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74	77	88	67	73
82	71	86	72	73
80	79	84	75	73
91	78	69	80	73
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84	81	79	80	75
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78	80	77	73	78
92	82	88	96	79
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83	71	93	90	81
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83	77	81	67	83
77	79	81	73	83
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89	72	94	94	83
87	87	85	98	83
89	86	105	105	83
85	82	87	78	84
88	95	95	81	84
91	102	85	82	84
102	80	102	88	84
100	92	103	106	84
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95	103	102	91	89
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98	96	79	97	89
91	86	92	100	89
91	92	105	100	89
114	96	113	107	89
93	105	90	83	90
88	82	83	84	90
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95	104	84	85	91
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102	99	100	96	92
97	94	95	105	92
91	80	88	107	92
81	88	86	73	93
90	108	83	79	93
98	112	101	94	93
97	89	102	94	93
100	95	90	95	93
94	88	104	103	93
88	105	86	87	94
89	82	88	90	94
91	92	87	98	94
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114	105	105	105	99
94	112	104	69	100
91	90	88	86	100
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112	112	113	105	100
98	105	93	96	101
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92	94	92	84	104
104	92	105	110	104
114	100	96	111	105
103	103	94	96	107
102	100	105	101	107
113	112	102	106	107
114	112	105	111	107
114	100	113	111	107
106	109	113	111	107
114	112	113	111	107
74	71	69	67	NA

par5 <- '2'
par4 <- '1'
par3 <- '0'
par2 <- 'FALSE'
par1 <- 'grey'
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')