## Aufgabe 2

## (a)
daten <- read.table("/home/wkarcher/Desktop/apprentice.dat", header=TRUE)
attach(daten)
glm.move1 <- glm(Apprentices ~ 1+Distance+Population+Urbanization+Location, family=poisson(link="log"))
summary(glm.move1)

## (c)
detach(daten)
daten[daten[,5]=="West",5] <- "North"
attach(daten)
glm.move2 <- glm(Apprentices ~ 1+Distance+Population+Urbanization+Location, family=poisson(link="log"))
summary(glm.move2)

## (d)
glm.lqt <- glm(Apprentices ~ 1, family=poisson(link="log"))
anova(glm.lqt, glm.move2, test="Chisq")

## (e)
# mit gerundeten Koeffizienten
exp(4.251947-0.033857*50+0.021342*40-0.033452*50+1.052247*1)
# mit "exakten" Koeffizienten
exp(glm.move2$coefficients[1]+glm.move2$coefficients[2]*50+glm.move2$coefficients[3]*40+glm.move2$coefficients[4]*50+glm.move2$coefficients[5]*1)
# mit der R-Funktion predict()
predict(glm.move2, data.frame(Distance=50,Population=40,Urbanization=50.0,Location="South"), type="response")