Lösungen
Aufgabe SLR 1 Lsg
album1 <- read.delim("Daten/Album Sales 1.dat", header = TRUE)
ggplot(album1, aes(x = adverts, y = sales)) +
geom_point() +
geom_smooth(method=lm, se=FALSE) +
theme_bw()
albumSales.1 <- lm(sales ~ adverts, data = album1)
pander(summary(albumSales.1))
# #---- Modell1_Pred_1
#
# new_input <- data.frame(educ = 10:14)
# pander(predict(model_1, newdata = new_input), style = "rmarkdown")
Aufgabe MLR 1 Lsg
album2 <- read.delim("Daten/Album Sales 2.dat", header = TRUE)
# Erstes Modell
albumSales.2 <- lm(sales ~ adverts, data = album2)
# zweites Modell
albumSales.3 <- lm(sales ~ adverts + airplay + attract, data = album2)
# Ausgabe Ergebnisse
pander(summary(albumSales.2))
pander(summary(albumSales.3))
# Modellvergleich
anova(albumSales.2, albumSales.3)
Tol <- 1/vif(albumSales.3)
VIF <- vif(albumSales.3)