5.1.3

library(languageR)

oldFrench[1:3, 1:4]
oldFrenchMeta[1:3, ]

oldFrench.ca = corres.fnc(oldFrench)
summary(oldFrench.ca, head = TRUE)
plot(oldFrench.ca)
plot(oldFrench.ca, rlabels = oldFrenchMeta$Genre, rcol = as.numeric(oldFrenchMeta$Genre), rcex=0.5, extreme = 0.1, ccol = "blue")

prose = oldFrench[oldFrenchMeta$Genre == gproseh & !is.na(oldFrenchMeta$Year),]
proseinfo = oldFrenchMeta[oldFrenchMeta$Genre==hproseh & !is.na(oldFrenchMeta$Year),]
proseinfo$Period = as.factor(proseinfo$Year <= 1250)
prose.ca = corres.fnc(prose)
plot(prose.ca, addcol = F, rcol = as.numeric(proseinfo$Period) + 1, rlabels = proseinfo$Year, rcex = 0.7)

proseSup = oldFrench[oldFrenchMeta$Genre == "prose" & is.na(oldFrenchMeta$Year),]
corsup.fnc(prose.ca, bycol = F, supp = proseSup, font = 2, cex = 0.8, labels = substr(rownames(proseSup), 1, 4))

variationLijk[1:5,1:4]
colnames(variationLijk)
chisq.test(variationLijk)
variationLijk.ca = corres.fnc(variationLijk)
plot(variationLijk.ca)

5.1.4

dutchSpeakersDist.d = as.dist(dutchSpeakersDist)
dutchSpeakersDist.mds = cmdscale(dutchSpeakersDist.d, k = 3)
head(dutchSpeakersDist.mds)
dat = data.frame(dutchSpeakersDist.mds, Sex = dutchSpeakersDistMeta$Sex, Year = dutchSpeakersDistMeta$AgeYear, EduLevel = dutchSpeakersDistMeta$EduLevel)
dat = dat[!is.na(dat$Year),]
dat[1:2, ]
par(mfrow=c(1,2))
plot(dat$Year, dat$X1, xlab="year of birth", ylab = "dimension 1", type = "p")
lines(lowess(dat$Year, dat$X1))
boxplot(dat$X3 ~ dat$Sex, ylab = "dimension 3")
par(mfrow=c(1,1))
cor.test(dat$X1, dat$Year, method="sp")
t.test(dat$X3~dat$Sex)