I hope someone could help me with the following problem: If I create a linear model that predicts the height of people (y) with the following parameters:
y = a + b*(xi-xavg)
with "a" the normally distributed (178,20) the prior distribution of heights and "b" a coefficient for the effect of the weight on the height prediction. The question is if I have to choose the normal distribution or the lognormal distribution for coefficient "b". I understand that the normal distribution has the maximum entropy for a given variance (sigma = Uniform(0,50) here) so do I just pick the normal distribution here?
If anyone has some insights, thank you so much! :)