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gemiddelde consumptieprijzen mean

*Unverified author*
R Software Module: rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Sat, 24 Oct 2009 06:45:49 -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/Oct/24/t1256388510qqb7mpgcl6hafcb.htm/, Retrieved Sat, 24 Oct 2009 14:48:31 +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/Oct/24/t1256388510qqb7mpgcl6hafcb.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:
KDGP1W51
 
Dataseries X:
» Textbox « » Textfile « » CSV «
25 25 25 25 29 30 30 29 35 30 30 30 29 30 30 26 30 30 30 35 30 30 30 50 25 29 30 25 30 30 25 42 29 15 29 30 25 20 10 30 29 30 50 25 30 30 25 50 29 30 30 30 30 30 30 29 35 40 29 26 23 25 30 30 30 30 20 29 25 25 28 30 30 25 30 31 30 29 45 30 30 35 30 30 25 50 40 20 35 22 30 25 30 30 29 50 45 30 26 30 29 35 20 29 25 30 45 35 30 30 40 20 26 29 20 25 30 30 25 30 23 25 30 30 40 30 40 35 40 30 25 33 30 30 30 35 33 35 30 40 29 25 27 30 30 35 20 30 30 25 25 30 30 30 40 40 30 40 20 50 20 30 30 30 30 25 30 30 30 30 30 30 23 30 25 50 20 23 25 29 26 40 30 30 35 20 29 25 30 30 30 50 30 35 30 30 30 35 30 35 15 30 20 35 40 30 30 40 29 30 20 35 50 30 30 40 30 50 18 15 30 23 29 30 35 30 23 30 25 26 25 30 20 25 30 29 40 30 30 30 40 37 20 25 30 32 35 32 30 30 35 30 25 30 24 30 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk
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 Mean29.89292730844790.198718710730186150.428347681038
Geometric Mean29.1822625752968
Harmonic Mean27.8520430883571
Quadratic Mean30.5572829977458
Winsorized Mean ( 1 / 339 )29.89194499017680.196417942612462152.185409299162
Winsorized Mean ( 2 / 339 )29.89194499017680.196417942612462152.185409299162
Winsorized Mean ( 3 / 339 )29.89783889980350.195859648010744152.649303741032
Winsorized Mean ( 4 / 339 )29.9017681728880.195516112468263152.937616216883
Winsorized Mean ( 5 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 6 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 7 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 8 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 9 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 10 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 11 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 12 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 13 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 14 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 15 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 16 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 17 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 18 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 19 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 20 / 339 )29.91159135559920.194728697499065153.606488102468
Winsorized Mean ( 21 / 339 )29.97347740667980.190481670692675157.356229067516
Winsorized Mean ( 22 / 339 )29.97347740667980.190481670692675157.356229067516
Winsorized Mean ( 23 / 339 )29.97347740667980.190481670692675157.356229067516
Winsorized Mean ( 24 / 339 )29.97347740667980.190481670692675157.356229067516
Winsorized Mean ( 25 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 26 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 27 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 28 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 29 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 30 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 31 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 32 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 33 / 339 )30.02259332023580.187672504187978159.973318681592
Winsorized Mean ( 34 / 339 )29.92239685658150.177680190515385168.405925105031
Winsorized Mean ( 35 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 36 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 37 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 38 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 39 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 40 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 41 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 42 / 339 )29.85363457760310.171439480327441174.135120571902
Winsorized Mean ( 43 / 339 )29.72691552062870.16116764207557184.447170274353
Winsorized Mean ( 44 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 45 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 46 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 47 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 48 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 49 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 50 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 51 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 52 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 53 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 54 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 55 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 56 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 57 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 58 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 59 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 60 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 61 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 62 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 63 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 64 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 65 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 66 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 67 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 68 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 69 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 70 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 71 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 72 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 73 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 74 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 75 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 76 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 77 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 78 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 79 / 339 )29.64047151277010.155084682768614191.124429464086
Winsorized Mean ( 80 / 339 )29.71905697445970.150441298433332197.545868614194
Winsorized Mean ( 81 / 339 )29.71905697445970.150441298433332197.545868614194
Winsorized Mean ( 82 / 339 )29.79960707269160.146028237040275204.067430222229
Winsorized Mean ( 83 / 339 )29.79960707269160.146028237040275204.067430222229
Winsorized Mean ( 84 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 85 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 86 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 87 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 88 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 89 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 90 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 91 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 92 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 93 / 339 )29.88212180746560.141890935551514210.599230256092
Winsorized Mean ( 94 / 339 )29.97445972495090.137716127686753217.653954031661
Winsorized Mean ( 95 / 339 )29.97445972495090.137716127686753217.653954031661
Winsorized Mean ( 96 / 339 )30.06876227897840.133946764496835224.482930901171
Winsorized Mean ( 97 / 339 )30.06876227897840.133946764496835224.482930901171
Winsorized Mean ( 98 / 339 )29.77996070726920.114329430809686260.475019392350
Winsorized Mean ( 99 / 339 )29.77996070726920.114329430809686260.475019392350
Winsorized Mean ( 100 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 101 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 102 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 103 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 104 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 105 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 106 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 107 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 108 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 109 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 110 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 111 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 112 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 113 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 114 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 115 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 116 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 117 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 118 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 119 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 120 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 121 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 122 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 123 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 124 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 125 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 126 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 127 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 128 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 129 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 130 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 131 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 132 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 133 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 134 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 135 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 136 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 137 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 138 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 139 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 140 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 141 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 142 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 143 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 144 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 145 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 146 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 147 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 148 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 149 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 150 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 151 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 152 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 153 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 154 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 155 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 156 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 157 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 158 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 159 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 160 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 161 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 162 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 163 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 164 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 165 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 166 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 167 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 168 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 169 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 170 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 171 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 172 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 173 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 174 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 175 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 176 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 177 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 178 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 179 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 180 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 181 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 182 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 183 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 184 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 185 / 339 )29.58349705304520.103102359630117286.933268638826
Winsorized Mean ( 186 / 339 )29.40078585461690.0939718180404173312.868117992265
Winsorized Mean ( 187 / 339 )29.21709233791750.0855377063696325341.569742490665
Winsorized Mean ( 188 / 339 )29.21709233791750.0855377063696325341.569742490665
Winsorized Mean ( 189 / 339 )29.21709233791750.0855377063696325341.569742490665
Winsorized Mean ( 190 / 339 )29.03045186640470.077958221698377372.384736772531
Winsorized Mean ( 191 / 339 )29.03045186640470.077958221698377372.384736772531
Winsorized Mean ( 192 / 339 )29.03045186640470.077958221698377372.384736772531
Winsorized Mean ( 193 / 339 )29.03045186640470.077958221698377372.384736772531
Winsorized Mean ( 194 / 339 )29.03045186640470.077958221698377372.384736772531
Winsorized Mean ( 195 / 339 )29.03045186640470.077958221698377372.384736772531
Winsorized Mean ( 196 / 339 )28.83791748526520.071456171856863403.574901032086
Winsorized Mean ( 197 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 198 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 199 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 200 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 201 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 202 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 203 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 204 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 205 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 206 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 207 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 208 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 209 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 210 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 211 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 212 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 213 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 214 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 215 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 216 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 217 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 218 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 219 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 220 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 221 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 222 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 223 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 224 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 225 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 226 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 227 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 228 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 229 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 230 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 231 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 232 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 233 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 234 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 235 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 236 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 237 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 238 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 239 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 240 / 339 )28.64440078585460.0666080573870473430.044080394166
Winsorized Mean ( 241 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 242 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 243 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 244 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 245 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 246 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 247 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 248 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 249 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 250 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 251 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 252 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 253 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 254 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 255 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 256 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 257 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 258 / 339 )28.88113948919450.0540148940804015534.688440677209
Winsorized Mean ( 259 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 260 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 261 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 262 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 263 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 264 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 265 / 339 )29.13555992141450.0407749091329823714.546286943094
Winsorized Mean ( 266 / 339 )29.39685658153240.0274775078321521069.85163141814
Winsorized Mean ( 267 / 339 )29.39685658153240.0274775078321521069.85163141814
Winsorized Mean ( 268 / 339 )29.39685658153240.0274775078321521069.85163141814
Winsorized Mean ( 269 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 270 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 271 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 272 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 273 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 274 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 275 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 276 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 277 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 278 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 279 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 280 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 281 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 282 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 283 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 284 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 285 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 286 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 287 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 288 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 289 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 290 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 291 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 292 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 293 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 294 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 295 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 296 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 297 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 298 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 299 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 300 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 301 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 302 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 303 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 304 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 305 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 306 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 307 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 308 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 309 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 310 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 311 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 312 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 313 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 314 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 315 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 316 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 317 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 318 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 319 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 320 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 321 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 322 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 323 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 324 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 325 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 326 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 327 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 328 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 329 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 330 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 331 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 332 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 333 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 334 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 335 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 336 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 337 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 338 / 339 )29.66110019646370.01484256040943541998.38163889891
Winsorized Mean ( 339 / 339 )29.66110019646370.01484256040943541998.38163889891
Trimmed Mean ( 1 / 339 )29.89292730844790.194823855460546153.435662371960
Trimmed Mean ( 2 / 339 )29.89173228346460.193203086888461154.716639184557
Trimmed Mean ( 3 / 339 )29.89130434782610.191554835755349156.045678669281
Trimmed Mean ( 4 / 339 )29.89130434782610.190073403224881157.261899038346
Trimmed Mean ( 5 / 339 )29.88591269841270.188658439268780158.412805778779
Trimmed Mean ( 6 / 339 )29.88071570576540.187388298289323159.458813482741
Trimmed Mean ( 7 / 339 )29.87549800796810.186098343639423160.536076913472
Trimmed Mean ( 8 / 339 )29.87549800796810.184788055789859161.674399788818
Trimmed Mean ( 9 / 339 )29.8650.183456892569975162.790285944742
Trimmed Mean ( 10 / 339 )29.85971943887780.182104287724511163.970435907856
Trimmed Mean ( 11 / 339 )29.85441767068270.180729649348156165.188267549678
Trimmed Mean ( 12 / 339 )29.84909456740440.179332358184828166.445670315898
Trimmed Mean ( 13 / 339 )29.843750.177911765777003167.744667530345
Trimmed Mean ( 14 / 339 )29.83838383838380.176467192448523169.087428798347
Trimmed Mean ( 15 / 339 )29.8329959514170.174997925102051170.476283841764
Trimmed Mean ( 16 / 339 )29.8329959514170.173503214809806171.944917470952
Trimmed Mean ( 17 / 339 )29.82215447154470.171982274173207173.402489383936
Trimmed Mean ( 18 / 339 )29.81670061099800.170434274423565174.945448688902
Trimmed Mean ( 19 / 339 )29.81122448979590.168858342231928176.545760758743
Trimmed Mean ( 20 / 339 )29.80572597137010.167253556191366178.206829499443
Trimmed Mean ( 21 / 339 )29.80020491803280.165618942929419179.932345847254
Trimmed Mean ( 22 / 339 )29.79158110882960.164209930812127181.423748012622
Trimmed Mean ( 23 / 339 )29.78292181069960.162775769071007182.969013021265
Trimmed Mean ( 24 / 339 )29.77422680412370.161315658781513184.571212918952
Trimmed Mean ( 25 / 339 )29.76549586776860.159828757952343186.233668140273
Trimmed Mean ( 26 / 339 )29.75465838509320.158459873023742187.774089536440
Trimmed Mean ( 27 / 339 )29.74377593361000.157066049350103189.371134351960
Trimmed Mean ( 28 / 339 )29.73284823284820.155646484318958191.028074697262
Trimmed Mean ( 29 / 339 )29.7218750.154200331549438192.748450676780
Trimmed Mean ( 30 / 339 )29.71085594989560.152726697384853194.536099180014
Trimmed Mean ( 31 / 339 )29.69979079497910.151224637010527196.395186539026
Trimmed Mean ( 32 / 339 )29.69979079497910.149693150146453198.404474526204
Trimmed Mean ( 33 / 339 )29.67752100840340.148131176256089200.34621852389
Trimmed Mean ( 34 / 339 )29.66631578947370.146537589202819202.448504515885
Trimmed Mean ( 35 / 339 )29.65822784810130.145345071194641204.053894668255
Trimmed Mean ( 36 / 339 )29.65221987315010.144384854798348205.369322942931
Trimmed Mean ( 37 / 339 )29.64618644067800.143409046341162206.724660661583
Trimmed Mean ( 38 / 339 )29.64012738853500.142417232304692208.121776479422
Trimmed Mean ( 39 / 339 )29.63404255319150.141408981120099209.562662275483
Trimmed Mean ( 40 / 339 )29.62793176972280.140383842016127211.049443755210
Trimmed Mean ( 41 / 339 )29.62179487179490.139341343769288212.584392187581
Trimmed Mean ( 42 / 339 )29.61563169164880.138280993345776214.169937422954
Trimmed Mean ( 43 / 339 )29.60944206008580.137202274423317215.808682359962
Trimmed Mean ( 44 / 339 )29.60645161290320.136458682864211216.962753790936
Trimmed Mean ( 45 / 339 )29.60560344827590.135898914733856217.850183029462
Trimmed Mean ( 46 / 339 )29.60475161987040.135331308946667218.757594604640
Trimmed Mean ( 47 / 339 )29.60389610389610.134755710199839219.685652355618
Trimmed Mean ( 48 / 339 )29.60303687635570.134171958447718220.635050861921
Trimmed Mean ( 49 / 339 )29.60217391304350.133579888693631221.606517287470
Trimmed Mean ( 50 / 339 )29.60130718954250.132979330769577222.60081336125
Trimmed Mean ( 51 / 339 )29.60043668122270.132370109102892223.618737506775
Trimmed Mean ( 52 / 339 )29.59956236323850.131752042468938224.661127133699
Trimmed Mean ( 53 / 339 )29.59868421052630.131124943728751225.728861106358
Trimmed Mean ( 54 / 339 )29.59780219780220.130488619550510226.822862405602
Trimmed Mean ( 55 / 339 )29.59691629955950.129842870113568227.944101002022
Trimmed Mean ( 56 / 339 )29.59602649006620.129187488793691229.093596960695
Trimmed Mean ( 57 / 339 )29.59513274336280.128522261827998230.272423799778
Trimmed Mean ( 58 / 339 )29.59423503325940.127846967957959231.481712127824
Trimmed Mean ( 59 / 339 )29.59333333333330.127161378048664232.722653587539
Trimmed Mean ( 60 / 339 )29.59242761692650.126465254682368233.996505136935
Trimmed Mean ( 61 / 339 )29.59151785714290.125758351724149235.304593702467
Trimmed Mean ( 62 / 339 )29.59060402684560.125040413857267236.648321242947
Trimmed Mean ( 63 / 339 )29.58968609865470.124311176085582238.029170267713
Trimmed Mean ( 64 / 339 )29.58968609865470.123570363200097239.456171628630
Trimmed Mean ( 65 / 339 )29.58783783783780.122817689206388240.908602246351
Trimmed Mean ( 66 / 339 )29.58690744920990.122052856709316242.410610016894
Trimmed Mean ( 67 / 339 )29.58597285067870.121275556251029243.956603995603
Trimmed Mean ( 68 / 339 )29.58503401360540.120485465597802245.548571911276
Trimmed Mean ( 69 / 339 )29.58409090909090.119682248970756247.188627916908
Trimmed Mean ( 70 / 339 )29.58314350797270.118865556214908248.879023074493
Trimmed Mean ( 71 / 339 )29.58219178082190.118035021900355250.622156920469
Trimmed Mean ( 72 / 339 )29.58123569794050.117190264348621252.420590245801
Trimmed Mean ( 73 / 339 )29.58027522935780.116330884576358254.277059244243
Trimmed Mean ( 74 / 339 )29.57931034482760.115456465147577256.19449120514
Trimmed Mean ( 75 / 339 )29.57834101382490.114566568924470258.176021953881
Trimmed Mean ( 76 / 339 )29.57736720554270.113660737705552260.225015274539
Trimmed Mean ( 77 / 339 )29.57638888888890.112738490738365262.345084586306
Trimmed Mean ( 78 / 339 )29.57540603248260.111799323092205264.540117189177
Trimmed Mean ( 79 / 339 )29.57441860465120.110842703874315266.814301446362
Trimmed Mean ( 80 / 339 )29.57342657342660.109868074270599269.172157332883
Trimmed Mean ( 81 / 339 )29.5712616822430.108988634666419271.324269477745
Trimmed Mean ( 82 / 339 )29.56908665105390.108093022062428273.552224619796
Trimmed Mean ( 83 / 339 )29.56572769953050.107284479906755275.582523448194
Trimmed Mean ( 84 / 339 )29.56235294117650.106461352936066277.681544766107
Trimmed Mean ( 85 / 339 )29.55778301886790.105716204406472279.595575577232
Trimmed Mean ( 86 / 339 )29.55319148936170.104957790256382281.572157885297
Trimmed Mean ( 87 / 339 )29.54857819905210.104185730225064283.614446385516
Trimmed Mean ( 88 / 339 )29.54394299287410.103399626186194285.725820126987
Trimmed Mean ( 89 / 339 )29.53928571428570.102599060919354287.909903361636
Trimmed Mean ( 90 / 339 )29.53460620525060.101783596768863290.170588806364
Trimmed Mean ( 91 / 339 )29.52990430622010.100952774176951292.512063655228
Trimmed Mean ( 92 / 339 )29.52517985611510.100106110076438294.938838733926
Trimmed Mean ( 93 / 339 )29.52043269230770.0992430961260165297.455781254782
Trimmed Mean ( 94 / 339 )29.51566265060240.0983631967687057300.068151709287
Trimmed Mean ( 95 / 339 )29.50966183574880.0975558600146818302.489894828539
Trimmed Mean ( 96 / 339 )29.50363196125910.0967328120510885305.001284834737
Trimmed Mean ( 97 / 339 )29.4963592233010.0959703517915482307.348662088562
Trimmed Mean ( 98 / 339 )29.48905109489050.0951929967496363309.781728717383
Trimmed Mean ( 99 / 339 )29.48536585365850.0948259763853699310.941864008137
Trimmed Mean ( 100 / 339 )29.48166259168700.0944531613366323312.129971876897
Trimmed Mean ( 101 / 339 )29.48039215686270.0942826553846692312.680970180401
Trimmed Mean ( 102 / 339 )29.47911547911550.094109562877024313.242507752765
Trimmed Mean ( 103 / 339 )29.47783251231530.0939338418140596313.814829065185
Trimmed Mean ( 104 / 339 )29.47654320987650.0937554492791816314.398186308108
Trimmed Mean ( 105 / 339 )29.47524752475250.0935743414119403314.99283970372
Trimmed Mean ( 106 / 339 )29.47394540942930.0933904733801066315.599057833961
Trimmed Mean ( 107 / 339 )29.47263681592040.0932037993506756316.217117984974
Trimmed Mean ( 108 / 339 )29.47132169576060.0930142724597432316.847306508965
Trimmed Mean ( 109 / 339 )29.470.092821844781203317.489919204535
Trimmed Mean ( 110 / 339 )29.4686716791980.0926264672942056318.145261716588
Trimmed Mean ( 111 / 339 )29.46733668341710.0924280898493186318.813649957025
Trimmed Mean ( 112 / 339 )29.46599496221660.0922266611333219319.495410547508
Trimmed Mean ( 113 / 339 )29.46464646464650.0920221286325712320.190881285672
Trimmed Mean ( 114 / 339 )29.46329113924050.091814438594855320.900411636253
Trimmed Mean ( 115 / 339 )29.46192893401020.0916035359896693321.624363248737
Trimmed Mean ( 116 / 339 )29.46055979643770.0913893644668253322.363110503214
Trimmed Mean ( 117 / 339 )29.45918367346940.091171866313306323.117041086281
Trimmed Mean ( 118 / 339 )29.45780051150900.090950982408276323.886556598958
Trimmed Mean ( 119 / 339 )29.45641025641030.0907266521761471324.672073198735
Trimmed Mean ( 120 / 339 )29.45501285347040.0904988135375933325.474022278036
Trimmed Mean ( 121 / 339 )29.45360824742270.0902674028584045326.292851181553
Trimmed Mean ( 122 / 339 )29.45219638242890.090032354896058327.129023965122
Trimmed Mean ( 123 / 339 )29.45077720207250.0897936027438807327.983022198979
Trimmed Mean ( 124 / 339 )29.44935064935060.0895510777726666328.855345818511
Trimmed Mean ( 125 / 339 )29.44791666666670.0893047095696023329.746514025842
Trimmed Mean ( 126 / 339 )29.44647519582250.089054425874347330.657066245877
Trimmed Mean ( 127 / 339 )29.44502617801050.088800152512099331.587563140712
Trimmed Mean ( 128 / 339 )29.44502617801050.0885418133234726332.555038944572
Trimmed Mean ( 129 / 339 )29.44210526315790.0882793300909919333.510746318658
Trimmed Mean ( 130 / 339 )29.44063324538260.0880126224619994334.504670146534
Trimmed Mean ( 131 / 339 )29.43915343915340.0877416078677584335.521016249477
Trimmed Mean ( 132 / 339 )29.43766578249340.087466201438514336.560469053719
Trimmed Mean ( 133 / 339 )29.43617021276600.0871863159142593337.623741800423
Trimmed Mean ( 134 / 339 )29.43466666666670.0869018615509337338.711578110612
Trimmed Mean ( 135 / 339 )29.43315508021390.086612746021761339.824753654837
Trimmed Mean ( 136 / 339 )29.43163538873990.086318874313409340.964077935941
Trimmed Mean ( 137 / 339 )29.43010752688170.0860201486166322342.130396194077
Trimmed Mean ( 138 / 339 )29.42857142857140.085716468211026343.324591443980
Trimmed Mean ( 139 / 339 )29.42702702702700.085407729343498344.547586655484
Trimmed Mean ( 140 / 339 )29.42547425474250.0850938251000234345.80034708928
Trimmed Mean ( 141 / 339 )29.42391304347830.0847746452702182347.083882801159
Trimmed Mean ( 142 / 339 )29.42234332425070.0844500762042277348.399251329246
Trimmed Mean ( 143 / 339 )29.42076502732240.084120000661379349.747560580204
Trimmed Mean ( 144 / 339 )29.41917808219180.0837842976500038351.129971932043
Trimmed Mean ( 145 / 339 )29.41758241758240.0834428422577841352.547703572959
Trimmed Mean ( 146 / 339 )29.41597796143250.0830955054719153354.002034097675
Trimmed Mean ( 147 / 339 )29.4143646408840.0827421539883187355.49430638507
Trimmed Mean ( 148 / 339 )29.41274238227150.082382650009066357.025931783388
Trimmed Mean ( 149 / 339 )29.41111111111110.0820168510270988358.598394632263
Trimmed Mean ( 150 / 339 )29.40947075208910.0816446095972429360.213257153995
Trimmed Mean ( 151 / 339 )29.40782122905030.0812657730924182361.87216475018
Trimmed Mean ( 152 / 339 )29.4061624649860.0808801834438426363.576851743957
Trimmed Mean ( 153 / 339 )29.40449438202250.0804876768639074365.329147612759
Trimmed Mean ( 154 / 339 )29.40281690140840.0800880835502696367.130983761809
Trimmed Mean ( 155 / 339 )29.40112994350280.0796812273695619368.984400894583
Trimmed Mean ( 156 / 339 )29.39943342776200.0792669255189513370.891557043336
Trimmed Mean ( 157 / 339 )29.39772727272730.0788449881635973372.854736330599
Trimmed Mean ( 158 / 339 )29.39601139601140.078415218047848374.876358541455
Trimmed Mean ( 159 / 339 )29.39428571428570.0779774100777813376.958989596671
Trimmed Mean ( 160 / 339 )29.39255014326650.0775313508724334379.10535302845
Trimmed Mean ( 161 / 339 )29.39080459770110.0770768182807568381.318342574072
Trimmed Mean ( 162 / 339 )29.38904899135450.0766135808610156383.601036018262
Trimmed Mean ( 163 / 339 )29.38728323699420.0761413973189379385.956710433064
Trimmed Mean ( 164 / 339 )29.38550724637680.0756600159005128388.388858984864
Trimmed Mean ( 165 / 339 )29.38372093023260.0751691737348211390.901209502333
Trimmed Mean ( 166 / 339 )29.38192419825070.0746685961217187393.497745027303
Trimmed Mean ( 167 / 339 )29.38011695906430.0741579957585448396.182726603409
Trimmed Mean ( 168 / 339 )29.37829912023460.0736370718992772398.960718595914
Trimmed Mean ( 169 / 339 )29.37647058823530.0731055094386972401.836616881372
Trimmed Mean ( 170 / 339 )29.37463126843660.0725629779131346404.815680299133
Trimmed Mean ( 171 / 339 )29.37278106508880.0720091304082122407.903565819745
Trimmed Mean ( 172 / 339 )29.37091988130560.0714436023626741411.106367960115
Trimmed Mean ( 173 / 339 )29.36904761904760.0708660102558288414.430663064343
Trimmed Mean ( 174 / 339 )29.36716417910450.0702759501643161417.8835591755
Trimmed Mean ( 175 / 339 )29.36526946107780.0696729961717808421.47275235124
Trimmed Mean ( 176 / 339 )29.36336336336340.0690566986125242425.206590429708
Trimmed Mean ( 177 / 339 )29.36144578313250.0684265821272455429.094145437985
Trimmed Mean ( 178 / 339 )29.35951661631420.0677821435054734433.145296060804
Trimmed Mean ( 179 / 339 )29.35757575757580.0671228492851091437.370821862424
Trimmed Mean ( 180 / 339 )29.35562310030400.066448133074508441.782511291741
Trimmed Mean ( 181 / 339 )29.35365853658540.0657573925565303446.393285916114
Trimmed Mean ( 182 / 339 )29.35168195718650.0650499861267574451.217343843723
Trimmed Mean ( 183 / 339 )29.34969325153370.0643252291093076456.270325934789
Trimmed Mean ( 184 / 339 )29.34769230769230.0635823894830025461.569509204083
Trimmed Mean ( 185 / 339 )29.34567901234570.0628206830375581467.134032828026
Trimmed Mean ( 186 / 339 )29.3436532507740.0620392678633586472.985163451692
Trimmed Mean ( 187 / 339 )29.34316770186340.061440294379206477.588331865062
Trimmed Mean ( 188 / 339 )29.34423676012460.0609930345346228481.10799838082
Trimmed Mean ( 189 / 339 )29.34531250.0605361643531464484.756720442509
Trimmed Mean ( 190 / 339 )29.3463949843260.0600693713651144488.541736286075
Trimmed Mean ( 191 / 339 )29.34905660377360.0597231399804267491.418512378825
Trimmed Mean ( 192 / 339 )29.35173501577290.0593696757797059494.389343217637
Trimmed Mean ( 193 / 339 )29.35443037974680.0590087682656833497.458788625791
Trimmed Mean ( 194 / 339 )29.35714285714290.058640197530396500.63171840316
Trimmed Mean ( 195 / 339 )29.35987261146500.0582637336481572503.913339793211
Trimmed Mean ( 196 / 339 )29.36261980830670.057879136016178507.309227976372
Trimmed Mean ( 197 / 339 )29.36698717948720.0575815552958847510.006842096987
Trimmed Mean ( 198 / 339 )29.37299035369770.0573283688549728512.363964654296
Trimmed Mean ( 199 / 339 )29.37903225806450.057069126899532514.79729679035
Trimmed Mean ( 200 / 339 )29.38511326860840.0568036560673264517.310245554965
Trimmed Mean ( 201 / 339 )29.39123376623380.0565317758500134519.906430044101
Trimmed Mean ( 202 / 339 )29.39739413680780.0562532981775517522.589698545694
Trimmed Mean ( 203 / 339 )29.40359477124180.0559680269703848525.364147405099
Trimmed Mean ( 204 / 339 )29.40983606557380.0556757576562379528.234141817353
Trimmed Mean ( 205 / 339 )29.41611842105260.0553762766479942531.204338782827
Trimmed Mean ( 206 / 339 )29.42244224422440.055069360778685534.27971249691
Trimmed Mean ( 207 / 339 )29.42880794701990.0547547766891378537.465582484202
Trimmed Mean ( 208 / 339 )29.43521594684390.0544322801632622540.767644834222
Trimmed Mean ( 209 / 339 )29.44166666666670.0541016154053086544.192006950273
Trimmed Mean ( 210 / 339 )29.44816053511710.0537625142526863547.745226287397
Trimmed Mean ( 211 / 339 )29.45469798657720.0534146953170679551.434353631244
Trimmed Mean ( 212 / 339 )29.46127946127950.0530578630455044555.266981559592
Trimmed Mean ( 213 / 339 )29.46790540540540.052691706692117559.251298835116
Trimmed Mean ( 214 / 339 )29.47457627118640.0523158991895731563.396151605494
Trimmed Mean ( 215 / 339 )29.48129251700680.0519300959079693567.71111243957
Trimmed Mean ( 216 / 339 )29.48805460750850.051533933286882572.206558411771
Trimmed Mean ( 217 / 339 )29.49486301369860.0511270273241485576.893759668431
Trimmed Mean ( 218 / 339 )29.50171821305840.0507089719023483581.784980178078
Trimmed Mean ( 219 / 339 )29.50862068965520.0502793369308656586.893592694544
Trimmed Mean ( 220 / 339 )29.51557093425610.0498376662777406592.234210361468
Trimmed Mean ( 221 / 339 )29.52256944444440.0493834754611076597.822837878132
Trimmed Mean ( 222 / 339 )29.52961672473870.0489162490647215603.677045753606
Trimmed Mean ( 223 / 339 )29.53671328671330.0484354378356632609.816171930323
Trimmed Mean ( 224 / 339 )29.54385964912280.0479404554145345616.261556000274
Trimmed Mean ( 225 / 339 )29.55105633802820.0474306746389388623.036812421131
Trimmed Mean ( 226 / 339 )29.55830388692580.0469054233493701630.168150637164
Trimmed Mean ( 227 / 339 )29.56560283687940.0463639796122009637.684751916746
Trimmed Mean ( 228 / 339 )29.57295373665480.0458055662565197645.619215163519
Trimmed Mean ( 229 / 339 )29.58035714285710.0452293445991155654.008087117752
Trimmed Mean ( 230 / 339 )29.58781362007170.0446344072036113662.892496479213
Trimmed Mean ( 231 / 339 )29.59532374100720.0440197694838059672.318916887895
Trimmed Mean ( 232 / 339 )29.60288808664260.0433843599152872682.340090863287
Trimmed Mean ( 233 / 339 )29.61050724637680.0427270085599839693.016156392203
Trimmed Mean ( 234 / 339 )29.61818181818180.0420464335309378704.41603082432
Trimmed Mean ( 235 / 339 )29.62591240875910.0413412249227443716.619124472534
Trimmed Mean ( 236 / 339 )29.63369963369960.0406098255976784729.717480869796
Trimmed Mean ( 237 / 339 )29.64154411764710.0398505080353313743.818475071057
Trimmed Mean ( 238 / 339 )29.64944649446490.0390613462054084759.048250373913
Trimmed Mean ( 239 / 339 )29.65740740740740.0382401810806897775.556144591158
Trimmed Mean ( 240 / 339 )29.66542750929370.0373845779270064793.520460956269
Trimmed Mean ( 241 / 339 )29.67350746268660.0364917728232662813.15609429004
Trimmed Mean ( 242 / 339 )29.67977528089890.0359693156895831825.141504971537
Trimmed Mean ( 243 / 339 )29.68609022556390.0354284575919091837.91652934796
Trimmed Mean ( 244 / 339 )29.69245283018870.0348681173774460851.564554196288
Trimmed Mean ( 245 / 339 )29.69886363636360.0342871057806620866.181701842966
Trimmed Mean ( 246 / 339 )29.70532319391630.0336841091730284881.879435829107
Trimmed Mean ( 247 / 339 )29.71183206106870.0330576699761506898.78784810013
Trimmed Mean ( 248 / 339 )29.71839080459770.032406162854141917.05984871949
Trimmed Mean ( 249 / 339 )29.7250.0317277655090058936.876566096743
Trimmed Mean ( 250 / 339 )29.73166023166020.0310204224931673958.4543936566
Trimmed Mean ( 251 / 339 )29.73837209302330.0302817998692211982.054310558
Trimmed Mean ( 252 / 339 )29.74513618677040.02950922769930561007.99439720581
Trimmed Mean ( 253 / 339 )29.7519531250.02869962609119551036.66692487423
Trimmed Mean ( 254 / 339 )29.75882352941180.02784940862772371068.56213455776
Trimmed Mean ( 255 / 339 )29.76574803149610.02695435405609471104.30203482341
Trimmed Mean ( 256 / 339 )29.76574803149610.0260094324036221144.42128415501
Trimmed Mean ( 257 / 339 )29.77976190476190.02500856392090421190.78256548228
Trimmed Mean ( 258 / 339 )29.78685258964140.02394427596796241244.00723703220
Trimmed Mean ( 259 / 339 )29.7940.02280719922904491306.34190111592
Trimmed Mean ( 260 / 339 )29.79919678714860.02219443220359871342.64289862377
Trimmed Mean ( 261 / 339 )29.8044354838710.02155095823042621382.97495476522
Trimmed Mean ( 262 / 339 )29.80971659919030.02087363570624221428.10371028348
Trimmed Mean ( 263 / 339 )29.81504065040650.02015873244226601479.01366000049
Trimmed Mean ( 264 / 339 )29.82040816326530.01940175306683571536.99555192456
Trimmed Mean ( 265 / 339 )29.82581967213110.01859719488169431603.78056270677
Trimmed Mean ( 266 / 339 )29.83127572016460.01773819202085121681.75401896079
Trimmed Mean ( 267 / 339 )29.83471074380170.01740000599662341714.63795757262
Trimmed Mean ( 268 / 339 )29.83817427385890.01704753889318521750.29219530256
Trimmed Mean ( 269 / 339 )29.84166666666670.01667970957984061789.09989552419
Trimmed Mean ( 270 / 339 )29.84309623430960.01665313752790081792.04045990194
Trimmed Mean ( 271 / 339 )29.84453781512600.01662551583359101795.10447157536
Trimmed Mean ( 272 / 339 )29.84599156118140.01659681313758641798.29653523000
Trimmed Mean ( 273 / 339 )29.84745762711860.01656699692672221801.62148632836
Trimmed Mean ( 274 / 339 )29.84893617021280.01653603347949771805.08440595631
Trimmed Mean ( 275 / 339 )29.85042735042730.01650388780830171808.69063684571
Trimmed Mean ( 276 / 339 )29.85193133047210.01647052359811281812.44580068436
Trimmed Mean ( 277 / 339 )29.85344827586210.01643590314140711816.35581683686
Trimmed Mean ( 278 / 339 )29.85497835497840.01639998726897961820.42692261407
Trimmed Mean ( 279 / 339 )29.85652173913040.01636273527635911824.66569524395
Trimmed Mean ( 280 / 339 )29.85807860262010.01632410484546671829.07907571495
Trimmed Mean ( 281 / 339 )29.8596491228070.01628405196113181833.67439468251
Trimmed Mean ( 282 / 339 )29.86123348017620.01624253082204371838.45940065262
Trimmed Mean ( 283 / 339 )29.86283185840710.01619949374567331843.44229068165
Trimmed Mean ( 284 / 339 )29.86444444444440.0161548910666541848.63174386170
Trimmed Mean ( 285 / 339 )29.86607142857140.01610867102805501854.03695789407
Trimmed Mean ( 286 / 339 )29.86771300448430.01606077966492371859.66768909199
Trimmed Mean ( 287 / 339 )29.86936936936940.01601116067940571865.53429619807
Trimmed Mean ( 288 / 339 )29.87104072398190.01595975530667531871.6477884525
Trimmed Mean ( 289 / 339 )29.87272727272730.01590650217082481878.01987840664
Trimmed Mean ( 290 / 339 )29.87442922374430.01585133712976541884.66304004389
Trimmed Mean ( 291 / 339 )29.87614678899080.01579419310808191891.59057284814
Trimmed Mean ( 292 / 339 )29.87788018433180.01573499991666001898.81667255031
Trimmed Mean ( 293 / 339 )29.87962962962960.01567368405776451906.35650938923
Trimmed Mean ( 294 / 339 )29.88139534883720.01561016851408391914.22631484583
Trimmed Mean ( 295 / 339 )29.88317757009350.01554437252007281922.44347795349
Trimmed Mean ( 296 / 339 )29.88497652582160.01547621131371201931.02665245617
Trimmed Mean ( 297 / 339 )29.88679245283020.01540559586656091939.99587628428
Trimmed Mean ( 298 / 339 )29.88862559241710.01533243258969521949.37270505301
Trimmed Mean ( 299 / 339 )29.89047619047620.01525662301279871959.18036156502
Trimmed Mean ( 300 / 339 )29.89234449760770.01517806343329491969.44390362971
Trimmed Mean ( 301 / 339 )29.89423076923080.01509664453196861980.19041290446
Trimmed Mean ( 302 / 339 )29.89613526570050.01501225095100661991.44920793479
Trimmed Mean ( 303 / 339 )29.89805825242720.01492476082978612003.25208513615
Trimmed Mean ( 304 / 339 )29.90.01483404529302452015.63359214362
Trimmed Mean ( 305 / 339 )29.90196078431370.01473996788506722028.63133878378
Trimmed Mean ( 306 / 339 )29.90394088669950.01464238394308892042.28635193068
Trimmed Mean ( 307 / 339 )29.90594059405940.01454113990079982056.64348174069
Trimmed Mean ( 308 / 339 )29.9079601990050.01443607251282582071.75186827533
Trimmed Mean ( 309 / 339 )29.910.01432700798822762087.66547939227
Trimmed Mean ( 310 / 339 )29.91206030150750.01421376101956142104.44373310778
Trimmed Mean ( 311 / 339 )29.91414141414140.01409613369138652122.15222053552
Trimmed Mean ( 312 / 339 )29.91624365482230.01397391424907752140.86354915175
Trimmed Mean ( 313 / 339 )29.91836734693880.01384687570505822160.65833074603
Trimmed Mean ( 314 / 339 )29.92051282051280.01371477425496532181.626344282
Trimmed Mean ( 315 / 339 )29.92268041237110.01357734747052302203.8679114116
Trimmed Mean ( 316 / 339 )29.92487046632120.01343431222875442227.49553209512
Trimmed Mean ( 317 / 339 )29.92708333333330.01328536232815312252.63584041773
Trimmed Mean ( 318 / 339 )29.92931937172780.01313016573102272279.43195728395
Trimmed Mean ( 319 / 339 )29.93157894736840.01296836135660062308.04633864817
Trimmed Mean ( 320 / 339 )29.93386243386240.01279955533077972338.66424733359
Trimmed Mean ( 321 / 339 )29.93617021276600.01262331657377992371.49801621445
Trimmed Mean ( 322 / 339 )29.93850267379680.01243917157498942406.79232481946
Trimmed Mean ( 323 / 339 )29.94086021505380.01224659816154362444.83078648512
Trimmed Mean ( 324 / 339 )29.94324324324320.01204501800993472485.94424836444
Trimmed Mean ( 325 / 339 )29.94565217391300.01183378757208802530.52135603186
Trimmed Mean ( 326 / 339 )29.9480874316940.01161218698006362579.02215001450
Trimmed Mean ( 327 / 339 )29.95054945054940.01137940634355102631.99577783979
Trimmed Mean ( 328 / 339 )29.95303867403310.01113452864120142690.10387769781
Trimmed Mean ( 329 / 339 )29.95555555555560.01087650809861022754.15191015057
Trimmed Mean ( 330 / 339 )29.95810055865920.01060414249113542825.13183727046
Trimmed Mean ( 331 / 339 )29.96067415730340.01031603712438222904.28134331648
Trimmed Mean ( 332 / 339 )29.96327683615820.01001055718639212993.16774064173
Trimmed Mean ( 333 / 339 )29.96590909090910.009685763484029523093.80970744523
Trimmed Mean ( 334 / 339 )29.96857142857140.009339323820116383208.8588002507
Trimmed Mean ( 335 / 339 )29.97126436781610.008968387584734873341.87880314521
Trimmed Mean ( 336 / 339 )29.97398843930640.008569402834439873497.79197201967
Trimmed Mean ( 337 / 339 )29.97674418604650.008137839677020533683.62432485544
Trimmed Mean ( 338 / 339 )29.97953216374270.007667753236493673909.81963543884
Trimmed Mean ( 339 / 339 )29.98235294117650.00715105457462244192.71767937243
Median30
Midrange30.5
Midmean - Weighted Average at Xnp29.6982758620690
Midmean - Weighted Average at X(n+1)p29.6982758620690
Midmean - Empirical Distribution Function29.6982758620690
Midmean - Empirical Distribution Function - Averaging29.6982758620690
Midmean - Empirical Distribution Function - Interpolation29.6982758620690
Midmean - Closest Observation29.6982758620690
Midmean - True Basic - Statistics Graphics Toolkit29.6982758620690
Midmean - MS Excel (old versions)29.6982758620690
Number of observations1018
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Oct/24/t1256388510qqb7mpgcl6hafcb/1xmdv1256388332.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Oct/24/t1256388510qqb7mpgcl6hafcb/1xmdv1256388332.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Oct/24/t1256388510qqb7mpgcl6hafcb/2tsv01256388332.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Oct/24/t1256388510qqb7mpgcl6hafcb/2tsv01256388332.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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