Next, they say the complexity of the global warming problem makes forecasting a fool’s errand. “There’s been no case in history where we’ve had a complex thing with lots of variables and lots of uncertainty, where people have been able to make econometric models or any complex models work,” Armstrong told me. “The more complex you make the model the worse the forecast gets.”
Counterexample: integrated circuits. Trying to simulate an Intel microprocessor is damn hard, but they work anyway. In general, engineers sometimes have to deal with the kinds of problems that this implies are impossible, and they frequently get the job done anyway.
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Um.
Probability of a head = 0.5 necessarily means that the expected number of heads in 1000 tosses is 500.
Probability of a head = 0.6 necessarily means that the expected number of heads in 1000 tosses is 600.
I don't think so. None of the available potential coin-states would generate an expected value of 600 heads.
p = 0.6 -> 600 expected heads is the many-trials (where each trial is 1000 flips) expected value given the prior and the result of the first flip, but this is different from the expectation of this trial, which is bimodally distributed at [1000]x0.2 and [central limit around 500]x0.8