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70.80		66.67
69.60		66.33
69.87		64.33
67.47		64.00
67.60		63.33
67.13		61.33
66.27		64.67
66.73		63.00
68.07		60.67
67.80		63.67
64.80		60.67
64.60		61.67
64.20		62.33
64.20		60.33
63.67		59.67
61.00		60.33
59.67		59.33
59.67		58.67
59.80		58.67
60.73		59.33
59.40		57.33
58.07		59.33
57.47		56.00
70.73		53.67
72.87		58.67
66.00		49.33
66.07		71.33
66.00		70.33
66.27		69.00
64.00		66.00
63.67		66.00
63.73		63.33
63.33		65.33
63.53		64.33
63.53		64.00
62.87		61.67
59.53		63.67
62.80		64.67
60.80		61.67
59.80		62.00
56.67		61.33
57.67		63.67
58.40		61.33
55.47		62.33
56.20		59.67
71.53		59.33
68.67		61.67
65.67		58.67
66.73		58.00
67.33		56.67
66.73		59.67
66.87		58.00
65.80		57.00
64.73		57.67
65.47		58.67
63.60		55.33
64.07		56.00
64.67		55.67
63.73		53.33
62.53		53.67
61.93		51.00
62.67		47.00
62.80		4.33
61.33		70.00
62.60		68.67
59.13		67.67
61.27		66.00
59.47		65.67
57.87		65.67
59.73		63.67
61.40		63.67
58.80		64.00
58.33		62.00
57.47		62.00
57.13		61.67
55.00		61.67
51.53		63.33
72.73		61.00
73.00		62.33
70.80		60.33
70.07		60.33
71.67		60.67
71.07		57.67
70.67		58.33
70.73		58.00
70.73		57.33
68.60		56.67
69.60		58.00
66.47		55.33
67.07		55.67
68.67		54.67
66.93		56.33
65.93		55.00
68.87		55.00
66.53		54.67
65.80		54.33
66.60		49.00
66.00		48.33
65.00		49.67
66.80		43.67
65.60		6.33
66.00		3.00
65.67		66.67
64.67		67.33
65.07		65.33
64.67		66.00
65.07		65.67
65.20		66.67
64.87		65.67
63.47		65.00
62.60		64.67
64.07		66.67
63.73		63.67
64.67		63.33
61.60		63.67
61.60		63.33
60.47		63.67
61.27		63.00
63.00		61.67
61.47		61.33
60.87		60.67
61.67		60.00
62.87		61.67
62.40		61.33
59.73		58.67
60.13		60.33
58.80		59.67
59.60		59.33
58.93		59.67
60.13		61.00
58.20		61.00
58.27		60.00
58.27		60.00
55.07		58.67
53.87		58.33
52.33		58.00
47.20		56.33
37.93		54.67
72.73		55.33
70.07		54.00
70.67		52.67
72.07		44.00
68.80		65.67
68.80		65.00
67.47		66.33
66.73		64.00
66.53		62.33
66.00		61.33
67.60		63.00
66.00		63.67
66.00		62.00
66.53		61.33
65.80		64.67
64.27		62.67
64.67		64.00
64.60		61.00
64.13		60.67
65.47		59.67
62.93		60.33
63.53		56.67
62.13		56.67
63.87		54.33
64.67		51.00
63.33		51.00
63.13		47.00
62.80		68.00
62.40		65.00
62.40		64.00
62.60		64.00
61.47		64.00
62.20		62.00
63.00		61.00
61.80		60.00
59.73		60.00
60.33		62.00
60.13		60.00
59.53		59.00
59.00		61.00
55.93		60.00
41.87		60.00
36.33		58.00
71.67		58.00
71.47		60.00
70.47		58.00
69.53		59.00
70.73		56.00
69.93		54.00
68.73		51.00
67.53		47.00

bitmap(file='test1.png')
par2<- as.logical(par2) # notches
par3<-as.numeric(par3) # percentage trim
if(par3>45){par3<-45;warning('trim limited to 45%')}
if(par3<0){par3<-0;warning('negative trim makes no sense. Trim is zero.')}
par4 <- as.numeric(par4) #factor column
par5 <- as.numeric(par5) # response column
x <- t(x)
x1<-as.numeric(x[,par5]) # response
f1<-as.character(x[,par4]) # factor
x2<-x1[f1=='no']
f2 <- f1[f1=='no']
lotrm<-as.integer(length(x2)*par3/100)
hitrm<-as.integer(length(x2)*(100-par3)/100)
srt<-order(x2,f2)
trmx1<-x2[srt[lotrm:hitrm]]
trmf1<-f2[srt[lotrm:hitrm]]
x3<-x1[f1=='yes']
f3 <- f1[f1=='yes']
lotrm<-as.integer(length(x3)*par3/100)
hitrm<-as.integer(length(x3)*(100-par3)/100)
srt<-order(x3,f3)
trmx2<-x3[srt[lotrm:hitrm]]
trmf2<-f3[srt[lotrm:hitrm]]
xtrm<-c(trmx1,trmx2)
ftrm<-c(trmf1,trmf2)
xtrm[1:6]
ftrm[1:6]
r<-boxplot(xtrm~as.factor(ftrm), col=par1, notch=par2, main=main, xlab=xlab, ylab=ylab)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('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('lower_whisker.htm','lower whisker','definition of lower whisker'),1,TRUE)
a<-table.element(a,hyperlink('lower_hinge.htm','lower hinge','definition of lower hinge'),1,TRUE)
a<-table.element(a,hyperlink('central_tendency.htm','median','definitions about measures of central tendency'),1,TRUE)
a<-table.element(a,hyperlink('upper_hinge.htm','upper hinge','definition of upper hinge'),1,TRUE)
a<-table.element(a,hyperlink('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,'no',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,1])
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'yes',1,TRUE)
for (j in 1:5)
{
a<-table.element(a,r$stats[j,2])
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
tr.mns<-tapply(x1,f1,mean, trim=par3/100)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('trimmed_mean.htm','Trimmed Mean Equation','Trimmed Mean'),2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'No Placement')
a<-table.element(a,'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')