Post #1812227

2026-04-29 18:10 UTC

You’re mixing two population averages, so you need a weighted calculation. Let’s approximate first: France has about 67 million people out of roughly 447 million in the European Union, so ≈15% French and 85% non-French. We set up: Overall EU rate = weighted average 1.7=0.15⋅8+0.85⋅x Solve: 1.7=1.2+0.85x 0.5=0.85x x≈0.59 So, among non-French Europeans, the rate is roughly 0.6 per 100,000. That’s substantially lower than both the French rate (8) and the EU average (1.7), which makes sense given how high the French figure is relative to the rest. thans france, for ruining our numbers!

Replies (2)

@atopi@piefed.blahaj.zone 2026-04-29 22:29

it says Europe though, not the European Union if you click the question mark near the Europe statistic, it says it also includes countries like Russia and the UK which mess with the statistic a lot

Open ##1817145
@merdaverse@lemmy.world 2026-05-01 11:45

Dunno what you’re trying to prove here, apart from “removing an outlier from the data makes the data closer to the average”, which is pretty obvious. But you can clearly see that the graph shows Europe, not EU, so using your same calculation with the population of Europe, which is 745 million and excluding France, the result is 1.13. Also I don’t see any indication that OurWorldInData is using an average of countries (which would be stupid). Considering their jobs are statistics, they probably know how to aggregate per population, aka a weighted average.

Open ##1847656