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The relevant metric here seems to be 'miles between fire events'. On this metric, we have exactly 1 data point for Tesla. I would hardly call that "probably e

The relevant metric here seems to be 'miles between fire events'. On this metric, we have exactly 1 data point for Tesla. I would hardly call that "probably enough". Of course, I'm exaggerating in the other direction. What we really should be calculating is the odds that Teslas burst into flames less often than the average car, given that the average car does so every 20 million miles and the first such event in a Tesla was at the 100 million-mile mark. We're still failing to account for the fact that the average Tesla is newer and probably better-kept than the average car, but it would at least be a reasonable start. I don't know enough statistics to perform this calculation, but I would like to see how it is done.

jurjenh 13y ago
An easy starting point would be to get this kind of data on similarly aged cars - cars sold over the last 2-3 years, then see what stats you can get there. I'd guess that you'd find some models that have never caught fire and some that have done so a lot more than tesla's, but that's pure speculation on my part.
PeterisP 13y ago
We have enough events, because in this case it is appropriate to model the actual random event as 'million miles driven' with a chance of fire happening or not happening. Gasoline cars have a mean of 0.05 fires per million miles, and given the current Tesla data, the mean is 0.01 fires per million miles. I'm not taking out a calculator, but it would come out to an extremely low (0.0001%) the 'true' fire chance is the 0.05 gas car rate or higher; the 95% confidence interval should be 0.01 +- 0.02 or tighter, so still twice better than gas cars. For an exaggerated example, if Tesla had driven a billion miles and had 0 fires, you shouldn't say that there's not enough data - you definitely would have enough data to say that the chance of fire is below the gas-car rate of 5 fires per 100 million miles.
- thedufer 13y ago
  Why is million miles driven a better way to model it than billion miles driven, for example? If you happen to choose that, there clearly isn't anywhere near enough data. I'm honestly curious how one models this type of thing statistically, and I am not convinced enough of its obviousness to just accept numbers that someone throws around.

jurjenh 13y ago

An easy starting point would be to get this kind of data on similarly aged cars - cars sold over the last 2-3 years, then see what stats you can get there. I'd guess that you'd find some models that have never caught fire and some that have done so a lot more than tesla's, but that's pure speculation on my part.

PeterisP 13y ago

We have enough events, because in this case it is appropriate to model the actual random event as 'million miles driven' with a chance of fire happening or not happening. Gasoline cars have a mean of 0.05 fires per million miles, and given the current Tesla data, the mean is 0.01 fires per million miles. I'm not taking out a calculator, but it would come out to an extremely low (0.0001%) the 'true' fire chance is the 0.05 gas car rate or higher; the 95% confidence interval should be 0.01 +- 0.02 or tighter, so still twice better than gas cars. For an exaggerated example, if Tesla had driven a billion miles and had 0 fires, you shouldn't say that there's not enough data - you definitely would have enough data to say that the chance of fire is below the gas-car rate of 5 fires per 100 million miles.

thedufer 13y ago
Why is million miles driven a better way to model it than billion miles driven, for example? If you happen to choose that, there clearly isn't anywhere near enough data. I'm honestly curious how one models this type of thing statistically, and I am not convinced enough of its obviousness to just accept numbers that someone throws around.