The project analyses 140'000 daily meteorological measurements of 24 variables from 49 different Australian cities between the 2008 and 2017. The main aim was to adapt a multiple linear regression model to the meteorological conditions (pressure, air direction, irradiation, ...) on day i wrt the quantity of fallen rain of day i+1, to overcome serious residuals' correlation the Cochrane-Orcutt procedure was applied. Another approach was to predict whether it could rain or not using logistic regression.
This project was made in collaboration with Luca Dal Zotto for the Statistical Learning Course @ Unipd.