[gyrovagueGeist]

The uncertainty is epistemic not aleatoric. The percentage represents our knowledge about the system at the time of measurement propagated through the forward model and is not an inherit random process in the system/model itself.

[s1artibartfast]

If your model is consistently wrong in a statistically predictable way, either your measurement or model is inaccurate.

A 3% chance that never occurs is an inaccurate prediction.

[msandford]

Right! Yes absolutely!

It's wrong because the measurements are suggestive of possibility, rather than certain of it.

If we observe an asteroid that with two poor measurements is determined to be headed away from Earth, that's the end. Look no further.

If we observe an asteroid with two poor measurements that has some significant chance of hitting, more and better measurements are made. Then very often those better measurements show it was never actually going to hit anyhow.

But we never would have known without the better measurements, and we never would have devoted more time to making better measurements without a reason to do so.

A 3% chance that never occurs is because that 3% is based on data that's at the limit of what the telescopes can provide, not based upon bad math.

[MauranKilom]

Then what does 3% mean? Surely it means "given the data we have, one in every 33 will hit". Since that empirically doesn't happen, it must be that "the data we have" has a very low prior probability of being real. In other words, the measurement noise seems distributed in a way that over-represents unlikely trajectories.

Hence it seems that it would lead to more accurate predictions if the measurements and their uncertainties were fitted to a model that corrects for the prior probability of observing an asteroid on a given trajectory/making a certain observation.

This discrepancy between distribution of measurement error vs distribution of actual trajectories is what people are wondering about, because it seems interesting to know more about (e.g. "why are certain trajectories less likely?").

[s1artibartfast]

Despite all the people coming out of the Woodworks with weird theories, my best one is that the 3% number doesn't take into account their entire measurement process and sampling.

It's is similar to P hacking.

[msandford]

I don't think you understand how this works at all. You might read up on this here if you want to learn more. https://astronomy.stackexchange.com/questions/8450/how-is-th...

If you just want to argue with people, feel free. But based on how this conversation has been going it doesn't seem like you want to learn.

[s1artibartfast]

Setting your condescension aside, I browsed the thread.

I understand that calculating trajectories is difficult.

If someone claims something like a 3% impact probability, and they are wrong 99.999% of the time, that speaks to a methodological error in how the numbers are conveyed and or defined.

I work in medical devices and testing. I perform tests like X percentage of patients will die based on the statistical calculations. You may undergo treatment with a medical device that I have worked on.

[canadaduane]

That conclusion may be too early to reach with confidence, based on the limited data!