Relatedly, if you perform an experiment n times, and the probability of success is p, and the expected number of total successes kp is much smaller than one, then kp is a reasonable measure of getting at least once success, because the probability of getting more than one success can be neglected.
For example, if Bob plays the lottery for ten days, and each days has a 1:1000,000 chance of winning, then overall he will have a chance of 100,000 of winning once.
This is also why micromorts are roughly additive: if travelling by railway has a mortality of one micomort per 10Mm, then travelling for 50Mm will set you back 5 micomort. Only if you leave what I would call the ‘Newtonian regime of probability’, e.g. by somehow managing to travel 1Tm with the railway, you are required to do proper probability math, because naive addition would tell you that you will surely have a fatal accident (1 mort) in that distance, which is clearly wrong.
Relatedly, if you perform an experiment n times, and the probability of success is p, and the expected number of total successes kp is much smaller than one, then kp is a reasonable measure of getting at least once success, because the probability of getting more than one success can be neglected.
For example, if Bob plays the lottery for ten days, and each days has a 1:1000,000 chance of winning, then overall he will have a chance of 100,000 of winning once.
This is also why micromorts are roughly additive: if travelling by railway has a mortality of one micomort per 10Mm, then travelling for 50Mm will set you back 5 micomort. Only if you leave what I would call the ‘Newtonian regime of probability’, e.g. by somehow managing to travel 1Tm with the railway, you are required to do proper probability math, because naive addition would tell you that you will surely have a fatal accident (1 mort) in that distance, which is clearly wrong.
So, travelling 1Tm with the railway you have a 63% chance of dying according to the math in the post