# Exercice 1

tab<-matrix(c(13,2,5,
20,2,8,
10,5,5,
7,1,22),ncol=3,byrow=TRUE)
colnames(tab) <- c("Univ", "Prepa", "Autres")
rownames(tab) <- c("A", "BDD'", "CE", "Tech")
summary(as.table(tab))
afc <-dudi.coa(tab, scan = FALSE)
afc
afc$tab
afc$eig
afc$c1
afc$l1
afc$co
afc$li
scatter(afc, method=1,clab.row=0.90,clab.col=1.5,posieig="none")

# Exercice 2
# Source:http://www.cons-dev.org/elearning/stat/multivarie/6-5/6-5.html

tab<-matrix(c(160,28,0,321,36,141,45,65,
35,34,1,178,8,0,4,0,
700,354,229,959,185,292,119,140,
961,471,633,1580,305,360,162,148,
572,537,279,1689,206,748,155,112,
441,404,166,1079,178,434,178,92,
783,1114,387,4052,497,1464,525,387,
65,43,21,294,79,57,18,6,
77,60,189,839,53,124,28,53,
741,332,327,1789,311,236,102,102),ncol=8,byrow=TRUE)
colnames(tab) <- c("hotel","locat","propri","parent","amis","tente", 	"villag","divers")
rownames(tab) <- c("Agriculteur","Salaries","Patrons","Cadre sup","Cadre moy","Employes","Ouvriers","Personnels","Autres actif","Non actifs")
summary(as.table(tab))
afc <-dudi.coa(tab, scan = FALSE)
afcin <- inertia.dudi(afc,col.inertia=T,row.inertia=T)
afcin$TOT
afcin$row.abs
afcin$row.rel
afcin$col.abs
afcin$col.rel
scatterutil.eigen(afc$eig,nf=3,box=T,sub="")
scatter(afc, method=1,clab.row=0.90,clab.col=1.5,posieig="none")