Additional Info: I asked a large language model, 'On a scale of 1-10, how _______ do you think this YouTube video title is?' for every video.
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How 'hip and with it' PBS Space Time YouTube video titles are correlates with...
Variable | Correlation | Years | Has img? |
The number of registered nurses in Louisiana | r=0.97 | 6yrs | No |
Carjackings in the US | r=0.96 | 7yrs | No |
The number of nuclear medicine technologists in Connecticut | r=0.95 | 8yrs | Yes! |
Automotive recalls issued by Volvo Trucks North America | r=0.88 | 8yrs | No |
Google searches for 'hottest man on earth' | r=0.85 | 9yrs | No |
Snow days in Chicago | r=0.83 | 8yrs | No |
Google searches for 'fbi hotline' | r=0.75 | 9yrs | No |
Number of times 18 was a winning Mega Millions number | r=0.25 | 9yrs | Yes! |
How 'hip and with it' PBS Space Time YouTube video titles are also correlates with...
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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.)