A logistic model for beer demand
The linear model does not fit the data when it comes to predicting purchase probabilities. You need a response function that bounds the model predictions between zero and one.
The logistic response function can do this job for you. Therefore, you will need the function glm(). The function glm() works very similar to the lm() function. The main difference is the additional family argument. As HOPPINESS is a binary variable, you have to specify the family argument as binomial.
Latihan ini adalah bagian dari kursus
Building Response Models in R
Petunjuk latihan
- Explain
HOPPINESSbyprice.ratiousing the functionglm()and the argumentfamily = binomial. Assign the result to an object namedlogistic.model. - Obtain the coefficients of the
logistic.modelby using the functioncoef().
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# Explain HOPPINESS by price.ratio
___ <- ___(___, family = ___, data = choice.data)
# Obtain the coefficients