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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationSat, 10 Oct 2015 11:05:44 +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/2015/Oct/10/t1444471575hbwfib46wja8gu1.htm/, Retrieved Mon, 13 May 2024 20:43:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=282107, Retrieved Mon, 13 May 2024 20:43:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [Consumptieprijsin...] [2015-10-10 10:05:44] [91f26e786dd8a1c147ebc049dd81fbad] [Current]
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Dataseries X:
73,97
75,01
75,98
78,85
79,34
79,62
79,76
79,62
79,89
79,88
79,97
79,63
80,04
80,23
80,44
81,78
82,51
82,43
82,35
82,53
82,08
82,73
82,46
81,98
82,11
82,26
82,51
82,89
83,83
84,73
84,48
84,84
84,99
84,7
84,54
84,73
84,51
84,54
84,27
84,47
84,25
84,33
84,29
84,53
84,01
84,18
84,08
83,44
83,61
83,89
83,4
82,96
82,76
83,35
87,78
88,99
88,92
88,91
89,79
90,54
93,15
92,79
93,21
95,35
100,91
103,69
104,04
104,16
104,71
105,18
104,92
104,83
104,9
105,05
104,6
103,21
102,52
101,09
101,19
102,34
102,62
102,47
101,82
101,86
101,54
101,98
101,23
100,4
99,94
99,94
100
98,8
99,07
99,46
99,18
98,47
97,12
96,91
96,09
97,17
96,8
97,13
99,9
100,56
100,84
99,81
100,44
100,07




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282107&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282107&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 time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean90.73101851851850.897949588688089101.042441203272
Geometric Mean90.2588436511195
Harmonic Mean89.792434122805
Quadratic Mean91.2052260675727
Winsorized Mean ( 1 / 36 )90.73944444444440.896139443542683101.2559430324
Winsorized Mean ( 2 / 36 )90.7550.892918919585627101.63856763402
Winsorized Mean ( 3 / 36 )90.83416666666670.881600949453626103.033199684008
Winsorized Mean ( 4 / 36 )90.84972222222220.87895159686326103.361462162923
Winsorized Mean ( 5 / 36 )90.85712962962960.876558623207316103.652085809372
Winsorized Mean ( 6 / 36 )90.85101851851850.875658946260702103.751602043783
Winsorized Mean ( 7 / 36 )90.82314814814820.871449148259307104.220823819226
Winsorized Mean ( 8 / 36 )90.82388888888890.869030901687708104.511690795464
Winsorized Mean ( 9 / 36 )90.80472222222220.863738868600585105.129832086106
Winsorized Mean ( 10 / 36 )90.76120370370370.85751573857893105.842026706253
Winsorized Mean ( 11 / 36 )90.70925925925920.848532234094089106.901371114207
Winsorized Mean ( 12 / 36 )90.70592592592590.846160377126329107.19708506557
Winsorized Mean ( 13 / 36 )90.72277777777780.842697818259608107.65754439135
Winsorized Mean ( 14 / 36 )90.73314814814810.837360897021911108.356084539942
Winsorized Mean ( 15 / 36 )90.86925925925930.810459538970196112.120661044624
Winsorized Mean ( 16 / 36 )90.88111111111110.805104199114542112.881178872328
Winsorized Mean ( 17 / 36 )90.89055555555560.802681780920362113.233609776641
Winsorized Mean ( 18 / 36 )90.84888888888890.796271591943735114.092841949972
Winsorized Mean ( 19 / 36 )90.82074074074070.786782839245966115.433047354949
Winsorized Mean ( 20 / 36 )90.830.784177976386771115.828297574122
Winsorized Mean ( 21 / 36 )90.82611111111110.780213954659602116.411800338457
Winsorized Mean ( 22 / 36 )90.79555555555560.775109661100466117.138980601336
Winsorized Mean ( 23 / 36 )90.79129629629630.772225480460258117.570966762432
Winsorized Mean ( 24 / 36 )90.72907407407410.764703777988037118.646038748214
Winsorized Mean ( 25 / 36 )90.70592592592590.760909532511788119.207240874618
Winsorized Mean ( 26 / 36 )90.74444444444440.754952270449274120.198915873771
Winsorized Mean ( 27 / 36 )90.66944444444440.744408472728663121.800661553584
Winsorized Mean ( 28 / 36 )90.6850.738933650921264122.724144294875
Winsorized Mean ( 29 / 36 )90.68768518518520.735187340658849123.353164791867
Winsorized Mean ( 30 / 36 )90.79601851851850.724663812910058125.293987226857
Winsorized Mean ( 31 / 36 )90.79888888888890.721934026691261125.771726406961
Winsorized Mean ( 32 / 36 )90.78407407407410.71766154516364126.499844788777
Winsorized Mean ( 33 / 36 )90.72907407407410.700192224225599129.577380232148
Winsorized Mean ( 34 / 36 )90.71018518518520.683401384316111132.733393971626
Winsorized Mean ( 35 / 36 )90.69398148148150.677449888426764133.875557485291
Winsorized Mean ( 36 / 36 )90.64398148148150.663332014951632136.649489906033
Trimmed Mean ( 1 / 36 )90.75283018867920.890601982576716101.900548128256
Trimmed Mean ( 2 / 36 )90.76673076923080.884252388222639102.647990526408
Trimmed Mean ( 3 / 36 )90.77294117647060.878835627160061103.287734783581
Trimmed Mean ( 4 / 36 )90.75090.877035411503038103.47461323651
Trimmed Mean ( 5 / 36 )90.72367346938780.875508308822163103.624000543684
Trimmed Mean ( 6 / 36 )90.69364583333330.874059282783492103.761435430917
Trimmed Mean ( 7 / 36 )90.66351063829790.872270166761254103.939712824218
Trimmed Mean ( 8 / 36 )90.63673913043480.870732170571975104.092558186861
Trimmed Mean ( 9 / 36 )90.60866666666670.869041347646992104.262779799831
Trimmed Mean ( 10 / 36 )90.58193181818180.867617142045514104.403114494285
Trimmed Mean ( 11 / 36 )90.55941860465120.866562123534109104.504242852574
Trimmed Mean ( 12 / 36 )90.54190476190480.866247181174312104.522019499288
Trimmed Mean ( 13 / 36 )90.52390243902440.865711302978837104.565924145312
Trimmed Mean ( 14 / 36 )90.503250.865036341795292104.623639062574
Trimmed Mean ( 15 / 36 )90.48051282051280.864414840743512104.672558308563
Trimmed Mean ( 16 / 36 )90.44368421052630.866503476716388104.377751089081
Trimmed Mean ( 17 / 36 )90.40378378378380.868814375574034104.054198831659
Trimmed Mean ( 18 / 36 )90.36083333333330.870968125336463103.74757778699
Trimmed Mean ( 19 / 36 )90.3190.873430734773631103.407169457356
Trimmed Mean ( 20 / 36 )90.27705882352940.87655536060864102.99070986326
Trimmed Mean ( 21 / 36 )90.23181818181820.879517480265637102.592410277697
Trimmed Mean ( 22 / 36 )90.18406250.882425879310936102.200155972785
Trimmed Mean ( 23 / 36 )90.13564516129030.885389833412906101.803343295512
Trimmed Mean ( 24 / 36 )90.08433333333330.888068346439208101.438513932553
Trimmed Mean ( 25 / 36 )90.03431034482760.891008425346955101.0476531799
Trimmed Mean ( 26 / 36 )89.98250.893678529973203100.687771924764
Trimmed Mean ( 27 / 36 )89.92388888888890.896177199048328100.341638890591
Trimmed Mean ( 28 / 36 )89.86653846153850.89916426274001399.9445175764539
Trimmed Mean ( 29 / 36 )89.80340.90182896292331899.5791926097587
Trimmed Mean ( 30 / 36 )89.73479166666670.90378567435859999.2876897836978
Trimmed Mean ( 31 / 36 )89.65173913043480.90557480634604698.9998159204269
Trimmed Mean ( 32 / 36 )89.56090909090910.90601174090032798.8518195160586
Trimmed Mean ( 33 / 36 )89.4626190476190.90493126127536798.8612316492798
Trimmed Mean ( 34 / 36 )89.3590.90423383066152898.8228895778274
Trimmed Mean ( 35 / 36 )89.24605263157890.90360818837832898.7663168388785
Trimmed Mean ( 36 / 36 )89.12194444444450.90073081610790998.9440383860116
Median86.385
Midrange89.575
Midmean - Weighted Average at Xnp89.7930909090909
Midmean - Weighted Average at X(n+1)p89.9238888888889
Midmean - Empirical Distribution Function89.7930909090909
Midmean - Empirical Distribution Function - Averaging89.9238888888889
Midmean - Empirical Distribution Function - Interpolation89.9238888888889
Midmean - Closest Observation89.7930909090909
Midmean - True Basic - Statistics Graphics Toolkit89.9238888888889
Midmean - MS Excel (old versions)89.9825
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 90.7310185185185 & 0.897949588688089 & 101.042441203272 \tabularnewline
Geometric Mean & 90.2588436511195 &  &  \tabularnewline
Harmonic Mean & 89.792434122805 &  &  \tabularnewline
Quadratic Mean & 91.2052260675727 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 90.7394444444444 & 0.896139443542683 & 101.2559430324 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 90.755 & 0.892918919585627 & 101.63856763402 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 90.8341666666667 & 0.881600949453626 & 103.033199684008 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 90.8497222222222 & 0.87895159686326 & 103.361462162923 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 90.8571296296296 & 0.876558623207316 & 103.652085809372 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 90.8510185185185 & 0.875658946260702 & 103.751602043783 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 90.8231481481482 & 0.871449148259307 & 104.220823819226 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 90.8238888888889 & 0.869030901687708 & 104.511690795464 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 90.8047222222222 & 0.863738868600585 & 105.129832086106 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 90.7612037037037 & 0.85751573857893 & 105.842026706253 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 90.7092592592592 & 0.848532234094089 & 106.901371114207 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 90.7059259259259 & 0.846160377126329 & 107.19708506557 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 90.7227777777778 & 0.842697818259608 & 107.65754439135 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 90.7331481481481 & 0.837360897021911 & 108.356084539942 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 90.8692592592593 & 0.810459538970196 & 112.120661044624 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 90.8811111111111 & 0.805104199114542 & 112.881178872328 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 90.8905555555556 & 0.802681780920362 & 113.233609776641 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 90.8488888888889 & 0.796271591943735 & 114.092841949972 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 90.8207407407407 & 0.786782839245966 & 115.433047354949 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 90.83 & 0.784177976386771 & 115.828297574122 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 90.8261111111111 & 0.780213954659602 & 116.411800338457 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 90.7955555555556 & 0.775109661100466 & 117.138980601336 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 90.7912962962963 & 0.772225480460258 & 117.570966762432 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 90.7290740740741 & 0.764703777988037 & 118.646038748214 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 90.7059259259259 & 0.760909532511788 & 119.207240874618 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 90.7444444444444 & 0.754952270449274 & 120.198915873771 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 90.6694444444444 & 0.744408472728663 & 121.800661553584 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 90.685 & 0.738933650921264 & 122.724144294875 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 90.6876851851852 & 0.735187340658849 & 123.353164791867 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 90.7960185185185 & 0.724663812910058 & 125.293987226857 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 90.7988888888889 & 0.721934026691261 & 125.771726406961 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 90.7840740740741 & 0.71766154516364 & 126.499844788777 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 90.7290740740741 & 0.700192224225599 & 129.577380232148 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 90.7101851851852 & 0.683401384316111 & 132.733393971626 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 90.6939814814815 & 0.677449888426764 & 133.875557485291 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 90.6439814814815 & 0.663332014951632 & 136.649489906033 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 90.7528301886792 & 0.890601982576716 & 101.900548128256 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 90.7667307692308 & 0.884252388222639 & 102.647990526408 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 90.7729411764706 & 0.878835627160061 & 103.287734783581 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 90.7509 & 0.877035411503038 & 103.47461323651 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 90.7236734693878 & 0.875508308822163 & 103.624000543684 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 90.6936458333333 & 0.874059282783492 & 103.761435430917 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 90.6635106382979 & 0.872270166761254 & 103.939712824218 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 90.6367391304348 & 0.870732170571975 & 104.092558186861 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 90.6086666666667 & 0.869041347646992 & 104.262779799831 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 90.5819318181818 & 0.867617142045514 & 104.403114494285 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 90.5594186046512 & 0.866562123534109 & 104.504242852574 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 90.5419047619048 & 0.866247181174312 & 104.522019499288 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 90.5239024390244 & 0.865711302978837 & 104.565924145312 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 90.50325 & 0.865036341795292 & 104.623639062574 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 90.4805128205128 & 0.864414840743512 & 104.672558308563 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 90.4436842105263 & 0.866503476716388 & 104.377751089081 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 90.4037837837838 & 0.868814375574034 & 104.054198831659 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 90.3608333333333 & 0.870968125336463 & 103.74757778699 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 90.319 & 0.873430734773631 & 103.407169457356 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 90.2770588235294 & 0.87655536060864 & 102.99070986326 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 90.2318181818182 & 0.879517480265637 & 102.592410277697 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 90.1840625 & 0.882425879310936 & 102.200155972785 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 90.1356451612903 & 0.885389833412906 & 101.803343295512 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 90.0843333333333 & 0.888068346439208 & 101.438513932553 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 90.0343103448276 & 0.891008425346955 & 101.0476531799 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 89.9825 & 0.893678529973203 & 100.687771924764 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 89.9238888888889 & 0.896177199048328 & 100.341638890591 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 89.8665384615385 & 0.899164262740013 & 99.9445175764539 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 89.8034 & 0.901828962923318 & 99.5791926097587 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 89.7347916666667 & 0.903785674358599 & 99.2876897836978 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 89.6517391304348 & 0.905574806346046 & 98.9998159204269 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 89.5609090909091 & 0.906011740900327 & 98.8518195160586 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 89.462619047619 & 0.904931261275367 & 98.8612316492798 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 89.359 & 0.904233830661528 & 98.8228895778274 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 89.2460526315789 & 0.903608188378328 & 98.7663168388785 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 89.1219444444445 & 0.900730816107909 & 98.9440383860116 \tabularnewline
Median & 86.385 &  &  \tabularnewline
Midrange & 89.575 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 89.7930909090909 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 89.9238888888889 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 89.7930909090909 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 89.9238888888889 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 89.9238888888889 &  &  \tabularnewline
Midmean - Closest Observation & 89.7930909090909 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 89.9238888888889 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 89.9825 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=282107&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]90.7310185185185[/C][C]0.897949588688089[/C][C]101.042441203272[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]90.2588436511195[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]89.792434122805[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]91.2052260675727[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]90.7394444444444[/C][C]0.896139443542683[/C][C]101.2559430324[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]90.755[/C][C]0.892918919585627[/C][C]101.63856763402[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]90.8341666666667[/C][C]0.881600949453626[/C][C]103.033199684008[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]90.8497222222222[/C][C]0.87895159686326[/C][C]103.361462162923[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]90.8571296296296[/C][C]0.876558623207316[/C][C]103.652085809372[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]90.8510185185185[/C][C]0.875658946260702[/C][C]103.751602043783[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]90.8231481481482[/C][C]0.871449148259307[/C][C]104.220823819226[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]90.8238888888889[/C][C]0.869030901687708[/C][C]104.511690795464[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]90.8047222222222[/C][C]0.863738868600585[/C][C]105.129832086106[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]90.7612037037037[/C][C]0.85751573857893[/C][C]105.842026706253[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]90.7092592592592[/C][C]0.848532234094089[/C][C]106.901371114207[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]90.7059259259259[/C][C]0.846160377126329[/C][C]107.19708506557[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]90.7227777777778[/C][C]0.842697818259608[/C][C]107.65754439135[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]90.7331481481481[/C][C]0.837360897021911[/C][C]108.356084539942[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]90.8692592592593[/C][C]0.810459538970196[/C][C]112.120661044624[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]90.8811111111111[/C][C]0.805104199114542[/C][C]112.881178872328[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]90.8905555555556[/C][C]0.802681780920362[/C][C]113.233609776641[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]90.8488888888889[/C][C]0.796271591943735[/C][C]114.092841949972[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]90.8207407407407[/C][C]0.786782839245966[/C][C]115.433047354949[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]90.83[/C][C]0.784177976386771[/C][C]115.828297574122[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]90.8261111111111[/C][C]0.780213954659602[/C][C]116.411800338457[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]90.7955555555556[/C][C]0.775109661100466[/C][C]117.138980601336[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]90.7912962962963[/C][C]0.772225480460258[/C][C]117.570966762432[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]90.7290740740741[/C][C]0.764703777988037[/C][C]118.646038748214[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]90.7059259259259[/C][C]0.760909532511788[/C][C]119.207240874618[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]90.7444444444444[/C][C]0.754952270449274[/C][C]120.198915873771[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]90.6694444444444[/C][C]0.744408472728663[/C][C]121.800661553584[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]90.685[/C][C]0.738933650921264[/C][C]122.724144294875[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]90.6876851851852[/C][C]0.735187340658849[/C][C]123.353164791867[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]90.7960185185185[/C][C]0.724663812910058[/C][C]125.293987226857[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]90.7988888888889[/C][C]0.721934026691261[/C][C]125.771726406961[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]90.7840740740741[/C][C]0.71766154516364[/C][C]126.499844788777[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]90.7290740740741[/C][C]0.700192224225599[/C][C]129.577380232148[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]90.7101851851852[/C][C]0.683401384316111[/C][C]132.733393971626[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]90.6939814814815[/C][C]0.677449888426764[/C][C]133.875557485291[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]90.6439814814815[/C][C]0.663332014951632[/C][C]136.649489906033[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]90.7528301886792[/C][C]0.890601982576716[/C][C]101.900548128256[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]90.7667307692308[/C][C]0.884252388222639[/C][C]102.647990526408[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]90.7729411764706[/C][C]0.878835627160061[/C][C]103.287734783581[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]90.7509[/C][C]0.877035411503038[/C][C]103.47461323651[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]90.7236734693878[/C][C]0.875508308822163[/C][C]103.624000543684[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]90.6936458333333[/C][C]0.874059282783492[/C][C]103.761435430917[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]90.6635106382979[/C][C]0.872270166761254[/C][C]103.939712824218[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]90.6367391304348[/C][C]0.870732170571975[/C][C]104.092558186861[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]90.6086666666667[/C][C]0.869041347646992[/C][C]104.262779799831[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]90.5819318181818[/C][C]0.867617142045514[/C][C]104.403114494285[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]90.5594186046512[/C][C]0.866562123534109[/C][C]104.504242852574[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]90.5419047619048[/C][C]0.866247181174312[/C][C]104.522019499288[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]90.5239024390244[/C][C]0.865711302978837[/C][C]104.565924145312[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]90.50325[/C][C]0.865036341795292[/C][C]104.623639062574[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]90.4805128205128[/C][C]0.864414840743512[/C][C]104.672558308563[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]90.4436842105263[/C][C]0.866503476716388[/C][C]104.377751089081[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]90.4037837837838[/C][C]0.868814375574034[/C][C]104.054198831659[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]90.3608333333333[/C][C]0.870968125336463[/C][C]103.74757778699[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]90.319[/C][C]0.873430734773631[/C][C]103.407169457356[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]90.2770588235294[/C][C]0.87655536060864[/C][C]102.99070986326[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]90.2318181818182[/C][C]0.879517480265637[/C][C]102.592410277697[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]90.1840625[/C][C]0.882425879310936[/C][C]102.200155972785[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]90.1356451612903[/C][C]0.885389833412906[/C][C]101.803343295512[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]90.0843333333333[/C][C]0.888068346439208[/C][C]101.438513932553[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]90.0343103448276[/C][C]0.891008425346955[/C][C]101.0476531799[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]89.9825[/C][C]0.893678529973203[/C][C]100.687771924764[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]89.9238888888889[/C][C]0.896177199048328[/C][C]100.341638890591[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]89.8665384615385[/C][C]0.899164262740013[/C][C]99.9445175764539[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]89.8034[/C][C]0.901828962923318[/C][C]99.5791926097587[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]89.7347916666667[/C][C]0.903785674358599[/C][C]99.2876897836978[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]89.6517391304348[/C][C]0.905574806346046[/C][C]98.9998159204269[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]89.5609090909091[/C][C]0.906011740900327[/C][C]98.8518195160586[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]89.462619047619[/C][C]0.904931261275367[/C][C]98.8612316492798[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]89.359[/C][C]0.904233830661528[/C][C]98.8228895778274[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]89.2460526315789[/C][C]0.903608188378328[/C][C]98.7663168388785[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]89.1219444444445[/C][C]0.900730816107909[/C][C]98.9440383860116[/C][/ROW]
[ROW][C]Median[/C][C]86.385[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]89.575[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]89.7930909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]89.9238888888889[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]89.7930909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]89.9238888888889[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]89.9238888888889[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]89.7930909090909[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]89.9238888888889[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]89.9825[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]108[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=282107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=282107&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 Mean90.73101851851850.897949588688089101.042441203272
Geometric Mean90.2588436511195
Harmonic Mean89.792434122805
Quadratic Mean91.2052260675727
Winsorized Mean ( 1 / 36 )90.73944444444440.896139443542683101.2559430324
Winsorized Mean ( 2 / 36 )90.7550.892918919585627101.63856763402
Winsorized Mean ( 3 / 36 )90.83416666666670.881600949453626103.033199684008
Winsorized Mean ( 4 / 36 )90.84972222222220.87895159686326103.361462162923
Winsorized Mean ( 5 / 36 )90.85712962962960.876558623207316103.652085809372
Winsorized Mean ( 6 / 36 )90.85101851851850.875658946260702103.751602043783
Winsorized Mean ( 7 / 36 )90.82314814814820.871449148259307104.220823819226
Winsorized Mean ( 8 / 36 )90.82388888888890.869030901687708104.511690795464
Winsorized Mean ( 9 / 36 )90.80472222222220.863738868600585105.129832086106
Winsorized Mean ( 10 / 36 )90.76120370370370.85751573857893105.842026706253
Winsorized Mean ( 11 / 36 )90.70925925925920.848532234094089106.901371114207
Winsorized Mean ( 12 / 36 )90.70592592592590.846160377126329107.19708506557
Winsorized Mean ( 13 / 36 )90.72277777777780.842697818259608107.65754439135
Winsorized Mean ( 14 / 36 )90.73314814814810.837360897021911108.356084539942
Winsorized Mean ( 15 / 36 )90.86925925925930.810459538970196112.120661044624
Winsorized Mean ( 16 / 36 )90.88111111111110.805104199114542112.881178872328
Winsorized Mean ( 17 / 36 )90.89055555555560.802681780920362113.233609776641
Winsorized Mean ( 18 / 36 )90.84888888888890.796271591943735114.092841949972
Winsorized Mean ( 19 / 36 )90.82074074074070.786782839245966115.433047354949
Winsorized Mean ( 20 / 36 )90.830.784177976386771115.828297574122
Winsorized Mean ( 21 / 36 )90.82611111111110.780213954659602116.411800338457
Winsorized Mean ( 22 / 36 )90.79555555555560.775109661100466117.138980601336
Winsorized Mean ( 23 / 36 )90.79129629629630.772225480460258117.570966762432
Winsorized Mean ( 24 / 36 )90.72907407407410.764703777988037118.646038748214
Winsorized Mean ( 25 / 36 )90.70592592592590.760909532511788119.207240874618
Winsorized Mean ( 26 / 36 )90.74444444444440.754952270449274120.198915873771
Winsorized Mean ( 27 / 36 )90.66944444444440.744408472728663121.800661553584
Winsorized Mean ( 28 / 36 )90.6850.738933650921264122.724144294875
Winsorized Mean ( 29 / 36 )90.68768518518520.735187340658849123.353164791867
Winsorized Mean ( 30 / 36 )90.79601851851850.724663812910058125.293987226857
Winsorized Mean ( 31 / 36 )90.79888888888890.721934026691261125.771726406961
Winsorized Mean ( 32 / 36 )90.78407407407410.71766154516364126.499844788777
Winsorized Mean ( 33 / 36 )90.72907407407410.700192224225599129.577380232148
Winsorized Mean ( 34 / 36 )90.71018518518520.683401384316111132.733393971626
Winsorized Mean ( 35 / 36 )90.69398148148150.677449888426764133.875557485291
Winsorized Mean ( 36 / 36 )90.64398148148150.663332014951632136.649489906033
Trimmed Mean ( 1 / 36 )90.75283018867920.890601982576716101.900548128256
Trimmed Mean ( 2 / 36 )90.76673076923080.884252388222639102.647990526408
Trimmed Mean ( 3 / 36 )90.77294117647060.878835627160061103.287734783581
Trimmed Mean ( 4 / 36 )90.75090.877035411503038103.47461323651
Trimmed Mean ( 5 / 36 )90.72367346938780.875508308822163103.624000543684
Trimmed Mean ( 6 / 36 )90.69364583333330.874059282783492103.761435430917
Trimmed Mean ( 7 / 36 )90.66351063829790.872270166761254103.939712824218
Trimmed Mean ( 8 / 36 )90.63673913043480.870732170571975104.092558186861
Trimmed Mean ( 9 / 36 )90.60866666666670.869041347646992104.262779799831
Trimmed Mean ( 10 / 36 )90.58193181818180.867617142045514104.403114494285
Trimmed Mean ( 11 / 36 )90.55941860465120.866562123534109104.504242852574
Trimmed Mean ( 12 / 36 )90.54190476190480.866247181174312104.522019499288
Trimmed Mean ( 13 / 36 )90.52390243902440.865711302978837104.565924145312
Trimmed Mean ( 14 / 36 )90.503250.865036341795292104.623639062574
Trimmed Mean ( 15 / 36 )90.48051282051280.864414840743512104.672558308563
Trimmed Mean ( 16 / 36 )90.44368421052630.866503476716388104.377751089081
Trimmed Mean ( 17 / 36 )90.40378378378380.868814375574034104.054198831659
Trimmed Mean ( 18 / 36 )90.36083333333330.870968125336463103.74757778699
Trimmed Mean ( 19 / 36 )90.3190.873430734773631103.407169457356
Trimmed Mean ( 20 / 36 )90.27705882352940.87655536060864102.99070986326
Trimmed Mean ( 21 / 36 )90.23181818181820.879517480265637102.592410277697
Trimmed Mean ( 22 / 36 )90.18406250.882425879310936102.200155972785
Trimmed Mean ( 23 / 36 )90.13564516129030.885389833412906101.803343295512
Trimmed Mean ( 24 / 36 )90.08433333333330.888068346439208101.438513932553
Trimmed Mean ( 25 / 36 )90.03431034482760.891008425346955101.0476531799
Trimmed Mean ( 26 / 36 )89.98250.893678529973203100.687771924764
Trimmed Mean ( 27 / 36 )89.92388888888890.896177199048328100.341638890591
Trimmed Mean ( 28 / 36 )89.86653846153850.89916426274001399.9445175764539
Trimmed Mean ( 29 / 36 )89.80340.90182896292331899.5791926097587
Trimmed Mean ( 30 / 36 )89.73479166666670.90378567435859999.2876897836978
Trimmed Mean ( 31 / 36 )89.65173913043480.90557480634604698.9998159204269
Trimmed Mean ( 32 / 36 )89.56090909090910.90601174090032798.8518195160586
Trimmed Mean ( 33 / 36 )89.4626190476190.90493126127536798.8612316492798
Trimmed Mean ( 34 / 36 )89.3590.90423383066152898.8228895778274
Trimmed Mean ( 35 / 36 )89.24605263157890.90360818837832898.7663168388785
Trimmed Mean ( 36 / 36 )89.12194444444450.90073081610790998.9440383860116
Median86.385
Midrange89.575
Midmean - Weighted Average at Xnp89.7930909090909
Midmean - Weighted Average at X(n+1)p89.9238888888889
Midmean - Empirical Distribution Function89.7930909090909
Midmean - Empirical Distribution Function - Averaging89.9238888888889
Midmean - Empirical Distribution Function - Interpolation89.9238888888889
Midmean - Closest Observation89.7930909090909
Midmean - True Basic - Statistics Graphics Toolkit89.9238888888889
Midmean - MS Excel (old versions)89.9825
Number of observations108



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')