Bayesian Inference

sensitive

I am reading a topic on Bayesian Inference.I read books from different authors but they are all the same. I cannot see how the terms are derived.

Could anyone briefly explain what is going on and what is it that we are trying to find using this Bayesian. Bayesian is a combination of belief from past data. So Im thinking that we are making the prediction. But Im not sure of what sort of prediction. Is ther an example to this.

I need help in understanding the 1) Bayesian formalism and
2) the mean of a gaussian distribution - how are the parameters; mu and the variance are derived and how is the posterior distri bution derived as well.

By the way could anyone suggest any recommended books for this topic. Thx

Chris Hillman

Kapur and Kesevan.

EnumaElish

In practice Bayesian inference comes down to a weighting of prior beliefs vs. actual observations. I.e. the posterior mean is a weighted average of the prior beliefs (e.g. [itex]\mu_0[/itex]) and the data average.