4.14 Interpreting Poisson Regression

An increase in \(X_j\) by one unit is associated with a change in \(E(Y) = \lambda\) by a factor of \(exp(\beta_j)\)

Figure 4.16: Results for Poisson regression model fit to predict bikers in the Bikeshare data. For the qualitative variable weathersit, the baseline level corresponds to clear skies.

A change in weather from clear to cloudy skies is associated with a change in mean bike usage by a factor of

exp(-0.08) = 0.923

i.e. on average, only 92.3% as many people will use bikes compared to when it is clear (baseline weather).