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opgave5_oef1_hanne jacobs

*Unverified author*
R Software Module: rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Wed, 15 Jul 2009 10:28:25 -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/Jul/15/t1247675415c23clgyk1zn9l6s.htm/, Retrieved Wed, 15 Jul 2009 18:30:18 +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/Jul/15/t1247675415c23clgyk1zn9l6s.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 «
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 10 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10.76941457586620.0725840296821353148.371682077012
Geometric Mean10.5663819406343
Harmonic Mean10.3567321694176
Quadratic Mean10.9719965041889
Winsorized Mean ( 1 / 279 )10.76105137395460.0703413748840857152.983239120469
Winsorized Mean ( 2 / 279 )10.75627240143370.0696684019152861154.392408979222
Winsorized Mean ( 3 / 279 )10.75985663082440.0693440685232769155.166214788978
Winsorized Mean ( 4 / 279 )10.75507765830350.0687859928160697156.355636053143
Winsorized Mean ( 5 / 279 )10.75507765830350.0687859928160697156.355636053143
Winsorized Mean ( 6 / 279 )10.74790919952210.068065624490894157.905099378909
Winsorized Mean ( 7 / 279 )10.74790919952210.068065624490894157.905099378909
Winsorized Mean ( 8 / 279 )10.74790919952210.068065624490894157.905099378909
Winsorized Mean ( 9 / 279 )10.74790919952210.068065624490894157.905099378909
Winsorized Mean ( 10 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 11 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 12 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 13 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 14 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 15 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 16 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 17 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 18 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 19 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 20 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 21 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 22 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 23 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 24 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 25 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 26 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 27 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 28 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 29 / 279 )10.74790919952210.066148982558363162.480340344453
Winsorized Mean ( 30 / 279 )10.71206690561530.0636586227228541168.273620248613
Winsorized Mean ( 31 / 279 )10.71206690561530.0636586227228541168.273620248613
Winsorized Mean ( 32 / 279 )10.71206690561530.0636586227228541168.273620248613
Winsorized Mean ( 33 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 34 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 35 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 36 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 37 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 38 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 39 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 40 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 41 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 42 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 43 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 44 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 45 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 46 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 47 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 48 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 49 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 50 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 51 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 52 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 53 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 54 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 55 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 56 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 57 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 58 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 59 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 60 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 61 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 62 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 63 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 64 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 65 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 66 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 67 / 279 )10.75149342891280.0612175860364956175.627530012424
Winsorized Mean ( 68 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 69 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 70 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 71 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 72 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 73 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 74 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 75 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 76 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 77 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 78 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 79 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 80 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 81 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 82 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 83 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 84 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 85 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 86 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 87 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 88 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 89 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 90 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 91 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 92 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 93 / 279 )10.67025089605730.0566171140288477188.463348566665
Winsorized Mean ( 94 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 95 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 96 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 97 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 98 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 99 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 100 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 101 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 102 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 103 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 104 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 105 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 106 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 107 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 108 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 109 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 110 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 111 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 112 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 113 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 114 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 115 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 116 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 117 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 118 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 119 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 120 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 121 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 122 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 123 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 124 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 125 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 126 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 127 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 128 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 129 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 130 / 279 )10.5579450418160.0519500164306235203.232756546200
Winsorized Mean ( 131 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 132 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 133 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 134 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 135 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 136 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 137 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 138 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 139 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 140 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 141 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 142 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 143 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 144 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 145 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 146 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 147 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 148 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 149 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 150 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 151 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 152 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 153 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 154 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 155 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 156 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 157 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 158 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 159 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 160 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 161 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 162 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 163 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 164 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 165 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 166 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 167 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 168 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 169 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 170 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 171 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 172 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 173 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 174 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 175 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 176 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 177 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 178 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 179 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 180 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 181 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 182 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 183 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 184 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 185 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 186 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 187 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 188 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 189 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 190 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 191 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 192 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 193 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 194 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 195 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 196 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 197 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 198 / 279 )10.71445639187570.0435769269858958245.874528861193
Winsorized Mean ( 199 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 200 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 201 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 202 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 203 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 204 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 205 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 206 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 207 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 208 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 209 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 210 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 211 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 212 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 213 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 214 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 215 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 216 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 217 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 218 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 219 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 220 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 221 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 222 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 223 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 224 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 225 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 226 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 227 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 228 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 229 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 230 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 231 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 232 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 233 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 234 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 235 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 236 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 237 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 238 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 239 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 240 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 241 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 242 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 243 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 244 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 245 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 246 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 247 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 248 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 249 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 250 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 251 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 252 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 253 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 254 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 255 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 256 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 257 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 258 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 259 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 260 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 261 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 262 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 263 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 264 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 265 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 266 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 267 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 268 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 269 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 270 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 271 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 272 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 273 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 274 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 275 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 276 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 277 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 278 / 279 )10.95221027479090.0337722219301327324.296408375162
Winsorized Mean ( 279 / 279 )10.95221027479090.0337722219301327324.296408375162
Trimmed Mean ( 1 / 279 )10.76941457586620.0692921451244013155.420424011
Trimmed Mean ( 2 / 279 )10.75688622754490.068215724290033157.689247449896
Trimmed Mean ( 3 / 279 )10.75090252707580.067466210321814159.352399902025
Trimmed Mean ( 4 / 279 )10.75090252707580.0668149781828751160.905575657754
Trimmed Mean ( 5 / 279 )10.74607013301090.0662996698747524162.083312832650
Trimmed Mean ( 6 / 279 )10.74424242424240.0657747986821822163.348921463943
Trimmed Mean ( 7 / 279 )10.74362089914950.0653703799742395164.349983943541
Trimmed Mean ( 8 / 279 )10.74362089914950.0649590555650062165.390657325645
Trimmed Mean ( 9 / 279 )10.74236874236870.0645406432554984166.443471904095
Trimmed Mean ( 10 / 279 )10.74173806609550.0641149531084717167.538733872616
Trimmed Mean ( 11 / 279 )10.74110429447850.0638944640331339168.106962896011
Trimmed Mean ( 12 / 279 )10.74046740467400.0636706274316193168.687946670685
Trimmed Mean ( 13 / 279 )10.73982737361280.0634433774974872169.282087386319
Trimmed Mean ( 14 / 279 )10.73918417799750.0632126465185925169.889804800988
Trimmed Mean ( 15 / 279 )10.73853779429990.0629783647990811170.511537232808
Trimmed Mean ( 16 / 279 )10.73853779429990.0627404605771529171.15809631481
Trimmed Mean ( 17 / 279 )10.73723536737240.0624988599383052171.798899659473
Trimmed Mean ( 18 / 279 )10.73657927590510.0622534867237442172.465509017185
Trimmed Mean ( 19 / 279 )10.73591989987480.0620042624336263173.148094638934
Trimmed Mean ( 20 / 279 )10.73525721455460.0617511061247649173.84720514746
Trimmed Mean ( 21 / 279 )10.73459119496860.0614939343024017174.563415347281
Trimmed Mean ( 22 / 279 )10.73392181588900.0612326608056141175.297327842152
Trimmed Mean ( 23 / 279 )10.73324905183310.0609671966858858176.04957477597
Trimmed Mean ( 24 / 279 )10.73257287705960.0606974500783304176.820819708392
Trimmed Mean ( 25 / 279 )10.73189326556540.0604233260650084177.611759637647
Trimmed Mean ( 26 / 279 )10.73121019108280.0601447265297289178.423127184367
Trimmed Mean ( 27 / 279 )10.73052362707540.05986155000367179.255692951778
Trimmed Mean ( 28 / 279 )10.72983354673500.0595736915010874180.110268079310
Trimmed Mean ( 29 / 279 )10.72913992297820.0592810423443135180.987707008619
Trimmed Mean ( 30 / 279 )10.72844272844270.0589834899771689181.888910483178
Trimmed Mean ( 31 / 279 )10.72903225806450.0587879689787523182.503876974255
Trimmed Mean ( 32 / 279 )10.72903225806450.0585893521259518183.122561843659
Trimmed Mean ( 33 / 279 )10.73022049286640.0583875775000159183.775743956212
Trimmed Mean ( 34 / 279 )10.72951885565670.0582765092115759184.113959480699
Trimmed Mean ( 35 / 279 )10.72881355932200.058163654573688184.45906877687
Trimmed Mean ( 36 / 279 )10.72810457516340.0580489828708148184.811241207073
Trimmed Mean ( 37 / 279 )10.72739187418090.0579324626773996185.170651797024
Trimmed Mean ( 38 / 279 )10.72667542706960.0578140618358105185.537481478692
Trimmed Mean ( 39 / 279 )10.72595520421610.0576937474333937185.911917345965
Trimmed Mean ( 40 / 279 )10.72523117569350.0575714857785917186.294152923907
Trimmed Mean ( 41 / 279 )10.72450331125830.0574472423760782186.684388452458
Trimmed Mean ( 42 / 279 )10.72377158034530.0573209819008592187.082831185496
Trimmed Mean ( 43 / 279 )10.72303595206390.0571926681712866187.489695706265
Trimmed Mean ( 44 / 279 )10.72229639519360.0570622641209276187.905204260221
Trimmed Mean ( 45 / 279 )10.72155287817940.0569297317692283188.329587106444
Trimmed Mean ( 46 / 279 )10.72080536912750.0567950321909075188.763082888856
Trimmed Mean ( 47 / 279 )10.72005383580080.0566581254840115189.205939028568
Trimmed Mean ( 48 / 279 )10.71929824561400.0565189707365572189.658412138787
Trimmed Mean ( 49 / 279 )10.71853856562920.0563775259916845190.120768463841
Trimmed Mean ( 50 / 279 )10.71777476255090.0562337482112346190.593284343967
Trimmed Mean ( 51 / 279 )10.71700680272110.0560875932376667191.076246707692
Trimmed Mean ( 52 / 279 )10.71623465211460.0559390157542152191.569953593742
Trimmed Mean ( 53 / 279 )10.71545827633380.0557879692431887192.074714704588
Trimmed Mean ( 54 / 279 )10.71467764060360.0556344059422995192.590851993929
Trimmed Mean ( 55 / 279 )10.71389270976620.0554782767989084193.118700290579
Trimmed Mean ( 56 / 279 )10.71310344827590.0553195314220601193.658607961450
Trimmed Mean ( 57 / 279 )10.71230982019360.0551581180321744194.210937616563
Trimmed Mean ( 58 / 279 )10.71151178918170.0549939834082498194.776066859249
Trimmed Mean ( 59 / 279 )10.71070931849790.0548270728324263195.354389085009
Trimmed Mean ( 60 / 279 )10.70990237099020.0546573300317394195.946314332790
Trimmed Mean ( 61 / 279 )10.70909090909090.0544846971168889196.552270192787
Trimmed Mean ( 62 / 279 )10.70827489481070.0543091145178286197.172702775247
Trimmed Mean ( 63 / 279 )10.70745428973280.0541305209159717197.808077745164
Trimmed Mean ( 64 / 279 )10.70745428973280.0539488531727856198.474178041177
Trimmed Mean ( 65 / 279 )10.70579915134370.0537640462545382199.125621993900
Trimmed Mean ( 66 / 279 )10.70496453900710.0535760331529314199.808830721940
Trimmed Mean ( 67 / 279 )10.70412517780940.0533847448013432200.509063359615
Trimmed Mean ( 68 / 279 )10.70328102710410.0531901099863692201.226901577136
Trimmed Mean ( 69 / 279 )10.70386266094420.0531001198989746201.578879319082
Trimmed Mean ( 70 / 279 )10.70444763271160.053008489954859201.938361983662
Trimmed Mean ( 71 / 279 )10.70503597122300.0529151902743084202.305536760407
Trimmed Mean ( 72 / 279 )10.70562770562770.0528201902633242202.680597178030
Trimmed Mean ( 73 / 279 )10.70622286541240.0527234585910324203.063743379564
Trimmed Mean ( 74 / 279 )10.70682148040640.0526249631661706203.455182412159
Trimmed Mean ( 75 / 279 )10.70742358078600.0525246711126085203.855128532460
Trimmed Mean ( 76 / 279 )10.70802919708030.0524225487438493204.263803528566
Trimmed Mean ( 77 / 279 )10.70863836017570.0523185615364612204.681437059633
Trimmed Mean ( 78 / 279 )10.70925110132160.0522126741023829205.108267014289
Trimmed Mean ( 79 / 279 )10.70986745213550.052104850160042205.544539889084
Trimmed Mean ( 80 / 279 )10.71048744460860.0519950525042248205.990511188315
Trimmed Mean ( 81 / 279 )10.71111111111110.0518832429746279206.446445846669
Trimmed Mean ( 82 / 279 )10.71173848439820.0517693824230216206.912618676223
Trimmed Mean ( 83 / 279 )10.71236959761550.0516534306789476207.389314839480
Trimmed Mean ( 84 / 279 )10.71300448430490.0515353465138683207.876830350254
Trimmed Mean ( 85 / 279 )10.71364317841080.0514150876036821208.37547260434
Trimmed Mean ( 86 / 279 )10.71428571428570.0512926104895103208.885560942094
Trimmed Mean ( 87 / 279 )10.71493212669680.0511678705366559209.407427245205
Trimmed Mean ( 88 / 279 )10.71558245083210.0510408218916283209.941416570129
Trimmed Mean ( 89 / 279 )10.71623672230650.0509114174371187210.487887820886
Trimmed Mean ( 90 / 279 )10.71689497716900.0507796087448052211.047214464119
Trimmed Mean ( 91 / 279 )10.71755725190840.0506453460258552211.619785289589
Trimmed Mean ( 92 / 279 )10.71822358346090.0505085780789849212.206005219547
Trimmed Mean ( 93 / 279 )10.71889400921660.0503692522359245212.806296170735
Trimmed Mean ( 94 / 279 )10.71956856702620.0502273143041273213.421097973087
Trimmed Mean ( 95 / 279 )10.72179289026280.0501676223356567213.71937498904
Trimmed Mean ( 96 / 279 )10.72403100775190.0501064762419429214.024848923124
Trimmed Mean ( 97 / 279 )10.72628304821150.0500438468154011214.337700452525
Trimmed Mean ( 98 / 279 )10.72854914196570.0499797041174629214.658116357618
Trimmed Mean ( 99 / 279 )10.73082942097030.0499140174551407214.986289785518
Trimmed Mean ( 100 / 279 )10.73312401883830.0498467553566429215.322420527577
Trimmed Mean ( 101 / 279 )10.73543307086610.0497778855459904215.666715311713
Trimmed Mean ( 102 / 279 )10.73775671406000.0497073749165852216.019388110502
Trimmed Mean ( 103 / 279 )10.74009508716320.0496351895036758216.380660466056
Trimmed Mean ( 104 / 279 )10.74244833068360.0495612944556651216.750761832770
Trimmed Mean ( 105 / 279 )10.74244833068360.0494856540041977217.082072508780
Trimmed Mean ( 106 / 279 )10.74720.049408231432964217.518411169636
Trimmed Mean ( 107 / 279 )10.74959871589090.0493289890451528217.916460968850
Trimmed Mean ( 108 / 279 )10.75201288244770.0492478881294782218.324344267909
Trimmed Mean ( 109 / 279 )10.75201288244770.0491648889247056218.692915159719
Trimmed Mean ( 110 / 279 )10.75688816855750.0490799505825924219.170721259299
Trimmed Mean ( 111 / 279 )10.75934959349590.0489930311291563219.609796444967
Trimmed Mean ( 112 / 279 )10.76182707993470.0489040874241776220.059869159612
Trimmed Mean ( 113 / 279 )10.76182707993470.0488130751188348220.470172258872
Trimmed Mean ( 114 / 279 )10.76683087027910.0487199486113658220.994298581164
Trimmed Mean ( 115 / 279 )10.76935749588140.048624661000642221.479333207880
Trimmed Mean ( 116 / 279 )10.77190082644630.048527164037531221.976722524219
Trimmed Mean ( 117 / 279 )10.77190082644630.0484274080739172222.433973959634
Trimmed Mean ( 118 / 279 )10.77703826955070.0483253420092402223.010077559101
Trimmed Mean ( 119 / 279 )10.7796327212020.0482209132343992223.546838874718
Trimmed Mean ( 120 / 279 )10.78224455611390.0481140675728619224.097547765749
Trimmed Mean ( 121 / 279 )10.78487394957980.0480047492188038224.662645364999
Trimmed Mean ( 122 / 279 )10.7875210792580.0478929006720911225.242591863814
Trimmed Mean ( 123 / 279 )10.79018612521150.0477784626699044225.837867571412
Trimmed Mean ( 124 / 279 )10.79286926994910.0476613741147882226.448974046686
Trimmed Mean ( 125 / 279 )10.79557069846680.0475415719988906227.076435308422
Trimmed Mean ( 126 / 279 )10.79829059829060.0474189913241410227.720799130394
Trimmed Mean ( 127 / 279 )10.80102915951970.0472935650180936228.382638428451
Trimmed Mean ( 128 / 279 )10.80102915951970.0471652238451413229.004089856183
Trimmed Mean ( 129 / 279 )10.80656303972370.04703389631278229.761169856288
Trimmed Mean ( 130 / 279 )10.80935875216640.0468995085725779230.4791474614
Trimmed Mean ( 131 / 279 )10.81217391304350.046761984315475231.217175047582
Trimmed Mean ( 132 / 279 )10.81326352530540.04677244428707231.188762745390
Trimmed Mean ( 133 / 279 )10.81436077057790.0467824293677548231.162872829170
Trimmed Mean ( 134 / 279 )10.81546572934970.0467919286172335231.139558658123
Trimmed Mean ( 135 / 279 )10.81657848324520.0468009308349732231.118874993875
Trimmed Mean ( 136 / 279 )10.81769911504420.0468094245529717231.100878046523
Trimmed Mean ( 137 / 279 )10.81882770870340.046817398028287231.085625522518
Trimmed Mean ( 138 / 279 )10.81996434937610.0468248392353208231.073176674453
Trimmed Mean ( 139 / 279 )10.82110912343470.0468317358578444231.063592352880
Trimmed Mean ( 140 / 279 )10.82226211849190.0468380752807588231.056935060219
Trimmed Mean ( 141 / 279 )10.82342342342340.0468438445815769231.053269006877
Trimmed Mean ( 142 / 279 )10.82459312839060.0468490305216178231.052660169686
Trimmed Mean ( 143 / 279 )10.82577132486390.0468536195369017231.055176352759
Trimmed Mean ( 144 / 279 )10.82695810564660.046857597728733231.060887250896
Trimmed Mean ( 145 / 279 )10.82815356489950.0468609508539585231.069864515666
Trimmed Mean ( 146 / 279 )10.82935779816510.0468636643148891231.082181824278
Trimmed Mean ( 147 / 279 )10.83057090239410.0468657231488693231.097914951418
Trimmed Mean ( 148 / 279 )10.83179297597040.0468671120174813231.117141844161
Trimmed Mean ( 149 / 279 )10.83302411873840.046867815195368231.139942700146
Trimmed Mean ( 150 / 279 )10.83426443202980.046867816558659231.166400049164
Trimmed Mean ( 151 / 279 )10.83551401869160.0468670995729831231.196598838342
Trimmed Mean ( 152 / 279 )10.83677298311440.0468656472810493231.230626521112
Trimmed Mean ( 153 / 279 )10.83804143126180.0468634422897784231.268573150157
Trimmed Mean ( 154 / 279 )10.83931947069940.0468604667569657231.310531474555
Trimmed Mean ( 155 / 279 )10.84060721062620.0468567023774544231.356597041329
Trimmed Mean ( 156 / 279 )10.84190476190480.0468521303687981231.406868301662
Trimmed Mean ( 157 / 279 )10.84321223709370.0468467314563912231.461446722008
Trimmed Mean ( 158 / 279 )10.84452975047980.0468404858580411231.520436900382
Trimmed Mean ( 159 / 279 )10.84585741811180.0468333732679608231.583946688109
Trimmed Mean ( 160 / 279 )10.84719535783370.0468253728401524231.652087317333
Trimmed Mean ( 161 / 279 )10.84854368932040.0468164631711566231.724973534612
Trimmed Mean ( 162 / 279 )10.84990253411310.0468066222821372231.802723740946
Trimmed Mean ( 163 / 279 )10.85127201565560.046795827600272231.885460138598
Trimmed Mean ( 164 / 279 )10.85265225933200.046784055939416231.973308885102
Trimmed Mean ( 165 / 279 )10.85404339250490.0467712834800042232.066400254876
Trimmed Mean ( 166 / 279 )10.85544554455450.0467574857481582232.164868808885
Trimmed Mean ( 167 / 279 )10.85685884691850.0467426375939577232.268853572823
Trimmed Mean ( 168 / 279 )10.85828343313370.0467267131688379232.378498224333
Trimmed Mean ( 169 / 279 )10.85971943887780.0467096859020711232.493951289795
Trimmed Mean ( 170 / 279 )10.86116700201210.0466915284762851232.615366351275
Trimmed Mean ( 171 / 279 )10.86262626262630.0466722128019759232.742902264243
Trimmed Mean ( 172 / 279 )10.86409736308320.0466517099909597232.876723386741
Trimmed Mean ( 173 / 279 )10.86558044806520.0466299903287148233.016999820696
Trimmed Mean ( 174 / 279 )10.86707566462170.0466070232455564233.163907666164
Trimmed Mean ( 175 / 279 )10.86858316221770.0465827772865841233.317629289309
Trimmed Mean ( 176 / 279 )10.87010309278350.0465572200803406233.478353604998
Trimmed Mean ( 177 / 279 )10.87163561076600.0465303183061134233.646276374982
Trimmed Mean ( 178 / 279 )10.87318087318090.0465020376598096233.821600522642
Trimmed Mean ( 179 / 279 )10.87473903966600.0464723428183281234.004536465442
Trimmed Mean ( 180 / 279 )10.87631027253670.0464411974023494234.195302466221
Trimmed Mean ( 181 / 279 )10.87789473684210.0464085639374569234.39412500464
Trimmed Mean ( 182 / 279 )10.87949260042280.0463744038135013234.601239170118
Trimmed Mean ( 183 / 279 )10.88110403397030.0463386772421084234.816889077760
Trimmed Mean ( 184 / 279 )10.88272921108740.0463013432122312235.041328308864
Trimmed Mean ( 185 / 279 )10.88436830835120.0462623594436339235.274820377735
Trimmed Mean ( 186 / 279 )10.88602150537630.0462216823381919235.517639226677
Trimmed Mean ( 187 / 279 )10.88768898488120.0461792669288838235.770069751178
Trimmed Mean ( 188 / 279 )10.88937093275490.0461350668263407236.032408357489
Trimmed Mean ( 189 / 279 )10.89106753812640.0460890341628113236.304963554959
Trimmed Mean ( 190 / 279 )10.89277899343540.04604111953339236.588056585717
Trimmed Mean ( 191 / 279 )10.89450549450550.0459912719343449236.882022094497
Trimmed Mean ( 192 / 279 )10.89624724061810.0459394386983699237.187208841643
Trimmed Mean ( 193 / 279 )10.89800443458980.0458855654265754237.503980462623
Trimmed Mean ( 194 / 279 )10.89977728285080.045829595917014237.832716277655
Trimmed Mean ( 195 / 279 )10.90156599552570.0457714720895261238.173812155374
Trimmed Mean ( 196 / 279 )10.90337078651690.0457111339066735238.527681434852
Trimmed Mean ( 197 / 279 )10.90519187358920.0456485192905100238.894755910654
Trimmed Mean ( 198 / 279 )10.90702947845800.0455835640349199239.275486886075
Trimmed Mean ( 199 / 279 )10.90888382687930.0455162017132351239.670346300166
Trimmed Mean ( 200 / 279 )10.90846681922200.0456088647376101239.17426758984
Trimmed Mean ( 201 / 279 )10.90804597701150.0457020753593001238.677256804089
Trimmed Mean ( 202 / 279 )10.90762124711320.0457958386936467238.179309698424
Trimmed Mean ( 203 / 279 )10.90719257540600.0458901599167833237.680422016071
Trimmed Mean ( 204 / 279 )10.90675990675990.0459850442663814237.180589488604
Trimmed Mean ( 205 / 279 )10.90632318501170.0460804970424022236.679807836620
Trimmed Mean ( 206 / 279 )10.90588235294120.0461765236078504236.178072770447
Trimmed Mean ( 207 / 279 )10.90543735224590.0462731293895318235.675379990897
Trimmed Mean ( 208 / 279 )10.90498812351540.0463703198788135235.171725190059
Trimmed Mean ( 209 / 279 )10.90453460620530.0464681006323855234.667104052138
Trimmed Mean ( 210 / 279 )10.90453460620530.0465664772730249234.171344812506
Trimmed Mean ( 211 / 279 )10.90407673860910.04666545549036233.664851741598
Trimmed Mean ( 212 / 279 )10.90314769975790.0467650410416351233.147399358652
Trimmed Mean ( 213 / 279 )10.90267639902680.0468652397524751232.638869588861
Trimmed Mean ( 214 / 279 )10.90220048899760.0469660575176481232.129351817553
Trimmed Mean ( 215 / 279 )10.90171990171990.0470675003018269231.618841702047
Trimmed Mean ( 216 / 279 )10.90123456790120.0471695741403465231.107334899105
Trimmed Mean ( 217 / 279 )10.90074441687340.0472722851399592230.59482706621
Trimmed Mean ( 218 / 279 )10.90074441687340.0473756394795828230.091763121663
Trimmed Mean ( 219 / 279 )10.89974937343360.0474796434110447229.566790952311
Trimmed Mean ( 220 / 279 )10.89924433249370.0475843032598178229.051254002441
Trimmed Mean ( 221 / 279 )10.89873417721520.0476896254257479228.534698687965
Trimmed Mean ( 222 / 279 )10.89821882951650.0477956163837713228.017120691783
Trimmed Mean ( 223 / 279 )10.89769820971870.0479022826846221227.498515706791
Trimmed Mean ( 224 / 279 )10.89717223650390.0480096309555249226.978879437727
Trimmed Mean ( 225 / 279 )10.89664082687340.0481176679008742226.458207603104
Trimmed Mean ( 226 / 279 )10.89664082687340.0482264003028973225.947629481663
Trimmed Mean ( 227 / 279 )10.89556135770240.0483358350222986225.413740192467
Trimmed Mean ( 228 / 279 )10.89501312335960.0484459789988835224.889936141257
Trimmed Mean ( 229 / 279 )10.89445910290240.0485568392521601224.365079578727
Trimmed Mean ( 230 / 279 )10.89389920424400.0486684228819157223.839166325071
Trimmed Mean ( 231 / 279 )10.89333333333330.0487807370687659223.312192228196
Trimmed Mean ( 232 / 279 )10.89276139410190.0488937890746735222.784153166485
Trimmed Mean ( 233 / 279 )10.89276139410190.0490075862434343222.266841300743
Trimmed Mean ( 234 / 279 )10.89218328840970.0491221360011266221.736760147399
Trimmed Mean ( 235 / 279 )10.89100817438690.0492374458565212221.193605495369
Trimmed Mean ( 236 / 279 )10.89041095890410.0493535234014485220.661266072535
Trimmed Mean ( 237 / 279 )10.88980716253440.0494703763111182220.127841640998
Trimmed Mean ( 238 / 279 )10.88919667590030.0495880123443887219.593328328525
Trimmed Mean ( 239 / 279 )10.88857938718660.0497064393439801219.057722317125
Trimmed Mean ( 240 / 279 )10.88795518207280.0498256652366285218.521019847192
Trimmed Mean ( 241 / 279 )10.88795518207280.049945698033174217.995855715963
Trimmed Mean ( 242 / 279 )10.88668555240790.0500665458285793217.444310811503
Trimmed Mean ( 243 / 279 )10.88603988603990.0501882168018719216.904297058705
Trimmed Mean ( 244 / 279 )10.88538681948420.0503107192160037216.363172483164
Trimmed Mean ( 245 / 279 )10.88472622478390.050434061417623215.820933687099
Trimmed Mean ( 246 / 279 )10.88405797101450.0505582518367493215.277577360837
Trimmed Mean ( 247 / 279 )10.88338192419830.0506832989863467214.733100288718
Trimmed Mean ( 248 / 279 )10.88269794721410.0508092114617844214.187499355297
Trimmed Mean ( 249 / 279 )10.88269794721410.0509359979401786213.654358161298
Trimmed Mean ( 250 / 279 )10.88130563798220.0510636671796055213.092913983431
Trimmed Mean ( 251 / 279 )10.88059701492540.0511922280181747212.543923875758
Trimmed Mean ( 252 / 279 )10.87987987987990.0513216893729545211.993798583204
Trimmed Mean ( 253 / 279 )10.87915407854980.0514520602387361211.442535596648
Trimmed Mean ( 254 / 279 )10.87841945288750.0515833496866257210.890132551978
Trimmed Mean ( 255 / 279 )10.87767584097860.0517155668624508210.336587239007
Trimmed Mean ( 256 / 279 )10.87767584097860.0518487209849679209.796416080009
Trimmed Mean ( 257 / 279 )10.87616099071210.051982821343856209.226061793923
Trimmed Mean ( 258 / 279 )10.87538940809970.0521178772974802208.669078098188
Trimmed Mean ( 259 / 279 )10.87460815047020.0522538982704090208.110945028352
Trimmed Mean ( 260 / 279 )10.87381703470030.052390893750666207.551661295377
Trimmed Mean ( 261 / 279 )10.87301587301590.0525288732866977206.991225828736
Trimmed Mean ( 262 / 279 )10.87220447284340.0526678464840355206.429637789329
Trimmed Mean ( 263 / 279 )10.87138263665590.0528078230016305205.866896583112
Trimmed Mean ( 264 / 279 )10.87055016181230.0529488125478355205.303001875472
Trimmed Mean ( 265 / 279 )10.86970684039090.0530908248760099204.737953606416
Trimmed Mean ( 266 / 279 )10.86885245901640.0532338697797189204.171752006600
Trimmed Mean ( 267 / 279 )10.86798679867990.0533779570874975203.604397614262
Trimmed Mean ( 268 / 279 )10.86710963455150.0535230966571472203.035891293116
Trimmed Mean ( 269 / 279 )10.86622073578600.0536692983695306202.466234251256
Trimmed Mean ( 270 / 279 )10.86531986531990.0538165721218285201.895428061141
Trimmed Mean ( 271 / 279 )10.86440677966100.0539649278202177201.32347468073
Trimmed Mean ( 272 / 279 )10.86348122866890.0541143753719281200.75037647583
Trimmed Mean ( 273 / 279 )10.86254295532650.0542649246766331200.176136243749
Trimmed Mean ( 274 / 279 )10.86159169550170.0544165856171236199.600757238320
Trimmed Mean ( 275 / 279 )10.86062717770030.0545693680492123199.024243196401
Trimmed Mean ( 276 / 279 )10.85964912280700.0547232817908111198.446598365936
Trimmed Mean ( 277 / 279 )10.85865724381630.0548783366101204197.867827535679
Trimmed Mean ( 278 / 279 )10.85765124555160.0550345422128626197.287936066705
Trimmed Mean ( 279 / 279 )10.85663082437280.0551919082284898196.706929925800
Median10
Midrange16
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 observations837
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/15/t1247675415c23clgyk1zn9l6s/11ih01247675295.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/15/t1247675415c23clgyk1zn9l6s/11ih01247675295.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/15/t1247675415c23clgyk1zn9l6s/29zyc1247675295.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jul/15/t1247675415c23clgyk1zn9l6s/29zyc1247675295.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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