Statistics - Causation - Causality (Cause and Effect) Relationship

1 - About

Cause and Effect Relationship.

Nothing beats a simple, elegant, controlled, randomized experiment if you want to make strong claims about causality.

Causal inference is a difficult and slippery topic, which cannot be answered with observational data alone without additional assumptions.

Causation comes generally from directed research. From the raw data, you got generally a correlation but not a causation. An other approach is to say that if X causes Y, then the noise affecting X will also affect Y.

3 - Requirements

Strong causal claims require:

4 - Documentation / Reference

data_mining/causality.txt · Last modified: 2017/09/13 21:21 by gerardnico