We don't make statistical exemptions for vehicle fatalities just because the driver failed in a way we don't like. Drunk driving fatalities count too. If a 3 year old hit the accelerator and goes straight into a brick wall, that counts. They all count.
If that 3 year old shot himself with a gun inside the truck, which has nothing to do with the vehicle he was in, does it still count?
We can, and especially in this small sample size, we can exclude it if we want to. The question is if a cybertruck is a dangerous vehicle, not can I have mental illness and shoot myself inside of my vehicle, which happens to be a cybertruck. That danger is present for any vehicle, there's nothing particular about the design of the cybertruck that helps or hinders self-inflicted gunshot wound, unlike a gas tank at the back of the vehicle that causes fire when it gets into an accident.
Of course you can. In accordance with proper science and research they made their methodology and used dataset clear and transparent allowing you to run your own analysis.
Compensating for dataset bias in your preferred manner, we get 4 fire fatalities over 34,438 vehicles giving a Cybertruck fire fatality rate of ~11.6 per 100,000 units in comparison to a Ford Pinto fire fatality rate of ~0.85 per 100,000 units; ~13.6x the fatal fire rate of the Ford Pinto. Even counting mere incidents we get 2 over 34,438 vehicles which still results in a fire fatality rate of ~5.8 per 100,000 units; ~6.8x the fatal fire rate of the Ford Pinto.
Where the comparable analysis on vehicle-years, a much better comparable, actually places the fatal fire rate at ~43.5x if we discount the suicide and ~21.7x if we only count incidents. And in comparison to current vehicles would be ~41.4x and ~20.7x, respectively.
In accordance with proper science and research, we're gonna ignore the fact that we've got 35,000 data points and are extrapolating to 100,000? How about we say early results look really bad but we have to wait for more data before making any conclusions?
Are you joking? It is a rate. It is cited in per 100,000 because that is the characteristic rate that results in low integer-scale values. Rates are scale-invariant so you could just as well cite it in per 1,000 if you desire, but then you get a fire fatality rate of 0.0085 per 1,000 for the Pinto which is a much more annoying number to understand and compare for regular people.
Frankly, it would have been better to just cite the inverse of 1 fire fatality per ~8609.5 Cybertrucks (I already discounted the suicide) versus the 1 fire fatality per ~117,536 Pintos. Does that help you understand the usage and comparison of rates?
Are you? The smaller the data set the more likely it's anecdotal and down to luck,
good or bad.
If a self-driving car drives one mile with zero accidents, would we extrapolate from there and say they have a perfect driving record? Because thats just how the number work out? No! We'd want to see how this hypothetical self-driving car does over a million or a billion miles, over a wide range of conditions, before drawing any conclusions.
Oh I see. You appear to be unfamiliar with how to evaluate failure rates.
You appear to be under the mistaken assumption that your sample size needs to be in proportion to the failure rate you hope to achieve to draw any conclusions. That is untrue. Your sample size only needs to be in proportion to the actual failure rate to draw conclusions.
If your self-driving car drives one mile with zero crashes, that provides almost no evidence to support a claim that your self-driving car has a crash rate of 1 per billion miles. However, if your self-driving car drives one mile and crashes 10 times, that provides tremendous amounts of evidence against the claim that your self-driving car has a crash rate of 1 per billion miles. This is despite the fact that both instances only have a sample of a single mile.
Proving, failure to prove, and disproving are not symmetrical at all. But do not worry, that is a common mistake made by people with no training in scientific or statistical analysis; just take this as a learning experience.
You’re making a valid point about the asymmetry in proving vs. disproving failure rates, but the condescending tone is unnecessary. That might be acceptable behavior back on Reddit or Kiwi farms or wherever you come from, but we strive for a higher level of discourse here.
I never said a sample size needs to match the target failure rate—only that proving an extremely low failure rate requires significant data. Yes, a high failure rate can be detected quickly, but that doesn’t mean a small sample is enough to confirm an ultra-low failure rate. Just because a car doesn’t crash in one mile doesn’t mean it won’t in the next billion. You’re oversimplifying the problem while assuming I don’t understand statistical inference.
The guy who killed himself outside of the Trump tower lit the fire himself. It was not a failure of the truck. In-fact the truck protected people by venting the explosion up and containing the blast. It's as wrong as counting gunshot victims as dying of COVID
Lighting a truck on fire is fundamentally different than a truck starting on fire. The fact that they are willing to count that shows me they are disingenuous.
