Home » date » 2009 » Aug » 18 »

dennis volkaerts - opg5 oef1 - zonder extr

*Unverified author*
R Software Module: rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Tue, 18 Aug 2009 06:43:52 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Aug/18/t1250599504z71c1dqmb1ymobt.htm/, Retrieved Tue, 18 Aug 2009 14:45:04 +0200
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Aug/18/t1250599504z71c1dqmb1ymobt.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
8 10 10 13 14 12 11 8 8 10 10 12 12 12 11 12 12 12 12 12 12 10 12 10 11 10 10 12 10 12 7 12 18 12 11 13 10 10 10 8 12 10 10 8 14 9 8 12 15 14 1 9 7 8 12 12 10 10 8 8 16 14 13 10 12 9 12 11 10 8 8 9 12 8 12 10 12 9 8 12 8 12 10 12 9 10 12 9 14 12 12 13 13 14 12 12 10 11 12 14 10 12 12 6 12 10 12 12 12 9 12 12 13 8 12 10 10 10 9 12 9 10 8 12 10 8 8 9 12 12 10 10 9 11 10 9 15 10 8 10 8 9 9 6 16 12 12 12 12 10 12 8 9 12 12 8 14 10 12 8 11 10 12 12 12 12 8 10 7 10 10 12 11 9 10 12 14 13 10 11 10 10 8 10 10 10 8 8 4 14 8 12 12 10 8 12 12 10 10 12 12 9 11 14 10 8 12 8 10 11 12 10 10 12 8 9 12 8 8 10 10 10 14 10 12 12 13 9 12 12 10 12 6 8 12 10 9 11 11 9 10 15 12 7 7 10 9 10 10 9 12 10 9 12 10 7 12 10 10 12 8 12 10 10 9 8 8 12 12 10 12 10 9 10 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework
error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10.69249106078670.0721764425667261148.143780443343
Geometric Mean10.4368327451531
Harmonic Mean9.96066978811205
Quadratic Mean10.8947177499471
Winsorized Mean ( 1 / 279 )10.69249106078670.0721764425667261148.143780443343
Winsorized Mean ( 2 / 279 )10.69010727056020.071907597304618148.664503769669
Winsorized Mean ( 3 / 279 )10.69368295589990.0713600746074043149.855265913502
Winsorized Mean ( 4 / 279 )10.69845053635280.0696497046752183153.603674075008
Winsorized Mean ( 5 / 279 )10.70441001191900.0690136062509117155.105791356578
Winsorized Mean ( 6 / 279 )10.70441001191900.0690136062509117155.105791356578
Winsorized Mean ( 7 / 279 )10.71275327771160.0682580607485065156.944881824026
Winsorized Mean ( 8 / 279 )10.70321811680570.0674545123794216158.673122660819
Winsorized Mean ( 9 / 279 )10.70321811680570.0674545123794216158.673122660819
Winsorized Mean ( 10 / 279 )10.70321811680570.0674545123794216158.673122660819
Winsorized Mean ( 11 / 279 )10.70321811680570.0674545123794216158.673122660819
Winsorized Mean ( 12 / 279 )10.70321811680570.0674545123794216158.673122660819
Winsorized Mean ( 13 / 279 )10.70321811680570.0674545123794216158.673122660819
Winsorized Mean ( 14 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 15 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 16 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 17 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 18 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 19 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 20 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 21 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 22 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 23 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 24 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 25 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 26 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 27 / 279 )10.71990464839090.066199601583479161.933068960739
Winsorized Mean ( 28 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 29 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 30 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 31 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 32 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 33 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 34 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 35 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 36 / 279 )10.68653158522050.063874691168961167.304630200912
Winsorized Mean ( 37 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 38 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 39 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 40 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 41 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 42 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 43 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 44 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 45 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 46 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 47 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 48 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 49 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 50 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 51 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 52 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 53 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 54 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 55 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 56 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 57 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 58 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 59 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 60 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 61 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 62 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 63 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 64 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 65 / 279 )10.73063170441000.0611740968602407175.411362899650
Winsorized Mean ( 66 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 67 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 68 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 69 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 70 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 71 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 72 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 73 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 74 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 75 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 76 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 77 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 78 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 79 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 80 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 81 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 82 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 83 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 84 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 85 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 86 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 87 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 88 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 89 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 90 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 91 / 279 )10.65196662693680.0567005388705816187.863587174186
Winsorized Mean ( 92 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 93 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 94 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 95 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 96 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 97 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 98 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 99 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 100 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 101 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 102 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 103 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 104 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 105 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 106 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 107 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 108 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 109 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 110 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 111 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 112 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 113 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 114 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 115 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 116 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 117 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 118 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 119 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 120 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 121 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 122 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 123 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 124 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 125 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 126 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 127 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 128 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 129 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 130 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 131 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 132 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 133 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 134 / 279 )10.54231227651970.0521244970325744202.252546819424
Winsorized Mean ( 135 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 136 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 137 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 138 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 139 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 140 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 141 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 142 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 143 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 144 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 145 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 146 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 147 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 148 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 149 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 150 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 151 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 152 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 153 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 154 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 155 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 156 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 157 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 158 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 159 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 160 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 161 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 162 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 163 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 164 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 165 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 166 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 167 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 168 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 169 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 170 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 171 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 172 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 173 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 174 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 175 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 176 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 177 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 178 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 179 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 180 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 181 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 182 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 183 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 184 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 185 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 186 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 187 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 188 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 189 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 190 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 191 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 192 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 193 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 194 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 195 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 196 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 197 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 198 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 199 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 200 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 201 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 202 / 279 )10.70321811680570.0436093052212456245.434272857696
Winsorized Mean ( 203 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 204 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 205 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 206 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 207 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 208 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 209 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 210 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 211 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 212 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 213 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 214 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 215 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 216 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 217 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 218 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 219 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 220 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 221 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 222 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 223 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 224 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 225 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 226 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 227 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 228 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 229 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 230 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 231 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 232 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 233 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 234 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 235 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 236 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 237 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 238 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 239 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 240 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 241 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 242 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 243 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 244 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 245 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 246 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 247 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 248 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 249 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 250 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 251 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 252 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 253 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 254 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 255 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 256 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 257 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 258 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 259 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 260 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 261 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 262 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 263 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 264 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 265 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 266 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 267 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 268 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 269 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 270 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 271 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 272 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 273 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 274 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 275 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 276 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 277 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 278 / 279 )10.94517282479140.0337209852593388324.580457558257
Winsorized Mean ( 279 / 279 )10.94517282479140.0337209852593388324.580457558257
Trimmed Mean ( 1 / 279 )10.69534050179210.0708787516585292150.896287695906
Trimmed Mean ( 2 / 279 )10.69820359281440.0695434738589541153.834759743411
Trimmed Mean ( 3 / 279 )10.70228091236490.0683119947747514156.667667920606
Trimmed Mean ( 4 / 279 )10.7051744885680.0672437553246278159.199533650187
Trimmed Mean ( 5 / 279 )10.70687575392040.0666125679544587160.733568494768
Trimmed Mean ( 6 / 279 )10.70737605804110.0661062995701907161.972098387873
Trimmed Mean ( 7 / 279 )10.70787878787880.065590745592969163.252890191671
Trimmed Mean ( 8 / 279 )10.70716889428920.0651838290849977164.26112188542
Trimmed Mean ( 9 / 279 )10.70767356881850.0648797675528966165.038716578146
Trimmed Mean ( 10 / 279 )10.70818070818070.0645708798833518165.836066157457
Trimmed Mean ( 11 / 279 )10.70869033047740.0642570573262197166.653917500634
Trimmed Mean ( 12 / 279 )10.70920245398770.0639381873440258167.493056948359
Trimmed Mean ( 13 / 279 )10.70971709717100.063614153421969168.354313011613
Trimmed Mean ( 14 / 279 )10.71023427866830.0632848348652437169.238559308471
Trimmed Mean ( 15 / 279 )10.70951792336220.0630523386779157169.851240222327
Trimmed Mean ( 16 / 279 )10.70879801734820.0628162577452687170.478127824397
Trimmed Mean ( 17 / 279 )10.70807453416150.0625765192784577171.119689264146
Trimmed Mean ( 18 / 279 )10.70734744707350.0623330482916603171.776413002828
Trimmed Mean ( 19 / 279 )10.70661672908860.0620857675079677172.448810070917
Trimmed Mean ( 20 / 279 )10.70588235294120.0618345972599262173.137415417104
Trimmed Mean ( 21 / 279 )10.70514429109160.0615794553843478173.842789356864
Trimmed Mean ( 22 / 279 )10.70440251572330.0613202571109761174.565519129358
Trimmed Mean ( 23 / 279 )10.70365699873900.061056914944556175.306220572373
Trimmed Mean ( 24 / 279 )10.70290771175730.0607893385398166176.065539926001
Trimmed Mean ( 25 / 279 )10.7021546261090.0605174345688335176.844155776898
Trimmed Mean ( 26 / 279 )10.70139771283350.0602411065801858177.642781156238
Trimmed Mean ( 27 / 279 )10.70063694267520.059960254849271178.462165805909
Trimmed Mean ( 28 / 279 )10.69987228607920.0596747762190818179.303098629095
Trimmed Mean ( 29 / 279 )10.70038412291930.0594895205990404179.870068125779
Trimmed Mean ( 30 / 279 )10.70089858793320.0593013690721427180.449435744311
Trimmed Mean ( 31 / 279 )10.70141570141570.0591102654004663181.041577616251
Trimmed Mean ( 32 / 279 )10.70193548387100.0589161517711841181.646885652591
Trimmed Mean ( 33 / 279 )10.70245795601550.0587189687348419182.265768398365
Trimmed Mean ( 34 / 279 )10.70298313878080.0585186551404378182.898651944323
Trimmed Mean ( 35 / 279 )10.7035110533160.0583151480670963183.545980900207
Trimmed Mean ( 36 / 279 )10.70404172099090.0581083827521116184.208219434603
Trimmed Mean ( 37 / 279 )10.70457516339870.0578982925151184184.885852386813
Trimmed Mean ( 38 / 279 )10.70380078636960.0577802758668845185.250081031618
Trimmed Mean ( 39 / 279 )10.70302233902760.057660354869299185.621860345614
Trimmed Mean ( 40 / 279 )10.70223978919630.0575384960567565186.001382077132
Trimmed Mean ( 41 / 279 )10.70145310435930.0574146651669086186.388844613992
Trimmed Mean ( 42 / 279 )10.70066225165560.0572888271150466186.784453278590
Trimmed Mean ( 43 / 279 )10.69986719787520.0571609459674113187.188420639074
Trimmed Mean ( 44 / 279 )10.69906790945410.0570309849133722187.600966837685
Trimmed Mean ( 45 / 279 )10.69826435247000.0568989062364186188.022319937364
Trimmed Mean ( 46 / 279 )10.69745649263720.0567646712838967188.452716287849
Trimmed Mean ( 47 / 279 )10.69664429530200.0566282404354265188.892400912571
Trimmed Mean ( 48 / 279 )10.69582772543740.0564895730699256189.341627917733
Trimmed Mean ( 49 / 279 )10.69500674763830.0563486275311633189.800660925122
Trimmed Mean ( 50 / 279 )10.69418132611640.0562053610917625190.269773530264
Trimmed Mean ( 51 / 279 )10.69335142469470.0560597299155623190.749249787702
Trimmed Mean ( 52 / 279 )10.69251700680270.0559116890182475191.239384725313
Trimmed Mean ( 53 / 279 )10.69167803547070.0557611922261448191.740484889734
Trimmed Mean ( 54 / 279 )10.69083447332420.0556081921330789192.252868925129
Trimmed Mean ( 55 / 279 )10.68998628257890.0554526400551738192.776868187748
Trimmed Mean ( 56 / 279 )10.68913342503440.0552944859834774193.312827398891
Trimmed Mean ( 57 / 279 )10.68827586206900.0551336785342759193.861105339166
Trimmed Mean ( 58 / 279 )10.68741355463350.0549701648969587194.422075587129
Trimmed Mean ( 59 / 279 )10.68654646324550.054803890779282194.996127305717
Trimmed Mean ( 60 / 279 )10.68567454798330.0546348003498662195.583666080139
Trimmed Mean ( 61 / 279 )10.68479776847980.0544628361777549196.185114811262
Trimmed Mean ( 62 / 279 )10.68391608391610.0542879391688438196.800914668864
Trimmed Mean ( 63 / 279 )10.68302945301540.0541100484989784197.431526109557
Trimmed Mean ( 64 / 279 )10.68213783403660.0539291015434996198.077429964604
Trimmed Mean ( 65 / 279 )10.68124118476730.0537450338030012198.739128603373
Trimmed Mean ( 66 / 279 )10.68033946251770.0535577788250437199.417147178694
Trimmed Mean ( 67 / 279 )10.68085106382980.0534736231383093199.740553135960
Trimmed Mean ( 68 / 279 )10.68136557610240.0533879302757597200.070793546986
Trimmed Mean ( 69 / 279 )10.68188302425110.0533006727607399200.408033725967
Trimmed Mean ( 70 / 279 )10.68240343347640.0532118224768997200.752444404884
Trimmed Mean ( 71 / 279 )10.68292682926830.0531213506485864201.104201960885
Trimmed Mean ( 72 / 279 )10.68345323741010.0530292278204647201.463488655348
Trimmed Mean ( 73 / 279 )10.68398268398270.052935423836327201.830492885386
Trimmed Mean ( 74 / 279 )10.68451519536900.0528399078170522202.205409448519
Trimmed Mean ( 75 / 279 )10.68505079825830.0527426481376722202.588439821367
Trimmed Mean ( 76 / 279 )10.68558951965070.0526436124035202.979792453229
Trimmed Mean ( 77 / 279 )10.68613138686130.0525427674252714203.379683075499
Trimmed Mean ( 78 / 279 )10.68667642752560.052440079193251203.788335027934
Trimmed Mean ( 79 / 279 )10.68722466960350.0523355128502466204.205979602876
Trimmed Mean ( 80 / 279 )10.68777614138440.0522290326634759204.632856408586
Trimmed Mean ( 81 / 279 )10.68833087149190.052120601995224205.069213752967
Trimmed Mean ( 82 / 279 )10.68888888888890.0520101832722275205.515309049037
Trimmed Mean ( 83 / 279 )10.68945022288260.0518977379537155205.971409243615
Trimmed Mean ( 84 / 279 )10.69001490312970.0517832264980334206.437791270801
Trimmed Mean ( 85 / 279 )10.69058295964130.0516666083277728206.914742531970
Trimmed Mean ( 86 / 279 )10.69115442278860.0515478417933214207.402561404108
Trimmed Mean ( 87 / 279 )10.69172932330830.0514268841347459207.901557778503
Trimmed Mean ( 88 / 279 )10.69230769230770.0513036914419102208.412053631936
Trimmed Mean ( 89 / 279 )10.69288956127080.0511782186127281208.934383632717
Trimmed Mean ( 90 / 279 )10.69347496206370.0510504193094413209.468895784095
Trimmed Mean ( 91 / 279 )10.69406392694060.0509202459128043210.015952107795
Trimmed Mean ( 92 / 279 )10.69465648854960.0507876494740522210.575929370655
Trimmed Mean ( 93 / 279 )10.69678407350690.0507361614409191210.831560167653
Trimmed Mean ( 94 / 279 )10.69892473118280.0506833662002272211.093412558987
Trimmed Mean ( 95 / 279 )10.70107858243450.0506292380352732211.361636036851
Trimmed Mean ( 96 / 279 )10.70324574961360.0505737506068925211.636384906658
Trimmed Mean ( 97 / 279 )10.70542635658910.0505168769343227211.917818484847
Trimmed Mean ( 98 / 279 )10.70762052877140.0504585893753282212.206101306647
Trimmed Mean ( 99 / 279 )10.70982839313570.0503988596055495212.501403344381
Trimmed Mean ( 100 / 279 )10.71205007824730.05033765859704212.803900236972
Trimmed Mean ( 101 / 279 )10.71428571428570.0502749565959524213.113773531299
Trimmed Mean ( 102 / 279 )10.71653543307090.0502107230993313213.431210936167
Trimmed Mean ( 103 / 279 )10.71879936808850.0501449268309687213.756406589643
Trimmed Mean ( 104 / 279 )10.72107765451660.0500775357162761214.089561340617
Trimmed Mean ( 105 / 279 )10.72337042925280.0500085168561224214.430883045474
Trimmed Mean ( 106 / 279 )10.72567783094100.0499378364995863214.780586880848
Trimmed Mean ( 107 / 279 )10.7280.0498654600155669215.138895673497
Trimmed Mean ( 108 / 279 )10.73033707865170.0497913518631929215.506040248404
Trimmed Mean ( 109 / 279 )10.73268921095010.0497154755609686215.882259796309
Trimmed Mean ( 110 / 279 )10.73505654281100.0496377936545884216.26780226197
Trimmed Mean ( 111 / 279 )10.73743922204210.0495582676833498216.662924754523
Trimmed Mean ( 112 / 279 )10.73983739837400.0494768581450885217.067893981464
Trimmed Mean ( 113 / 279 )10.74225122349100.0493935244595551217.482986707845
Trimmed Mean ( 114 / 279 )10.74468085106380.0493082249301474217.908490242456
Trimmed Mean ( 115 / 279 )10.74712643678160.0492209167039064218.344702952854
Trimmed Mean ( 116 / 279 )10.74958813838550.0491315557296784218.791934811299
Trimmed Mean ( 117 / 279 )10.75206611570250.0490400967143384219.25050797379
Trimmed Mean ( 118 / 279 )10.75456053067990.0489464930769623219.720757394605
Trimmed Mean ( 119 / 279 )10.75707154742100.0488506969008302220.203031478925
Trimmed Mean ( 120 / 279 )10.75959933222040.0487526588831303220.697692776372
Trimmed Mean ( 121 / 279 )10.76214405360130.048652328282228221.205118718493
Trimmed Mean ( 122 / 279 )10.76470588235290.0485496528623527221.725702403535
Trimmed Mean ( 123 / 279 )10.76728499156830.048444578835544222.25985343211
Trimmed Mean ( 124 / 279 )10.76988155668360.0483370508006882222.807998797689
Trimmed Mean ( 125 / 279 )10.77249575551780.0482270116794632223.370583836219
Trimmed Mean ( 126 / 279 )10.77512776831350.0481144026489947223.948073239533
Trimmed Mean ( 127 / 279 )10.77777777777780.0479991630710144224.540952137689
Trimmed Mean ( 128 / 279 )10.78044596912520.047881230417291225.149727255801
Trimmed Mean ( 129 / 279 )10.78313253012050.0477605401910899225.774928151507
Trimmed Mean ( 130 / 279 )10.78583765112260.047637025844396226.417108539774
Trimmed Mean ( 131 / 279 )10.78856152513000.047510618690614227.07684771239
Trimmed Mean ( 132 / 279 )10.79130434782610.0473812478124351227.754752060243
Trimmed Mean ( 133 / 279 )10.79406631762650.0472488399645366228.451456707259
Trimmed Mean ( 134 / 279 )10.79684763572680.047113319470749229.167627265792
Trimmed Mean ( 135 / 279 )10.79964850615110.0469746081152965229.903961724258
Trimmed Mean ( 136 / 279 )10.80070546737210.0469855122366526229.873102435748
Trimmed Mean ( 137 / 279 )10.80176991150440.0469959366024428229.844763024532
Trimmed Mean ( 138 / 279 )10.80284191829480.0470058700512904229.818997212632
Trimmed Mean ( 139 / 279 )10.80392156862750.0470153011541825229.795860143423
Trimmed Mean ( 140 / 279 )10.80500894454380.0470242182069761229.775408428606
Trimmed Mean ( 141 / 279 )10.80610412926390.0470326092226561229.757700197048
Trimmed Mean ( 142 / 279 )10.80720720720720.0470404619233345229.742795145604
Trimmed Mean ( 143 / 279 )10.80831826401450.0470477637319832229.730754591997
Trimmed Mean ( 144 / 279 )10.80943738656990.0470545017638866229.721641529863
Trimmed Mean ( 145 / 279 )10.81056466302370.047060662817806229.715520686066
Trimmed Mean ( 146 / 279 )10.81170018281540.0470662333668421229.712458580383
Trimmed Mean ( 147 / 279 )10.81284403669720.0470711995489843229.712523587697
Trimmed Mean ( 148 / 279 )10.81399631675870.0470755471573342229.715786002797
Trimmed Mean ( 149 / 279 )10.81515711645100.04707926162999229.72231810793
Trimmed Mean ( 150 / 279 )10.81632653061220.0470823280395777229.732194243241
Trimmed Mean ( 151 / 279 )10.81750465549350.0470847310824145229.745490880242
Trimmed Mean ( 152 / 279 )10.81869158878500.0470864550672892229.762286698468
Trimmed Mean ( 153 / 279 )10.81988742964350.047087483903844229.782662665487
Trimmed Mean ( 154 / 279 )10.82109227871940.0470878010905402229.806702120421
Trimmed Mean ( 155 / 279 )10.82230623818530.0470873897021903229.834490861188
Trimmed Mean ( 156 / 279 )10.82352941176470.0470862323770388229.866117235634
Trimmed Mean ( 157 / 279 )10.82476190476190.0470843113033709229.901672236776
Trimmed Mean ( 158 / 279 )10.82600382409180.0470816082056299229.941249602371
Trimmed Mean ( 159 / 279 )10.82725527831090.0470781043300213229.984945919041
Trimmed Mean ( 160 / 279 )10.82851637764930.0470737804295808230.03286073121
Trimmed Mean ( 161 / 279 )10.82978723404260.047068616748683230.085096655099
Trimmed Mean ( 162 / 279 )10.83106796116500.0470625930069658230.141759498078
Trimmed Mean ( 163 / 279 )10.83235867446390.0470556883826435230.202958383655
Trimmed Mean ( 164 / 279 )10.83365949119370.0470478814951822230.268805882431
Trimmed Mean ( 165 / 279 )10.83497053045190.047039150387307230.339418149346
Trimmed Mean ( 166 / 279 )10.8362919132150.047029472506311230.414915067585
Trimmed Mean ( 167 / 279 )10.83762376237620.0470188246846344230.495420399522
Trimmed Mean ( 168 / 279 )10.83896620278330.0470071831196782230.581061945102
Trimmed Mean ( 169 / 279 )10.84031936127740.046994523352817230.671971708117
Trimmed Mean ( 170 / 279 )10.84168336673350.0469808202475735230.768286070812
Trimmed Mean ( 171 / 279 )10.84305835010060.0469660479669139230.870145977349
Trimmed Mean ( 172 / 279 )10.84444444444440.0469501799496216230.977697126629
Trimmed Mean ( 173 / 279 )10.84584178498990.0469331888857054231.091090175064
Trimmed Mean ( 174 / 279 )10.84725050916500.0469150466907932231.210480949893
Trimmed Mean ( 175 / 279 )10.84867075664620.0468957244794623231.336030673699
Trimmed Mean ( 176 / 279 )10.85010266940450.0468751925374528231.467906200820
Trimmed Mean ( 177 / 279 )10.85154639175260.0468534202927075231.606280266407
Trimmed Mean ( 178 / 279 )10.85300207039340.0468303762851792231.751331748921
Trimmed Mean ( 179 / 279 )10.85446985446990.0468060281353412231.903245946949
Trimmed Mean ( 180 / 279 )10.85594989561590.0467803425113351232.062214871244
Trimmed Mean ( 181 / 279 )10.85744234800840.0467532850946844232.228437552997
Trimmed Mean ( 182 / 279 )10.85894736842110.0467248205444969232.402120369406
Trimmed Mean ( 183 / 279 )10.86046511627910.0466949124600774232.583477387701
Trimmed Mean ( 184 / 279 )10.86199575371550.0466635233418644232.772730728856
Trimmed Mean ( 185 / 279 )10.8635394456290.0466306145505994232.970110952341
Trimmed Mean ( 186 / 279 )10.86509635974300.0465961462646322233.175857463345
Trimmed Mean ( 187 / 279 )10.86666666666670.04656007743526233.390218944037
Trimmed Mean ( 188 / 279 )10.86825053995680.0465223657399885233.613453810560
Trimmed Mean ( 189 / 279 )10.86984815618220.0464829675335995233.845830697558
Trimmed Mean ( 190 / 279 )10.87145969498910.0464418377968981234.087628972237
Trimmed Mean ( 191 / 279 )10.87308533916850.046398930083007234.339139280081
Trimmed Mean ( 192 / 279 )10.87472527472530.0463541964610644234.600664124544
Trimmed Mean ( 193 / 279 )10.87637969094920.0463075874571721234.872518483247
Trimmed Mean ( 194 / 279 )10.87804878048780.0462590519924304235.155030463396
Trimmed Mean ( 195 / 279 )10.87973273942090.0462085373178848235.448541999402
Trimmed Mean ( 196 / 279 )10.88143176733780.0461559889461951235.753409595935
Trimmed Mean ( 197 / 279 )10.88314606741570.046101350579826236.070005119941
Trimmed Mean ( 198 / 279 )10.88487584650110.0460445640355423236.398716645443
Trimmed Mean ( 199 / 279 )10.88662131519270.045985569164975236.739949355342
Trimmed Mean ( 200 / 279 )10.88838268792710.0459243037710084237.094126504774
Trimmed Mean ( 201 / 279 )10.89016018306640.0458607035197174237.461690451047
Trimmed Mean ( 202 / 279 )10.89195402298850.0457947018475650237.843103755629
Trimmed Mean ( 203 / 279 )10.89376443418010.0457262298635457238.238850364197
Trimmed Mean ( 204 / 279 )10.89327146171690.0458197213396494237.741984089515
Trimmed Mean ( 205 / 279 )10.89277389277390.0459137620034908237.244203425233
Trimmed Mean ( 206 / 279 )10.89227166276350.0460083568519476236.745504687642
Trimmed Mean ( 207 / 279 )10.89176470588240.0461035109368309236.245884197535
Trimmed Mean ( 208 / 279 )10.89125295508270.0461992293653846235.745338281403
Trimmed Mean ( 209 / 279 )10.89073634204280.0462955173007779235.243863272692
Trimmed Mean ( 210 / 279 )10.89021479713600.0463923799625892234.741455513123
Trimmed Mean ( 211 / 279 )10.88968824940050.0464898226272816234.238111354077
Trimmed Mean ( 212 / 279 )10.88915662650600.0465878506286688233.733827158043
Trimmed Mean ( 213 / 279 )10.88861985472150.0466864693583693233.228599300144
Trimmed Mean ( 214 / 279 )10.88807785888080.0467856842662484232.722424169727
Trimmed Mean ( 215 / 279 )10.88753056234720.0468855008608477232.215298172040
Trimmed Mean ( 216 / 279 )10.88697788697790.0469859247097979231.707217729987
Trimmed Mean ( 217 / 279 )10.88641975308640.0470869614402172231.19817928596
Trimmed Mean ( 218 / 279 )10.88585607940450.0471886167390909230.688179303774
Trimmed Mean ( 219 / 279 )10.88528678304240.0472908963536309230.177214270684
Trimmed Mean ( 220 / 279 )10.88471177944860.0473938060916155229.665280699501
Trimmed Mean ( 221 / 279 )10.88413098236780.0474973518217046229.152375130819
Trimmed Mean ( 222 / 279 )10.88354430379750.0476015394737305228.638494135335
Trimmed Mean ( 223 / 279 )10.88295165394400.0477063750389616228.123634316293
Trimmed Mean ( 224 / 279 )10.88235294117650.0478118645703361227.607792312041
Trimmed Mean ( 225 / 279 )10.88174807197940.0479180141826643227.090964798709
Trimmed Mean ( 226 / 279 )10.88113695090440.048024830052796226.573148493024
Trimmed Mean ( 227 / 279 )10.88051948051950.0481323184197514226.054340155254
Trimmed Mean ( 228 / 279 )10.87989556135770.048240485584811225.534536592296
Trimmed Mean ( 229 / 279 )10.87926509186350.0483493379115634225.013734660916
Trimmed Mean ( 230 / 279 )10.87862796833770.0484588818259059224.491931271143
Trimmed Mean ( 231 / 279 )10.87798408488060.0485691238159954223.969123389831
Trimmed Mean ( 232 / 279 )10.87733333333330.0486800704321457223.445308044389
Trimmed Mean ( 233 / 279 )10.87667560321720.0487917282866672222.920482326700
Trimmed Mean ( 234 / 279 )10.87601078167120.0489041040536443222.394643397228
Trimmed Mean ( 235 / 279 )10.87533875338750.0490172044686475221.867788489318
Trimmed Mean ( 236 / 279 )10.87465940054500.0491310363283726221.339914913721
Trimmed Mean ( 237 / 279 )10.87397260273970.0492456064902057220.811020063331
Trimmed Mean ( 238 / 279 )10.87327823691460.0493609218717047220.281101418155
Trimmed Mean ( 239 / 279 )10.87257617728530.049476989449994219.750156550534
Trimmed Mean ( 240 / 279 )10.87186629526460.0495938162610659219.218183130619
Trimmed Mean ( 241 / 279 )10.87114845938380.0497114093989811218.685178932114
Trimmed Mean ( 242 / 279 )10.87042253521130.0498297760149619218.151141838312
Trimmed Mean ( 243 / 279 )10.86968838526910.0499489233163707217.616069848428
Trimmed Mean ( 244 / 279 )10.86894586894590.0500688585655664217.079961084248
Trimmed Mean ( 245 / 279 )10.86819484240690.050189589078628216.542813797111
Trimmed Mean ( 246 / 279 )10.86743515850140.0503111222239395216.004626375247
Trimmed Mean ( 247 / 279 )10.86666666666670.0504334654206234215.465397351478
Trimmed Mean ( 248 / 279 )10.8658892128280.0505566261368149214.925125411317
Trimmed Mean ( 249 / 279 )10.86510263929620.0506806118877637214.383809401470
Trimmed Mean ( 250 / 279 )10.86430678466080.0508054302337536213.841448338781
Trimmed Mean ( 251 / 279 )10.86350148367950.0509310887778257213.29804141963
Trimmed Mean ( 252 / 279 )10.86268656716420.051057595163293212.753588029812
Trimmed Mean ( 253 / 279 )10.86186186186190.0511849570710312212.208087754933
Trimmed Mean ( 254 / 279 )10.86102719033230.051313182216531211.661540391337
Trimmed Mean ( 255 / 279 )10.86018237082070.0514422783466957211.113945957611
Trimmed Mean ( 256 / 279 )10.85932721712540.0515722532363653210.565304706681
Trimmed Mean ( 257 / 279 )10.85846153846150.0517031146845513210.015617138555
Trimmed Mean ( 258 / 279 )10.85758513931890.0518348705103583209.464884013729
Trimmed Mean ( 259 / 279 )10.85669781931460.0519675285485752208.913106367309
Trimmed Mean ( 260 / 279 )10.85579937304080.0521010966449099208.360285523881
Trimmed Mean ( 261 / 279 )10.85488958990540.0522355826508452207.806423113186
Trimmed Mean ( 262 / 279 )10.85396825396830.0523709944180889207.251521086629
Trimmed Mean ( 263 / 279 )10.85303514377000.0525073397925898206.695581734682
Trimmed Mean ( 264 / 279 )10.85209003215430.052644626608091206.138607705245
Trimmed Mean ( 265 / 279 )10.85113268608410.052782862679187205.580602022991
Trimmed Mean ( 266 / 279 )10.85016286644950.0529220557938513205.021568109796
Trimmed Mean ( 267 / 279 )10.84918032786890.0530622137053964204.461509806280
Trimmed Mean ( 268 / 279 )10.84818481848180.053203344123829203.900431394558
Trimmed Mean ( 269 / 279 )10.84717607973420.0533454547065549203.338337622256
Trimmed Mean ( 270 / 279 )10.84615384615380.0534885530483914202.775233727883
Trimmed Mean ( 271 / 279 )10.84511784511780.0536326466708357202.211125467638
Trimmed Mean ( 272 / 279 )10.84406779661020.0537777430105392201.646019143737
Trimmed Mean ( 273 / 279 )10.84300341296930.0539238494069296201.079921634376
Trimmed Mean ( 274 / 279 )10.84192439862540.0540709730889218200.512840425406
Trimmed Mean ( 275 / 279 )10.8408304498270.0542191211606515199.944783643865
Trimmed Mean ( 276 / 279 )10.83972125435540.0543683005861626199.375760093451
Trimmed Mean ( 277 / 279 )10.83859649122810.0545185181729728198.805779292095
Trimmed Mean ( 278 / 279 )10.83745583038870.0546697805544364198.234851511751
Trimmed Mean ( 279 / 279 )10.83629893238430.0548220941708178197.662987820567
Median10
Midrange9.5
Midmean - Weighted Average at Xnp11.1194852941176
Midmean - Weighted Average at X(n+1)p11.1194852941176
Midmean - Empirical Distribution Function11.1194852941176
Midmean - Empirical Distribution Function - Averaging11.1194852941176
Midmean - Empirical Distribution Function - Interpolation11.1194852941176
Midmean - Closest Observation11.1194852941176
Midmean - True Basic - Statistics Graphics Toolkit11.1194852941176
Midmean - MS Excel (old versions)11.1194852941176
Number of observations839
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250599504z71c1dqmb1ymobt/1pjuj1250599419.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250599504z71c1dqmb1ymobt/1pjuj1250599419.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250599504z71c1dqmb1ymobt/28i9e1250599419.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t1250599504z71c1dqmb1ymobt/28i9e1250599419.ps (open in new window)


 
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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/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')
 





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