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Female hurricanes being 'quite a bit deadlier' than male hurricanes may well be surprising but it has equal probability with the event that male hurricanes are

by quacker 12y ago

Female hurricanes being 'quite a bit deadlier' than male hurricanes may well be surprising but it has equal probability with the event that male hurricanes are 'quite a bit deadlier' than female hurricanes. I definitely agree with this. What you're describing is a rare event. Rare events happen, just rarely. I'll restate this hurricane problem. Suppose we're flipping a fair coin. We should expect to see roughly equal numbers of heads and tails. If I flip the same coin a thousand times and see 523 heads, that seems "reasonable". It's certainly possible to get 873 heads, but I might start to wonder if the coin is really fair not because it's very unlikely to get 873 heads with a fair coin (and it is very unlikely) but because it's more plausible that the coin is biased. That is, it's more likely that a coin that gets heads with some probability near 0.873 produces 873 heads in a thousand flips than it is for fair coin to produce 873 heads in a thousand flips. In the context of hurricanes, if we assign genders randomly we expect close to equal deadliness between male and female hurricanes. If there have been a thousand hurricanes, and female hurricanes cause 87.3% of all hurricane deaths, well... I might start wondering if giving hurricanes female names somehow makes a hurricane more deadly. Of course, this is all in the context of a uniform distribution of names on hurricanes.

coherentpony 12y ago
>Suppose we're flipping a fair coin. We should expect to see roughly equal numbers of heads and tails. If I flip the same coin a thousand times and see 523 heads, that seems "reasonable". It's certainly possible to get 873 heads, but I might start to wonder if the coin is really fair not because it's very unlikely to get 873 heads with a fair coin (and it is very unlikely) but because it's more plausible that the coin is biased. The first sentence said the coin was fair. Given that the coin is fair, flipping 873 heads in a thousand tosses is perfectly fine, it just has a smaller probability than flipping 523 heads (as you have already clearly stated). Believing that the coin is biased is nothing more than human scepticism because we were told the coin was fair. Given that the coin is biased, you are right to state that the probability is higher. Probability is about working with given information, not about being suspicious about given information. If you had a reason to believe the coin wasn't fair, it being fair would not be part of the information given. The point I'm making here is that it is easy to mislead someone. You told me the coin was fair. If you then cheat and flip a biased coin there is no way for me tell if the coin is biased because it is my belief the coin is fair. Prior information doesn't change after you look at the data. The distribution taking into account observations is different, and it is called the posterior distribution. You have essentially taken my statement: What you're describing is a rare event. Rare events happen, just rarely. and repeated exactly my argument back to me. Given that the hurricane gender is assigned uniformly at random, it is fine to observe that female hurricanes are more deadly. Quite a bit more deadly is nothing more than random chance. Remember, the prior was that they were assigned uniformly at random. It could be the case that people assign names to hurricanes based on behaviour, path, time of year, or whatever other characteristic you like (and perhaps this is done subconsciously). In this case, the prior belief is that they are no longer assigned uniformly at random, but a human assigns them genders correlated with some physical quantity. Now, is it surprising that female hurricanes are more deadly? Perhaps not.
- theseoafs 12y ago
  If any of this were true, we wouldn't have statistics departments at universities. Of course you can draw conclusions from data. Of course we should be skeptical of an assumption if the data shows that an incredibly unlikely sequence of events happened in light of that assumption. By the way, hurricanes are assigned genders alternately. The genders go back and forth.
  - coherentpony 12y ago
    If any of this were true, we wouldn't have statistics departments at universities. I'm not sure what statement you're making here. Of course you can draw conclusions from data. I never once said you could not make conclusions from data. The data I had was that a) a fair coin was flipped; and b) out of 1000 flips, 873 of them were heads. Sure, this event has a small probability, but so what? Does it mean the coin was biased? Of course not. You told me that the coin was fair. If you didn't give me a) then I could certainly try to tell the probability of how biased the coin was doing an inference based on the data. But that wasn't part of the parent's question or background information. You go with what you know, not what you're sceptical about. If you win the lottery (which has a tiny probability), does that mean the lottery was biased towards those numbers? Of course we should be skeptical of an assumption if the data shows that an incredibly unlikely sequence of events happened in light of that assumption. Let me pose the question to you. You are given a fair two-sided coin. You flip the coin 1000 times. 875 of the flips turn up heads. Is the coin biased?
    - theseoafs 12y ago
      > I'm not sure what statement you're making here. The statement I'm making is that you can simply brush off every scientific study by saying "yeah, that's just random chance, don't worry about it". The way that you're looking at this is completely backwards. If the data shows something incredibly unlikely happened, that means we should re-evaluate our assumptions. > Let me pose the question to you. You are given a fair two-sided coin. You flip the coin 1000 times. 875 of the flips turn up heads. Is the coin biased? Probably.

by quacker 12y ago

coherentpony 12y ago

>Suppose we're flipping a fair coin. We should expect to see roughly equal numbers of heads and tails. If I flip the same coin a thousand times and see 523 heads, that seems "reasonable". It's certainly possible to get 873 heads, but I might start to wonder if the coin is really fair not because it's very unlikely to get 873 heads with a fair coin (and it is very unlikely) but because it's more plausible that the coin is biased. The first sentence said the coin was fair. Given that the coin is fair, flipping 873 heads in a thousand tosses is perfectly fine, it just has a smaller probability than flipping 523 heads (as you have already clearly stated). Believing that the coin is biased is nothing more than human scepticism because we were told the coin was fair. Given that the coin is biased, you are right to state that the probability is higher. Probability is about working with given information, not about being suspicious about given information. If you had a reason to believe the coin wasn't fair, it being fair would not be part of the information given. The point I'm making here is that it is easy to mislead someone. You told me the coin was fair. If you then cheat and flip a biased coin there is no way for me tell if the coin is biased because it is my belief the coin is fair. Prior information doesn't change after you look at the data. The distribution taking into account observations is different, and it is called the posterior distribution. You have essentially taken my statement: What you're describing is a rare event. Rare events happen, just rarely. and repeated exactly my argument back to me. Given that the hurricane gender is assigned uniformly at random, it is fine to observe that female hurricanes are more deadly. Quite a bit more deadly is nothing more than random chance. Remember, the prior was that they were assigned uniformly at random. It could be the case that people assign names to hurricanes based on behaviour, path, time of year, or whatever other characteristic you like (and perhaps this is done subconsciously). In this case, the prior belief is that they are no longer assigned uniformly at random, but a human assigns them genders correlated with some physical quantity. Now, is it surprising that female hurricanes are more deadly? Perhaps not.

theseoafs 12y ago
If any of this were true, we wouldn't have statistics departments at universities. Of course you can draw conclusions from data. Of course we should be skeptical of an assumption if the data shows that an incredibly unlikely sequence of events happened in light of that assumption. By the way, hurricanes are assigned genders alternately. The genders go back and forth.
- coherentpony 12y ago
  If any of this were true, we wouldn't have statistics departments at universities. I'm not sure what statement you're making here. Of course you can draw conclusions from data. I never once said you could not make conclusions from data. The data I had was that a) a fair coin was flipped; and b) out of 1000 flips, 873 of them were heads. Sure, this event has a small probability, but so what? Does it mean the coin was biased? Of course not. You told me that the coin was fair. If you didn't give me a) then I could certainly try to tell the probability of how biased the coin was doing an inference based on the data. But that wasn't part of the parent's question or background information. You go with what you know, not what you're sceptical about. If you win the lottery (which has a tiny probability), does that mean the lottery was biased towards those numbers? Of course we should be skeptical of an assumption if the data shows that an incredibly unlikely sequence of events happened in light of that assumption. Let me pose the question to you. You are given a fair two-sided coin. You flip the coin 1000 times. 875 of the flips turn up heads. Is the coin biased?
  - theseoafs 12y ago
    > I'm not sure what statement you're making here. The statement I'm making is that you can simply brush off every scientific study by saying "yeah, that's just random chance, don't worry about it". The way that you're looking at this is completely backwards. If the data shows something incredibly unlikely happened, that means we should re-evaluate our assumptions. > Let me pose the question to you. You are given a fair two-sided coin. You flip the coin 1000 times. 875 of the flips turn up heads. Is the coin biased? Probably.