I was given the following problem:
The probability of being sick is $0.05$. Probability of a test detecting sickness when you're truly sick is $0.8$. Probability of detecting sickness when you're not sick is $0.01$. If you take 3 consecutive tests, and they all are positive, what is the actual probability of you being sick?
I think this is a Bayes Rule problem. Let $S$ denote that you're truly sick and $S^c$ denote that you're not sick. Let $+$ and $-$ denote positive and negative test, respectively. I think first I need to find $P(S|+)$, probability that you're sick given one positive test.
We know: \begin{align} P(+|S) = 0.8 \\ P(-|S) = 0.2 \\ P(+|S^c) = 0.01 \\ P(-|S^c) = 0.99 \\ \end{align}
According to Bayes rule, we have $$ P(S|+) = \frac{P(+|S)P(S)}{P(+)} $$
Then I think I can find the marginals using: \begin{align} P(+) = P(+|S)P(S) + P(+|S^c)P(S^c) \\ P(S) = P(S|+)P(+) + P(S|-)P(-) \\ \end{align}
Assuming this is the correct approach, and I find $P(S|+)$, how does this generalize to the case where there are 3 consecutive positive tests, i.e., how do I find $P(S|+,+,+)$?