This article is meant to summarize the basics of Bayesian statistics for beginners.
In Bayesian statistics:
- a statistical model is created to link data to parameters
- prior information about parameters is formulated
- inferences about parameters are derived from the resulting posterior distribution
Until the 1990s, computational tools for conducting Bayesian analysis were nascent or non-existent. While there are tools for the specialist available today, the general practitioner of Bayesian analysis will find there are few user friendly tools available.
The author enumerates a number of benefits for using Bayesian analysis. They are:
- It provides meaningful and intuitive inferences.
- It can answer complex questions cleanly and exactly.
- It makes use of all available information.
- It is well suited for decision-making.