Yeah, but what about the confidence intervals? You don't get an R-squared like that very often in the social sciences. It was irresistible!

Good catch. I hadn't noticed it until you pointed it out.

What would you suggest?

1. According to Wikipedia, the The total fertility rate (TFR) of a population is the average number of children that would be born to a woman over her lifetime if: a) she were to experience the exact current age-specific fertility rates (ASFRs) through her lifetime, and b) she were to live from birth until the end of her reproductive life. It is obtained by summing the single-year age-specific rates at a given time.
2. What's the scientific definition of "evil"? The label is a parody of the morally conceited social dynamics of Reddit. (For example, saying "what a terrible graph".)
3. The data for "lower access to contraceptives and safe abortions" would make a different, less convenient graph.

Do you think it would change the R-squared? It doesn't look like it's worth the trouble.

In the social sciences, something that "explains" 67 percent of the variability is rare. What are you basing your claim on?

We could curve-fit to an exponential decay – what do you suggest? y0 - (yp - y0) * (1 - np.exp(-K * (x-X0)))?

It was just a bone I threw to the morally conceited. You can't stop the comments, so I'm making a parody of it.

"Outside of... lin-e-ar systems, line fits are bad."

The female school enrollment data is from https://data.worldbank.org/indicator/SE.SEC.ENRR.FE and the fertility data is from https://en.wikipedia.org/wiki/List_of_sovereign_states_and_dependencies_by_total_fertility_rate. The jupyter notebook can be seen at https://github.com/dbabbitt/StatsByCountry/blob/master/ipynb/Weekly%20Worship%20vs%20Fertility%20Rate.ipynb.

A low R-square of at least 0.1 (or 10 percent)is acceptable in the social sciences on the condition that some or most of the predictors or explanatory variables are statistically significant. So female school enrollment "explains" 67 percent of the variance in the fertility rate.

I threw a bone to those who use the mention of the United States as a soapbox on which to stand to trumpet their virtues. (They get a little anxious when they know one of those tiny dots is their target and they can't find it.) And, yes, the data for Puerto Rico is separate from the US data in both datasets. Thank you for noticing.

A low R-square of at least 0.1 (or 10 percent) is acceptable in the social sciences on the condition that some or most of the predictors or explanatory variables are statistically significant.

Watifalthist claims in his Is China the Next World Power? video that urban-ism and atheism are "the two worst predictors for sustainable birthrate". He shows two plots, side by side, of "Urbanisation and Fertility" and "Weekly Worship vs. Fertility". The second one mentions its source as John Mueller, Redeeming Economics (2014): 239. I wanted to see if I could reproduce it.

I threw a bone to those who use the mention of the United States as a soapbox on which to stand to trumpet their virtues. They get a little anxious when they know one of those tiny dots is their target (imagining it is probably at some extreme) and they can't find it.

How are they not available? Have you cloned the repository and found them missing from your local copy?

The worship data is from https://assets.pewresearch.org/wp-content/uploads/sites/11/2018/06/12094011/Appendix-B.pdf and the fertility data is from https://en.wikipedia.org/wiki/List_of_sovereign_states_and_dependencies_by_total_fertility_rate . The jupyter notebook can be seen at https://github.com/dbabbitt/StatsByCountry/blob/master/ipynb/Weekly%20Worship%20vs%20Fertility%20Rate.ipynb .