Model fitting step-by-step
In the video lecture, you learned the key components for fitting a GLM in Python using the statsmodels package. In this exercise you will define the components of the GLM step by step and finally fit the model by calling the .fit() method.
The dataset which you will use is on the contamination of groundwater with arsenic in Bangladesh where we want to model the household decision on switching the current well.
The columns in the dataset are:
switch: 1 if the change of the current well occurred; 0 otherwisearsenic: The level of arsenic contamination in the welldistance: Distance to the closest known safe welleducation: Years of education of the head of the household
Dataset wells has been preloaded in the workspace.
Diese Übung ist Teil des Kurses
Generalized Linear Models in Python
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# Define the formula the the logistic model
model_formula = '____ ~ ____'