3 ms·
>>if you receive P particles in a time period and don’t get ill, and repeat that immediately, is the probability of getting ill in that second period the same a
by mech422 5y ago
>>if you receive P particles in a time period and don’t get ill, and repeat that immediately, is the probability of getting ill in that second period the same as in the first, higher, or lower?
This is the part I was trying to figure out how to compute. I think the binomial distribution stuff deals with that.. eg how to calculate an 'overall' probability from n trials with p probability each.
But I'll have to read up more on it
- Someone 5y agoThat depends on how you model infection. If you treat it as gunshots, that is: if you didn’t get hit by the infection in the first time period, you’re 100% healthy, and just as likely to get hit in the second time period, the probability of surviving n trials each of probability p of getting infected is 1 - (1-p)^n. That’s a simple model, though. Another model may have your resistance decrease after being ‘attacked’ by the virus in the first period (as a boxer who gets knocked out in round 10 due to a blow that wouldn’t have hurt him in round 1), and/or it increasing (I would guess over longer time periods) because your body develops some resistance. Such models are likely better in the sense that they can better predict what happens, but also more complex, and their parameters may be harder to estimate.
- mech422 5y agothanks - those were very understandable examples!