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January 1st, 2013, 09:18 PM   #1
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Stats question

I ran across the following in a post by an Austrian professor who, at the time, was advocating the death penalty for Global Warming deniers. He has since apologized, and retracted his stand. The Global Warming bit doesn't really interest me, and isn't relevant. It's that statistics part I'm curious about. So here's the quote (with one parenthetical clarification by me):

Quote:
For the purpose of argument, let’s give the GW deniers the benefit of the doubt and imagine that the scientists are wrong with a high probability, say 90%. If they (the scientists) are right, some 100 million people will die as a direct result of GW. Probably more like a billion, but this is a conservative estimate. If the probability of that happening is only 10%, then effectively “only” 10 million people will die.
I'm not any kind of an expert on stats. For the record, the professor who wrote the above is a professor of music, so while he might know plenty about stats, he also might not. But, here's my understanding of the situation he's describing. If the scientists are right, 100 million people die. If not, then 100 million people don't die. If there's a 90% chance (however imaginary that chance might be) that the scientists are wrong, then there is a 10% chance that 100 million people die, and a 90% chance they don't. I can't see a way to get to 10 million people dying.

Obviously there's a chance that if the scientists are wrong, they still might be partially right, but it's hard to see whether or not that's how he's getting to his 10 million number. The one potential flaw I can see in my own logic is that I'm assuming there are only two outcomes, and that they are mutually exclusive. If that's not the case, then the 10 million number could make sense. Anyway, that's my read on all of this, am I right, or is our Austrian professor?
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January 2nd, 2013, 03:02 PM   #2
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Re: Stats question

All the professor is doing is computing the mathematical expectation. In this context it is meaningless since we are dealing with a one time event (GW or not GW), while expectations are useful when the experiments are repeated.
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