I am building a Marketing Mix Model in PyMC and am not sure how to interpret the posteriors, especially those with half-normal priors (sigma=1). I’ve chosen this prior because media could not have a negative effect on the revenue. After sampling, the posteriors for some beta’s look like this:
Is there a non-zero effect here at all? and how can I test this? Furthermore, I am curious how to determine the effect size. I feel that the mean and median are positively biased here, as the the posterior cannot take on negative values.
All variables are 0-1 transformed.