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Data X:
70.80 69.60 69.87 67.47 67.60 67.13 66.27 66.73 68.07 67.80 64.80 64.60 64.20 64.20 63.67 61.00 59.67 59.67 59.80 60.73 59.40 58.07 57.47 66.67 66.33 64.33 64.00 63.33 61.33 64.67 63.00 60.67 63.67 60.67 61.67 62.33 60.33 59.67 60.33 59.33 58.67 58.67 59.33 57.33 59.33 56.00 53.67 58.67 49.33 70.73 72.87 66.00 66.07 66.00 66.27 64.00 63.67 63.73 63.33 63.53 63.53 62.87 59.53 62.80 60.80 59.80 56.67 57.67 58.40 55.47 56.20 71.33 70.33 69.00 66.00 66.00 63.33 65.33 64.33 64.00 61.67 63.67 64.67 61.67 62.00 61.33 63.67 61.33 62.33 59.67 59.33 61.67 58.67 58.00 56.67 59.67 58.00 57.00 57.67 58.67 55.33 56.00 55.67 53.33 53.67 51.00 47.00 4.33 71.53 68.67 65.67 66.73 67.33 66.73 66.87 65.80 64.73 65.47 63.60 64.07 64.67 63.73 62.53 61.93 62.67 62.80 61.33 62.60 59.13 61.27 59.47 57.87 59.73 61.40 58.80 58.33 57.47 57.13 55.00 51.53 70.00 68.67 67.67 66.00 65.67 65.67 63.67 63.67 64.00 62.00 62.00 61.67 61.67 63.33 61.00 62.33 60.33 60.33 60.67 57.67 58.33 58.00 57.33 56.67 58.00 55.33 55.67 54.67 56.33 55.00 55.00 54.67 54.33 49.00 48.33 49.67 43.67 6.33 3.00 72.73 73.00 70.80 70.07 71.67 71.07 70.67 70.73 70.73 68.60 69.60 66.47 67.07 68.67 66.93 65.93 68.87 66.53 65.80 66.60 66.00 65.00 66.80 65.60 66.00 65.67 64.67 65.07 64.67 65.07 65.20 64.87 63.47 62.60 64.07 63.73 64.67 61.60 61.60 60.47 61.27 63.00 61.47 60.87 61.67 62.87 62.40 59.73 60.13 58.80 59.60 58.93 60.13 58.20 58.27 58.27 55.07 53.87 52.33 47.20 37.93 66.67 67.33 65.33 66.00 65.67 66.67 65.67 65.00 64.67 66.67 63.67 63.33 63.67 63.33 63.67 63.00 61.67 61.33 60.67 60.00 61.67 61.33 58.67 60.33 59.67 59.33 59.67 61.00 61.00 60.00 60.00 58.67 58.33 58.00 56.33 54.67 55.33 54.00 52.67 44.00 72.73 70.07 70.67 72.07 68.80 68.80 67.47 66.73 66.53 66.00 67.60 66.00 66.00 66.53 65.80 64.27 64.67 64.60 64.13 65.47 62.93 63.53 62.13 63.87 64.67 63.33 63.13 62.80 62.40 62.40 62.60 61.47 62.20 63.00 61.80 59.73 60.33 60.13 59.53 59.00 55.93 41.87 36.33 65.67 65.00 66.33 64.00 62.33 61.33 63.00 63.67 62.00 61.33 64.67 62.67 64.00 61.00 60.67 59.67 60.33 56.67 56.67 54.33 51.00 51.00 47.00 71.67 71.47 70.47 69.53 70.73 69.93 68.73 67.53 64.40 66.20 66.20 63.07 64.27 65.00 63.67 62.67 64.67 64.67 64.47 61.93 63.27 62.93 61.93 64.07 61.40 62.00 62.60 62.40 61.60 59.87 63.20 62.40 60.40 61.87 59.13 59.53 57.80 57.67 61.00 56.33 54.20 54.73 52.67 17.60 68 65 64 64 64 62 61 60 60 62 60 59 61 60 60 58 58 60 58 59 56 54 51 47
Data Y:
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
box colour
Notched Boxes
TRUE
FALSE
% to trim
Chart options
Label y-axis:
Label x-axis:
R Code
par3 <- '0' par2 <- '1' par1 <- '3' bitmap(file='test1.png') par1 <- as.numeric(par1) par2<- as.logical(par2) par3<-as.numeric(par3) if(par3>45){par3<-45;warning('trim limited to 45%')} if(par3<0){par3<-0;warning('negative trim makes no sense. Trim is zero.')} x1<-x[y==1] y1<-y[y==1] lotrm<-as.integer(length(x1)*par3/100) hitrm<-as.integer(length(x1)*(100-par3)/100) srt<-order(x1,y1) trmx1<-x1[srt[lotrm:hitrm]] trmy1<-y1[srt[lotrm:hitrm]] x2<-x[y==2] y2<-y[y==2] lotrm<-as.integer(length(x2)*par3/100) hitrm<-as.integer(length(x2)*(100-par3)/100) srt<-order(x2,y2) trmx2<-x2[srt[lotrm:hitrm]] trmy2<-y2[srt[lotrm:hitrm]] xtrm<-c(trmx1,trmx2) ytrm<-c(trmy1,trmy2) r<-boxplot(xtrm~as.factor(ytrm), col=par1, notch=par2, names =c('yes', 'no'), main='Reddy and Moores Placements Data', xlab='Placement Student', ylab='Degree Grade') 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,'Placement',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) a<-table.row.start(a) a<-table.element(a,'yes',1,TRUE) for (j in 1:5) { a<-table.element(a,r$stats[j,1]) } a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'no',1,TRUE) for (j in 1:5) { a<-table.element(a,r$stats[j,2]) } a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') tr.mns<-tapply(x,y,mean, trim=par3/100) a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/trimmed_mean.htm','Trimmed Mean Equation','Trimmed Mean'),2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Placement') a<-table.element(a,'No Placement') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,tr.mns[1]) a<-table.element(a,tr.mns[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab')
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