Data: https://en.wikipedia.org/wiki/List_of_countries_by_number_of_scientific_and_technical_journal_articles

https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita

Tools: R, ggplot

Why polynomial trend lines?

Used GAM since the relationship is nonlinear.

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This looks like too many degrees of freedom.

How much better does this perform over linear?

Linear Model without region effects: R2 ~ 50%

Linear Model with region effects: ~ 63%

With random slope: ~ 70%

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Polynomial model with random intercept: ~ 71%

Polynomial model with random intercept & random slope: ~ 74%

So...maybe worth it.

Is there any reason why Grenada has so many papers per capita?

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I meant vanilla linear regression. GAM are beyond overkill here.

These lines imply really bizarre relationships (the blue line dipping near france, the red line flattening out right below 5) that aren’t in these data.

Yeah I do agree that there is overfit both for Europe around the point that you specify as well as for the Americas. Oceania and Asia fit quite nicely.

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Can someone explain please?

Would want to see citations per capita instead of just articles. Better metric for actual scientific influence.

EDIT: Stumbled upon this! Paints a very different picture for France and Germany.

Would be interesting to see how many of the non-US based research and development projects have financial ties to US sources of funding and/or expect to make money on their products by selling at higher prices in the US.

I remember looking this up years ago and basically found that the vast majority of biomedical research in the world had ties to the US health industrial complex in some major financial way.

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Causation might be going the other way. Places with high GDPs have more money to fund science. Qatar and other oil countries being the prime example.

The range is compressed by use of a log scale. The y axis is ln(papers per million people). Switzerland has five times as many papers per capita as Japan, but on a log scale it's 8.6 vs. 6.9.

Edit: This was in response to a comment expressing surprise that there was very little difference in output among wealthy countries.

Mo' money, Mo' problems..... that are funded to be researched and published

You should’ve added U.S. states if you’re gonna add a U.S. Territory to the mix.

Just because your r squared is better does not make your prediction better. You should check with cross validation.

Adding more freedom to your trend lines makes it fit your current data better sure. But just “joining the dots” fits the best.

They fit quite nicely to your eye sure, but look at the lack of data points you have for the higher gdp in those continents. This is just bad practice.

Fully agree. As is typical of data is beautiful, there’s a lot of bad data analytics practice here.

Definitely. Since scientific papers are released internationally and every country is able to benefit from the discoveries, it doesn't make sense for differences in scientific output to be driving differences in economic development.

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Hi Bro, May I just use it to tweet?

Sure, go ahead.