[wjnc]

Have I gone overboard in remembering that Gauss-Markov is overrated? It's nice that some assumptions guarantee BLUE, but then there is real world data and modelling. Understand where your data come from, what distributions they have, what the relationship is with your dependent variable. Testing for these assumptions might be helpful as a teaching tool, but please get to the level to be able to demonstrate that your model can fail a few of these (like heteroskedacity) and still work (or recognize you need more than a linear model).