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opgave 6 stap 6

*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 07:21:37 -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/t125060189848lkkwn6b01iq8e.htm/, Retrieved Tue, 18 Aug 2009 15:25:00 +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/t125060189848lkkwn6b01iq8e.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 «
2 4 5 5 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 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'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10.75894988066830.0732487362672086146.882395914928
Geometric Mean10.5454146298950
Harmonic Mean10.3053484956167
Quadratic Mean10.9656656610085
Winsorized Mean ( 1 / 279 )10.75178997613370.0708450579964355151.764855308250
Winsorized Mean ( 2 / 279 )10.74940334128880.0699234312375512153.731061977920
Winsorized Mean ( 3 / 279 )10.74940334128880.0699234312375512153.731061977920
Winsorized Mean ( 4 / 279 )10.74940334128880.0689377856326972155.929048817465
Winsorized Mean ( 5 / 279 )10.74940334128880.0689377856326972155.929048817465
Winsorized Mean ( 6 / 279 )10.74224343675420.0682200336757918157.464645763816
Winsorized Mean ( 7 / 279 )10.74224343675420.0682200336757918157.464645763816
Winsorized Mean ( 8 / 279 )10.74224343675420.0682200336757918157.464645763816
Winsorized Mean ( 9 / 279 )10.74224343675420.0682200336757918157.464645763816
Winsorized Mean ( 10 / 279 )10.73031026252980.0672171068283802159.636598015541
Winsorized Mean ( 11 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 12 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 13 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 14 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 15 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 16 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 17 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 18 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 19 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 20 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 21 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 22 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 23 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 24 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 25 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 26 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 27 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 28 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 29 / 279 )10.74343675417660.066221201224971162.235606655311
Winsorized Mean ( 30 / 279 )10.70763723150360.063736728911509167.997909751062
Winsorized Mean ( 31 / 279 )10.70763723150360.063736728911509167.997909751062
Winsorized Mean ( 32 / 279 )10.70763723150360.063736728911509167.997909751062
Winsorized Mean ( 33 / 279 )10.70763723150360.063736728911509167.997909751062
Winsorized Mean ( 34 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 35 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 36 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 37 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 38 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 39 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 40 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 41 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 42 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 43 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 44 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 45 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 46 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 47 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 48 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 49 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 50 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 51 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 52 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 53 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 54 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 55 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 56 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 57 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 58 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 59 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 60 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 61 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 62 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 63 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 64 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 65 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 66 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 67 / 279 )10.74821002386630.0612325848970795175.530888364946
Winsorized Mean ( 68 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 69 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 70 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 71 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 72 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 73 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 74 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 75 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 76 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 77 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 78 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 79 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 80 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 81 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 82 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 83 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 84 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 85 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 86 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 87 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 88 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 89 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 90 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 91 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 92 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 93 / 279 )10.66706443914080.0566392157110858188.333547794042
Winsorized Mean ( 94 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 95 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 96 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 97 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 98 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 99 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 100 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 101 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 102 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 103 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 104 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 105 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 106 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 107 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 108 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 109 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 110 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 111 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 112 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 113 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 114 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 115 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 116 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 117 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 118 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 119 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 120 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 121 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 122 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 123 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 124 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 125 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 126 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 127 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 128 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 129 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 130 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 131 / 279 )10.55489260143200.0519776927083134203.06581634286
Winsorized Mean ( 132 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 133 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 134 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 135 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 136 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 137 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 138 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 139 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 140 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 141 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 142 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 143 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 144 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 145 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 146 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 147 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 148 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 149 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 150 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 151 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 152 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 153 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 154 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 155 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 156 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 157 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 158 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 159 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 160 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 161 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 162 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 163 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 164 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 165 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 166 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 167 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 168 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 169 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 170 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 171 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 172 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 173 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 174 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 175 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 176 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 177 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 178 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 179 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 180 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 181 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 182 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 183 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 184 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 185 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 186 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 187 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 188 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 189 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 190 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 191 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 192 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 193 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 194 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 195 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 196 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 197 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 198 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 199 / 279 )10.71241050119330.0435729519014196245.850006339467
Winsorized Mean ( 200 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 201 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 202 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 203 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 204 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 205 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 206 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 207 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 208 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 209 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 210 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 211 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 212 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 213 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 214 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 215 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 216 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 217 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 218 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 219 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 220 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 221 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 222 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 223 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 224 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 225 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 226 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 227 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 228 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 229 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 230 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 231 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 232 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 233 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 234 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 235 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 236 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 237 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 238 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 239 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 240 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 241 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 242 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 243 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 244 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 245 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 246 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 247 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 248 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 249 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 250 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 251 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 252 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 253 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 254 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 255 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 256 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 257 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 258 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 259 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 260 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 261 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 262 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 263 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 264 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 265 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 266 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 267 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 268 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 269 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 270 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 271 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 272 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 273 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 274 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 275 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 276 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 277 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 278 / 279 )10.95107398568020.0337510299058347324.466364914898
Winsorized Mean ( 279 / 279 )10.95107398568020.0337510299058347324.466364914898
Trimmed Mean ( 1 / 279 )10.74880382775120.0696795519230999154.260518776209
Trimmed Mean ( 2 / 279 )10.74580335731410.0684821467821149156.913938336416
Trimmed Mean ( 3 / 279 )10.74399038461540.0677386572585981158.609438383157
Trimmed Mean ( 4 / 279 )10.74216867469880.0669791496315506160.380786166904
Trimmed Mean ( 5 / 279 )10.74033816425120.0664671662432128161.588627457816
Trimmed Mean ( 6 / 279 )10.73849878934620.0659457210316508162.838446852257
Trimmed Mean ( 7 / 279 )10.73786407766990.0655443019393978163.826049861636
Trimmed Mean ( 8 / 279 )10.73722627737230.0651360555476107164.843053315133
Trimmed Mean ( 9 / 279 )10.73658536585370.0647208029364922165.890793666281
Trimmed Mean ( 10 / 279 )10.73594132029340.0642983576478837166.970692767714
Trimmed Mean ( 11 / 279 )10.73651960784310.0639805888685327167.809015167156
Trimmed Mean ( 12 / 279 )10.73587223587220.0637581666274768168.384268302432
Trimmed Mean ( 13 / 279 )10.73522167487680.0635323591798478168.972501784288
Trimmed Mean ( 14 / 279 )10.73456790123460.0633030996294129169.574127713754
Trimmed Mean ( 15 / 279 )10.73391089108910.0630703191296489170.189576320745
Trimmed Mean ( 16 / 279 )10.73325062034740.0628339468033204170.819296994729
Trimmed Mean ( 17 / 279 )10.73258706467660.0625939096576628171.463759387695
Trimmed Mean ( 18 / 279 )10.73192019950120.0623501324948675172.123454595460
Trimmed Mean ( 19 / 279 )10.731250.0621025378175419172.798896423984
Trimmed Mean ( 20 / 279 )10.73057644110280.0618510457287926173.490622747992
Trimmed Mean ( 21 / 279 )10.72989949748740.0615955738265448174.199196969951
Trimmed Mean ( 22 / 279 )10.72921914357680.0613360370916826174.925209588276
Trimmed Mean ( 23 / 279 )10.72853535353540.0610723477695562175.669279884527
Trimmed Mean ( 24 / 279 )10.72784810126580.0608044152443616176.432057740422
Trimmed Mean ( 25 / 279 )10.72715736040610.060532145905855177.214225596593
Trimmed Mean ( 26 / 279 )10.72646310432570.060255443007814178.016500566342
Trimmed Mean ( 27 / 279 )10.72576530612240.0599742065176045178.839636719063
Trimmed Mean ( 28 / 279 )10.72506393861890.0596883329561515179.684427549649
Trimmed Mean ( 29 / 279 )10.72506393861890.059397715227543180.563577193718
Trimmed Mean ( 30 / 279 )10.72365038560410.0591022424374268181.442360616986
Trimmed Mean ( 31 / 279 )10.72365038560410.0589084917692819182.039126508345
Trimmed Mean ( 32 / 279 )10.72480620155040.0587116801434834182.669039198681
Trimmed Mean ( 33 / 279 )10.72538860103630.0585117466483695183.303169284815
Trimmed Mean ( 34 / 279 )10.72597402597400.0583086286116517183.951745759815
Trimmed Mean ( 35 / 279 )10.72526041666670.0581964398598743184.294098444699
Trimmed Mean ( 36 / 279 )10.72454308093990.0580824459007619184.643448026683
Trimmed Mean ( 37 / 279 )10.72382198952880.0579666155847491184.999967332062
Trimmed Mean ( 38 / 279 )10.72309711286090.0578489170387644185.363834999286
Trimmed Mean ( 39 / 279 )10.72236842105260.0577293176436285185.735235729675
Trimmed Mean ( 40 / 279 )10.72163588390500.0576077840105358186.114360551417
Trimmed Mean ( 41 / 279 )10.72089947089950.0574842819565698186.50140709767
Trimmed Mean ( 42 / 279 )10.72015915119360.0573587764792061186.896579899677
Trimmed Mean ( 43 / 279 )10.71941489361700.0572312317297468187.300090695854
Trimmed Mean ( 44 / 279 )10.71866666666670.0571016109856344187.712158757890
Trimmed Mean ( 45 / 279 )10.71791443850270.0569698766215824188.133011234964
Trimmed Mean ( 46 / 279 )10.71715817694370.0568359900794615188.562883517296
Trimmed Mean ( 47 / 279 )10.71639784946240.0566999118368741189.002019620304
Trimmed Mean ( 48 / 279 )10.71563342318060.0565616013743441189.450672590772
Trimmed Mean ( 49 / 279 )10.71486486486490.0564210171410475189.909104936528
Trimmed Mean ( 50 / 279 )10.71409214092140.0562781165190016190.377589081254
Trimmed Mean ( 51 / 279 )10.71331521739130.0561328557856247190.856407846168
Trimmed Mean ( 52 / 279 )10.71253405994550.0559851900745768191.345854960491
Trimmed Mean ( 53 / 279 )10.71253405994550.055835073334778191.860302496871
Trimmed Mean ( 54 / 279 )10.71095890410960.055682458287502192.357866975023
Trimmed Mean ( 55 / 279 )10.71016483516480.0555272963814296192.88107891287
Trimmed Mean ( 56 / 279 )10.70936639118460.0553695377455396193.416214533004
Trimmed Mean ( 57 / 279 )10.70856353591160.05520913113971193.963630922083
Trimmed Mean ( 58 / 279 )10.70856353591160.0550460239028853194.538365837361
Trimmed Mean ( 59 / 279 )10.70694444444440.0548801618986636195.096808646718
Trimmed Mean ( 60 / 279 )10.70612813370470.0547114894581394195.683360839521
Trimmed Mean ( 61 / 279 )10.70530726256980.0545399493198303196.283777232581
Trimmed Mean ( 62 / 279 )10.70530726256980.0543654825664989196.913680467662
Trimmed Mean ( 63 / 279 )10.70365168539330.0541880285586708197.527977490529
Trimmed Mean ( 64 / 279 )10.70281690140850.0540075248646296198.172697753418
Trimmed Mean ( 65 / 279 )10.70197740112990.0538239071866554198.833157243986
Trimmed Mean ( 66 / 279 )10.70113314447590.0536371092832538199.509878281545
Trimmed Mean ( 67 / 279 )10.70028409090910.0534470628871009200.203407126634
Trimmed Mean ( 68 / 279 )10.69943019943020.0532536976184079200.914315398294
Trimmed Mean ( 69 / 279 )10.70.0531647140301077201.261310160354
Trimmed Mean ( 70 / 279 )10.70057306590260.0530741084318233201.615691380818
Trimmed Mean ( 71 / 279 )10.70114942528740.0529818513660543201.977642331760
Trimmed Mean ( 72 / 279 )10.70172910662820.0528879126742903202.347352457162
Trimmed Mean ( 73 / 279 )10.70231213872830.0527922614749586202.725017639277
Trimmed Mean ( 74 / 279 )10.70289855072460.0526948661404775203.110840479073
Trimmed Mean ( 75 / 279 )10.70348837209300.0525956942733702203.505030591683
Trimmed Mean ( 76 / 279 )10.70408163265310.0524947126813927203.907804917794
Trimmed Mean ( 77 / 279 )10.70467836257310.0523918873516225204.319388052005
Trimmed Mean ( 78 / 279 )10.70527859237540.0522871834234564204.740012589259
Trimmed Mean ( 79 / 279 )10.70588235294120.0521805651604585205.169919490521
Trimmed Mean ( 80 / 279 )10.70648967551620.0520719959209982205.609358468988
Trimmed Mean ( 81 / 279 )10.70710059171600.0519614381276119206.058588398197
Trimmed Mean ( 82 / 279 )10.70771513353120.0518488532350211206.517877743508
Trimmed Mean ( 83 / 279 )10.70833333333330.0517342016967317206.987505018558
Trimmed Mean ( 84 / 279 )10.70895522388060.0516174429301362207.467759268414
Trimmed Mean ( 85 / 279 )10.70958083832340.0514985352800352207.958940581271
Trimmed Mean ( 86 / 279 )10.71021021021020.0513774359804887208.461360630717
Trimmed Mean ( 87 / 279 )10.71084337349400.0512541011149004208.975343250731
Trimmed Mean ( 88 / 279 )10.71148036253780.0511284855742342209.501225045784
Trimmed Mean ( 89 / 279 )10.71212121212120.0510005430132527210.039356038574
Trimmed Mean ( 90 / 279 )10.71276595744680.0508702258046599210.590100358184
Trimmed Mean ( 91 / 279 )10.71341463414630.050737484991023211.153836971657
Trimmed Mean ( 92 / 279 )10.71406727828750.0506022702343386211.730960462262
Trimmed Mean ( 93 / 279 )10.71472392638040.0504645297630987212.321881858004
Trimmed Mean ( 94 / 279 )10.71538461538460.0503242103166996212.927029514238
Trimmed Mean ( 95 / 279 )10.71759259259260.0502659423460818213.217779123722
Trimmed Mean ( 96 / 279 )10.71981424148610.0502062460373649213.515550107213
Trimmed Mean ( 97 / 279 )10.7220496894410.0501450928049186213.820517416398
Trimmed Mean ( 98 / 279 )10.72429906542060.050082453351811214.132861864539
Trimmed Mean ( 99 / 279 )10.72656250.0500182976471684214.452770377467
Trimmed Mean ( 100 / 279 )10.72884012539180.0499525949026256214.780436257735
Trimmed Mean ( 101 / 279 )10.73113207547170.0498853135478191215.116059462772
Trimmed Mean ( 102 / 279 )10.73343848580440.0498164212048775215.459846897904
Trimmed Mean ( 103 / 279 )10.73575949367090.049745884661857215.812012725197
Trimmed Mean ( 104 / 279 )10.73809523809520.0496736698450682216.172778689138
Trimmed Mean ( 105 / 279 )10.74044585987260.0495997417902373216.542374460237
Trimmed Mean ( 106 / 279 )10.74044585987260.0495240646124409216.873270478177
Trimmed Mean ( 107 / 279 )10.74281150159740.049446601474749217.260866898678
Trimmed Mean ( 108 / 279 )10.74758842443730.0493673145555085217.706563972661
Trimmed Mean ( 109 / 279 )10.750.0492861650141928218.113947329932
Trimmed Mean ( 110 / 279 )10.75242718446600.0492031129557411218.531441174017
Trimmed Mean ( 111 / 279 )10.75487012987010.0491181173933025218.959331111021
Trimmed Mean ( 112 / 279 )10.75732899022800.0490311362092982219.397913691178
Trimmed Mean ( 113 / 279 )10.75980392156860.0489421261147055219.847496946718
Trimmed Mean ( 114 / 279 )10.76229508196720.0488510426064642220.308400962216
Trimmed Mean ( 115 / 279 )10.76229508196720.0487578399228965220.72952983533
Trimmed Mean ( 116 / 279 )10.76480263157890.0486624709970255221.213645978581
Trimmed Mean ( 117 / 279 )10.76986754966890.048564887407669221.762432171688
Trimmed Mean ( 118 / 279 )10.77242524916940.048465039328176222.272083103556
Trimmed Mean ( 119 / 279 )10.7750.0483628754726641222.794858549928
Trimmed Mean ( 120 / 279 )10.77759197324410.048258343039607223.331165025676
Trimmed Mean ( 121 / 279 )10.78020134228190.0481513876526066223.881426222995
Trimmed Mean ( 122 / 279 )10.78282828282830.048041953298177224.446083944664
Trimmed Mean ( 123 / 279 )10.78547297297300.0479299822603496225.025599099696
Trimmed Mean ( 124 / 279 )10.78547297297300.0478154150518978225.564767371917
Trimmed Mean ( 125 / 279 )10.78813559322030.0476981903419616226.174945336022
Trimmed Mean ( 126 / 279 )10.79351535836180.047578244879837226.858207687605
Trimmed Mean ( 127 / 279 )10.79623287671230.0474555134146751227.502182567763
Trimmed Mean ( 128 / 279 )10.79896907216490.0473299286108167228.163645902837
Trimmed Mean ( 129 / 279 )10.80172413793100.0472014209584636228.8431983316
Trimmed Mean ( 130 / 279 )10.80449826989620.0470699186793664229.54146879868
Trimmed Mean ( 131 / 279 )10.80729166666670.0469353476271782230.259116274418
Trimmed Mean ( 132 / 279 )10.81010452961670.0467976311820968230.996831603568
Trimmed Mean ( 133 / 279 )10.81118881118880.0468081679988257230.967997112385
Trimmed Mean ( 134 / 279 )10.81228070175440.0468182291682981230.941684335974
Trimmed Mean ( 135 / 279 )10.81338028169010.0468278037147278230.917946687498
Trimmed Mean ( 136 / 279 )10.81448763250880.0468368804008998230.896838985482
Trimmed Mean ( 137 / 279 )10.81560283687940.0468454477208958230.878417500000
Trimmed Mean ( 138 / 279 )10.81672597864770.0468534938925803230.862740000712
Trimmed Mean ( 139 / 279 )10.81785714285710.0468610068498378230.849865806812
Trimmed Mean ( 140 / 279 )10.81899641577060.0468679742345521230.839855839014
Trimmed Mean ( 141 / 279 )10.82014388489210.0468743833883167230.832772673634
Trimmed Mean ( 142 / 279 )10.82129963898920.0468802213438657230.828680598906
Trimmed Mean ( 143 / 279 )10.82246376811590.0468854748162152230.827645673603
Trimmed Mean ( 144 / 279 )10.82363636363640.0468901301935023230.829735788113
Trimmed Mean ( 145 / 279 )10.82481751824820.04689417352751230.835020728063
Trimmed Mean ( 146 / 279 )10.82600732600730.0468975905238663230.843572240624
Trimmed Mean ( 147 / 279 )10.82720588235290.046900366531902230.855464103637
Trimmed Mean ( 148 / 279 )10.82841328413280.0469024865341557230.870772197702
Trimmed Mean ( 149 / 279 )10.82962962962960.0469039351355093230.889574581364
Trimmed Mean ( 150 / 279 )10.83085501858740.0469046965519405230.911951569576
Trimmed Mean ( 151 / 279 )10.83208955223880.0469047545988747230.937985815593
Trimmed Mean ( 152 / 279 )10.83333333333330.0469040926791198230.967762396478
Trimmed Mean ( 153 / 279 )10.83458646616540.0469026937703676231.001368902409
Trimmed Mean ( 154 / 279 )10.83584905660380.0469005404122411231.038895529988
Trimmed Mean ( 155 / 279 )10.83712121212120.0468976146928693231.080435179766
Trimmed Mean ( 156 / 279 )10.83840304182510.0468938982349695231.126083558196
Trimmed Mean ( 157 / 279 )10.83969465648860.0468893721814144231.175939284278
Trimmed Mean ( 158 / 279 )10.84099616858240.0468840171802622231.230104001121
Trimmed Mean ( 159 / 279 )10.84230769230770.0468778133692256231.288682492718
Trimmed Mean ( 160 / 279 )10.84362934362930.0468707403595542231.351782806199
Trimmed Mean ( 161 / 279 )10.84496124031010.0468627772193057231.419516379886
Trimmed Mean ( 162 / 279 )10.84630350194550.0468539024559749231.491998177462
Trimmed Mean ( 163 / 279 )10.847656250.0468440939984549231.569346828605
Trimmed Mean ( 164 / 279 )10.84901960784310.0468333291782971231.651684776462
Trimmed Mean ( 165 / 279 )10.85039370078740.0468215847102381231.73913843234
Trimmed Mean ( 166 / 279 )10.85177865612650.0468088366719604231.831838338058
Trimmed Mean ( 167 / 279 )10.85317460317460.0467950604830489231.929919336381
Trimmed Mean ( 168 / 279 )10.85458167330680.046780230883106232.033520750039
Trimmed Mean ( 169 / 279 )10.8560.0467643219089854232.142786569821
Trimmed Mean ( 170 / 279 )10.85742971887550.0467473068711007232.257865652312
Trimmed Mean ( 171 / 279 )10.85887096774190.0467291583287647232.378911927836
Trimmed Mean ( 172 / 279 )10.86032388663970.0467098480645116232.506084619250
Trimmed Mean ( 173 / 279 )10.86178861788620.0466893470573515232.639548472245
Trimmed Mean ( 174 / 279 )10.86326530612240.0466676254549031232.779473997881
Trimmed Mean ( 175 / 279 )10.86475409836070.0466446525443498232.926037728128
Trimmed Mean ( 176 / 279 )10.86625514403290.0466203967221573233.079422485234
Trimmed Mean ( 177 / 279 )10.86776859504130.04659482546249233.239817665808
Trimmed Mean ( 178 / 279 )10.86929460580910.0465679052842589233.407419540583
Trimmed Mean ( 179 / 279 )10.87083333333330.0465396017167288233.582431570869
Trimmed Mean ( 180 / 279 )10.87238493723850.0465098792636091233.765064742824
Trimmed Mean ( 181 / 279 )10.87394957983190.0464787013655467233.955537920698
Trimmed Mean ( 182 / 279 )10.87552742616030.0464460303609358234.154078220372
Trimmed Mean ( 183 / 279 )10.87711864406780.0464118274449528234.360921404543
Trimmed Mean ( 184 / 279 )10.87872340425530.0463760526267178234.576312301059
Trimmed Mean ( 185 / 279 )10.88034188034190.0463386646844801234.800505246021
Trimmed Mean ( 186 / 279 )10.88197424892700.0462996211187166235.033764553378
Trimmed Mean ( 187 / 279 )10.88362068965520.0462588781030240235.276365012919
Trimmed Mean ( 188 / 279 )10.88528138528140.0462163904326798235.528592418683
Trimmed Mean ( 189 / 279 )10.88695652173910.046172111470737235.790744130016
Trimmed Mean ( 190 / 279 )10.88864628820960.0461259930915072236.06312966765
Trimmed Mean ( 191 / 279 )10.89035087719300.0460779856212794236.346071347435
Trimmed Mean ( 192 / 279 )10.89207048458150.0460280377761085236.639904954523
Trimmed Mean ( 193 / 279 )10.89380530973450.0459760965964965236.9449804611
Trimmed Mean ( 194 / 279 )10.89555555555560.0459221073787773237.261662791000
Trimmed Mean ( 195 / 279 )10.89732142857140.0458660136029994237.590332634855
Trimmed Mean ( 196 / 279 )10.89910313901350.0458077568570909237.931387319751
Trimmed Mean ( 197 / 279 )10.90090090090090.045747276757068238.285241737733
Trimmed Mean ( 198 / 279 )10.90271493212670.0456845108630365238.652329337910
Trimmed Mean ( 199 / 279 )10.90454545454550.0456193945907121239.033103187335
Trimmed Mean ( 200 / 279 )10.90639269406390.0455518611181662239.428037106357
Trimmed Mean ( 201 / 279 )10.90596330275230.045644672468009238.931790131607
Trimmed Mean ( 202 / 279 )10.90552995391700.0457380318946705238.434613431362
Trimmed Mean ( 203 / 279 )10.90509259259260.045831944499353237.936502841299
Trimmed Mean ( 204 / 279 )10.90465116279070.0459264154432504237.437454187235
Trimmed Mean ( 205 / 279 )10.90420560747660.0460214499482593236.937463285836
Trimmed Mean ( 206 / 279 )10.90375586854460.046117053297694236.436525945378
Trimmed Mean ( 207 / 279 )10.90330188679250.0462132308370027235.934637966542
Trimmed Mean ( 208 / 279 )10.90284360189570.0463099879744852235.431795143258
Trimmed Mean ( 209 / 279 )10.90238095238100.0464073301820114234.927993263594
Trimmed Mean ( 210 / 279 )10.90191387559810.0465052629957400234.423228110692
Trimmed Mean ( 211 / 279 )10.90144230769230.0466037920168371233.917495463756
Trimmed Mean ( 212 / 279 )10.90144230769230.046702922912193233.420985838259
Trimmed Mean ( 213 / 279 )10.90048543689320.0468026614151376232.903110791208
Trimmed Mean ( 214 / 279 )10.90048543689320.046903013326153232.404800115798
Trimmed Mean ( 215 / 279 )10.89950980392160.0470039845135825231.884805441802
Trimmed Mean ( 216 / 279 )10.89901477832510.047105580914335231.374171951001
Trimmed Mean ( 217 / 279 )10.89851485148510.0472078085345836230.862545621051
Trimmed Mean ( 218 / 279 )10.89800995024880.0473106734504588230.349922236059
Trimmed Mean ( 219 / 279 )10.89750.0474141818087319229.836297586245
Trimmed Mean ( 220 / 279 )10.89698492462310.0475183398274912229.32166746951
Trimmed Mean ( 221 / 279 )10.89698492462310.0476231537968071228.816952592369
Trimmed Mean ( 222 / 279 )10.89593908629440.0477286300793852228.289374075301
Trimmed Mean ( 223 / 279 )10.89593908629440.0478347751112065227.782801548946
Trimmed Mean ( 224 / 279 )10.89487179487180.0479415954021523227.253008655250
Trimmed Mean ( 225 / 279 )10.89432989690720.0480490975366128226.73328856189
Trimmed Mean ( 226 / 279 )10.89378238341970.0481572881740765226.212538049098
Trimmed Mean ( 227 / 279 )10.89322916666670.0482661740496999225.690753019907
Trimmed Mean ( 228 / 279 )10.89267015706810.048375761974853225.167929400892
Trimmed Mean ( 229 / 279 )10.89210526315790.0484860588376415224.644063144641
Trimmed Mean ( 230 / 279 )10.89210526315790.0485970716033997224.130897269866
Trimmed Mean ( 231 / 279 )10.89095744680850.0487088073151549223.593186676529
Trimmed Mean ( 232 / 279 )10.89095744680850.0488212730940572223.078112400437
Trimmed Mean ( 233 / 279 )10.88978494623660.0489344761397748222.538091858414
Trimmed Mean ( 234 / 279 )10.88918918918920.0490484237308488222.008952804338
Trimmed Mean ( 235 / 279 )10.88858695652170.0491631232250065221.478747529680
Trimmed Mean ( 236 / 279 )10.88797814207650.049278582059427220.947472249633
Trimmed Mean ( 237 / 279 )10.88736263736260.0493948077509583220.415123230263
Trimmed Mean ( 238 / 279 )10.88674033149170.0495118078962779219.881696792375
Trimmed Mean ( 239 / 279 )10.88674033149170.0496295901719964219.359867646753
Trimmed Mean ( 240 / 279 )10.88547486033520.0497481623346959218.811597242524
Trimmed Mean ( 241 / 279 )10.88547486033520.0498675322209218.287819259141
Trimmed Mean ( 242 / 279 )10.88418079096050.0499877077469699217.737145420921
Trimmed Mean ( 243 / 279 )10.88352272727270.0501086969089191217.198278914643
Trimmed Mean ( 244 / 279 )10.88285714285710.050230507782143216.658314306869
Trimmed Mean ( 245 / 279 )10.88218390804600.0503531485210542216.117248427788
Trimmed Mean ( 246 / 279 )10.88150289017340.0504766273586181215.575078201328
Trimmed Mean ( 247 / 279 )10.88081395348840.0506009526057798215.03180065123
Trimmed Mean ( 248 / 279 )10.88081395348840.0507261326507756214.501153249695
Trimmed Mean ( 249 / 279 )10.87941176470590.0508521759583189213.941912212827
Trimmed Mean ( 250 / 279 )10.87941176470590.0509790910686522213.409292646173
Trimmed Mean ( 251 / 279 )10.87797619047620.0511068865964542212.847561550167
Trimmed Mean ( 252 / 279 )10.87724550898200.0512355712295927212.298706698122
Trimmed Mean ( 253 / 279 )10.87650602409640.0513651537277098211.74872914337
Trimmed Mean ( 254 / 279 )10.87575757575760.0514956429206295211.197626807387
Trimmed Mean ( 255 / 279 )10.8750.0516270477065723210.645397773066
Trimmed Mean ( 256 / 279 )10.87423312883440.0517593770501648210.092040294363
Trimmed Mean ( 257 / 279 )10.87345679012350.0518926399802272209.537552806460
Trimmed Mean ( 258 / 279 )10.87267080745340.0520268455873243208.981933936476
Trimmed Mean ( 259 / 279 )10.8718750.052162003021062208.425182514754
Trimmed Mean ( 260 / 279 )10.87106918238990.0522981214871105207.867297586764
Trimmed Mean ( 261 / 279 )10.87025316455700.0524352102439349207.308278425647
Trimmed Mean ( 262 / 279 )10.86942675159240.0525732785992118206.748124545448
Trimmed Mean ( 263 / 279 )10.86858974358970.052712335905909206.186835715079
Trimmed Mean ( 264 / 279 )10.86774193548390.0528523915580038205.624411973049
Trimmed Mean ( 265 / 279 )10.86688311688310.0529934549858138205.060853643005
Trimmed Mean ( 266 / 279 )10.86601307189540.0531355356509124204.496161350146
Trimmed Mean ( 267 / 279 )10.86513157894740.053278643040598203.930336038555
Trimmed Mean ( 268 / 279 )10.86423841059600.0534227866618854203.363378989497
Trimmed Mean ( 269 / 279 )10.86333333333330.0535679760349836202.79529184076
Trimmed Mean ( 270 / 279 )10.86241610738260.053714220686224202.226076607091
Trimmed Mean ( 271 / 279 )10.86148648648650.0538615301403969201.655735701801
Trimmed Mean ( 272 / 279 )10.86054421768710.0540099139124554201.084271959606
Trimmed Mean ( 273 / 279 )10.85958904109590.0541593814985376200.511688660793
Trimmed Mean ( 274 / 279 )10.85862068965520.0543099423662605199.937989556788
Trimmed Mean ( 275 / 279 )10.85763888888890.0544616059442278199.363178897218
Trimmed Mean ( 276 / 279 )10.85664335664340.0546143816106976198.787261458561
Trimmed Mean ( 277 / 279 )10.85563380281690.0547682786813451198.210242574494
Trimmed Mean ( 278 / 279 )10.85460992907800.0549233063960543197.632128168049
Trimmed Mean ( 279 / 279 )10.85357142857140.0550794739046662197.052924785688
Median10
Midrange15
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 observations838
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t125060189848lkkwn6b01iq8e/10ilv1250601687.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t125060189848lkkwn6b01iq8e/10ilv1250601687.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t125060189848lkkwn6b01iq8e/2lnry1250601687.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Aug/18/t125060189848lkkwn6b01iq8e/2lnry1250601687.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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