But the odds aren’t additive. If you sleep under a tree 4999 times and nothing happens, that doesn’t mean the 5000 time you sleep under one you’ll get crushed.
I don't believe the odd that you get crushed once if you play it multiple times are not as good as the odd of not getting crushed when playing only one time.
So you have 0.02% chance of getting crushed each time.
(1 - 0.0002)^10950 = 0.1119
1 - 0.1119 = 0.8881
So the probability of getting crushed at least one night over 30 years is ~89%
I think, my stats are from school over 10 years ago.
This is because, for example, if you flip a coin, each time you still only have 50% chance of getting tails. But the chances that you flip it 10 times in a row and never get heads are a lot less than 50%.
That's said. Another tricky bit is, what was measured when we said 1/5000 chance? This is where data can get confusing. Was that the odd of a tree falling at any given night? Or was that the odd of someone being crushed by a tree in their sleep at night? Or was it the odd of someone being crushed by a tree ever? Or the odd of a particular tree falling at night?
That's often where any prediction already begins to break down. For example, sorry to use the vaccines as an example, but when we say 90% efficacy, it means, out of x number of people who got a vaccine during the trial, 90% of those didn't get covid during some period, while in the placebo group it would be some other % who got it.
Reasoning about this already is tricky. You don't know the priors. What was the odd your participants were exposed to COVID? What if you'd measured over a longer period of time? What if that was just a lucky bunch?
Each and every time you have a 1 in 5000 chance.