Those two counties are Petroleum County, with a population of about 500, and Garfield County with a population of about 1,100. Both counties have a single town with about a quarter of the population.
This means a majority of the population live in the country, and likely work the lands they live on. This means no commute to work, which is what was measured.
This is a flaw in the methodology. Rurual Montana is not a bastion of urban planning. It is a mistake to look at travel to work exclusively. People need to travel to many destinations. And those living in those two counties probably use cars for everything else.
I wouldnt say it is a flaw, really. The data in general is a good approximation of auto dependence. And any researcher who isn’t an idiot will see the same thing you did and simply discard the data in these counties as obvious outliers. Sure, we can imagine a more accurate metric for measuring auto dependency for the purposes of creating a very nice map for public consumption. But it your purpose is simply to conduct some statistical analysis, I don’t think this dataset is bad - or at least not a bad start.
A portio of that area I know is full of retirees who relocated to escape the woke coasts. (Speaking anecdotally of extended family that relocated to that zone for a community of old conservatives.) So I wonder if retirees are counted.
The area in Arizona thats a little lighter may also be a shade of that too. Snowbirds might be skewing it with people who just plain don’t commute.
What’s going on in that one area in Montana?
I’m wondering that too. Just a guess, low population density with lots of farmers ‘working from home’ since they live on their farm.
Those two counties are Petroleum County, with a population of about 500, and Garfield County with a population of about 1,100. Both counties have a single town with about a quarter of the population.
This means a majority of the population live in the country, and likely work the lands they live on. This means no commute to work, which is what was measured.
This is a flaw in the methodology. Rurual Montana is not a bastion of urban planning. It is a mistake to look at travel to work exclusively. People need to travel to many destinations. And those living in those two counties probably use cars for everything else.
I wouldnt say it is a flaw, really. The data in general is a good approximation of auto dependence. And any researcher who isn’t an idiot will see the same thing you did and simply discard the data in these counties as obvious outliers. Sure, we can imagine a more accurate metric for measuring auto dependency for the purposes of creating a very nice map for public consumption. But it your purpose is simply to conduct some statistical analysis, I don’t think this dataset is bad - or at least not a bad start.
It’s only bad if misinterpreted.
Everyone works and lives on the same farm?
Horses, atvs.
low population density means high variance in stats.
always expect the highest and lowest stats to come from those areas.
But it’s probably farmers who live on their farm or something.
Nothing.
I drove though there once. Hours of seeing nothing but road.
A portio of that area I know is full of retirees who relocated to escape the woke coasts. (Speaking anecdotally of extended family that relocated to that zone for a community of old conservatives.) So I wonder if retirees are counted.
The area in Arizona thats a little lighter may also be a shade of that too. Snowbirds might be skewing it with people who just plain don’t commute.
jfc the whiny shit these assholes come up with to justify their racism
Also, note the scale. It starts at 50% reliance.
I’d expect it’s pretty lightly populated at least, as that generally makes it easier to stand out in statistics.