Fitting a Poisson regression
Continuing with the crab
dataset you will fit your first Poisson regression model in this exercise.
The crab
dataset has been preloaded in the workspace.
This is a part of the course
“Generalized Linear Models in Python”
Exercise instructions
- Import
statsmodels.api
library assm
. - Import
glm
fromstatsmodels.formula.api
. - Using
Poisson()
for the response distribution fit the Poisson regression withsat
as the response andweight
for the explanatory variable. - Display the model results using
.summary()
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import libraries
import ____.____ as sm
from ____.formula.api import ____
# Fit Poisson regression of sat by weight
model = ____('____ ~ ____', data = ____, family = ____.____.____).____
# Display model results
____(model.____)
This exercise is part of the course
Generalized Linear Models in Python
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.
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