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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 computationFri, 26 Nov 2010 16:01:16 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/26/t1290787148j3zpzyex71lzt55.htm/, Retrieved Fri, 03 May 2024 17:45:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102038, Retrieved Fri, 03 May 2024 17:45:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Arabica Price in ...] [2008-01-06 21:28:17] [74be16979710d4c4e7c6647856088456]
-  M D  [Central Tendency] [] [2010-11-26 10:45:03] [1ec36cc0fd92fd0f07d0b885ce2c369b]
-    D      [Central Tendency] [] [2010-11-26 16:01:16] [d42b17bf3b3c0d56878eb3f5a4351e6d] [Current]
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Dataseries X:
114,41
114,25
113,89
113,82
113,77
113,78
113,33
112,94
112,52
112,05
111,54
111,36
111,07
111,02
111,31
110,97
111,04
111,25
111,33
111,1
111,74
111,36
111,25
111,49
112,16
112,36
112,18
112,87
112,28
111,66
110,67
110,42
109,62
108,84
108,4
108,1
107,1
106,54
106,44
106,57
106,12
106,13
106,26
105,78
105,77
105,2
105,15
105,01
104,75
104,96
105,26
105,13
104,77
104,79
104,4
103,89
103,93
103,48




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102038&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102038&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102038&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean109.3031034482760.446251864276248244.935903238295
Geometric Mean109.250891516231
Harmonic Mean109.198415857858
Quadratic Mean109.355015636356
Winsorized Mean ( 1 / 19 )109.3074137931030.444140009994834246.110261028667
Winsorized Mean ( 2 / 19 )109.2963793103450.441500336104231247.556729570738
Winsorized Mean ( 3 / 19 )109.3170689655170.435842704648642250.817709691032
Winsorized Mean ( 4 / 19 )109.3384482758620.43069786795599253.863453735589
Winsorized Mean ( 5 / 19 )109.3393103448280.430220252126658254.14728805616
Winsorized Mean ( 6 / 19 )109.2958620689660.421901038224147259.05568407466
Winsorized Mean ( 7 / 19 )109.2693103448280.410444910954627266.221622996092
Winsorized Mean ( 8 / 19 )109.2665517241380.40767200554998268.025643744483
Winsorized Mean ( 9 / 19 )109.2308620689660.396104693586012275.76260478026
Winsorized Mean ( 10 / 19 )109.2067241379310.391519476887519278.930501762254
Winsorized Mean ( 11 / 19 )109.2010344827590.387670044625594281.68551064662
Winsorized Mean ( 12 / 19 )109.192758620690.382568040605705285.420492647031
Winsorized Mean ( 13 / 19 )109.3025862068970.361838800607697302.075360694669
Winsorized Mean ( 14 / 19 )109.2784482758620.357781343165755305.433612912664
Winsorized Mean ( 15 / 19 )109.2862068965520.332229797109605328.947637591029
Winsorized Mean ( 16 / 19 )109.2668965517240.328930070596782332.188833795219
Winsorized Mean ( 17 / 19 )109.2698275862070.318132832596703343.47233730738
Winsorized Mean ( 18 / 19 )109.3101724137930.306976305256723356.086676860539
Winsorized Mean ( 19 / 19 )109.3003448275860.296363109871581368.805499695788
Trimmed Mean ( 1 / 19 )109.3158928571430.440764225395713248.01444073416
Trimmed Mean ( 2 / 19 )109.3250.436206788901133250.626544065041
Trimmed Mean ( 3 / 19 )109.3409615384620.431862766909919253.184506552445
Trimmed Mean ( 4 / 19 )109.35020.428634899109596255.112685008041
Trimmed Mean ( 5 / 19 )109.353750.425967674434482256.718423869086
Trimmed Mean ( 6 / 19 )109.3573913043480.422114007401669259.070747207607
Trimmed Mean ( 7 / 19 )109.3709090909090.419013214354362261.020190638698
Trimmed Mean ( 8 / 19 )109.3909523809520.417371734631371262.094778597233
Trimmed Mean ( 9 / 19 )109.41350.414986955309348263.655275425317
Trimmed Mean ( 10 / 19 )109.4444736842110.413687352718459264.558423082116
Trimmed Mean ( 11 / 19 )109.4827777777780.41175516903129265.892904357099
Trimmed Mean ( 12 / 19 )109.5264705882350.408675719313827268.003371406875
Trimmed Mean ( 13 / 19 )109.5768750.404194848188865271.099138178028
Trimmed Mean ( 14 / 19 )109.6176666666670.402366186318781272.432600933867
Trimmed Mean ( 15 / 19 )109.6678571428570.398637347339505275.106830493373
Trimmed Mean ( 16 / 19 )109.7246153846150.398405371746776275.409477797794
Trimmed Mean ( 17 / 19 )109.793750.39560713407241277.532280244228
Trimmed Mean ( 18 / 19 )109.8750.39121508460723280.855734666549
Trimmed Mean ( 19 / 19 )109.9660.384350717033558286.108481463815
Median110.995
Midrange108.945
Midmean - Weighted Average at Xnp109.533793103448
Midmean - Weighted Average at X(n+1)p109.617666666667
Midmean - Empirical Distribution Function109.617666666667
Midmean - Empirical Distribution Function - Averaging109.617666666667
Midmean - Empirical Distribution Function - Interpolation109.667857142857
Midmean - Closest Observation109.617666666667
Midmean - True Basic - Statistics Graphics Toolkit109.617666666667
Midmean - MS Excel (old versions)109.617666666667
Number of observations58

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 109.303103448276 & 0.446251864276248 & 244.935903238295 \tabularnewline
Geometric Mean & 109.250891516231 &  &  \tabularnewline
Harmonic Mean & 109.198415857858 &  &  \tabularnewline
Quadratic Mean & 109.355015636356 &  &  \tabularnewline
Winsorized Mean ( 1 / 19 ) & 109.307413793103 & 0.444140009994834 & 246.110261028667 \tabularnewline
Winsorized Mean ( 2 / 19 ) & 109.296379310345 & 0.441500336104231 & 247.556729570738 \tabularnewline
Winsorized Mean ( 3 / 19 ) & 109.317068965517 & 0.435842704648642 & 250.817709691032 \tabularnewline
Winsorized Mean ( 4 / 19 ) & 109.338448275862 & 0.43069786795599 & 253.863453735589 \tabularnewline
Winsorized Mean ( 5 / 19 ) & 109.339310344828 & 0.430220252126658 & 254.14728805616 \tabularnewline
Winsorized Mean ( 6 / 19 ) & 109.295862068966 & 0.421901038224147 & 259.05568407466 \tabularnewline
Winsorized Mean ( 7 / 19 ) & 109.269310344828 & 0.410444910954627 & 266.221622996092 \tabularnewline
Winsorized Mean ( 8 / 19 ) & 109.266551724138 & 0.40767200554998 & 268.025643744483 \tabularnewline
Winsorized Mean ( 9 / 19 ) & 109.230862068966 & 0.396104693586012 & 275.76260478026 \tabularnewline
Winsorized Mean ( 10 / 19 ) & 109.206724137931 & 0.391519476887519 & 278.930501762254 \tabularnewline
Winsorized Mean ( 11 / 19 ) & 109.201034482759 & 0.387670044625594 & 281.68551064662 \tabularnewline
Winsorized Mean ( 12 / 19 ) & 109.19275862069 & 0.382568040605705 & 285.420492647031 \tabularnewline
Winsorized Mean ( 13 / 19 ) & 109.302586206897 & 0.361838800607697 & 302.075360694669 \tabularnewline
Winsorized Mean ( 14 / 19 ) & 109.278448275862 & 0.357781343165755 & 305.433612912664 \tabularnewline
Winsorized Mean ( 15 / 19 ) & 109.286206896552 & 0.332229797109605 & 328.947637591029 \tabularnewline
Winsorized Mean ( 16 / 19 ) & 109.266896551724 & 0.328930070596782 & 332.188833795219 \tabularnewline
Winsorized Mean ( 17 / 19 ) & 109.269827586207 & 0.318132832596703 & 343.47233730738 \tabularnewline
Winsorized Mean ( 18 / 19 ) & 109.310172413793 & 0.306976305256723 & 356.086676860539 \tabularnewline
Winsorized Mean ( 19 / 19 ) & 109.300344827586 & 0.296363109871581 & 368.805499695788 \tabularnewline
Trimmed Mean ( 1 / 19 ) & 109.315892857143 & 0.440764225395713 & 248.01444073416 \tabularnewline
Trimmed Mean ( 2 / 19 ) & 109.325 & 0.436206788901133 & 250.626544065041 \tabularnewline
Trimmed Mean ( 3 / 19 ) & 109.340961538462 & 0.431862766909919 & 253.184506552445 \tabularnewline
Trimmed Mean ( 4 / 19 ) & 109.3502 & 0.428634899109596 & 255.112685008041 \tabularnewline
Trimmed Mean ( 5 / 19 ) & 109.35375 & 0.425967674434482 & 256.718423869086 \tabularnewline
Trimmed Mean ( 6 / 19 ) & 109.357391304348 & 0.422114007401669 & 259.070747207607 \tabularnewline
Trimmed Mean ( 7 / 19 ) & 109.370909090909 & 0.419013214354362 & 261.020190638698 \tabularnewline
Trimmed Mean ( 8 / 19 ) & 109.390952380952 & 0.417371734631371 & 262.094778597233 \tabularnewline
Trimmed Mean ( 9 / 19 ) & 109.4135 & 0.414986955309348 & 263.655275425317 \tabularnewline
Trimmed Mean ( 10 / 19 ) & 109.444473684211 & 0.413687352718459 & 264.558423082116 \tabularnewline
Trimmed Mean ( 11 / 19 ) & 109.482777777778 & 0.41175516903129 & 265.892904357099 \tabularnewline
Trimmed Mean ( 12 / 19 ) & 109.526470588235 & 0.408675719313827 & 268.003371406875 \tabularnewline
Trimmed Mean ( 13 / 19 ) & 109.576875 & 0.404194848188865 & 271.099138178028 \tabularnewline
Trimmed Mean ( 14 / 19 ) & 109.617666666667 & 0.402366186318781 & 272.432600933867 \tabularnewline
Trimmed Mean ( 15 / 19 ) & 109.667857142857 & 0.398637347339505 & 275.106830493373 \tabularnewline
Trimmed Mean ( 16 / 19 ) & 109.724615384615 & 0.398405371746776 & 275.409477797794 \tabularnewline
Trimmed Mean ( 17 / 19 ) & 109.79375 & 0.39560713407241 & 277.532280244228 \tabularnewline
Trimmed Mean ( 18 / 19 ) & 109.875 & 0.39121508460723 & 280.855734666549 \tabularnewline
Trimmed Mean ( 19 / 19 ) & 109.966 & 0.384350717033558 & 286.108481463815 \tabularnewline
Median & 110.995 &  &  \tabularnewline
Midrange & 108.945 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 109.533793103448 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 109.617666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 109.617666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 109.617666666667 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 109.667857142857 &  &  \tabularnewline
Midmean - Closest Observation & 109.617666666667 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 109.617666666667 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 109.617666666667 &  &  \tabularnewline
Number of observations & 58 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102038&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]109.303103448276[/C][C]0.446251864276248[/C][C]244.935903238295[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]109.250891516231[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]109.198415857858[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]109.355015636356[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 19 )[/C][C]109.307413793103[/C][C]0.444140009994834[/C][C]246.110261028667[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 19 )[/C][C]109.296379310345[/C][C]0.441500336104231[/C][C]247.556729570738[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 19 )[/C][C]109.317068965517[/C][C]0.435842704648642[/C][C]250.817709691032[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 19 )[/C][C]109.338448275862[/C][C]0.43069786795599[/C][C]253.863453735589[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 19 )[/C][C]109.339310344828[/C][C]0.430220252126658[/C][C]254.14728805616[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 19 )[/C][C]109.295862068966[/C][C]0.421901038224147[/C][C]259.05568407466[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 19 )[/C][C]109.269310344828[/C][C]0.410444910954627[/C][C]266.221622996092[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 19 )[/C][C]109.266551724138[/C][C]0.40767200554998[/C][C]268.025643744483[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 19 )[/C][C]109.230862068966[/C][C]0.396104693586012[/C][C]275.76260478026[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 19 )[/C][C]109.206724137931[/C][C]0.391519476887519[/C][C]278.930501762254[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 19 )[/C][C]109.201034482759[/C][C]0.387670044625594[/C][C]281.68551064662[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 19 )[/C][C]109.19275862069[/C][C]0.382568040605705[/C][C]285.420492647031[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 19 )[/C][C]109.302586206897[/C][C]0.361838800607697[/C][C]302.075360694669[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 19 )[/C][C]109.278448275862[/C][C]0.357781343165755[/C][C]305.433612912664[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 19 )[/C][C]109.286206896552[/C][C]0.332229797109605[/C][C]328.947637591029[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 19 )[/C][C]109.266896551724[/C][C]0.328930070596782[/C][C]332.188833795219[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 19 )[/C][C]109.269827586207[/C][C]0.318132832596703[/C][C]343.47233730738[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 19 )[/C][C]109.310172413793[/C][C]0.306976305256723[/C][C]356.086676860539[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 19 )[/C][C]109.300344827586[/C][C]0.296363109871581[/C][C]368.805499695788[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 19 )[/C][C]109.315892857143[/C][C]0.440764225395713[/C][C]248.01444073416[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 19 )[/C][C]109.325[/C][C]0.436206788901133[/C][C]250.626544065041[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 19 )[/C][C]109.340961538462[/C][C]0.431862766909919[/C][C]253.184506552445[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 19 )[/C][C]109.3502[/C][C]0.428634899109596[/C][C]255.112685008041[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 19 )[/C][C]109.35375[/C][C]0.425967674434482[/C][C]256.718423869086[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 19 )[/C][C]109.357391304348[/C][C]0.422114007401669[/C][C]259.070747207607[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 19 )[/C][C]109.370909090909[/C][C]0.419013214354362[/C][C]261.020190638698[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 19 )[/C][C]109.390952380952[/C][C]0.417371734631371[/C][C]262.094778597233[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 19 )[/C][C]109.4135[/C][C]0.414986955309348[/C][C]263.655275425317[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 19 )[/C][C]109.444473684211[/C][C]0.413687352718459[/C][C]264.558423082116[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 19 )[/C][C]109.482777777778[/C][C]0.41175516903129[/C][C]265.892904357099[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 19 )[/C][C]109.526470588235[/C][C]0.408675719313827[/C][C]268.003371406875[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 19 )[/C][C]109.576875[/C][C]0.404194848188865[/C][C]271.099138178028[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 19 )[/C][C]109.617666666667[/C][C]0.402366186318781[/C][C]272.432600933867[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 19 )[/C][C]109.667857142857[/C][C]0.398637347339505[/C][C]275.106830493373[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 19 )[/C][C]109.724615384615[/C][C]0.398405371746776[/C][C]275.409477797794[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 19 )[/C][C]109.79375[/C][C]0.39560713407241[/C][C]277.532280244228[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 19 )[/C][C]109.875[/C][C]0.39121508460723[/C][C]280.855734666549[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 19 )[/C][C]109.966[/C][C]0.384350717033558[/C][C]286.108481463815[/C][/ROW]
[ROW][C]Median[/C][C]110.995[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]108.945[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]109.533793103448[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]109.617666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]109.617666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]109.617666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]109.667857142857[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]109.617666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]109.617666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]109.617666666667[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]58[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102038&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102038&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 Mean109.3031034482760.446251864276248244.935903238295
Geometric Mean109.250891516231
Harmonic Mean109.198415857858
Quadratic Mean109.355015636356
Winsorized Mean ( 1 / 19 )109.3074137931030.444140009994834246.110261028667
Winsorized Mean ( 2 / 19 )109.2963793103450.441500336104231247.556729570738
Winsorized Mean ( 3 / 19 )109.3170689655170.435842704648642250.817709691032
Winsorized Mean ( 4 / 19 )109.3384482758620.43069786795599253.863453735589
Winsorized Mean ( 5 / 19 )109.3393103448280.430220252126658254.14728805616
Winsorized Mean ( 6 / 19 )109.2958620689660.421901038224147259.05568407466
Winsorized Mean ( 7 / 19 )109.2693103448280.410444910954627266.221622996092
Winsorized Mean ( 8 / 19 )109.2665517241380.40767200554998268.025643744483
Winsorized Mean ( 9 / 19 )109.2308620689660.396104693586012275.76260478026
Winsorized Mean ( 10 / 19 )109.2067241379310.391519476887519278.930501762254
Winsorized Mean ( 11 / 19 )109.2010344827590.387670044625594281.68551064662
Winsorized Mean ( 12 / 19 )109.192758620690.382568040605705285.420492647031
Winsorized Mean ( 13 / 19 )109.3025862068970.361838800607697302.075360694669
Winsorized Mean ( 14 / 19 )109.2784482758620.357781343165755305.433612912664
Winsorized Mean ( 15 / 19 )109.2862068965520.332229797109605328.947637591029
Winsorized Mean ( 16 / 19 )109.2668965517240.328930070596782332.188833795219
Winsorized Mean ( 17 / 19 )109.2698275862070.318132832596703343.47233730738
Winsorized Mean ( 18 / 19 )109.3101724137930.306976305256723356.086676860539
Winsorized Mean ( 19 / 19 )109.3003448275860.296363109871581368.805499695788
Trimmed Mean ( 1 / 19 )109.3158928571430.440764225395713248.01444073416
Trimmed Mean ( 2 / 19 )109.3250.436206788901133250.626544065041
Trimmed Mean ( 3 / 19 )109.3409615384620.431862766909919253.184506552445
Trimmed Mean ( 4 / 19 )109.35020.428634899109596255.112685008041
Trimmed Mean ( 5 / 19 )109.353750.425967674434482256.718423869086
Trimmed Mean ( 6 / 19 )109.3573913043480.422114007401669259.070747207607
Trimmed Mean ( 7 / 19 )109.3709090909090.419013214354362261.020190638698
Trimmed Mean ( 8 / 19 )109.3909523809520.417371734631371262.094778597233
Trimmed Mean ( 9 / 19 )109.41350.414986955309348263.655275425317
Trimmed Mean ( 10 / 19 )109.4444736842110.413687352718459264.558423082116
Trimmed Mean ( 11 / 19 )109.4827777777780.41175516903129265.892904357099
Trimmed Mean ( 12 / 19 )109.5264705882350.408675719313827268.003371406875
Trimmed Mean ( 13 / 19 )109.5768750.404194848188865271.099138178028
Trimmed Mean ( 14 / 19 )109.6176666666670.402366186318781272.432600933867
Trimmed Mean ( 15 / 19 )109.6678571428570.398637347339505275.106830493373
Trimmed Mean ( 16 / 19 )109.7246153846150.398405371746776275.409477797794
Trimmed Mean ( 17 / 19 )109.793750.39560713407241277.532280244228
Trimmed Mean ( 18 / 19 )109.8750.39121508460723280.855734666549
Trimmed Mean ( 19 / 19 )109.9660.384350717033558286.108481463815
Median110.995
Midrange108.945
Midmean - Weighted Average at Xnp109.533793103448
Midmean - Weighted Average at X(n+1)p109.617666666667
Midmean - Empirical Distribution Function109.617666666667
Midmean - Empirical Distribution Function - Averaging109.617666666667
Midmean - Empirical Distribution Function - Interpolation109.667857142857
Midmean - Closest Observation109.617666666667
Midmean - True Basic - Statistics Graphics Toolkit109.617666666667
Midmean - MS Excel (old versions)109.617666666667
Number of observations58



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,hyperlink('arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
a<-table.element(a,arm)
a<-table.element(a,hyperlink('arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
a<-table.element(a,armose)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
a<-table.element(a,geo)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
a<-table.element(a,har)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
a<-table.element(a,qua)
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,hyperlink('winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
a<-table.element(a,win[j,1])
a<-table.element(a,win[j,2])
a<-table.element(a,win[j,1]/win[j,2])
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,hyperlink('arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
a<-table.element(a,tri[j,1])
a<-table.element(a,tri[j,2])
a<-table.element(a,tri[j,1]/tri[j,2])
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,hyperlink('median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
a<-table.element(a,median(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,hyperlink('midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
a<-table.element(a,midr)
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_1.htm','Weighted Average at Xnp',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[2])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_3.htm','Empirical Distribution Function',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[3])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[4])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[5])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_6.htm','Closest Observation',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[6])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[7])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <- hyperlink('midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('method_8.htm','MS Excel (old versions)',''),sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,midm[8])
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,length(x))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')