# Non-informative Priors

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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 \(\theta\).