The line graphs are weird and bumpy since she's visualizing discrete data points and doing connect-the-dots. It's not a line of best fit, it's just a series of straight lines between each data point.
If the error bars are "too small to plot" then why are there clear peaks in "how many siblings did you grow up with?" and "I feel little concern for others"? Those look like noise to me...
Without the raw data I can't be 100% sure, but I would assume that there are some other (likely spurious) correlations between the men with BMI 34-36 who answer Kink Surveys on Tik Tok that are being captured by these weird bumps.
Short answer: Weird bumps in data are not necessarily caused by variance.
error bars
n=570,000
that implies a relative reduction in variance compared to smaller sample sizes; there’s still a variance.
I don't know enough about statistics to know for sure, but elsewhere Aella has said the error bars would be so small one can completely ignore them.
Then why are there weird notches in the graphs?
The line graphs are weird and bumpy since she's visualizing discrete data points and doing connect-the-dots. It's not a line of best fit, it's just a series of straight lines between each data point.
If the error bars are "too small to plot" then why are there clear peaks in "how many siblings did you grow up with?" and "I feel little concern for others"? Those look like noise to me...
Without the raw data I can't be 100% sure, but I would assume that there are some other (likely spurious) correlations between the men with BMI 34-36 who answer Kink Surveys on Tik Tok that are being captured by these weird bumps.
Short answer: Weird bumps in data are not necessarily caused by variance.
Aella is right! Her cleverness in statistical realms is a big reason why I read knowingless.