ABSTRACT
We have introduced probability as a language for expressing our degrees of belief or uncertainties about events. Whenever we observe new evidence (i.e., obtain data), we acquire information that may affect our uncertainties. A new observation that is consistent with an existing belief could make us more sure of that belief, while a surprising observation could throw that belief into question. Conditional probability is the concept that addresses this fundamental question: how should we update our beliefs in light of the evidence we observe?
