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Data X:
105.3 102.7 99.5 112.1 103 103.2 101.6 104.2 103.8 105.6 103.9 102.4 103.4 103.9 106.6 100.3 105.8 107.2 108.3 102.6 101.4 100.7 102 101.5 97 92.1 93.8 103.4 94.3 90.3 91.6 99.4 96.6 93.4 97.7 97.9 97.1 98.5 94.8 98 95.7 100.8 98 90.2 96.9 102.3 103.8 87.1 97.4 104.7 97.8 91.8 95.3 101.1 91.2 94.8 93.6 101.4 89.3 91.8 91.5 99.5 87.5 89.3 93.1 98.4 90.4 91.7 91.7 96.3 94.2 86.2 94.3 100.7 102.2 82.8 93.9 101.2 101.3 82.3 90.9 100.3 96 79.8 88.3 97.8 90.8 79.4 91.3 97.4 93.2 85.3 91.7 98.6 90.9 87.5 92.4 99.7 91.1 88.3 92 99 90.2 88.6 95.6 98.1 94.3 94.9 95.8 97 96 94.7 96.4 98.5 99 92.6 99 103.8 103.3 91.8 107 114.4 113.1 96.4 109.7 124.5 112.8 96.4 116.2 134.2 112.1 107.1 115.9 131.8 107.4 111.9 113.8 125.6 111 107.8 112.6 119.9 110.5 109.2 113.7 114.9 110.8 115.3 115.9 115.5 112.4 119.2 110.3 112.5 111.5 107.8 111.3 111.4 116.2 106.8 113.4 115.3 122.5 104.2 108.2 110.8 121.3 94.8 104.8 103.7 113.9 97.5 106 111.1 110.7 98.3 110.9 113 120.8 100.6 115 111.2 141.1 94.9 118.4 117.6 147.4 93.6 121.4 121.7 148 98 128.8 127.3 158.1 104.3 131.7 129.8 165 103.9 141.7 137.1 187 105.3 142.9 141.4 190.3 102.6 139.4 137.4 182.4 103.3 134.7 130.7 168.8 107.9 125 117.2 151.2 107.8 113.6 110.8 120.1 109.8 111.5 111.4 112.5 110.6 108.5 108.2 106.2 110.8 112.3 108.8 107.1 119.3 116.6 110.2 108.5 128.1 115.5 109.5 106.5 127.6 120.1 109.5 108.3 137.9 132.9 116 125.6 151.4 128.1 111.2 124 143.6 129.3 112.1 127.2 143.4 132.5 114 136.9 141.9 131 119.1 135.8 135.2 124.9 114.1 124.3 133.1 120.8 115.1 115.4 129.6 122 115.4 113.6 134.1 122.1 110.8 114.4 136.8 127.4 116 118.4 143.5 135.2 119.2 117 162.5 137.3 126.5 116.5 163.1 135 127.8 115.4 157.2 136 131.3 113.6 158.8 138.4 140.3 117.4 155.4 134.7 137.3 116.9 148.5 138.4 143 116.4 154.2 133.9 134.5 111.1 153.3 133.6 139.9 110.2 149.4 141.2 159.3 118.9 147.9 151.8 170.4 131.8 156 155.4 175 130.6 163 156.6 175.8 138.3 159.1 161.6 180.9 148.4 159.5 160.7 180.3 148.7 157.3 156 169.6 144.3 156.4 159.5 172.3 152.5 156.6 168.7 184.8 162.9 162.4 169.9 177.7 167.2 166.8 169.9 184.6 166.5 162.6 185.9 211.4 185.6 168.1
Names of X columns:
totaal graan oliezaden suiker
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Omit all rows with missing values?
no
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R Code
z <- as.data.frame(t(y)) bitmap(file='test1.png') (r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=TRUE,col=par1)) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/overview.htm','Boxplot statistics','Boxplot overview'),6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/lower_whisker.htm','lower whisker','definition of lower whisker'),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/lower_hinge.htm','lower hinge','definition of lower hinge'),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/central_tendency.htm','median','definitions about measures of central tendency'),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/upper_hinge.htm','upper hinge','definition of upper hinge'),1,TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/upper_whisker.htm','upper whisker','definition of upper whisker'),1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) for (j in 1:5) { a<-table.element(a,r$stats[j,i]) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot Notches',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower bound',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper bound',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) a<-table.element(a,r$conf[1,i]) a<-table.element(a,r$stats[3,i]) a<-table.element(a,r$conf[2,i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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