The correlation between tabooness and sexual interest was statistically significant at p < 0.01.
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Question: Is there more blue because more males responded, or because the males who did respond were more likely to like fetishes than females?
I have a nagging suspicion that “taboo-ness” here is not just a correlation, but a source of bias (specifically, response bias.) Instead of graphing by it, could you try correcting for it? You’d get, I think, something like “interest given complete disinhibition,” which seems useful for predicting e.g. fetish demand.
(I’d also like to try a few other things with the data; would it be possible to get a raw CSV to play with? Reconstructing the X/Y-axis-mapped variables is easy enough, but the color-mapped variable is a bit harder.)
What did you use to make that chart? It’s different from the charts in previous posts.
If trans people were counted in the chart gender data, would futa be the pinkest one?
Interesting and surprising in many cases.
I agree some of them may be missnumbered