Priors can be considered weak or strong depending on how concentrated the probability density in the prior is.

• Weak prior: with high entropy and high freedom to change parameters and allows the data to move the parameters more or less freely. E.g., Gaussian distribution with large variance.

• Strong prior: has low entropy and low freedom to change parameters and plays a more active role in determining where the parameters end. E.g., Gaussian distribution with small variance