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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 computationThu, 03 Mar 2016 21:38:56 +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/2016/Mar/03/t14570414628tldrvjdg1depym.htm/, Retrieved Fri, 03 May 2024 14:38:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293322, Retrieved Fri, 03 May 2024 14:38:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [Opgave 4 oef 1a] [2016-03-03 21:14:40] [74be16979710d4c4e7c6647856088456]
- RMPD    [Central Tendency] [Opgave 5 oef 1a] [2016-03-03 21:38:56] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
96.86
96.89
96.9
96.94
96.88
96.89
96.89
96.95
97.03
97.29
97.37
97.41
97.41
97.32
97.33
97.38
97.47
97.5
97.5
97.58
97.7
97.9
97.98
98.03
98.03
97.94
98.12
98.19
98.34
98.42
98.43
98.45
98.77
99.24
99.46
99.54
99.55
99.24
99.43
99.47
99.57
99.62
99.64
99.75
99.85
100.28
100.52
100.57
100.57
100.27
100.27
100.18
100.16
100.18
100.18
100.59
100.69
101.06
101.15
101.16
101.16
100.81
100.94
101.13
101.29
101.34
101.35
101.7
102.05
102.48
102.66
102.72
102.73
102.18
102.22
102.37
102.53
102.61
102.62
103
103.17
103.52
103.69
103.73
99.57
99.09
99.14
99.36
99.6
99.65
99.8
100.15
100.45
100.89
101.13
101.17
101.21
101.1
101.17
101.11
101.2
101.15
100.92
101.1
101.22
101.25
101.39
101.43




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=293322&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=293322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293322&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 Mean99.91231481481480.179861038553002555.497263991236
Geometric Mean99.8949802940607
Harmonic Mean99.8776350766272
Quadratic Mean99.9296357489905
Winsorized Mean ( 1 / 36 )99.91212962962960.179758647994079555.812645146957
Winsorized Mean ( 2 / 36 )99.90916666666670.179123723994758557.766243569114
Winsorized Mean ( 3 / 36 )99.89944444444440.177369818452805563.226851760161
Winsorized Mean ( 4 / 36 )99.89314814814810.176308766186094566.580722609736
Winsorized Mean ( 5 / 36 )99.88111111111110.174250177891478573.205217462197
Winsorized Mean ( 6 / 36 )99.88277777777780.173811885982462574.660226561583
Winsorized Mean ( 7 / 36 )99.8795370370370.173120845086456576.935359731855
Winsorized Mean ( 8 / 36 )99.88250.171749247948844581.560042869884
Winsorized Mean ( 9 / 36 )99.90333333333330.168370470801349593.354243519364
Winsorized Mean ( 10 / 36 )99.89870370370370.166866084881581598.675900945349
Winsorized Mean ( 11 / 36 )99.89462962962960.165973033562545601.872650547087
Winsorized Mean ( 12 / 36 )99.88685185185190.163575733418229610.6459055052
Winsorized Mean ( 13 / 36 )99.870.160888574063248620.740164933896
Winsorized Mean ( 14 / 36 )99.86870370370370.159622645429021625.654984199043
Winsorized Mean ( 15 / 36 )99.85064814814820.157220375058306635.099923347201
Winsorized Mean ( 16 / 36 )99.80768518518520.149460643704757667.785730819841
Winsorized Mean ( 17 / 36 )99.76990740740740.143958794689808693.044892619339
Winsorized Mean ( 18 / 36 )99.76324074074070.143245754880095696.448148318589
Winsorized Mean ( 19 / 36 )99.77027777777780.14043745987913710.424966840375
Winsorized Mean ( 20 / 36 )99.79064814814810.137038111413281728.196317936685
Winsorized Mean ( 21 / 36 )99.81981481481480.130566037546656764.515923822421
Winsorized Mean ( 22 / 36 )99.81981481481480.128597352285767776.219829106564
Winsorized Mean ( 23 / 36 )99.82194444444440.126775821848737787.389448467129
Winsorized Mean ( 24 / 36 )99.83083333333330.125044618205087798.361694939958
Winsorized Mean ( 25 / 36 )99.82851851851850.124806448615608799.866670559474
Winsorized Mean ( 26 / 36 )99.8429629629630.121166967641385824.011402665997
Winsorized Mean ( 27 / 36 )99.8604629629630.118854677989905840.189588258733
Winsorized Mean ( 28 / 36 )99.89675925925930.113539290343816879.84308301342
Winsorized Mean ( 29 / 36 )99.91824074074070.110805433265949901.744957766846
Winsorized Mean ( 30 / 36 )99.91824074074070.110163966399945906.995672051172
Winsorized Mean ( 31 / 36 )99.92398148148150.109440262199148913.045888903756
Winsorized Mean ( 32 / 36 )100.012870370370.09715938193963081029.36914967731
Winsorized Mean ( 33 / 36 )100.1106481481480.08585754108703381166.00879643951
Winsorized Mean ( 34 / 36 )100.1200925925930.08342035906280741200.18774454341
Winsorized Mean ( 35 / 36 )100.1492592592590.07954838603036771258.97286239129
Winsorized Mean ( 36 / 36 )100.1492592592590.07954838603036771258.97286239129
Trimmed Mean ( 1 / 36 )99.90509433962260.177316436106812563.428278467325
Trimmed Mean ( 2 / 36 )99.89778846153850.174573360058238572.239592731744
Trimmed Mean ( 3 / 36 )99.89176470588240.171862275259131581.231480586809
Trimmed Mean ( 4 / 36 )99.8890.169529443823875589.213282052499
Trimmed Mean ( 5 / 36 )99.88785714285710.167233856753109597.294465858812
Trimmed Mean ( 6 / 36 )99.8893750.165185489338979604.710349557496
Trimmed Mean ( 7 / 36 )99.89063829787230.162955418074433612.993660954834
Trimmed Mean ( 8 / 36 )99.89250.160558525943735622.156309749665
Trimmed Mean ( 9 / 36 )99.8940.158089704145476631.881756879478
Trimmed Mean ( 10 / 36 )99.89272727272730.15588052783131640.828772281479
Trimmed Mean ( 11 / 36 )99.89197674418610.153596627350491650.352670285155
Trimmed Mean ( 12 / 36 )99.89166666666670.151107674707532661.062827285288
Trimmed Mean ( 13 / 36 )99.89219512195120.148613184078974672.162404305043
Trimmed Mean ( 14 / 36 )99.89450.146133814608912683.582374601941
Trimmed Mean ( 15 / 36 )99.89705128205130.143436384166788696.455448611217
Trimmed Mean ( 16 / 36 )99.9014473684210.14064097677786710.329589975857
Trimmed Mean ( 17 / 36 )99.910.138480407996009721.473899779954
Trimmed Mean ( 18 / 36 )99.92236111111110.136654427062073731.204712934205
Trimmed Mean ( 19 / 36 )99.9360.134540764793814742.793458571116
Trimmed Mean ( 20 / 36 )99.94985294117650.132400092810593754.90772566271
Trimmed Mean ( 21 / 36 )99.96287878787880.1303215970401767.04768095437
Trimmed Mean ( 22 / 36 )99.9743750.128748338523722776.510020605658
Trimmed Mean ( 23 / 36 )99.98661290322580.127062350885722786.909829750845
Trimmed Mean ( 24 / 36 )99.99950.125214037091477798.628511010662
Trimmed Mean ( 25 / 36 )100.0125862068970.123161509537798812.044173396586
Trimmed Mean ( 26 / 36 )100.0267857142860.120599182424609829.415122916076
Trimmed Mean ( 27 / 36 )100.0409259259260.117988104352048847.889933271818
Trimmed Mean ( 28 / 36 )100.0548076923080.115096683859008869.310950912133
Trimmed Mean ( 29 / 36 )100.0670.112417316554099890.13866428527
Trimmed Mean ( 30 / 36 )100.0785416666670.109497154009185913.983039762586
Trimmed Mean ( 31 / 36 )100.0910869565220.1058109828098945.94232374195
Trimmed Mean ( 32 / 36 )100.1043181818180.101139071631561989.769003877039
Trimmed Mean ( 33 / 36 )100.1116666666670.0979427863202781022.1443602727
Trimmed Mean ( 34 / 36 )100.111750.09620350192197411040.62480055243
Trimmed Mean ( 35 / 36 )100.1110526315790.09427856598820061061.86439709009
Trimmed Mean ( 36 / 36 )100.1077777777780.09241049819347831083.29442795757
Median100.17
Midrange100.295
Midmean - Weighted Average at Xnp100.026785714286
Midmean - Weighted Average at X(n+1)p100.061454545455
Midmean - Empirical Distribution Function100.026785714286
Midmean - Empirical Distribution Function - Averaging100.061454545455
Midmean - Empirical Distribution Function - Interpolation100.061454545455
Midmean - Closest Observation100.026785714286
Midmean - True Basic - Statistics Graphics Toolkit100.061454545455
Midmean - MS Excel (old versions)100.026785714286
Number of observations108

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 99.9123148148148 & 0.179861038553002 & 555.497263991236 \tabularnewline
Geometric Mean & 99.8949802940607 &  &  \tabularnewline
Harmonic Mean & 99.8776350766272 &  &  \tabularnewline
Quadratic Mean & 99.9296357489905 &  &  \tabularnewline
Winsorized Mean ( 1 / 36 ) & 99.9121296296296 & 0.179758647994079 & 555.812645146957 \tabularnewline
Winsorized Mean ( 2 / 36 ) & 99.9091666666667 & 0.179123723994758 & 557.766243569114 \tabularnewline
Winsorized Mean ( 3 / 36 ) & 99.8994444444444 & 0.177369818452805 & 563.226851760161 \tabularnewline
Winsorized Mean ( 4 / 36 ) & 99.8931481481481 & 0.176308766186094 & 566.580722609736 \tabularnewline
Winsorized Mean ( 5 / 36 ) & 99.8811111111111 & 0.174250177891478 & 573.205217462197 \tabularnewline
Winsorized Mean ( 6 / 36 ) & 99.8827777777778 & 0.173811885982462 & 574.660226561583 \tabularnewline
Winsorized Mean ( 7 / 36 ) & 99.879537037037 & 0.173120845086456 & 576.935359731855 \tabularnewline
Winsorized Mean ( 8 / 36 ) & 99.8825 & 0.171749247948844 & 581.560042869884 \tabularnewline
Winsorized Mean ( 9 / 36 ) & 99.9033333333333 & 0.168370470801349 & 593.354243519364 \tabularnewline
Winsorized Mean ( 10 / 36 ) & 99.8987037037037 & 0.166866084881581 & 598.675900945349 \tabularnewline
Winsorized Mean ( 11 / 36 ) & 99.8946296296296 & 0.165973033562545 & 601.872650547087 \tabularnewline
Winsorized Mean ( 12 / 36 ) & 99.8868518518519 & 0.163575733418229 & 610.6459055052 \tabularnewline
Winsorized Mean ( 13 / 36 ) & 99.87 & 0.160888574063248 & 620.740164933896 \tabularnewline
Winsorized Mean ( 14 / 36 ) & 99.8687037037037 & 0.159622645429021 & 625.654984199043 \tabularnewline
Winsorized Mean ( 15 / 36 ) & 99.8506481481482 & 0.157220375058306 & 635.099923347201 \tabularnewline
Winsorized Mean ( 16 / 36 ) & 99.8076851851852 & 0.149460643704757 & 667.785730819841 \tabularnewline
Winsorized Mean ( 17 / 36 ) & 99.7699074074074 & 0.143958794689808 & 693.044892619339 \tabularnewline
Winsorized Mean ( 18 / 36 ) & 99.7632407407407 & 0.143245754880095 & 696.448148318589 \tabularnewline
Winsorized Mean ( 19 / 36 ) & 99.7702777777778 & 0.14043745987913 & 710.424966840375 \tabularnewline
Winsorized Mean ( 20 / 36 ) & 99.7906481481481 & 0.137038111413281 & 728.196317936685 \tabularnewline
Winsorized Mean ( 21 / 36 ) & 99.8198148148148 & 0.130566037546656 & 764.515923822421 \tabularnewline
Winsorized Mean ( 22 / 36 ) & 99.8198148148148 & 0.128597352285767 & 776.219829106564 \tabularnewline
Winsorized Mean ( 23 / 36 ) & 99.8219444444444 & 0.126775821848737 & 787.389448467129 \tabularnewline
Winsorized Mean ( 24 / 36 ) & 99.8308333333333 & 0.125044618205087 & 798.361694939958 \tabularnewline
Winsorized Mean ( 25 / 36 ) & 99.8285185185185 & 0.124806448615608 & 799.866670559474 \tabularnewline
Winsorized Mean ( 26 / 36 ) & 99.842962962963 & 0.121166967641385 & 824.011402665997 \tabularnewline
Winsorized Mean ( 27 / 36 ) & 99.860462962963 & 0.118854677989905 & 840.189588258733 \tabularnewline
Winsorized Mean ( 28 / 36 ) & 99.8967592592593 & 0.113539290343816 & 879.84308301342 \tabularnewline
Winsorized Mean ( 29 / 36 ) & 99.9182407407407 & 0.110805433265949 & 901.744957766846 \tabularnewline
Winsorized Mean ( 30 / 36 ) & 99.9182407407407 & 0.110163966399945 & 906.995672051172 \tabularnewline
Winsorized Mean ( 31 / 36 ) & 99.9239814814815 & 0.109440262199148 & 913.045888903756 \tabularnewline
Winsorized Mean ( 32 / 36 ) & 100.01287037037 & 0.0971593819396308 & 1029.36914967731 \tabularnewline
Winsorized Mean ( 33 / 36 ) & 100.110648148148 & 0.0858575410870338 & 1166.00879643951 \tabularnewline
Winsorized Mean ( 34 / 36 ) & 100.120092592593 & 0.0834203590628074 & 1200.18774454341 \tabularnewline
Winsorized Mean ( 35 / 36 ) & 100.149259259259 & 0.0795483860303677 & 1258.97286239129 \tabularnewline
Winsorized Mean ( 36 / 36 ) & 100.149259259259 & 0.0795483860303677 & 1258.97286239129 \tabularnewline
Trimmed Mean ( 1 / 36 ) & 99.9050943396226 & 0.177316436106812 & 563.428278467325 \tabularnewline
Trimmed Mean ( 2 / 36 ) & 99.8977884615385 & 0.174573360058238 & 572.239592731744 \tabularnewline
Trimmed Mean ( 3 / 36 ) & 99.8917647058824 & 0.171862275259131 & 581.231480586809 \tabularnewline
Trimmed Mean ( 4 / 36 ) & 99.889 & 0.169529443823875 & 589.213282052499 \tabularnewline
Trimmed Mean ( 5 / 36 ) & 99.8878571428571 & 0.167233856753109 & 597.294465858812 \tabularnewline
Trimmed Mean ( 6 / 36 ) & 99.889375 & 0.165185489338979 & 604.710349557496 \tabularnewline
Trimmed Mean ( 7 / 36 ) & 99.8906382978723 & 0.162955418074433 & 612.993660954834 \tabularnewline
Trimmed Mean ( 8 / 36 ) & 99.8925 & 0.160558525943735 & 622.156309749665 \tabularnewline
Trimmed Mean ( 9 / 36 ) & 99.894 & 0.158089704145476 & 631.881756879478 \tabularnewline
Trimmed Mean ( 10 / 36 ) & 99.8927272727273 & 0.15588052783131 & 640.828772281479 \tabularnewline
Trimmed Mean ( 11 / 36 ) & 99.8919767441861 & 0.153596627350491 & 650.352670285155 \tabularnewline
Trimmed Mean ( 12 / 36 ) & 99.8916666666667 & 0.151107674707532 & 661.062827285288 \tabularnewline
Trimmed Mean ( 13 / 36 ) & 99.8921951219512 & 0.148613184078974 & 672.162404305043 \tabularnewline
Trimmed Mean ( 14 / 36 ) & 99.8945 & 0.146133814608912 & 683.582374601941 \tabularnewline
Trimmed Mean ( 15 / 36 ) & 99.8970512820513 & 0.143436384166788 & 696.455448611217 \tabularnewline
Trimmed Mean ( 16 / 36 ) & 99.901447368421 & 0.14064097677786 & 710.329589975857 \tabularnewline
Trimmed Mean ( 17 / 36 ) & 99.91 & 0.138480407996009 & 721.473899779954 \tabularnewline
Trimmed Mean ( 18 / 36 ) & 99.9223611111111 & 0.136654427062073 & 731.204712934205 \tabularnewline
Trimmed Mean ( 19 / 36 ) & 99.936 & 0.134540764793814 & 742.793458571116 \tabularnewline
Trimmed Mean ( 20 / 36 ) & 99.9498529411765 & 0.132400092810593 & 754.90772566271 \tabularnewline
Trimmed Mean ( 21 / 36 ) & 99.9628787878788 & 0.1303215970401 & 767.04768095437 \tabularnewline
Trimmed Mean ( 22 / 36 ) & 99.974375 & 0.128748338523722 & 776.510020605658 \tabularnewline
Trimmed Mean ( 23 / 36 ) & 99.9866129032258 & 0.127062350885722 & 786.909829750845 \tabularnewline
Trimmed Mean ( 24 / 36 ) & 99.9995 & 0.125214037091477 & 798.628511010662 \tabularnewline
Trimmed Mean ( 25 / 36 ) & 100.012586206897 & 0.123161509537798 & 812.044173396586 \tabularnewline
Trimmed Mean ( 26 / 36 ) & 100.026785714286 & 0.120599182424609 & 829.415122916076 \tabularnewline
Trimmed Mean ( 27 / 36 ) & 100.040925925926 & 0.117988104352048 & 847.889933271818 \tabularnewline
Trimmed Mean ( 28 / 36 ) & 100.054807692308 & 0.115096683859008 & 869.310950912133 \tabularnewline
Trimmed Mean ( 29 / 36 ) & 100.067 & 0.112417316554099 & 890.13866428527 \tabularnewline
Trimmed Mean ( 30 / 36 ) & 100.078541666667 & 0.109497154009185 & 913.983039762586 \tabularnewline
Trimmed Mean ( 31 / 36 ) & 100.091086956522 & 0.1058109828098 & 945.94232374195 \tabularnewline
Trimmed Mean ( 32 / 36 ) & 100.104318181818 & 0.101139071631561 & 989.769003877039 \tabularnewline
Trimmed Mean ( 33 / 36 ) & 100.111666666667 & 0.097942786320278 & 1022.1443602727 \tabularnewline
Trimmed Mean ( 34 / 36 ) & 100.11175 & 0.0962035019219741 & 1040.62480055243 \tabularnewline
Trimmed Mean ( 35 / 36 ) & 100.111052631579 & 0.0942785659882006 & 1061.86439709009 \tabularnewline
Trimmed Mean ( 36 / 36 ) & 100.107777777778 & 0.0924104981934783 & 1083.29442795757 \tabularnewline
Median & 100.17 &  &  \tabularnewline
Midrange & 100.295 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & 100.026785714286 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & 100.061454545455 &  &  \tabularnewline
Midmean - Empirical Distribution Function & 100.026785714286 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & 100.061454545455 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & 100.061454545455 &  &  \tabularnewline
Midmean - Closest Observation & 100.026785714286 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & 100.061454545455 &  &  \tabularnewline
Midmean - MS Excel (old versions) & 100.026785714286 &  &  \tabularnewline
Number of observations & 108 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293322&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]99.9123148148148[/C][C]0.179861038553002[/C][C]555.497263991236[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]99.8949802940607[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]99.8776350766272[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]99.9296357489905[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 36 )[/C][C]99.9121296296296[/C][C]0.179758647994079[/C][C]555.812645146957[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 36 )[/C][C]99.9091666666667[/C][C]0.179123723994758[/C][C]557.766243569114[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 36 )[/C][C]99.8994444444444[/C][C]0.177369818452805[/C][C]563.226851760161[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 36 )[/C][C]99.8931481481481[/C][C]0.176308766186094[/C][C]566.580722609736[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 36 )[/C][C]99.8811111111111[/C][C]0.174250177891478[/C][C]573.205217462197[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 36 )[/C][C]99.8827777777778[/C][C]0.173811885982462[/C][C]574.660226561583[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 36 )[/C][C]99.879537037037[/C][C]0.173120845086456[/C][C]576.935359731855[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 36 )[/C][C]99.8825[/C][C]0.171749247948844[/C][C]581.560042869884[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 36 )[/C][C]99.9033333333333[/C][C]0.168370470801349[/C][C]593.354243519364[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 36 )[/C][C]99.8987037037037[/C][C]0.166866084881581[/C][C]598.675900945349[/C][/ROW]
[ROW][C]Winsorized Mean ( 11 / 36 )[/C][C]99.8946296296296[/C][C]0.165973033562545[/C][C]601.872650547087[/C][/ROW]
[ROW][C]Winsorized Mean ( 12 / 36 )[/C][C]99.8868518518519[/C][C]0.163575733418229[/C][C]610.6459055052[/C][/ROW]
[ROW][C]Winsorized Mean ( 13 / 36 )[/C][C]99.87[/C][C]0.160888574063248[/C][C]620.740164933896[/C][/ROW]
[ROW][C]Winsorized Mean ( 14 / 36 )[/C][C]99.8687037037037[/C][C]0.159622645429021[/C][C]625.654984199043[/C][/ROW]
[ROW][C]Winsorized Mean ( 15 / 36 )[/C][C]99.8506481481482[/C][C]0.157220375058306[/C][C]635.099923347201[/C][/ROW]
[ROW][C]Winsorized Mean ( 16 / 36 )[/C][C]99.8076851851852[/C][C]0.149460643704757[/C][C]667.785730819841[/C][/ROW]
[ROW][C]Winsorized Mean ( 17 / 36 )[/C][C]99.7699074074074[/C][C]0.143958794689808[/C][C]693.044892619339[/C][/ROW]
[ROW][C]Winsorized Mean ( 18 / 36 )[/C][C]99.7632407407407[/C][C]0.143245754880095[/C][C]696.448148318589[/C][/ROW]
[ROW][C]Winsorized Mean ( 19 / 36 )[/C][C]99.7702777777778[/C][C]0.14043745987913[/C][C]710.424966840375[/C][/ROW]
[ROW][C]Winsorized Mean ( 20 / 36 )[/C][C]99.7906481481481[/C][C]0.137038111413281[/C][C]728.196317936685[/C][/ROW]
[ROW][C]Winsorized Mean ( 21 / 36 )[/C][C]99.8198148148148[/C][C]0.130566037546656[/C][C]764.515923822421[/C][/ROW]
[ROW][C]Winsorized Mean ( 22 / 36 )[/C][C]99.8198148148148[/C][C]0.128597352285767[/C][C]776.219829106564[/C][/ROW]
[ROW][C]Winsorized Mean ( 23 / 36 )[/C][C]99.8219444444444[/C][C]0.126775821848737[/C][C]787.389448467129[/C][/ROW]
[ROW][C]Winsorized Mean ( 24 / 36 )[/C][C]99.8308333333333[/C][C]0.125044618205087[/C][C]798.361694939958[/C][/ROW]
[ROW][C]Winsorized Mean ( 25 / 36 )[/C][C]99.8285185185185[/C][C]0.124806448615608[/C][C]799.866670559474[/C][/ROW]
[ROW][C]Winsorized Mean ( 26 / 36 )[/C][C]99.842962962963[/C][C]0.121166967641385[/C][C]824.011402665997[/C][/ROW]
[ROW][C]Winsorized Mean ( 27 / 36 )[/C][C]99.860462962963[/C][C]0.118854677989905[/C][C]840.189588258733[/C][/ROW]
[ROW][C]Winsorized Mean ( 28 / 36 )[/C][C]99.8967592592593[/C][C]0.113539290343816[/C][C]879.84308301342[/C][/ROW]
[ROW][C]Winsorized Mean ( 29 / 36 )[/C][C]99.9182407407407[/C][C]0.110805433265949[/C][C]901.744957766846[/C][/ROW]
[ROW][C]Winsorized Mean ( 30 / 36 )[/C][C]99.9182407407407[/C][C]0.110163966399945[/C][C]906.995672051172[/C][/ROW]
[ROW][C]Winsorized Mean ( 31 / 36 )[/C][C]99.9239814814815[/C][C]0.109440262199148[/C][C]913.045888903756[/C][/ROW]
[ROW][C]Winsorized Mean ( 32 / 36 )[/C][C]100.01287037037[/C][C]0.0971593819396308[/C][C]1029.36914967731[/C][/ROW]
[ROW][C]Winsorized Mean ( 33 / 36 )[/C][C]100.110648148148[/C][C]0.0858575410870338[/C][C]1166.00879643951[/C][/ROW]
[ROW][C]Winsorized Mean ( 34 / 36 )[/C][C]100.120092592593[/C][C]0.0834203590628074[/C][C]1200.18774454341[/C][/ROW]
[ROW][C]Winsorized Mean ( 35 / 36 )[/C][C]100.149259259259[/C][C]0.0795483860303677[/C][C]1258.97286239129[/C][/ROW]
[ROW][C]Winsorized Mean ( 36 / 36 )[/C][C]100.149259259259[/C][C]0.0795483860303677[/C][C]1258.97286239129[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 36 )[/C][C]99.9050943396226[/C][C]0.177316436106812[/C][C]563.428278467325[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 36 )[/C][C]99.8977884615385[/C][C]0.174573360058238[/C][C]572.239592731744[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 36 )[/C][C]99.8917647058824[/C][C]0.171862275259131[/C][C]581.231480586809[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 36 )[/C][C]99.889[/C][C]0.169529443823875[/C][C]589.213282052499[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 36 )[/C][C]99.8878571428571[/C][C]0.167233856753109[/C][C]597.294465858812[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 36 )[/C][C]99.889375[/C][C]0.165185489338979[/C][C]604.710349557496[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 36 )[/C][C]99.8906382978723[/C][C]0.162955418074433[/C][C]612.993660954834[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 36 )[/C][C]99.8925[/C][C]0.160558525943735[/C][C]622.156309749665[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 36 )[/C][C]99.894[/C][C]0.158089704145476[/C][C]631.881756879478[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 36 )[/C][C]99.8927272727273[/C][C]0.15588052783131[/C][C]640.828772281479[/C][/ROW]
[ROW][C]Trimmed Mean ( 11 / 36 )[/C][C]99.8919767441861[/C][C]0.153596627350491[/C][C]650.352670285155[/C][/ROW]
[ROW][C]Trimmed Mean ( 12 / 36 )[/C][C]99.8916666666667[/C][C]0.151107674707532[/C][C]661.062827285288[/C][/ROW]
[ROW][C]Trimmed Mean ( 13 / 36 )[/C][C]99.8921951219512[/C][C]0.148613184078974[/C][C]672.162404305043[/C][/ROW]
[ROW][C]Trimmed Mean ( 14 / 36 )[/C][C]99.8945[/C][C]0.146133814608912[/C][C]683.582374601941[/C][/ROW]
[ROW][C]Trimmed Mean ( 15 / 36 )[/C][C]99.8970512820513[/C][C]0.143436384166788[/C][C]696.455448611217[/C][/ROW]
[ROW][C]Trimmed Mean ( 16 / 36 )[/C][C]99.901447368421[/C][C]0.14064097677786[/C][C]710.329589975857[/C][/ROW]
[ROW][C]Trimmed Mean ( 17 / 36 )[/C][C]99.91[/C][C]0.138480407996009[/C][C]721.473899779954[/C][/ROW]
[ROW][C]Trimmed Mean ( 18 / 36 )[/C][C]99.9223611111111[/C][C]0.136654427062073[/C][C]731.204712934205[/C][/ROW]
[ROW][C]Trimmed Mean ( 19 / 36 )[/C][C]99.936[/C][C]0.134540764793814[/C][C]742.793458571116[/C][/ROW]
[ROW][C]Trimmed Mean ( 20 / 36 )[/C][C]99.9498529411765[/C][C]0.132400092810593[/C][C]754.90772566271[/C][/ROW]
[ROW][C]Trimmed Mean ( 21 / 36 )[/C][C]99.9628787878788[/C][C]0.1303215970401[/C][C]767.04768095437[/C][/ROW]
[ROW][C]Trimmed Mean ( 22 / 36 )[/C][C]99.974375[/C][C]0.128748338523722[/C][C]776.510020605658[/C][/ROW]
[ROW][C]Trimmed Mean ( 23 / 36 )[/C][C]99.9866129032258[/C][C]0.127062350885722[/C][C]786.909829750845[/C][/ROW]
[ROW][C]Trimmed Mean ( 24 / 36 )[/C][C]99.9995[/C][C]0.125214037091477[/C][C]798.628511010662[/C][/ROW]
[ROW][C]Trimmed Mean ( 25 / 36 )[/C][C]100.012586206897[/C][C]0.123161509537798[/C][C]812.044173396586[/C][/ROW]
[ROW][C]Trimmed Mean ( 26 / 36 )[/C][C]100.026785714286[/C][C]0.120599182424609[/C][C]829.415122916076[/C][/ROW]
[ROW][C]Trimmed Mean ( 27 / 36 )[/C][C]100.040925925926[/C][C]0.117988104352048[/C][C]847.889933271818[/C][/ROW]
[ROW][C]Trimmed Mean ( 28 / 36 )[/C][C]100.054807692308[/C][C]0.115096683859008[/C][C]869.310950912133[/C][/ROW]
[ROW][C]Trimmed Mean ( 29 / 36 )[/C][C]100.067[/C][C]0.112417316554099[/C][C]890.13866428527[/C][/ROW]
[ROW][C]Trimmed Mean ( 30 / 36 )[/C][C]100.078541666667[/C][C]0.109497154009185[/C][C]913.983039762586[/C][/ROW]
[ROW][C]Trimmed Mean ( 31 / 36 )[/C][C]100.091086956522[/C][C]0.1058109828098[/C][C]945.94232374195[/C][/ROW]
[ROW][C]Trimmed Mean ( 32 / 36 )[/C][C]100.104318181818[/C][C]0.101139071631561[/C][C]989.769003877039[/C][/ROW]
[ROW][C]Trimmed Mean ( 33 / 36 )[/C][C]100.111666666667[/C][C]0.097942786320278[/C][C]1022.1443602727[/C][/ROW]
[ROW][C]Trimmed Mean ( 34 / 36 )[/C][C]100.11175[/C][C]0.0962035019219741[/C][C]1040.62480055243[/C][/ROW]
[ROW][C]Trimmed Mean ( 35 / 36 )[/C][C]100.111052631579[/C][C]0.0942785659882006[/C][C]1061.86439709009[/C][/ROW]
[ROW][C]Trimmed Mean ( 36 / 36 )[/C][C]100.107777777778[/C][C]0.0924104981934783[/C][C]1083.29442795757[/C][/ROW]
[ROW][C]Median[/C][C]100.17[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]100.295[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]100.026785714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]100.061454545455[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]100.026785714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]100.061454545455[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]100.061454545455[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]100.026785714286[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]100.061454545455[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]100.026785714286[/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=293322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293322&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 Mean99.91231481481480.179861038553002555.497263991236
Geometric Mean99.8949802940607
Harmonic Mean99.8776350766272
Quadratic Mean99.9296357489905
Winsorized Mean ( 1 / 36 )99.91212962962960.179758647994079555.812645146957
Winsorized Mean ( 2 / 36 )99.90916666666670.179123723994758557.766243569114
Winsorized Mean ( 3 / 36 )99.89944444444440.177369818452805563.226851760161
Winsorized Mean ( 4 / 36 )99.89314814814810.176308766186094566.580722609736
Winsorized Mean ( 5 / 36 )99.88111111111110.174250177891478573.205217462197
Winsorized Mean ( 6 / 36 )99.88277777777780.173811885982462574.660226561583
Winsorized Mean ( 7 / 36 )99.8795370370370.173120845086456576.935359731855
Winsorized Mean ( 8 / 36 )99.88250.171749247948844581.560042869884
Winsorized Mean ( 9 / 36 )99.90333333333330.168370470801349593.354243519364
Winsorized Mean ( 10 / 36 )99.89870370370370.166866084881581598.675900945349
Winsorized Mean ( 11 / 36 )99.89462962962960.165973033562545601.872650547087
Winsorized Mean ( 12 / 36 )99.88685185185190.163575733418229610.6459055052
Winsorized Mean ( 13 / 36 )99.870.160888574063248620.740164933896
Winsorized Mean ( 14 / 36 )99.86870370370370.159622645429021625.654984199043
Winsorized Mean ( 15 / 36 )99.85064814814820.157220375058306635.099923347201
Winsorized Mean ( 16 / 36 )99.80768518518520.149460643704757667.785730819841
Winsorized Mean ( 17 / 36 )99.76990740740740.143958794689808693.044892619339
Winsorized Mean ( 18 / 36 )99.76324074074070.143245754880095696.448148318589
Winsorized Mean ( 19 / 36 )99.77027777777780.14043745987913710.424966840375
Winsorized Mean ( 20 / 36 )99.79064814814810.137038111413281728.196317936685
Winsorized Mean ( 21 / 36 )99.81981481481480.130566037546656764.515923822421
Winsorized Mean ( 22 / 36 )99.81981481481480.128597352285767776.219829106564
Winsorized Mean ( 23 / 36 )99.82194444444440.126775821848737787.389448467129
Winsorized Mean ( 24 / 36 )99.83083333333330.125044618205087798.361694939958
Winsorized Mean ( 25 / 36 )99.82851851851850.124806448615608799.866670559474
Winsorized Mean ( 26 / 36 )99.8429629629630.121166967641385824.011402665997
Winsorized Mean ( 27 / 36 )99.8604629629630.118854677989905840.189588258733
Winsorized Mean ( 28 / 36 )99.89675925925930.113539290343816879.84308301342
Winsorized Mean ( 29 / 36 )99.91824074074070.110805433265949901.744957766846
Winsorized Mean ( 30 / 36 )99.91824074074070.110163966399945906.995672051172
Winsorized Mean ( 31 / 36 )99.92398148148150.109440262199148913.045888903756
Winsorized Mean ( 32 / 36 )100.012870370370.09715938193963081029.36914967731
Winsorized Mean ( 33 / 36 )100.1106481481480.08585754108703381166.00879643951
Winsorized Mean ( 34 / 36 )100.1200925925930.08342035906280741200.18774454341
Winsorized Mean ( 35 / 36 )100.1492592592590.07954838603036771258.97286239129
Winsorized Mean ( 36 / 36 )100.1492592592590.07954838603036771258.97286239129
Trimmed Mean ( 1 / 36 )99.90509433962260.177316436106812563.428278467325
Trimmed Mean ( 2 / 36 )99.89778846153850.174573360058238572.239592731744
Trimmed Mean ( 3 / 36 )99.89176470588240.171862275259131581.231480586809
Trimmed Mean ( 4 / 36 )99.8890.169529443823875589.213282052499
Trimmed Mean ( 5 / 36 )99.88785714285710.167233856753109597.294465858812
Trimmed Mean ( 6 / 36 )99.8893750.165185489338979604.710349557496
Trimmed Mean ( 7 / 36 )99.89063829787230.162955418074433612.993660954834
Trimmed Mean ( 8 / 36 )99.89250.160558525943735622.156309749665
Trimmed Mean ( 9 / 36 )99.8940.158089704145476631.881756879478
Trimmed Mean ( 10 / 36 )99.89272727272730.15588052783131640.828772281479
Trimmed Mean ( 11 / 36 )99.89197674418610.153596627350491650.352670285155
Trimmed Mean ( 12 / 36 )99.89166666666670.151107674707532661.062827285288
Trimmed Mean ( 13 / 36 )99.89219512195120.148613184078974672.162404305043
Trimmed Mean ( 14 / 36 )99.89450.146133814608912683.582374601941
Trimmed Mean ( 15 / 36 )99.89705128205130.143436384166788696.455448611217
Trimmed Mean ( 16 / 36 )99.9014473684210.14064097677786710.329589975857
Trimmed Mean ( 17 / 36 )99.910.138480407996009721.473899779954
Trimmed Mean ( 18 / 36 )99.92236111111110.136654427062073731.204712934205
Trimmed Mean ( 19 / 36 )99.9360.134540764793814742.793458571116
Trimmed Mean ( 20 / 36 )99.94985294117650.132400092810593754.90772566271
Trimmed Mean ( 21 / 36 )99.96287878787880.1303215970401767.04768095437
Trimmed Mean ( 22 / 36 )99.9743750.128748338523722776.510020605658
Trimmed Mean ( 23 / 36 )99.98661290322580.127062350885722786.909829750845
Trimmed Mean ( 24 / 36 )99.99950.125214037091477798.628511010662
Trimmed Mean ( 25 / 36 )100.0125862068970.123161509537798812.044173396586
Trimmed Mean ( 26 / 36 )100.0267857142860.120599182424609829.415122916076
Trimmed Mean ( 27 / 36 )100.0409259259260.117988104352048847.889933271818
Trimmed Mean ( 28 / 36 )100.0548076923080.115096683859008869.310950912133
Trimmed Mean ( 29 / 36 )100.0670.112417316554099890.13866428527
Trimmed Mean ( 30 / 36 )100.0785416666670.109497154009185913.983039762586
Trimmed Mean ( 31 / 36 )100.0910869565220.1058109828098945.94232374195
Trimmed Mean ( 32 / 36 )100.1043181818180.101139071631561989.769003877039
Trimmed Mean ( 33 / 36 )100.1116666666670.0979427863202781022.1443602727
Trimmed Mean ( 34 / 36 )100.111750.09620350192197411040.62480055243
Trimmed Mean ( 35 / 36 )100.1110526315790.09427856598820061061.86439709009
Trimmed Mean ( 36 / 36 )100.1077777777780.09241049819347831083.29442795757
Median100.17
Midrange100.295
Midmean - Weighted Average at Xnp100.026785714286
Midmean - Weighted Average at X(n+1)p100.061454545455
Midmean - Empirical Distribution Function100.026785714286
Midmean - Empirical Distribution Function - Averaging100.061454545455
Midmean - Empirical Distribution Function - Interpolation100.061454545455
Midmean - Closest Observation100.026785714286
Midmean - True Basic - Statistics Graphics Toolkit100.061454545455
Midmean - MS Excel (old versions)100.026785714286
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')