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WJ10AFS	WJ10AVA	WJ10ARD	WJ10AMA	WJ10AKN			
88	95	95	81	84			
98	92	87	90	97			
89	95	91	91	88			
81	97	84	87	87			
88	92	92	89	92			
95	104	84	85	91			These 5 variables have been abstracted from the complete dataset for 
79	79	84	81	80			The Carolina Abecedarian Project and
91	78	69	80	73			the Carolina Approach to
80	79	84	75	73			Responsive Education (CARE),
91	86	84	84	77			1972-1992
85	92	85	91	86			
94	78	89	87	82			Bibliographic Citation: Ramey, Craig T., James J. Gallagher, Frances A. Campbell, Barbara
86	86	83	90	82			H. Wasik, and Joseph J. Sparling. CAROLINA ABECEDARIAN
82	71	86	72	73			PROJECT AND THE CAROLINA APPROACH TO RESPONSIVE
107	90	91	96	99			EDUCATION (CARE), 1972-1992 [Computer file]. ICPSR version.
97	93	90	88	90			Chapel Hill, NC: University of North Carolina [producer], 2002. Ann
78	80	77	73	78			Arbor, MI: Inter-university Consortium for Political and Social Research
91	90	88	86	100			[distributor], 2004.
74	77	88	67	73			
95	86	88	89	95			CAUTION:
97	89	102	94	93			For study use missing values have been removed. This excel file 
112	88	103	88	91			is not for use other than for educational study purposes.
80	86	84	77	81			
98	97	87	89	98			The full datset is available to interested professionals from ICPSR
102	81	88	104	88			Please register and retrieve the origianl dataset from
100	88	93	89	90			the Inter-UnivesrityConsortium on Political and Social research
97	82	101	107	85			http://www.icpsr.umich.edu/icpsrweb/ICPSR/
92	82	88	96	79			
114	100	113	111	107			
88	91	95	84	82			
96	111	99	83	98			
91	102	85	82	84			
114	105	105	105	99			
91	92	105	100	89			
114	100	96	111	105			
89	82	88	90	94			
103	91	93	87	92			
83	71	93	90	81			
74	71	69	67	NA			
88	89	83	84	86			
88	82	83	84	90			
98	105	93	96	101			
74	71	69	67	73			
86	91	86	90	88			
93	105	90	83	90			
85	82	87	78	84			
91	86	92	100	89			
75	72	75	67	73			
97	98	89	94	98			
88	80	88	89	82			
79	84	87	89	77			
106	109	113	111	107			
102	80	102	88	84			
98	112	101	94	93			
98	86	87	111	96			
114	112	105	111	107			
95	90	101	105	95			
98	96	79	97	89			
82	84	86	83	82			
97	94	95	105	92			
94	112	104	69	100			
84	81	79	80	75			
88	105	86	87	94			
83	77	81	67	83			
98	105	92	92	92			
106	112	95	102	102			
94	91	97	90	98			
91	92	87	98	94			
89	72	94	94	83			
102	100	105	101	107			
103	103	94	96	107			
96	89	88	94	91			
89	86	105	105	83			
112	112	113	105	100			
74	71	69	84	77			
74	73	69	72	74			
102	99	100	96	92			
106	85	113	94	100			
91	80	88	107	92			
94	88	104	103	93			
98	95	94	95	89			
85	86	91	73	86			
108	92	103	110	97			
90	96	95	84	82			
74	71	69	67	73			
81	88	86	73	93			
104	98	108	84	97			
90	108	83	79	93			
95	103	102	91	89			
85	81	94	92	86			
114	96	113	107	89			
114	112	113	111	107			
93	95	93	89	90			
104	92	105	110	104			
92	103	88	98	96			
100	95	90	95	93			
92	94	92	84	104			
77	79	81	73	83			
86	91	86	86	92			
87	87	85	98	83			
91	82	86	90	83			
102	97	97	97	96			
100	92	103	106	84			
113	112	102	106	107			

par1 <- as.numeric(par1) #colour
par2<- as.logical(par2) # Notches ?
par3<-as.numeric(par3) # % 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.')}
lotrm<-as.integer(length(y[1,])*par3/100)+1
hitrm<-as.integer(length(y[1,])*(100-par3)/100)
y1<-array(dim=c(dim(y)[1], hitrm-lotrm+1), dimnames=list(dimnames(y)[[1]], 1:(hitrm-lotrm+1) ))
for(i in 1:dim(y)[1]){
tmp<-order(y[i,])
y1[i,]<- y[i, tmp[lotrm:hitrm] ]
}
bitmap(file='test2.png')
pairs(t(y))
dev.off()
y<-y1
z <- as.data.frame(t(y))
bitmap(file='test1.png')
(r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=par2,col=par1))
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,'Variable',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)
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,round(r$stats[j,i], digits=2))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
if (par2){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Notches',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,'lower bound',1,TRUE)
a<-table.element(a,'median',1,TRUE)
a<-table.element(a,'upper bound',1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
a<-table.element(a,round(r$conf[1,i], digits=2))
a<-table.element(a, round(r$stats[3,i], digits=2))
a<-table.element(a,round(r$conf[2,i], digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Means',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,hyperlink('trimmed_mean.htm','trimmed mean','definition of trimmed mean'),1,TRUE)
a<-table.element(a,hyperlink('unbiased1.htm','unbiased SD','definition of unbiased SD'),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,round(mean(unlist(z[i]), trim=par3/100, na.rm=TRUE), digits=2))
a<-table.element(a,round(sd(unlist(z[i]), na.rm=TRUE), digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')