I think it's interesting to see this violate the usual political leanings. Blue California and New York don't fare too well, but neither do deep south Louisiana, Mississippi or Florida. On the other hand leftward leaning Illinois, New Jersey and Massachusetts are middle-of-the-road.

It doesn't have to be either of those two specific measures. I just want some way to quantify the quality of the fit to the data.

That's interesting. Can you supply some measure of performance (mean squared error, mean absolute error, ...) for those curve fits?

Was that regression line fit weighted by population?

In the interactive map, Utah and Minnesota which show up as dark for "Bachelor's degree and higher", disappear when for "Graduate or professional degree".

You make very good points, and I appreciate your work on this. Still, I think it's worth at least pointing out the subtlety of the "independents".

I think it'd be interesting to separate independents who are really either: 1. mixed opinion Republican/Democrat or 2. late-decision Republican or Democrat undecideds from people who consistently adhere to other parties (Libertarian, Greens, etc.).

The result of k-means clustering is a set of cluster centers. Usually, I would think "running" it over new data would mean assigning each observation in the new set to one of those clusters. I'm not sure what the rest of your question is getting at.

I encourage you to continue your own exploration, regardless of what anyone says "what everybody else is doing". The truth is, all of this is applied math, and the computers are merely where we do our work. Personally, I find this field much more interesting at the algorithm level: If you do something genuinely interesting, it is not somehow less valid because of the tools you used.

Is this data available, breaking out whether the individual in question was armed at the time of shooting by police or not?

What did you assume is the rate of return on the money you could leave in the bank if you didn't pay for a solar installation?

How many countries abstained?

That's cool!

Is the raw data available?

Why do you think so?

In which country do you live?

In which country do you live?

Are you a Millennial?

As a start, I suggest learning the following:

Statistics:

- probability (distributions, basic manipulations)

- statistical summaries (univariate and bivariate)

- hypothesis testing / confidence intervals

- linear regression

Linear Algebra:

- basic understanding of arranging data in vectors and matrices

- operators (matrix multiplication, ...)

Calculus:

- limits

- basic differentiation and integration (at least of polynomials)

Information Theory (Discrete):

- entropy, joint entropy, conditional entropy, mutual information

Perhaps some countries who jail journalists for political reasons, but fewer of them, are actually worse because the government threat has been made clear?

Given the small sample size, I was curious about the confidence interval, which is (95% C.I.) 5.1% to 28.3%. I'd be curious to know how well the surveyed population matches that of Georgia.

I'm curious as to the retention of foreign language skills for graduating seniors in New York.

I wonder what effect the grade definition has on this? For instance, a place might have more students having taken a foreign language by the time they graduate from high school, but not before grade 10, diluting that place's average across K - 12. It'd also be interesting to see this qualified some how, like "percent of students passing some standardized test of fluency in any foreign language by graduation".

How was the red smooth calculated?

It would be interesting to see this displayed as a rent vs. income scatterplot.

The correlation with the geographic distribution of obesity has already been noted in the Comments. Notice, too, the association with Tobacco Nation:

https://truthinitiative.org/sites/default/files/media/images/standard/2019/05/tobacco-nation-2019-social.jpg