A few lessons learned along the way in completing my PhD

The mysteries multiply as we look through the literature but some answers are still forthcoming.

The mystery continues, leading us down an algorithmic path filled with broken sticks.

A parameter collapses, a sophisticated model looms afoot and we find the start of a trail of clues in this unexpected mystery.

An overview of two of the main obstacles to causal inference: Confounding and Selection Bias

An overview of the conditions required for instrumental variables and an example application in the built environment

A motivation and illustration of some of the basic principles underlying Causal Inference