Baye’s Theorem provides a simple model for reasoning about conditional probability using algebra. Conditional probability is a way to incorporate prior knowledge into a measure of probability.
Conditional Probability ===
Say 40% of a population has an illness. I can estimate that I have a 40% chance of having that illness as a member of that population.
Say 66% of elderly folks in that population have that illness. I can more accurately estimate that I have a 66% chance of having that illness *given* that I am elderly.
Young & healthy – .5
Young & ill – .2
Old & healthy – .1
Old & ill – .2
Sum = 100%
edit:
Back to Baye’s ===
To tie this back to Baye’s without getting into math, Baye’s formula allows you to translate between the “elderly *given* ill” and “ill *given* elderly” scenarios by plugging and chugging into a nifty lil formula.
Thanks toferino 🙂
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