But tomorrow is unique. It will never repeat again -- n is always equal to 1.
The prediction is not unique. I group predictions (with some binning of similar-enough predictions), not days. Then if I've seen enough past predictions to be justified that they're well calibrated, I can use the predicted probability as my subjective probability (or a factor of it).
The prediction is not unique.
The trouble with this approach is that it breaks down when we want to describe uncertain events that are unique. The question of who will win the 2016 presidential election is one that we still want to be able to describe with probabilities, even though it doesn't make great sense to aggregate probabilities across different presidential elections.
In order to explain what a single probability means, instead of what calibration means, you need to describe it as a measure of uncertainty. The three main 'correctness' questions t...
Alternatively, what single concept from statistics would most improve people's interpretations of popular news and daily life events?