Bayes - Medreonet

Bayesian inference
Bayesian inference involves three steps:
1. Determining a prior estimate of a parameter in the form of
a probability distribution that expresses our state of
knowledge (or ignorance) before any observations are
made.
2. Finding an appropriate likelihood function for the
2. Finding an appropriate likelihood function for the
observed data. The likelihood function calculates the
probability of observing the data for a given value of the
prior estimate of the parameter
3. Calculating the posterior (i.e. revised) estimate of the
parameter in form of a probability distribution of all
possible values of the parameter