Thought experiment: If a bicycle cannot fly, is it a defective bicycle?
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What models CAN do for you is show the potential size of a problem and persuade non-experts that it is worth fixing. The
#coronavirus models did just that. If there was an award for "best prediction model of all time," the#coronavirus models would be contenders.Show this thread -
The lower bounds of the models said 100K deaths but now have been revised to 60K. That's a 40% change! Terrible models! Fire everyone involved! Right?
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Keep in mind the models had a range from 100K at the low end, with mitigation, to over 1 million without. If the actual death toll comes in at 140K with mitigation, would you say the models were wrong or right? I think you would say they were damned good.
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But if we miss the bottom estimate by exactly the same amount on the low side, and the final tally is 60K dead, you call that a gross miss. Yet it would be a miss by exactly as much as the 140K, only in the other direction.
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I contend there is an illusion here that is skewing opinions. If you compare the revised 60K estimate to 100K, it looks like a big difference. But if you consider the range of uncertainty was 900K, depending on mitigation, then 60K and 100K are in the same ballpark.
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End of conversation
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There is no science for predicting the future
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Stanford and Oxford got it right. These models are not that complicated.https://justthenews.com/politics-policy/coronavirus/stanford-doctors-coronavirus-fatality-rate-may-be-far-lower-current …
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“Fog of war.” And as you were asking for specific numbers on how many ventilators we had, were being produced, would need, and where, we were (and are) in that fog. A little mea culpa?
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I got that one
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Some high net worth financial advisors might suggest otherwise...
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