This analysis is to look into aspects of analysing churn data. Customer churn time is the length of time a customer stays with a company before leaving. This is a vital metric in many businesses and there is great interest in estimating it. The churn time changes, so we always want to estimate it with the most recent data available. This is statistically challenging as many (hopefully most) customers will have not churned at the time when the data is collected. This means that customer churn data is highly censored.

This is to create the best model that can predict if it is going to be cloudy tomorrow for 10 locations in Australia.

This visualisation depicts the Global Macro-economic analysis using Vegalite.