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Through the discussion and the examples presented here, we have seen how the Bayesian approach is applied to data analysis and how Bayesian point estimators and confidence intervals are obtained and updated. In particular we have seen how they are implemented to a life data analysis example.
Bayesian techniques are widely used by some practitioners in industrial statistics and can become very useful analysis tools. However, it is always necessary to bear in mind this large dependency that exists between the applicability of the postulated prior distributions and its parameters, and the results obtained, through them (e.g., our estimations).
We have just touched on a few relevant concepts of Bayesian statistics, a topic that is very extensive and parallels Classical statistics. In For Further Study, we list the usual background readings plus several references that can serve as starting points for those interested in studying in this topic at a more advanced level.