.23464[/C][C]7.93564[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 25 )[/C][C]17.1333[/C][C]2.11893[/C][C]8.08586[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 25 )[/C][C]17.1333[/C][C]2.11893[/C][C]8.08586[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 25 )[/C][C]16.9067[/C][C]2.07587[/C][C]8.14436[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 25 )[/C][C]15.2267[/C][C]1.76325[/C][C]8.63559[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 25 )[/C][C]13.96[/C][C]1.53593[/C][C]9.08896[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 25 )[/C][C]12.36[/C][C]1.26001[/C][C]9.80947[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 25 )[/C][C]10.96[/C][C]0.955296[/C][C]11.4729[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 25 )[/C][C]10.3733[/C][C]0.865302[/C][C]11.9881[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 25 )[/C][C]10.0667[/C][C]0.819653[/C][C]12.2816[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 25 )[/C][C]9.74667[/C][C]0.772988[/C][C]12.6091[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 25 )[/C][C]9.41333[/C][C]0.725369[/C][C]12.9773[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 25 )[/C][C]34.6849[/C][C]8.62262[/C][C]4.02255[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 25 )[/C][C]29.0141[/C][C]6.28067[/C][C]4.61958[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 25 )[/C][C]25.3188[/C][C]4.92092[/C][C]5.14514[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 25 )[/C][C]23.0149[/C][C]4.26234[/C][C]5.39959[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 25 )[/C][C]21.3538[/C][C]3.87518[/C][C]5.51041[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 25 )[/C][C]19.6349[/C][C]3.395[/C][C]5.78349[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 25 )[/C][C]18.2951[/C][C]3.0591[/C][C]5.98054[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 25 )[/C][C]17.3051[/C][C]2.85918[/C][C]6.05247[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 25 )[/C][C]16.2807[/C][C]2.61847[/C][C]6.21765[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 25 )[/C][C]15.5091[/C][C]2.48143[/C][C]6.25006[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 25 )[/C][C]14.7736[/C][C]2.34747[/C][C]6.2934[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 25 )[/C][C]14.0588[/C][C]2.2095[/C][C]6.3629[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 25 )[/C][C]13.4286[/C][C]2.09551[/C][C]6.40826[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 25 )[/C][C]12.8085[/C][C]1.98669[/C][C]6.44716[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 25 )[/C][C]12.2222[/C][C]1.88264[/C][C]6.49207[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 25 )[/C][C]11.6512[/C][C]1.77496[/C][C]6.56419[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 25 )[/C][C]11.0244[/C][C]1.62507[/C][C]6.78397[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 25 )[/C][C]10.359[/C][C]1.4249[/C][C]7.26995[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 25 )[/C][C]9.81081[/C][C]1.25791[/C][C]7.79929[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 25 )[/C][C]9.34286[/C][C]1.10533[/C][C]8.45256[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 25 )[/C][C]9[/C][C]0.996205[/C][C]9.03429[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 25 )[/C][C]8.77419[/C][C]0.951185[/C][C]9.22449[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 25 )[/C][C]8.58621[/C][C]0.915812[/C][C]9.37551[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 25 )[/C][C]8.40741[/C][C]0.877479[/C][C]9.58132[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 25 )[/C][C]8.24[/C][C]0.835225[/C][C]9.86561[/C][/ROW]
[ROW][C]Median[/C][C]7[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]651[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]8.72093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]9.40909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]9.40909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]9.40909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]8.72093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]8.72093[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]9.40909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]9.40909[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]75[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308467&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308467&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 Mean51.1218.87762.70797
Geometric Mean0
Harmonic Mean0
Quadratic Mean170.247
Winsorized Mean ( 1 / 25 )40.053310.23223.91446
Winsorized Mean ( 2 / 25 )35.81338.004094.47438
Winsorized Mean ( 3 / 25 )31.49336.144495.12546
Winsorized Mean ( 4 / 25 )28.77335.174395.56073
Winsorized Mean ( 5 / 25 )28.57335.10935.59242
Winsorized Mean ( 6 / 25 )26.17334.365655.99529
Winsorized Mean ( 7 / 25 )23.74673.689536.43623
Winsorized Mean ( 8 / 25 )23.53333.634146.47563
Winsorized Mean ( 9 / 25 )21.37333.061696.98088
Winsorized Mean ( 10 / 25 )20.70672.909437.11709
Winsorized Mean ( 11 / 25 )20.122.779597.23848
Winsorized Mean ( 12 / 25 )192.540987.47743
Winsorized Mean ( 13 / 25 )18.482.382777.75567
Winsorized Mean ( 14 / 25 )17.73332.234647.93564
Winsorized Mean ( 15 / 25 )17.13332.118938.08586
Winsorized Mean ( 16 / 25 )17.13332.118938.08586
Winsorized Mean ( 17 / 25 )16.90672.075878.14436
Winsorized Mean ( 18 / 25 )15.22671.763258.63559
Winsorized Mean ( 19 / 25 )13.961.535939.08896
Winsorized Mean ( 20 / 25 )12.361.260019.80947
Winsorized Mean ( 21 / 25 )10.960.95529611.4729
Winsorized Mean ( 22 / 25 )10.37330.86530211.9881
Winsorized Mean ( 23 / 25 )10.06670.81965312.2816
Winsorized Mean ( 24 / 25 )9.746670.77298812.6091
Winsorized Mean ( 25 / 25 )9.413330.72536912.9773
Trimmed Mean ( 1 / 25 )34.68498.622624.02255
Trimmed Mean ( 2 / 25 )29.01416.280674.61958
Trimmed Mean ( 3 / 25 )25.31884.920925.14514
Trimmed Mean ( 4 / 25 )23.01494.262345.39959
Trimmed Mean ( 5 / 25 )21.35383.875185.51041
Trimmed Mean ( 6 / 25 )19.63493.3955.78349
Trimmed Mean ( 7 / 25 )18.29513.05915.98054
Trimmed Mean ( 8 / 25 )17.30512.859186.05247
Trimmed Mean ( 9 / 25 )16.28072.618476.21765
Trimmed Mean ( 10 / 25 )15.50912.481436.25006
Trimmed Mean ( 11 / 25 )14.77362.347476.2934
Trimmed Mean ( 12 / 25 )14.05882.20956.3629
Trimmed Mean ( 13 / 25 )13.42862.095516.40826
Trimmed Mean ( 14 / 25 )12.80851.986696.44716
Trimmed Mean ( 15 / 25 )12.22221.882646.49207
Trimmed Mean ( 16 / 25 )11.65121.774966.56419
Trimmed Mean ( 17 / 25 )11.02441.625076.78397
Trimmed Mean ( 18 / 25 )10.3591.42497.26995
Trimmed Mean ( 19 / 25 )9.810811.257917.79929
Trimmed Mean ( 20 / 25 )9.342861.105338.45256
Trimmed Mean ( 21 / 25 )90.9962059.03429
Trimmed Mean ( 22 / 25 )8.774190.9511859.22449
Trimmed Mean ( 23 / 25 )8.586210.9158129.37551
Trimmed Mean ( 24 / 25 )8.407410.8774799.58132
Trimmed Mean ( 25 / 25 )8.240.8352259.86561
Median7
Midrange651
Midmean - Weighted Average at Xnp8.72093
Midmean - Weighted Average at X(n+1)p9.40909
Midmean - Empirical Distribution Function9.40909
Midmean - Empirical Distribution Function - Averaging9.40909
Midmean - Empirical Distribution Function - Interpolation8.72093
Midmean - Closest Observation8.72093
Midmean - True Basic - Statistics Graphics Toolkit9.40909
Midmean - MS Excel (old versions)9.40909
Number of observations75



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')