sven van roy - tweede zittijd - oefening 5 - gemidd vs mediaan zonder extremen

R Software Module: rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Mon, 11 Aug 2008 14:35:12 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Aug/11/t1218487080t60ldjzn3iluyoh.htm/, Retrieved Mon, 11 Aug 2008 20:38:00 +0000

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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8 10 10 13 14 12 11 8 8 10 10 12 12 12 11 12 12 12 12 12 12 10 12 10 11 10 10 12 10 12 7 12 18 12 11 13 10 10 10 8 12 10 10 8 14 9 8 12 15 14 9 7 8 12 12 10 10 8 8 16 14 13 10 12 9 12 11 10 8 8 9 12 8 12 10 12 9 8 12 8 12 10 12 9 10 12 9 14 12 12 13 13 14 12 12 10 11 12 14 10 12 12 6 12 10 12 12 12 9 12 12 13 8 12 10 10 10 9 12 9 10 8 12 10 8 8 9 12 12 10 10 9 11 10 9 15 10 8 10 8 9 9 6 16 12 12 12 12 10 12 8 9 12 12 8 14 10 12 8 11 10 12 12 12 12 8 10 7 10 10 12 11 9 10 12 14 13 10 11 10 10 8 10 10 10 8 8 4 14 8 12 12 10 8 12 12 10 10 12 12 9 11 14 10 8 12 8 10 11 12 10 10 12 8 9 12 8 8 10 10 10 14 10 12 12 13 9 12 12 10 12 6 8 12 10 9 11 11 9 10 15 12 7 7 10 9 10 10 9 12 10 9 12 10 7 12 10 10 12 8 12 10 10 9 8 8 12 12 10 12 10 9 10 10 8 10 12 12 16 10 9 12 12 10 7 12 10 10 6 9 6 18 13 10 12 15 12 12 9 7 12 13 14 13 12 8 8 10 10 8 12 10 12 12 12 9 12 7 12 8 8 12 14 10 5 9 8 13 10 10 14 10 10 12 17 14 8 14 12 12 10 10 8 12 12 12 10 12 10 10 12 12 12 12 13 12 8 10 12 8 10 10 12 12 12 12 12 12 14 10 12 14 12 14 12 13 8 12 14 10 10 11 16 12 10 10 8 11 12 12 11 10 20 9 14 12 10 12 10 12 12 8 12 12 10 12 10 10 10 12 12 12 12 9 12 14 8 12 10 10 10 7 8 10 1 10 10 9 15 10 12 12 12 11 12 12 14 8 12 12 10 14 8 10 12 10 10 10 12 9 12 11 8 14 12 10 12 10 8 14 12 12 12 8 12 12 10 12 12 12 9 11 10 15 10 9 9 10 7 10 9 10 10 10 15 12 12 10 12 8 12 11 8 14 8 12 10 15 9 13 12 14 12 12 17 10 13 12 12 10 12 10 12 10 10 10 8 12 10 10 10 12 12 11 12 8 8 12 12 10 12 9 10 12 12 12 12 10 10 9 12 10 9 12 7 14 10 10 9 10 8 10 12 12 10 9 10 9 12 10 12 10 9 7 12 11 12 9 13 12 12 7 8 12 12 12 11 12 13 10 12 10 12 12 15 12 12 13 10 10 8 11 12 12 12 12 10 10 12 15 12 10 10 7 12 10 11 10 10 10 10 11 7 15 8 10 6 8 9 8 7 10 12 14 11 8 10 8 8 14 12 15 12 12 9 12 12 9 11 15 11 12 7 15 9 10 15 15 8 11 12 10 10 12 7 12 10 11 12 10 10 8 9 8 10 10 14 10 10 12 12 7 12 10 12 9 9 13 14 10 12 12 12 12 12 10 10 8 12 8 14 10 12 10 8 8 11 10 8 7 8 9 12 12 7 10 8 10 10 10 8 12 7 13 13 8 8 11 6 12 9 12 13 13 12 12 10 8 12 10 10 15 12 10 12 8 8 12 12 10 12 9 12 12 10 9 10 10 10 12 12 12 12 8 10 12 15 10 8 15 10 9 12 10 10 11 11 12 12 14 12 14 9 10 12 13 10 11 10 12 12 12 13 14 9 10 10 12 12 10 8 12 12 10 12 10 12 12 12 10 12 12 10 10 12 12 12 9 12 12 9 12 12 12 15 12 12 12 8 8 12 8 12 12 10 10 12 8 8 10 10 5 9 9 9 10 12

Text written by user:

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 12 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 10.7371565113501 0.0705641439144953 152.161649184898 Geometric Mean 10.5243994412192 Harmonic Mean 10.2346156109618 Quadratic Mean 10.9292828409263 Winsorized Mean ( 1 / 279 ) 10.7383512544803 0.0697239637865222 154.012346276791 Winsorized Mean ( 2 / 279 ) 10.7407407407407 0.0694677113608881 154.614863946533 Winsorized Mean ( 3 / 279 ) 10.7371565113501 0.0690491770915141 155.500137201050 Winsorized Mean ( 4 / 279 ) 10.7419354838710 0.0686140320696918 156.555957430986 Winsorized Mean ( 5 / 279 ) 10.7359617682198 0.0680114191989477 157.855282166880 Winsorized Mean ( 6 / 279 ) 10.7359617682198 0.0680114191989477 157.855282166880 Winsorized Mean ( 7 / 279 ) 10.7359617682198 0.0680114191989477 157.855282166880 Winsorized Mean ( 8 / 279 ) 10.7359617682198 0.0680114191989477 157.855282166880 Winsorized Mean ( 9 / 279 ) 10.7252090800478 0.0671033835210845 159.831122027965 Winsorized Mean ( 10 / 279 ) 10.7252090800478 0.0671033835210845 159.831122027965 Winsorized Mean ( 11 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 12 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 13 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 14 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 15 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 16 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 17 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 18 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 19 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 20 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 21 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 22 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 23 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 24 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 25 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 26 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 27 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 28 / 279 ) 10.7383512544803 0.0661045712161869 162.444912007096 Winsorized Mean ( 29 / 279 ) 10.7037037037037 0.0636912831200708 168.056022415581 Winsorized Mean ( 30 / 279 ) 10.7037037037037 0.0636912831200708 168.056022415581 Winsorized Mean ( 31 / 279 ) 10.7037037037037 0.0636912831200708 168.056022415581 Winsorized Mean ( 32 / 279 ) 10.7037037037037 0.0636912831200708 168.056022415581 Winsorized Mean ( 33 / 279 ) 10.7037037037037 0.0636912831200708 168.056022415581 Winsorized Mean ( 34 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 35 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 36 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 37 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 38 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 39 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 40 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 41 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 42 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 43 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 44 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 45 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 46 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 47 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 48 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 49 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 50 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 51 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 52 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 53 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 54 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 55 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 56 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 57 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 58 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 59 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 60 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 61 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 62 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 63 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 64 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 65 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 66 / 279 ) 10.7443249701314 0.0611822656362415 175.611753804798 Winsorized Mean ( 67 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 68 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 69 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 70 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 71 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 72 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 73 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 74 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 75 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 76 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 77 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 78 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 79 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 80 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 81 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 82 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 83 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 84 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 85 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 86 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 87 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 88 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 89 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 90 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 91 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 92 / 279 ) 10.6642771804062 0.056638220332195 188.287646007555 Winsorized Mean ( 93 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 94 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 95 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 96 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 97 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 98 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 99 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 100 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 101 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 102 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 103 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 104 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 105 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 106 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 107 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 108 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 109 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 110 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 111 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 112 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 113 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 114 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 115 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 116 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 117 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 118 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 119 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 120 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 121 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 122 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 123 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 124 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 125 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 126 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 127 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 128 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 129 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 130 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 131 / 279 ) 10.5531660692951 0.0520111127093171 202.902139938349 Winsorized Mean ( 132 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 133 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 134 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 135 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 136 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 137 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 138 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 139 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 140 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 141 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 142 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 143 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 144 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 145 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 146 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 147 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 148 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 149 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 150 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 151 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 152 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 153 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 154 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 155 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 156 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 157 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 158 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 159 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 160 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 161 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 162 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 163 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 164 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 165 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 166 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 167 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 168 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 169 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 170 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 171 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 172 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 173 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 174 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 175 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 176 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 177 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 178 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 179 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 180 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 181 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 182 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 183 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 184 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 185 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 186 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 187 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 188 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 189 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 190 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 191 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 192 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 193 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 194 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 195 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 196 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 197 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 198 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 199 / 279 ) 10.7108721624851 0.0435978451342377 245.674347654255 Winsorized Mean ( 200 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 201 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 202 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 203 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 204 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 205 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 206 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 207 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 208 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 209 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 210 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 211 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 212 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 213 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 214 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 215 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 216 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 217 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 218 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 219 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 220 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 221 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 222 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 223 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 224 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 225 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 226 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 227 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 228 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 229 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 230 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 231 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 232 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 233 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 234 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 235 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 236 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 237 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 238 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 239 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 240 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 241 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 242 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 243 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 244 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 245 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 246 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 247 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 248 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 249 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 250 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 251 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 252 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 253 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 254 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 255 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 256 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 257 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 258 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 259 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 260 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 261 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 262 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 263 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 264 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 265 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 266 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 267 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 268 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 269 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 270 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 271 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 272 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 273 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 274 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 275 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 276 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 277 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 278 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Winsorized Mean ( 279 / 279 ) 10.9498207885305 0.0337680759837367 324.265462853261 Trimmed Mean ( 1 / 279 ) 10.7371565113501 0.0688755288654505 155.89218243718 Trimmed Mean ( 2 / 279 ) 10.7377245508982 0.068007774429253 157.889662483639 Trimmed Mean ( 3 / 279 ) 10.7352587244284 0.0672544182235119 159.621613092408 Trimmed Mean ( 4 / 279 ) 10.7352587244284 0.0666327469751335 161.110853323136 Trimmed Mean ( 5 / 279 ) 10.7327690447400 0.0661146803203772 162.335641535759 Trimmed Mean ( 6 / 279 ) 10.7321212121212 0.0657162182523671 163.310085356816 Trimmed Mean ( 7 / 279 ) 10.7314702308627 0.0653110056707398 164.313351488791 Trimmed Mean ( 8 / 279 ) 10.7314702308627 0.06489886684191 165.356819819427 Trimmed Mean ( 9 / 279 ) 10.7301587301587 0.0644796186865622 166.411634385098 Trimmed Mean ( 10 / 279 ) 10.7307221542228 0.064164673879406 167.237227362685 Trimmed Mean ( 11 / 279 ) 10.7312883435583 0.0638446565153866 168.084361781664 Trimmed Mean ( 12 / 279 ) 10.7306273062731 0.0636202745930752 168.666787040888 Trimmed Mean ( 13 / 279 ) 10.7299630086313 0.0633924690675358 169.262424487679 Trimmed Mean ( 14 / 279 ) 10.7292954264524 0.0631611719245189 169.871696479516 Trimmed Mean ( 15 / 279 ) 10.7286245353160 0.0629263131534033 170.495044086907 Trimmed Mean ( 16 / 279 ) 10.7286245353160 0.0626878206642579 171.143683440139 Trimmed Mean ( 17 / 279 ) 10.7272727272727 0.0624456202003368 171.785830501126 Trimmed Mean ( 18 / 279 ) 10.7265917602996 0.0621996352456882 172.454255043935 Trimmed Mean ( 19 / 279 ) 10.7259073842303 0.061949786927538 173.138729222366 Trimmed Mean ( 20 / 279 ) 10.7252195734003 0.0616959939130755 173.839805360964 Trimmed Mean ( 21 / 279 ) 10.7245283018868 0.0614381723002377 174.558062200774 Trimmed Mean ( 22 / 279 ) 10.7238335435057 0.061176235502056 175.294106534968 Trimmed Mean ( 23 / 279 ) 10.7231352718078 0.0609100941240868 176.048574969570 Trimmed Mean ( 24 / 279 ) 10.7224334600760 0.0606396558344086 176.822135820762 Trimmed Mean ( 25 / 279 ) 10.7217280813215 0.0603648252256172 177.615491161423 Trimmed Mean ( 26 / 279 ) 10.7210191082803 0.060085503668203 178.429379030965 Trimmed Mean ( 27 / 279 ) 10.7203065134100 0.0598015891546332 179.264575824059 Trimmed Mean ( 28 / 279 ) 10.7195902688860 0.0595129761333984 180.121898875601 Trimmed Mean ( 29 / 279 ) 10.7188703465982 0.0592195553322133 181.002209261229 Trimmed Mean ( 30 / 279 ) 10.7194337194337 0.0590275506256912 181.600517145094 Trimmed Mean ( 31 / 279 ) 10.72 0.0588325192077399 182.212153148623 Trimmed Mean ( 32 / 279 ) 10.72 0.0586344011485992 182.827824451246 Trimmed Mean ( 33 / 279 ) 10.7211413748379 0.0584331347974421 183.477087306758 Trimmed Mean ( 34 / 279 ) 10.7217165149545 0.0582286567130024 184.131270068614 Trimmed Mean ( 35 / 279 ) 10.7209908735332 0.0581153327893393 184.477836725042 Trimmed Mean ( 36 / 279 ) 10.7202614379085 0.0580001844864243 184.831505844912 Trimmed Mean ( 37 / 279 ) 10.7195281782438 0.0578831802113017 185.192453820130 Trimmed Mean ( 38 / 279 ) 10.7187910643890 0.0577642876336533 185.560863008795 Trimmed Mean ( 39 / 279 ) 10.7180500658762 0.057643473662634 185.936921994066 Trimmed Mean ( 40 / 279 ) 10.7173051519155 0.0575207044227606 186.320825856831 Trimmed Mean ( 41 / 279 ) 10.7165562913907 0.0573959452288053 186.712776463038 Trimmed Mean ( 42 / 279 ) 10.7158034528552 0.0572691605596433 187.112982766618 Trimmed Mean ( 43 / 279 ) 10.7150466045273 0.0571403140309991 187.521661129029 Trimmed Mean ( 44 / 279 ) 10.7142857142857 0.057009368367034 187.939035656485 Trimmed Mean ( 45 / 279 ) 10.7135207496653 0.0568762853707132 188.365338556057 Trimmed Mean ( 46 / 279 ) 10.7127516778523 0.0567410258928865 188.800810511877 Trimmed Mean ( 47 / 279 ) 10.7119784656797 0.0566035498000129 189.245701082818 Trimmed Mean ( 48 / 279 ) 10.7112010796221 0.0564638159404549 189.700269123112 Trimmed Mean ( 49 / 279 ) 10.7104194857916 0.056321782109262 190.164783227452 Trimmed Mean ( 50 / 279 ) 10.7096336499322 0.0561774050113609 190.639522202322 Trimmed Mean ( 51 / 279 ) 10.7088435374150 0.0560306402230585 191.124775565351 Trimmed Mean ( 52 / 279 ) 10.7080491132333 0.0558814421517651 191.620844074710 Trimmed Mean ( 53 / 279 ) 10.7072503419973 0.0557297639938304 192.128040290689 Trimmed Mean ( 54 / 279 ) 10.7064471879287 0.0555755576903849 192.646689171794 Trimmed Mean ( 55 / 279 ) 10.7056396148556 0.0554187738810655 193.177128707882 Trimmed Mean ( 56 / 279 ) 10.7048275862069 0.0552593618555012 193.719710593096 Trimmed Mean ( 57 / 279 ) 10.7040110650069 0.05509726950242 194.274800941574 Trimmed Mean ( 58 / 279 ) 10.7031900138696 0.0549324432562318 194.842781049164 Trimmed Mean ( 59 / 279 ) 10.7023643949930 0.0547648280409316 195.424048204699 Trimmed Mean ( 60 / 279 ) 10.7015341701534 0.0545943672111512 196.019016554652 Trimmed Mean ( 61 / 279 ) 10.7006993006993 0.0544210024901811 196.628118025389 Trimmed Mean ( 62 / 279 ) 10.6998597475456 0.0542446739047634 197.251803307568 Trimmed Mean ( 63 / 279 ) 10.6990154711674 0.0540653197164477 197.890542907721 Trimmed Mean ( 64 / 279 ) 10.6990154711674 0.0538828763492802 198.560585404055 Trimmed Mean ( 65 / 279 ) 10.6973125884017 0.0536972783135811 199.215172991294 Trimmed Mean ( 66 / 279 ) 10.6964539007092 0.0535084581255441 199.902114084706 Trimmed Mean ( 67 / 279 ) 10.6955903271693 0.0533163462223707 200.606213384547 Trimmed Mean ( 68 / 279 ) 10.6961483594864 0.0532283551892185 200.948316390076 Trimmed Mean ( 69 / 279 ) 10.6967095851216 0.0531387596909502 201.297690185707 Trimmed Mean ( 70 / 279 ) 10.6972740315638 0.0530475306832763 201.654514239930 Trimmed Mean ( 71 / 279 ) 10.6978417266187 0.0529546384338199 202.018974031677 Trimmed Mean ( 72 / 279 ) 10.6984126984127 0.0528600525005851 202.391261308230 Trimmed Mean ( 73 / 279 ) 10.6989869753980 0.0527637417095574 202.771574356714 Trimmed Mean ( 74 / 279 ) 10.6995645863570 0.0526656741313934 203.160118290011 Trimmed Mean ( 75 / 279 ) 10.7001455604076 0.0525658170571523 203.557105348022 Trimmed Mean ( 76 / 279 ) 10.7007299270073 0.0524641369730212 203.962755215243 Trimmed Mean ( 77 / 279 ) 10.701317715959 0.0523605995339821 204.377295355716 Trimmed Mean ( 78 / 279 ) 10.7019089574156 0.0522551695363634 204.800961366479 Trimmed Mean ( 79 / 279 ) 10.7025036818851 0.0521478108892206 205.233997350739 Trimmed Mean ( 80 / 279 ) 10.7031019202363 0.0520384865844802 205.676656312069 Trimmed Mean ( 81 / 279 ) 10.7037037037037 0.0519271586657821 206.129200571049 Trimmed Mean ( 82 / 279 ) 10.7043090638930 0.0518137881959489 206.591902205868 Trimmed Mean ( 83 / 279 ) 10.7049180327869 0.0516983352230069 207.065043518518 Trimmed Mean ( 84 / 279 ) 10.7055306427504 0.051580758744678 207.548917528379 Trimmed Mean ( 85 / 279 ) 10.7061469265367 0.0514610166712555 208.043828495072 Trimmed Mean ( 86 / 279 ) 10.7067669172932 0.0513390657867742 208.550092472689 Trimmed Mean ( 87 / 279 ) 10.7073906485671 0.0512148617083737 209.068037897610 Trimmed Mean ( 88 / 279 ) 10.7080181543116 0.051088358843752 209.598006212353 Trimmed Mean ( 89 / 279 ) 10.7086494688923 0.050959510346596 210.140352528085 Trimmed Mean ( 90 / 279 ) 10.7092846270928 0.0508282680698684 210.695446328643 Trimmed Mean ( 91 / 279 ) 10.7099236641221 0.0506945825168219 211.263672219182 Trimmed Mean ( 92 / 279 ) 10.7105666156202 0.050558402789603 211.845430722799 Trimmed Mean ( 93 / 279 ) 10.7112135176651 0.050419676535295 212.441139128829 Trimmed Mean ( 94 / 279 ) 10.7134052388290 0.0503628092820991 212.724536052379 Trimmed Mean ( 95 / 279 ) 10.7156105100464 0.0503045389388347 213.014784273751 Trimmed Mean ( 96 / 279 ) 10.7178294573643 0.0502448375250225 213.312053243813 Trimmed Mean ( 97 / 279 ) 10.7200622083981 0.0501836763678893 213.61651804485 Trimmed Mean ( 98 / 279 ) 10.7223088923557 0.0501210260804888 213.928359629686 Trimmed Mean ( 99 / 279 ) 10.7245696400626 0.0500568565389511 214.247765073250 Trimmed Mean ( 100 / 279 ) 10.7268445839874 0.0499911368588154 214.574927837351 Trimmed Mean ( 101 / 279 ) 10.7291338582677 0.0499238353704018 214.910048049487 Trimmed Mean ( 102 / 279 ) 10.7314375987362 0.0498549195931736 215.253332796581 Trimmed Mean ( 103 / 279 ) 10.7337559429477 0.049784356209039 215.60499643458 Trimmed Mean ( 104 / 279 ) 10.7360890302067 0.0497121110345371 215.965260914948 Trimmed Mean ( 105 / 279 ) 10.7360890302067 0.0496381489918521 216.287054377652 Trimmed Mean ( 106 / 279 ) 10.7408 0.049562434078593 216.712520272268 Trimmed Mean ( 107 / 279 ) 10.7431781701445 0.0494849293362744 217.100000227126 Trimmed Mean ( 108 / 279 ) 10.7455716586151 0.0494055968174292 217.497051970119 Trimmed Mean ( 109 / 279 ) 10.7455716586151 0.0493243975512796 217.855101979576 Trimmed Mean ( 110 / 279 ) 10.7504051863857 0.0492412915078865 218.320942793792 Trimmed Mean ( 111 / 279 ) 10.7528455284553 0.0491562375606968 218.748343283555 Trimmed Mean ( 112 / 279 ) 10.7553017944535 0.0490691934473954 219.186439369209 Trimmed Mean ( 113 / 279 ) 10.7553017944535 0.0489801157289704 219.585062925689 Trimmed Mean ( 114 / 279 ) 10.7602627257800 0.0488889597468872 220.095964027238 Trimmed Mean ( 115 / 279 ) 10.7627677100494 0.0487956795782643 220.568046250628 Trimmed Mean ( 116 / 279 ) 10.7652892561983 0.0487002279889342 221.052132623372 Trimmed Mean ( 117 / 279 ) 10.7652892561983 0.0486025563842651 221.496358567748 Trimmed Mean ( 118 / 279 ) 10.7703826955075 0.0485026147576098 222.057774603124 Trimmed Mean ( 119 / 279 ) 10.7729549248748 0.0484003516362403 222.580096232367 Trimmed Mean ( 120 / 279 ) 10.7755443886097 0.0482957140246133 223.115955654328 Trimmed Mean ( 121 / 279 ) 10.7781512605042 0.0481886473448032 223.665777198176 Trimmed Mean ( 122 / 279 ) 10.7807757166948 0.048079095373926 224.230003348635 Trimmed Mean ( 123 / 279 ) 10.7834179357022 0.0479670001783633 224.809095745085 Trimmed Mean ( 124 / 279 ) 10.7860780984720 0.0478523020445828 225.403536248327 Trimmed Mean ( 125 / 279 ) 10.7887563884157 0.0477349394063337 226.013828080489 Trimmed Mean ( 126 / 279 ) 10.791452991453 0.0476148487679811 226.640497044060 Trimmed Mean ( 127 / 279 ) 10.7941680960549 0.0474919646237203 227.284092826592 Trimmed Mean ( 128 / 279 ) 10.7941680960549 0.047366219372397 227.887474218499 Trimmed Mean ( 129 / 279 ) 10.7996545768566 0.0472375432276304 228.624391510261 Trimmed Mean ( 130 / 279 ) 10.8024263431542 0.0471058641229169 229.322326302446 Trimmed Mean ( 131 / 279 ) 10.8052173913043 0.0469711076113615 230.039655030207 Trimmed Mean ( 132 / 279 ) 10.8080279232112 0.046833196759656 230.77706992066 Trimmed Mean ( 133 / 279 ) 10.8091068301226 0.0468438093281639 230.747818871849 Trimmed Mean ( 134 / 279 ) 10.8101933216169 0.0468539454719447 230.721088965492 Trimmed Mean ( 135 / 279 ) 10.8112874779541 0.0468635941791951 230.696933671250 Trimmed Mean ( 136 / 279 ) 10.8123893805310 0.0468727441754749 230.675407867165 Trimmed Mean ( 137 / 279 ) 10.8134991119005 0.04688138391639 230.656567886002 Trimmed Mean ( 138 / 279 ) 10.8146167557932 0.0468895015800343 230.640471563428 Trimmed Mean ( 139 / 279 ) 10.8157423971377 0.0468970850591804 230.627178288142 Trimmed Mean ( 140 / 279 ) 10.8168761220826 0.0469041219532113 230.616749054013 Trimmed Mean ( 141 / 279 ) 10.8180180180180 0.0469105995597802 230.609246514365 Trimmed Mean ( 142 / 279 ) 10.8191681735986 0.0469165048661901 230.604735038464 Trimmed Mean ( 143 / 279 ) 10.8203266787659 0.0469218245404804 230.603280770358 Trimmed Mean ( 144 / 279 ) 10.8214936247723 0.0469265449222102 230.604951690158 Trimmed Mean ( 145 / 279 ) 10.8226691042048 0.0469306520129245 230.609817677884 Trimmed Mean ( 146 / 279 ) 10.8238532110092 0.0469341314662916 230.617950580015 Trimmed Mean ( 147 / 279 ) 10.8250460405157 0.0469369685778983 230.629424278861 Trimmed Mean ( 148 / 279 ) 10.8262476894640 0.0469391482746876 230.644314764913 Trimmed Mean ( 149 / 279 ) 10.8274582560297 0.0469406551040261 230.662700212316 Trimmed Mean ( 150 / 279 ) 10.8286778398510 0.0469414732223841 230.68466105762 Trimmed Mean ( 151 / 279 ) 10.8299065420561 0.0469415863836119 230.710280081991 Trimmed Mean ( 152 / 279 ) 10.8311444652908 0.0469409779267977 230.739642497041 Trimmed Mean ( 153 / 279 ) 10.8323917137476 0.046939630763686 230.772836034491 Trimmed Mean ( 154 / 279 ) 10.8336483931947 0.0469375273656406 230.809951039841 Trimmed Mean ( 155 / 279 ) 10.8349146110057 0.0469346497501301 230.851080570291 Trimmed Mean ( 156 / 279 ) 10.8361904761905 0.0469309794667179 230.896320497108 Trimmed Mean ( 157 / 279 ) 10.8374760994264 0.0469264975825315 230.945769612703 Trimmed Mean ( 158 / 279 ) 10.8387715930902 0.0469211846671925 230.999529742665 Trimmed Mean ( 159 / 279 ) 10.8400770712909 0.046915020777179 231.057705863021 Trimmed Mean ( 160 / 279 ) 10.8413926499033 0.0469079854395981 231.120406223017 Trimmed Mean ( 161 / 279 ) 10.8427184466019 0.0469000576353411 231.187742473722 Trimmed Mean ( 162 / 279 ) 10.8440545808967 0.0468912157815922 231.259829802785 Trimmed Mean ( 163 / 279 ) 10.8454011741683 0.0468814377136629 231.336787075699 Trimmed Mean ( 164 / 279 ) 10.8467583497053 0.04687070066612 231.418736983929 Trimmed Mean ( 165 / 279 ) 10.8481262327416 0.0468589812531744 231.505806200315 Trimmed Mean ( 166 / 279 ) 10.8495049504950 0.0468462554482965 231.598125542168 Trimmed Mean ( 167 / 279 ) 10.8508946322068 0.0468324985630209 231.695830142504 Trimmed Mean ( 168 / 279 ) 10.8522954091816 0.0468176852249033 231.799059629908 Trimmed Mean ( 169 / 279 ) 10.8537074148297 0.0468017893545868 231.907958317537 Trimmed Mean ( 170 / 279 ) 10.8551307847082 0.0467847841419363 232.022675401810 Trimmed Mean ( 171 / 279 ) 10.8565656565657 0.0467666420211948 232.143365171385 Trimmed Mean ( 172 / 279 ) 10.8580121703854 0.0467473346451130 232.270187227038 Trimmed Mean ( 173 / 279 ) 10.8594704684318 0.046726832858002 232.403306713138 Trimmed Mean ( 174 / 279 ) 10.8609406952965 0.0467051066676552 232.542894561422 Trimmed Mean ( 175 / 279 ) 10.8624229979466 0.0466821252160808 232.689127747868 Trimmed Mean ( 176 / 279 ) 10.8639175257732 0.0466578567489863 232.842189563481 Trimmed Mean ( 177 / 279 ) 10.8654244306418 0.046632268583949 233.002269899898 Trimmed Mean ( 178 / 279 ) 10.8669438669439 0.046605327077206 233.169565550774 Trimmed Mean ( 179 / 279 ) 10.8684759916493 0.0465769975889889 233.344280529981 Trimmed Mean ( 180 / 279 ) 10.8700209643606 0.046547244447329 233.526626407728 Trimmed Mean ( 181 / 279 ) 10.8715789473684 0.0465160309102489 233.716822665819 Trimmed Mean ( 182 / 279 ) 10.8731501057082 0.0464833191262553 233.915097073323 Trimmed Mean ( 183 / 279 ) 10.8747346072187 0.0464490700930388 234.121686084055 Trimmed Mean ( 184 / 279 ) 10.8763326226013 0.0464132436142832 234.336835257388 Trimmed Mean ( 185 / 279 ) 10.8779443254818 0.0463757982544793 234.560799703995 Trimmed Mean ( 186 / 279 ) 10.8795698924731 0.0463366912916302 234.793844558304 Trimmed Mean ( 187 / 279 ) 10.8812095032397 0.0462958786677291 235.036245479548 Trimmed Mean ( 188 / 279 ) 10.882863340564 0.0462533149368827 235.288289183484 Trimmed Mean ( 189 / 279 ) 10.8845315904139 0.0462089532109421 235.550274006997 Trimmed Mean ( 190 / 279 ) 10.8862144420131 0.046162745102497 235.822510508031 Trimmed Mean ( 191 / 279 ) 10.8879120879121 0.0461146406650757 236.10532210344 Trimmed Mean ( 192 / 279 ) 10.8896247240618 0.0460645883303853 236.399045747658 Trimmed Mean ( 193 / 279 ) 10.8913525498891 0.0460125348424115 236.704032655253 Trimmed Mean ( 194 / 279 ) 10.8930957683742 0.0459584251881863 237.020649070766 Trimmed Mean ( 195 / 279 ) 10.8948545861298 0.0459022025250183 237.349277089518 Trimmed Mean ( 196 / 279 ) 10.8966292134831 0.0458438081039626 237.690315533392 Trimmed Mean ( 197 / 279 ) 10.8984198645598 0.0457831811892927 238.044180885985 Trimmed Mean ( 198 / 279 ) 10.9002267573696 0.0457202589737187 238.411308291919 Trimmed Mean ( 199 / 279 ) 10.9020501138952 0.045654976489074 238.792152625558 Trimmed Mean ( 200 / 279 ) 10.9038901601831 0.0455872665121745 239.187189634875 Trimmed Mean ( 201 / 279 ) 10.9034482758621 0.0456802222352296 238.690788755688 Trimmed Mean ( 202 / 279 ) 10.9030023094688 0.0457737264323938 238.193460730626 Trimmed Mean ( 203 / 279 ) 10.9025522041763 0.0458677841885933 237.695201480599 Trimmed Mean ( 204 / 279 ) 10.9020979020979 0.0459624006478782 237.196006919216 Trimmed Mean ( 205 / 279 ) 10.9016393442623 0.0460575810140974 236.695872953586 Trimmed Mean ( 206 / 279 ) 10.9011764705882 0.0461533305515735 236.194795485168 Trimmed Mean ( 207 / 279 ) 10.9007092198582 0.0462496545857794 235.692770410654 Trimmed Mean ( 208 / 279 ) 10.9002375296912 0.0463465585040128 235.189793622917 Trimmed Mean ( 209 / 279 ) 10.8997613365155 0.0464440477560708 234.685861011991 Trimmed Mean ( 210 / 279 ) 10.8997613365155 0.0465421278549221 234.191298053486 Trimmed Mean ( 211 / 279 ) 10.8992805755396 0.046640804377377 233.685518957864 Trimmed Mean ( 212 / 279 ) 10.8983050847458 0.0467400829647541 233.168287120158 Trimmed Mean ( 213 / 279 ) 10.8978102189781 0.0468399693235422 232.660490097733 Trimmed Mean ( 214 / 279 ) 10.8973105134474 0.0469404692260582 232.151716698178 Trimmed Mean ( 215 / 279 ) 10.8968058968059 0.0470415885110980 231.641962818393 Trimmed Mean ( 216 / 279 ) 10.8962962962963 0.0471433330845805 231.131224360974 Trimmed Mean ( 217 / 279 ) 10.8957816377171 0.0472457089201833 230.619497235705 Trimmed Mean ( 218 / 279 ) 10.8957816377171 0.0473487220599689 230.117755320138 Trimmed Mean ( 219 / 279 ) 10.8947368421053 0.0474523786150003 229.593060666116 Trimmed Mean ( 220 / 279 ) 10.8942065491184 0.0475566847659439 229.078343091735 Trimmed Mean ( 221 / 279 ) 10.8936708860759 0.0476616467636589 228.56262059292 Trimmed Mean ( 222 / 279 ) 10.8931297709924 0.0477672709297716 228.045889140447 Trimmed Mean ( 223 / 279 ) 10.8925831202046 0.0478735636572321 227.528144722920 Trimmed Mean ( 224 / 279 ) 10.8920308483290 0.0479805314108529 227.009383348875 Trimmed Mean ( 225 / 279 ) 10.8914728682171 0.0480881807278259 226.489601048991 Trimmed Mean ( 226 / 279 ) 10.8914728682171 0.0481965182182169 225.980491348032 Trimmed Mean ( 227 / 279 ) 10.8903394255875 0.0483055505654351 225.446957919159 Trimmed Mean ( 228 / 279 ) 10.8897637795276 0.0484152845266745 224.924089282752 Trimmed Mean ( 229 / 279 ) 10.8891820580475 0.0485257269333257 224.400184112836 Trimmed Mean ( 230 / 279 ) 10.8885941644562 0.0486368846913546 223.875238588045 Trimmed Mean ( 231 / 279 ) 10.888 0.0487487647816453 223.349248924959 Trimmed Mean ( 232 / 279 ) 10.8873994638070 0.0488613742603049 222.822211381228 Trimmed Mean ( 233 / 279 ) 10.8873994638070 0.0489747202589246 222.306516632384 Trimmed Mean ( 234 / 279 ) 10.8867924528302 0.0490888099847967 221.777477518847 Trimmed Mean ( 235 / 279 ) 10.8855585831063 0.0492036507210809 221.234774728666 Trimmed Mean ( 236 / 279 ) 10.8849315068493 0.0493192498269177 220.703509178448 Trimmed Mean ( 237 / 279 ) 10.8842975206612 0.0494356147374838 220.171177772536 Trimmed Mean ( 238 / 279 ) 10.8836565096953 0.0495527529639843 219.637777089917 Trimmed Mean ( 239 / 279 ) 10.8830083565460 0.0496706720935786 219.103303777379 Trimmed Mean ( 240 / 279 ) 10.8823529411765 0.0497893797892328 218.567754554152 Trimmed Mean ( 241 / 279 ) 10.8823529411765 0.0499088837894936 218.044406424239 Trimmed Mean ( 242 / 279 ) 10.8810198300283 0.0500291919081786 217.493415644188 Trimmed Mean ( 243 / 279 ) 10.8803418803419 0.0501503120339752 216.954619803179 Trimmed Mean ( 244 / 279 ) 10.8796561604585 0.0502722521299418 216.414735753973 Trimmed Mean ( 245 / 279 ) 10.8789625360231 0.0503950202329046 215.873760656213 Trimmed Mean ( 246 / 279 ) 10.8782608695652 0.0505186244527408 215.331691775211 Trimmed Mean ( 247 / 279 ) 10.8775510204082 0.0506430729715415 214.788526488523 Trimmed Mean ( 248 / 279 ) 10.8768328445748 0.0507683740426436 214.244262292872 Trimmed Mean ( 249 / 279 ) 10.8768328445748 0.0508945359895224 213.713174373256 Trimmed Mean ( 250 / 279 ) 10.8753709198813 0.0510215672045346 213.152427801448 Trimmed Mean ( 251 / 279 ) 10.8746268656716 0.0511494761474996 212.604853162377 Trimmed Mean ( 252 / 279 ) 10.8738738738739 0.0512782713441091 212.056170944286 Trimmed Mean ( 253 / 279 ) 10.8731117824773 0.0514079613841508 211.506379356828 Trimmed Mean ( 254 / 279 ) 10.8723404255319 0.0515385549195348 210.955476778627 Trimmed Mean ( 255 / 279 ) 10.8715596330275 0.0516700606621057 210.403461767186 Trimmed Mean ( 256 / 279 ) 10.8715596330275 0.0518024873812283 209.865591067487 Trimmed Mean ( 257 / 279 ) 10.8699690402477 0.051935843901127 209.296089632074 Trimmed Mean ( 258 / 279 ) 10.8691588785047 0.052070139097965 208.740730614439 Trimmed Mean ( 259 / 279 ) 10.8683385579937 0.0522053818966413 208.184255399403 Trimmed Mean ( 260 / 279 ) 10.8675078864353 0.0523415812672869 207.626663606884 Trimmed Mean ( 261 / 279 ) 10.8666666666667 0.0524787462214392 207.067955107268 Trimmed Mean ( 262 / 279 ) 10.8658146964856 0.0526168858078699 206.508130035709 Trimmed Mean ( 263 / 279 ) 10.8649517684887 0.0527560091080424 205.947188807207 Trimmed Mean ( 264 / 279 ) 10.8640776699029 0.0528961252311729 205.385132132523 Trimmed Mean ( 265 / 279 ) 10.8631921824104 0.0530372433088648 204.821961034968 Trimmed Mean ( 266 / 279 ) 10.8622950819672 0.0531793724892879 204.257676868136 Trimmed Mean ( 267 / 279 ) 10.8613861386139 0.0533225219308679 203.692281334621 Trimmed Mean ( 268 / 279 ) 10.8604651162791 0.0534667007954521 203.125776505792 Trimmed Mean ( 269 / 279 ) 10.8595317725753 0.0536119182409128 202.558164842683 Trimmed Mean ( 270 / 279 ) 10.8585858585859 0.0537581834131482 201.989449218071 Trimmed Mean ( 271 / 279 ) 10.8576271186441 0.0539055054374363 201.419632939823 Trimmed Mean ( 272 / 279 ) 10.8566552901024 0.0540538934090967 200.848719775574 Trimmed Mean ( 273 / 279 ) 10.8556701030928 0.0542033563834072 200.27671397884 Trimmed Mean ( 274 / 279 ) 10.8546712802768 0.0543539033647232 199.703620316655 Trimmed Mean ( 275 / 279 ) 10.8536585365854 0.0545055432947406 199.129444098811 Trimmed Mean ( 276 / 279 ) 10.8526315789474 0.054658285039839 198.554191208838 Trimmed Mean ( 277 / 279 ) 10.8515901060071 0.0548121373774379 197.977868136809 Trimmed Mean ( 278 / 279 ) 10.8505338078292 0.0549671089812934 197.400482014106 Trimmed Mean ( 279 / 279 ) 10.8494623655914 0.0551232084056555 196.822040650273 Median 10 Midrange 10.5 Midmean - Weighted Average at Xnp 11.1194852941176 Midmean - Weighted Average at X(n+1)p 11.1194852941176 Midmean - Empirical Distribution Function 11.1194852941176 Midmean - Empirical Distribution Function - Averaging 11.1194852941176 Midmean - Empirical Distribution Function - Interpolation 11.1194852941176 Midmean - Closest Observation 11.1194852941176 Midmean - True Basic - Statistics Graphics Toolkit 11.1194852941176 Midmean - MS Excel (old versions) 11.1194852941176 Number of observations 837

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/11/t1218487080t60ldjzn3iluyoh/1puuv1218486895.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/11/t1218487080t60ldjzn3iluyoh/1puuv1218486895.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/11/t1218487080t60ldjzn3iluyoh/2kyc31218486895.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/11/t1218487080t60ldjzn3iluyoh/2kyc31218486895.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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