# Smoothing Techniques When working with events that have a significantly small probability of occuring, it is possible for them to not be present at all within a sample dataset. Despite this, we do not want to assign a probability of 0 to any new parameters/statistics that are calculated. To overcome this issue, smoothing techniques can be used to ensure that some small probability is retained despite gaps existing within a dataset. > [!note] Cromwell’s Rule > > States that the use of prior probabilities of $1.0$ (“the event will definitely occur”) or $0.0$ (“the event will definitely not occur”) should be avoided, except when applied to statements that are logically true or false. > > --- > > Apparently was based on this quote: > > “I beseech you, in the bowels of Christ, think it possible that you may be mistaken.” - Oliver Cromwell, 1650 >