Editing Prior probability (section)

== Weakly informative priors ==
A ''weakly informative prior'' expresses partial information about a variable, steering the analysis toward solutions that align with existing knowledge without overly constraining the results and preventing extreme estimates. An example is, when setting the prior distribution for the temperature at noon tomorrow in St. Louis, to use a normal distribution with mean 50 degrees Fahrenheit and standard deviation 40 degrees, which very loosely constrains the temperature to the range (10 degrees, 90 degrees) with a small chance of being below -30 degrees or above 130 degrees.  The purpose of a weakly informative prior is for [[regularization (mathematics)|regularization]], that is, to keep inferences in a reasonable range.