I read in the likelihood function Wikipedia article that:
This (the likelihood function) is not the same as the probability that those parameters are the right ones, given the observed sample. Attempting to interpret the likelihood of a hypothesis given observed evidence as the probability of the hypothesis is a common error, with potentially disastrous consequences in medicine, engineering or jurisprudence. See prosecutor's fallacy for an example of this.
My question is, what does it mean that the likelihood function is not the same as the probability that the parameters are the "right ones"? In this case, what IS the probability of the parameters being the right ones given an observed sample? Is it the posterior probability? Thanks.