Abstract
Modelling of the number of days of cannabis consumption. This article aims to show the appropriate way to model a count type response variable from a practical viewpoint. The results show that the Poisson regression model is more appropriate than the linear regression model, as it takes count data characteristics into consideration, although the presence of overdispersion indicates the correction of standard errors in the Poisson model parameters and may cause modelling through the negative binomial model. The Zero Inflated model shall be used whenever there is an excessive number of zeros. To do so, the number of days of cannabis consumption in accordance with peer group consumption and cannabis consumption by parents and siblings is modelled.
