Is it? The wikipedia article says that regression dilution occurs when errors in the x data bias the computed regression line.
But the stackexchange question is asking why an unbiased regression line doesn't lie on the major axis of the 3σ confidence ellipse. This lack of coincidence doesn't require any errors in the x data. https://stats.stackexchange.com/a/674135 gives a constructed example where errors in the x data are zero by definition.
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This problem is usually known as regression dilution, discussed here: https://en.wikipedia.org/wiki/Regression_dilution
Is it? The wikipedia article says that regression dilution occurs when errors in the x data bias the computed regression line.
But the stackexchange question is asking why an unbiased regression line doesn't lie on the major axis of the 3σ confidence ellipse. This lack of coincidence doesn't require any errors in the x data. https://stats.stackexchange.com/a/674135 gives a constructed example where errors in the x data are zero by definition.
Unless I'm misunderstanding something?