# Non-informative Priors

Non-informative priors are used in Bayesian Inference, in the situation where no prior information exists, or inference based dominantly on the data is desired. We wish to find a distribution $$p(\theta)$$ that contained “no information” about $$\theta$$ (favours no value of $$\theta$$ over another).

An example of such a non-informative prior in the discrete space would be a uniform distribution over $$\theta$$.