Source: Global status report on road safety 2018 from the WHO
Tools:

• Google Sheets for data preparation.
• R, and RStudio for creating the chart.
• Pixelmator for some last visual touches.

P.S: repost as the first submission was missing the y axis' legend :)

Correlation=Causation; poors can't drive.

Correlation/=Causation; higher income per capita likely means better funded government and better roads and safety programs. It also means there are more protections for workers to prevent unsafe practices that are more likely to lead to accidents.

Good reminder! Always important when using scatter plots.

Don't forget hospital and EMS infrastructure

I'm surprised that Saudi Arabia's road death rate per 100k people is so high, considering they don't let over half the population drive. I wonder if the low death rates in some countries are driven by lower car ownership in general.

/How the hell does a driver in the UK go fast enough to kill someone? Top Gear Episode 6.7: "Fiat Panda vs. Marathon Runner" in London.

>considering they don't let over half the population drive. I wonder if the low death rates in some countries are driven by lower car ownership in general.

The point of reporting deaths per 100k is to account for differences in the number of drivers. And Saudi Arabia's road death rate per 100k is probably so high exactly because only men can drive.

Edit: It's per total population not per driver. My mistake. I still maintain Saudi road death rates are high because only men can drive.

It'd be interesting to see "average miles driven" added to this.

>The point of reporting deaths per 100k is to account for differences in the number of drivers.

I thought it was per 100k people, not per 100k drivers? If it's 100k drivers, that might explain it.

It's per 100k population not per 100k drivers

Good point, it is per 100k population. But even if women can't drive in Saudi, they can still ride in cars and die in road accidents, although WHO statistics show 87% of reported road traffic fatalities were men. I also can't figure out if a pedestrian killed by a car counts as a road traffic fatality.

That also would be good to know.

Statisticians: "Higher per income capita correlates with lower road fatality rate"

USA: "Hold my beer"

Yes that also counts as a road traffic fatality in the source study.

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Women have been allowed to drive in Saudi Arabia since 2018.

I would use size of the circle to represent that country's population.

Once that was done you'd have more large circles on the left on top of each other, so then I'd stretch it vertically to make it easier to read.

Another way to reduce the clutter on the left would be using a log (or sort-of-log) scale for income. Because it's possible that a small increase in income in a poor country corresponds to a significant decrease in road death rate, and this would something worth noting.

Only 2% of Saudi Arabian women have driver’s licenses. So yes, technically you are correct, but I’m going to stand by my statement that they don’t let over half their population drive.

https://epod.cid.harvard.edu/sites/default/files/2021-12/AlNahda%20Blog_15Sep2021.pdf

Women are still travelling by having their fathers/husbands/etc or taxis (which in some cases adds to distance travelled, although there would be many more women who don't travel due to the difficulty).

I think counting registered vehicles is better than counting licensed drivers. Total distance driven is probably better again for comparing number of crashes. And passenger-distance better again for comparing number of road deaths.

If you've seen shuttle drivers in Thailand, this chart makes perfect sense

It's more like "Let me finish this beer first."

As someone who had spent some some time in Saudi Arabia (and the surrounding countries), the relatively high death rate in Saudi Arabia is largely down to Saudis being very poor drivers. Add in the prevalence of large powerful cars driven by relatively poor drivers and the high death rate is no surprise

What does the bubble size represent? If it’s per capita income isn’t that redundant with the x axis?

Also, it’d be interesting to see this chart with road deaths per x miles driven. People in USA for example drive far more miles per capita and would therefore have more deaths per capita, all else being equal.

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Yes the bubble size represents per capita income. I made that choice because I felt it strengthened the visual value of the correlation. But I can understand the argument for using pop size instead.

Indeed, having miles driven would be interesting, or maybe total length of the road network which might easier to find.

also, the safety systems in vehicles are better in higher income per capita because they cost more money and higher income can afford them which means accidents are less fatal

I'd have liked to see Germany because of the speed limit

> Correlation=Causation; poors can't drive.

also Correlation=Causation, road accidents make people poor.

public transit = less idiots in cars

No, it means fewer smart people in cars, unless you're implying that only idiots take public transit.

I don't think its as much as Poor= cant drive, its more so about infrastructure.

Ive been to many 3rd world countries, they are insane drivers in a good way, but most dont have proper signs, massive pot holes and little to no sidewalks.

Its not even about "idiots" its about the actual infrastructure of these roads. I honestly think people in 3rd world countries can control a car better then a lot of people in western countries just from the nature of how people drive. I think the problem comes because roads are poorly paved (Pot holes, bad condition) theres little to no signs, general overcrowding and lack of sidewalks.

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What i mean is that the less people on the roads, the less chances of more idiots on the road. Public transit IS infrastructure

Aren't there states without mandatory laws for helmet and seatbelts?