I wish to explain my confusion through an example, so I understand all the contextuals aswell:
Say I want to predict the chance of someone being a European man $C_M$ based on their height $x_i$. I.e I wish to deduce $P(C_k|x_i)$.
I know from biology, that species and their sexes tend to follow their average heights. Therefore I model the PDF of $p(x|C_k) = \aleph(x|\mu,\sigma^2 )$.
I still need to determine the parameters. As I have a lot of data on how many Europeans are men, I plan on utilizing this in order to generalize my model better. Therefore I wish to estimate the model parameters using Bayesian estimation.
In other words, I wish to estimate the likelihood of the model parameter using the PDF derived from the following equation:
$\theta_{Bayes} = \int{\theta * (p(x|\theta)*p(\theta))/p(x)}d\theta$
Problem is, I have no PDF for the priori. How would I go about modelling this? What does it even tell you?
