I used Poisson regression model to model how count of user actions on a website (dependent variable) are explained by website content (independent variables). The dependent variable distribution is shown in this plot.
As you can see, the distribution is positively skewed and has a long tail. The results of the Poisson regression model from
glm in R are shown here:
As you can see, residual deviance is much greater than the degrees of freedom, so there is overdispersion. Next, I tried Quasipoissson model that gave these results:
I see that the Quasipoisson model shows that none of the independent variables are significant. I am a little unsure how to interpret these results. Am I handling the overdispersion incorrectly, or am I using independent variables that just do not explain the variation in my dependent variable?