Causal inference is important in medical research to help determine if treatments are beneficial and if natural exposures are harmful. In many settings, data collection makes causal inference ...

Bayesian networks are probabilistic graphical models that encode conditional dependencies among variables within a directed acyclic graph. In the context of causal inference, these networks provide a ...

This course is available on the MPhil/PhD in Economic Geography, MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in Regional and Urban Planning Studies, MRes in ...

A new study links increased plastic waste imports to measurable increases in PM2.5 near waste disposal sites in Indonesia.

Time series is data collected over time, and statistical learning is a field of statistics and machine learning that develops algorithms to model and interpret this data. Together, they use ...