4 ms·

TL;DR Berkson's paradox is a false observation of a negative correlation between two positive traits

• zimablue 8y ago
  Which occurs when/because for whatever reason, samples with two negative traits are excluded, the example demonstrates it well: if P(a, b), P(~a, b), P(a, ~b), P(~b, ~a) all equal 0.25: If you exclude the (~a, ~b) sample then within the population that remains it looks like a and b are negatively correlated. (p(a|~b) = 1, p(a|b)=0.5) It's interesting because this is something that happens a lot => when dating, looks negatively correlate with niceness within people you date because you don't date people who are neither. Diseases in hospital populations are negatively correlated because if you don't have anything you're not in hospital.
  • Boulth 8y ago
    This is excellent, concise summary. Thank you zimablue!
  • pezo1919 8y ago
    Great examples, thanks! Can you suggest any good material you know on stats? (I'd prefer videos, but everything works) It seems to me you have a very solid background.
    • anchpop 8y ago
      look up 3blue1brown for some instructional videos on math, including some on stats