There are approximately 250 million cars on the road and they only used data from 8 million? That’s 3% of cars on the road to extrapolate into all the cars on the road. Seems like a huge flaw especially since we didn’t know how they got that subset. All seems like click bait as most articles related to Tesla are…
Another good way / better way to see what cars are dangerous are insurance rates. Since insurance companies take in way more data than 8M cars when determining rates.
Since they just use the 8m for the normalisation it’d be interesting to know how sensitive the rankings are if they assumed some bias. Or maybe even just swap around some normalisation factors and see how robust the ranking is.
I guess they do have near complete data on the deaths, and pretty good data on the population of registered vehicles.
The data on that is all there. Records like car fatalities are collected mainly through law enforcement reports and states have registration numbers. But the question is, how centralized is the data? City, county, state, or federal? There is a lot of data that simply isn’t required to be collected to a central agency to keep track of.
Tesla’s do cost more to insure than ‘average’ cars. But, that extra cost reflects more the cost to repair minor/moderate damage than cost of fatalities. Since fatalities are just a smaller subset accidents. Tesla’s are extremely costly to repair and often get totaled vs repaired. Premiums reflect that cost of loss.
3% of 250 million could very well be the approximate number of cars on the roads that are involved in a fatal collision. And that is the only consideration of the article in this study.
Just honestly asking Im not a statistician. From a lay person looking high level this seems weird. The conclusion also does not match up with insurance prices that I’ve personally seen nor correspond with my experience.
I’m here for discussion not trying to put anyone down. Could someone just explain to me what I’m missing. No need to downvote. So if you take a non random sample of data how can you extrapolate that out so much? Does this data line up with other people’s data? What am I missing?
There are approximately 250 million cars on the road and they only used data from 8 million? That’s 3% of cars on the road to extrapolate into all the cars on the road. Seems like a huge flaw especially since we didn’t know how they got that subset. All seems like click bait as most articles related to Tesla are…
Another good way / better way to see what cars are dangerous are insurance rates. Since insurance companies take in way more data than 8M cars when determining rates.
That’s more than 3% of the user base. 0.5% is considered sufficient for statistical relevance.
A sample of 8 million cars is more than enough to be representative.
… sufficiently random …
Since they just use the 8m for the normalisation it’d be interesting to know how sensitive the rankings are if they assumed some bias. Or maybe even just swap around some normalisation factors and see how robust the ranking is.
I guess they do have near complete data on the deaths, and pretty good data on the population of registered vehicles.
Yeah it would be nice to see more of the methodology & the raw data tbh, kind of a shame they’ve left it a bit of a black box.
The data on that is all there. Records like car fatalities are collected mainly through law enforcement reports and states have registration numbers. But the question is, how centralized is the data? City, county, state, or federal? There is a lot of data that simply isn’t required to be collected to a central agency to keep track of.
Tesla’s do cost more to insure than ‘average’ cars. But, that extra cost reflects more the cost to repair minor/moderate damage than cost of fatalities. Since fatalities are just a smaller subset accidents. Tesla’s are extremely costly to repair and often get totaled vs repaired. Premiums reflect that cost of loss.
3% of 250 million could very well be the approximate number of cars on the roads that are involved in a fatal collision. And that is the only consideration of the article in this study.
Found the Tesla driver
Just honestly asking Im not a statistician. From a lay person looking high level this seems weird. The conclusion also does not match up with insurance prices that I’ve personally seen nor correspond with my experience.
I’m here for discussion not trying to put anyone down. Could someone just explain to me what I’m missing. No need to downvote. So if you take a non random sample of data how can you extrapolate that out so much? Does this data line up with other people’s data? What am I missing?