1
# (a)
attach(glottal)
table(geschlecht, verschluss)

# (b)
tab = table(geschlecht, verschluss)
barplot(tab, beside=T, legend=T)

# (c)
chisq.test(tab)
# X-squared = 2.4037, df = 2, p-value = 0.3006
# Nein.

2. 
x = lvoc[1,]
n = apply(lvoc, 2, sum)
jahr = c(0:3)
prop.trend.test(x, n, jahr)
# X^2[1] = 13.4, p < 0.001

# das gleiche mit glm
y = t(lvoc)
lab = 0:3
o = glm(y ~ lab, "binomial")
anova(o, test="Chisq")

# X^2[1] = 13.52, p < 0.001

p = y[,1]/apply(y, 1, sum)

plot(lab, p, xlab="", ylab="Proportion")
m = coef(o)[2]
k = coef(o)[1]
plot(lab, p, xlab="", ylab="Proportion", xlim=c(-8, 8), ylim=c(0, 1))
m = coef(o)[2]
k = coef(o)[1]
curve(exp(m*x + k)/(1+ exp(m*x+k)), add=T, col=2)

(See chiantwortenb.txt for further info)


3. 
ui = as.matrix(ui)
f2 = as.numeric(rownames(ui))
ui.g = glm(ui ~ f2, binomial)
p = ui[,1]/apply(ui, 1, sum)
plot(f2, p)
coefs = coef(ui.g)
k = coefs[1]
m = coefs[2]
curve(exp(m*x + k)/(1+ exp(m*x+k)), add=T, col=2)
umkipp = -k/m
abline(v = umkipp)


4. 
stimm = factor(c("J", "J", "J", "J", "N", "N", "J", "N", "J", "J", "J", "N", "J", "N", "N", "N", "J", "J", "N", "J"))
dialekt = factor(c(rep("B", 12), rep("H", 8)   )    )
o = glm(stimm ~ dialekt, binomial)

5. 
lost3 = as.matrix(read.table(paste(pfad, "lost3.txt", sep="/")))
r = rownames(lost3)
alter = factor(substring(r, 1, 1))
gesch = factor(substring(r, 3, 3))
p = lost3[,1] / apply(lost3, 1, sum)
interaction.plot(alter, gesch, p)
g = glm(lost3 ~ alter * gesch, binomial)
anova(g, test="Chisq")


6. 
ver.m = as.matrix(read.table(paste(pfad, "verm.txt", sep="/")))
ver.w = as.matrix(read.table(paste(pfad, "verw.txt", sep="/")))
correct.m = diag(ver.m)
correct.f = diag(ver.w)
total.m = apply(ver.m, 1, sum)
total.f = apply(ver.w, 1, sum)

prop.m = correct.m/total.m
prop.f = correct.f/total.f
p = c(prop.m, prop.f)
plabs = names(p)
glabs = c(rep("m", 3), rep("f", 3))

col = c(rep(2, 3), rep(3, 3))
barplot(p, beside=T, col=col)

incorrect.m = total.m - correct.m
incorrect.f = total.f - correct.f

dat.m = cbind(correct.m, incorrect.m)
dat.f = cbind(correct.f, incorrect.f)
dat = rbind(dat.m, dat.f)
clabs = factor(rownames(dat))
glabs = factor(c(rep("m", 3), rep("f", 3)))
o = glm(dat ~ clabs * glabs, binomial)

o2 = glm(dat ~ glabs * clabs, binomial)