3 ms·
If the distribution of A and B is the same, any significant inequality of outcomes must be caused by bias. With mine, you need to replace the min estimator by
by yummyfajitas 11y ago
If the distribution of A and B is the same, any significant inequality of outcomes must be caused by bias.
With mine, you need to replace the min estimator by some sort of low quantile estimator (which is far less sensitive to noisE). Quantile estimators are, of course, invulnerable to variation on the right. I haven't worked out the details yet, but this is the pretty obvious next step.
I really don't get why you say this is "cargo cult application of mathematics". What sort of mathematics would you NOT consider "cargo cult"?
- SamReidHughes 11y agoMathematics that makes progress towards a solution. Looking at minimum for non-noisy distributions is just not the problem at hand, heck, you could look at a few graphs and the bias is obvious. Let's say you have Group A and Group B with distributions where people have EV for the returns on a $1M investment ranging from $0 (lose all your money) to $1B (maybe it gets real thin around $10M), and investors try to invest in anybody with EV > $1M. But maybe they're biased. Oh and by the way, the only possible exits are $0 and you sell the company for $1B. An attempt to make progress towards a solution would be better off targeting this model problem. Now you're attacking the noise head on.