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Fit a line through some data and ordinary regression hands you back a single answer: one slope, one intercept, the best fit. Bayesian linear regression asks a different question entirely. It starts before the data with a whole cloud of candidate lines, the prior, where every line you might believe gets a probability. Then Bayes' rule takes over ...
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