Though the visualization is cool here, I think this is actually not a good example. The final "hierarchical" model presented doesn't say anything about a relati

Though the visualization is cool here, I think this is actually not a good example. The final "hierarchical" model presented doesn't say anything about a relation between the coefficients for the different departments, so one can view this as really just having separate models, one for each department. To me, the point of a hierarchical model is that one can assume relationships between these parameters (e.g. suppose that they are from the same distribution). Then when one department has very few data points, some of the information in your beliefs about the parameters for that department come from what you learned in other departments. E.g. the base salary is likely to be similar to base salaries of other departments.