He stresses the use of robust methods in dealing with outliers. My question is how many and how serious do the outliers have to be to change your method. I think most data, mine has thousands of points, will have some serious outliers. There are many ways to define and detect outliers - but I remain unclear when you should be concerned about them to do things like transformations, robust regression, changing the assumed distribution etc.