From MLE to Bayesian Inference: Why Your Estimate Needs a Prior

In the MLE tutorial, we estimated a coin's bias by finding the single parameter value that maximises the likelihood. Flip a coin 3 times, get 3 heads, and MLE says \(\hat{\theta} = 1.0\) — the coin al