Tip: frame your estimates in terms of intervals with confidence levels, i.e. “90% probability that the answer is within and ”. Try to work out both a 90% and a 50% interval.
I’ve found interval estimates to be much more useful than point estimates, and they combine very well with Fermi techniques if you keep track of how much rounding you’ve introduced overall.
In addition, you can compute a Brier score when/if you find out the correct answer, which gives you a target for improvement.
Douglas W. Hubbard has a book titled How to Measure Anything where he states that half a day of exercising confidence interval calibration makes most people nearly perfectly calibrated. As you noted and as is said here, that method fits nicely with Fermi estimates.
This combination seems to have a great ratio between training time and usefulness.
Tip: frame your estimates in terms of intervals with confidence levels, i.e. “90% probability that the answer is within and ”. Try to work out both a 90% and a 50% interval.
I’ve found interval estimates to be much more useful than point estimates, and they combine very well with Fermi techniques if you keep track of how much rounding you’ve introduced overall.
In addition, you can compute a Brier score when/if you find out the correct answer, which gives you a target for improvement.
Douglas W. Hubbard has a book titled How to Measure Anything where he states that half a day of exercising confidence interval calibration makes most people nearly perfectly calibrated. As you noted and as is said here, that method fits nicely with Fermi estimates.
This combination seems to have a great ratio between training time and usefulness.