This tongue-in-cheek regression analysis found a way to predict the "Hipster Music Index" of a given artist by plotting # of Facebook shares of said artist's Pitchfork magazine review on they y-axis and Pitchfork magazine review score on the x-axis. If an artist falls above the linear regression line, they aren't "hipster". If they fall below the line, they are. For example, Kanye West is a Pitchfork darling but also widely shared on FB, and, thus demonstrating too much popular appeal to be a hipster darling (as opposed to Sun Kill Moon (?), who is beloved by both Pitchfork but not overly shared on FB).
As instructors, we typically talk about the regression line as an equation for prediction, but Priconomics uses the line in a slightly different way in order to make predictions. Also, if you go to the source article, there are tables displaying the difference between the predicted Y-value (FB Likes) for a given artist versus the actual Y-value, which could help an instructor introduce the idea of the Least Squares Estimate in selecting the best fitting regression line for data.
As instructors, we typically talk about the regression line as an equation for prediction, but Priconomics uses the line in a slightly different way in order to make predictions. Also, if you go to the source article, there are tables displaying the difference between the predicted Y-value (FB Likes) for a given artist versus the actual Y-value, which could help an instructor introduce the idea of the Least Squares Estimate in selecting the best fitting regression line for data.
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