 Consider a weather forecaster who says in the morning that the probability of rain equals .8. That day it either rains or does not. How good a forecaster is he? Clearly, to evaluate him we must look at his performance over a longer period of time. Calibration is a measure of agreement between judgments and actual frequencies… This forecaster was perfectly calibrated over the past year, for example, if, for every number r, the proportion of rainy days among those days on which he announced probability r for rain, equaled r. (van Fraassen 1984: 245)