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The comments here are full of poor understanding of statistics, in case ppl wanted to go help and e.g. explain what a "bin" means
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Escort monthly income by BMI, from my escort survey I've had open for a while. Sample size is still kinda low, like n=~30 per bin, and this is sampling escorts online enough to take my survey, but there still looks like a trend I'd expect. Interesting to see the degree of impact!
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More valuable information would be the standard deviation of how much is earned. If you know how to use seaborn you can easily graph correlation matrices to identify which elements contribute more to earnings
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I’m not sure what randomness you’re trying to measure here. If these were random samples of a particular population, error bars would reflect the range of likely results from the full population. In a self-selected sample, it’s not clear what the “full”population actually is.
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Sample size of 30 per bin is more than enough, i don't think you are limited by that at all. More sample would be wasted at this simple level of analysis.
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You have to specify what level of confidence the CI error bars are. When the sample is high enough (30 is good) I prefer to use standard error for the error bars because it allows you to eyeball significance (non overlapping bars means p < 0.05)
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I'm still just surprised the peak isn't 21-22. I'd assume if you're paying for it, you'd be almost exclusively seeking the most optimally sexually desirable options (i.e. big boobs\butt) which should tip the BMIs a bit, but maybe I don't understand why\who solicits these services