Least squares from bayesian perspective

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I am studying least squares estimation. However, I cannot understand the following formula. I do not know how to find distribution of y and x and beta. I am not even sure that they are random variable and probability of data does not make sense at all and why noise term is the back bone of the probability equation. Can you help me figure this out?

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