While studying bayesian analysis, I am told that the posterior distribution is the same as the likelihood function if we use a uniform prior distribution. I am having some difficulty to understand why it is so. I am referencing a lecture on the Intenet and the link is as follows:
The lecturer shows Bayes' Theorem to show the calculation for [pior * likelihood] done in the video but I cannot find when [pior * likelihood] is done in the video. What am I missing here?