Editing Calibration (statistics) (section)

===In probability prediction and forecasting===
{{See also|Scoring rule}}
In [[prediction]] and [[forecasting]], a [[Brier score]] is sometimes used to assess prediction accuracy of a set of predictions, specifically that the magnitude of the assigned probabilities track the relative frequency of the observed outcomes.  [[Philip E. Tetlock]] employs the term "calibration" in this sense in his 2015 book ''[[Superforecasting]]''.<ref name="Edge-II">
{{cite web|url=https://www.edge.org/conversation/philip_tetlock-edge-master-class-2015-a-short-course-in-superforecasting-class-ii|title=Edge Master Class 2015: A Short Course in Superforecasting, Class II|author=<!--Staff writer(s); no by-line.--> |date=24 August 2015|website=edge.org |publisher=Edge Foundation |accessdate=13 April 2018 |quote=Calibration is when I say there's a 70 percent likelihood of something happening, things happen 70 percent of time. 
}}</ref>  This differs from [[accuracy and precision]].  For example, as expressed by [[Daniel Kahneman]], "if you give all events that happen a probability of .6 and all the events that don't happen a probability of .4, your calibration is perfect but your discrimination is miserable".<ref name="Edge-II" /> In [[meteorology]], in particular, as concerns [[weather forecasting]], a related mode of assessment is known as [[forecast skill]].