We have a sample,
Xbar is the best estimate we have for mu.
Frequentist: Xbar is a random variable that its pdf is concentrate around mu. xbar is most probably mu.
Expected value of xbar is mu therefore it is an unbiased estimator.
MLE: xbar is most likely to happen if mu is xbar.
Bayesian: Mu is an unknown variable for me, conditional to this data, if I bet that it is Xbar, I will right most of the time. I will be probably be right.
Both Baysians and frequentists agree that least square method provide an unbiased estimator for regression line?
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