Kind of strange when someone who just joined this month knows what your degree is, but I think this would be quite hard. I wouldn't assume the weight and height of members here are normally distributed. The left tail of the distribution is probably very heavy, there seems to be a lot of very short members and very thin members so it would probably look like chi squared distribution, but it obvs wouldn't be because we aren't just a bunch of squared normal results. Having created a formula for this distribution, doing the necessary integration and creating estimators for the parameters we could create some confidence intervals for the mean height and weight. I'd rather create a multivariate linear regression to estimate an SF members weight based on their height and the size of items of clothes they've bought and sold and if they lift. We may have to use some time series for how long ago they bought the clothes. We could probably get an R value of like 0.8.
I think Superbobo has like a masters or Phd in stats so he'd probably be better at this.
you're drunk (or posing) if you think you'd get an R(squared) of .8 from any 'natural' data set.