USE: When your dependent variable is categorical. Your independent variable can have any measurement.

LOGISTIC REGRESSION dependent WITH independent.

b0: the log odds for the category 1 of the dependent variable when the independent variable’s category is 0

b1: how much larger or smaller the log odds becomes as the independent variable increases by 1 unit.

b0+b1: the log odds for the category 1 of the dependent variable when the independent variable’s category is 1.

b1 coefficient > 0 -> a 1 unit increase in X increases the likelihood/probability that y=1 This means that an increase in X makes the outcome of 1 more likely.

b1 coefficient < 0 -> a 1 unit increase in X decreases the likelihood/probability that y=1.  This means that an increase in X makes the outcome of 1 less likely.

Exp(B): < 1 -> we say „as low as” : a 1 unit increase in X decreases the likelihood/probability that y=1.  This means that an increase in X makes the outcome of 1 less likely. It indicates a negative effect.

Exp(B): > 1 -> we say „as high as” a 1 unit increase in X increases the likelihood/probability that y=1 This means that an increase in X makes the outcome of 1 more likely. It indicates a positive effect.

Exp(B)=1 -> no effect

We interpret the sign of the coefficient, not the magnitude! The magnitude cannot be interpreted using the coefficient because the different models have different scales of coefficients.

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