Imagine you are give the following problem:
- There is a 50% chance of diagnosing an illness correctly as "Known" instead of "Unknown".
- There is a 50% that available treatments "Control" the "Known" illness (and 50% they do not,lets us "Chaos" as a label for out of control)
What are the chances the patient has an "Unknown" illness that is out of control (in “Chaos”)
Initially I thought I could solve it with this code:
cause = CategoricalDistribution[{"Known", "Unknown"}, {1/2, 1/2}]
control = CategoricalDistribution[{"Control", "Chaos"}, {1/2, 1/2}]
Probability[ ca == "Unknown" && co == "Chaos" , {ca \[Distributed] cause, co \[Distributed] control} ]
Which results in the answer $\frac{1}{4}$ (0.25)
But then I realized that is only if probability of pick a treatment that "Controls" condition is independent of probability of "Known" condition, which feels intuitively wrong.
How can I tell Mathematica that if the illness is "Known" the probability to "Control" it should be higher, say: 60%, and if the illness is “Unknown" the probability to "Control" it is lower (say "40%") ?
CategoricalDistribution
, as explained in the corresponding section of the reference page. $\endgroup$