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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

Lihat Kursus

Petunjuk latihan

  • Explain HOPPINESS by price.ratio using the function glm() and the argument family = binomial. Assign the result to an object named logistic.model.
  • Obtain the coefficients of the logistic.model by using the function coef().

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Explain HOPPINESS by price.ratio
___ <- ___(___, family = ___, data = choice.data)

# Obtain the coefficients
Edit dan Jalankan Kode