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Data source: CDC National Vital Statistics
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The divorce rate in Kentucky correlates with...

Variable	Correlation	Years	Has img?
Milk consumption	r=0.98	23yrs	No
Popularity of the first name Jonathan	r=0.98	23yrs	No
Fossil fuel use in Denmark	r=0.97	23yrs	No
Popularity of the first name Jason	r=0.96	23yrs	No
Popularity of the first name Tyler	r=0.96	23yrs	No
Popularity of the first name Jillian	r=0.96	23yrs	No
Popularity of the first name Antonio	r=0.96	23yrs	No
Arson in United States	r=0.96	23yrs	No
Popularity of the first name Alex	r=0.96	23yrs	No
Popularity of the first name Miranda	r=0.96	23yrs	No
Popularity of the first name Amy	r=0.96	23yrs	No
Popularity of the first name Alexi	r=0.95	23yrs	No
Popularity of the first name Mario	r=0.95	23yrs	No
Ice cream consumption	r=0.94	23yrs	No
Popularity of the first name Abby	r=0.93	23yrs	No
Popularity of the first name Nathan	r=0.92	23yrs	No
The number of computer programmers in Kentucky	r=0.9	19yrs	No
Popularity of the first name Elvis	r=0.89	23yrs	No
Popularity of the first name Vicky	r=0.87	23yrs	No
Popularity of the first name Andres	r=0.86	23yrs	No
Popularity of the first name Alondra	r=0.86	23yrs	No
Popularity of the first name Diana	r=0.85	23yrs	No
Air pollution in Bowling Green, Kentucky	r=0.82	23yrs	Yes!

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The divorce rate in Kentucky also correlates with...

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^{What is Sys. Score?} You caught me! While it would be intuitive to sort only by "correlation," I have a big, weird database. If I sort only by correlation, often all the top results are from some one or two very large datasets (like the weather or labor statistics), and it overwhelms the page.

I can't show you *all* the correlations, because my database would get too large and this page would take a very long time to load. Instead I opt to show you a subset, and I sort them by a magic system score. It starts with the correlation, but penalizes variables that repeat from the same dataset. (It also gives a bonus to variables I happen to find interesting.)