Models are/were unreliable because the data was/is incomplete/corrupted.
Because model are terrible at predicting anything. Now, let’s discuss the models that are predicting catastrophic global warming.
Because it’s the same folks doing climate models?
I haven’t noticed the studies or the models being available for inspection by others, even though actual science requires results and the methodologies to be testable and repeatable. Just more wild ass guesses.
60,000 - 80,000 deaths seems to be realistic, slightly worse than some of the bad flu death years.
Now that deaths are in decline, and we know that UV light kills the virus well (although the media is too hung up on lying about what Trump said to report the actual news)- our economy can begin to open, and it is.
Most if not all of the economy will reopen over the next 30 days, despite recalcitrant Dem Governors.
It seems that way too many of these models are designed to show a desired outcome. If the data goes the wrong way, just let the software nudge it back to the appropriate direction.
Political polls are very much the same thing.
As they morphed with data being collected under the conditions being imposed, they got closer to reality.
The ones that finally predicted about 60K deaths in America seem to be proving out as we approach that number.
At this point I'm assuming this idiocy came from a COVID-19 model. :-P
+1.
these types of results are an indication of bias in the data
Not that it affects or negates anything else he says - but that's nonsense. Bias and variance are nearly independent; it's a well known phenomenon that a model have low variance but high bias.
Welcome anti science crowd!
First of all “model” is a very generic and overused word.
A predictive model is one that tries to extrapolate future events from present and/or historical data. Dynamic predictive models use algorithms based on processes that can influence change. Models are used in about everything from predicting consumer demand, weather forecasting, engineering, and ensuring safety of new products......
All models are not fully correct (black and white), that’s why they call them models. However, they provide guidance, but require expertise in knowing their assumptions, short comings, and range of validity. All models should have some verification and test results for range of applicability. I have been using and developing predictive models for many decades.
I like to think all models lie, and its the user’s job to figure out when and which models are lying. If you don’t trust models, you should never board an airplane, drive a car, take a medication, or listen to a weather forecast. However, never trust user’s/developer’s of models who have an agenda.
If you are not an expert in medical research, and have not seen the predictions of all the virus models, I doubt you have any claim to judging their validity and utilization in policy making. However, the agenda of many of you are clear. That is, current policy is incorrect and we must throw them out and open up the government. This notion is so “fourth world”, and I doubt much would change, other than creating a spike in new cases. The economy was killed by the virus long before policy for shelter-in-place policy was implemented. “Its the Virus stupid.”
Personally, I would like to see the evaluation and range of results and opinions from a team of reputable medical researchers, not just the opinion of some politically motivated doctor who only practices family medicine... and certainly not the opinion of uneducated biased layman. Also, data from economic models must be used in deciding which policy to follow, so experts in this field must be included as well. I have confidence that our elected president and his appointed team are having many heated arguments and reviewing difficult decisions. I do trust the President and his team will make the right decision.
For background, I was one of the earlier signers of the petition challenging the climate change/global warming hypothesis. Their agenda was clear and was used to select models that were supportive of their goals. It may be news to some of you, all models do not predict global warming.
Are we in the dark ages yet!
There is a bias in modelling. Suppose you task someone to develop a model of the effects of carbon on global warming. I guarantee you will find the model predicts global warming as a function of carbon. Now, if you task someone to develop a model of future temperatures, you will get a different answer.
Or, IOW, you want a model of sickness and deaths from a virus, that model will over predict. In effect, you will get what you pay for.
The problem with academia is there are too many academics...