Logistic Regression, Generalized Linear Model, Machine Learning, Data Science, Statistical Learning.
further (i.e. to analyze the breakdown of sum of square errors by ignoring the interaction term which destroys linearity) but if there is a significant interaction then we can’t proceed further and our analysis halts there. But why do they love linearity so much? The key is interpretability where