In this chapter model selection and averaging methods are applied in some usual regression set-ups, like those of generalised linear models and the Cox proportional hazards regression model, along with some less straightforward models for multivariate data. Answers are suggested to several of the specific model selection questions posed about the data sets of Chapter 1. In the process we explain in detail what the necessary key quantities are, for different strategies, and how these are estimated from data. A concrete application of methods for statistical model selection and averaging is often a nontrivial task. It involves a careful listing of all candidate models as well as specification of focus parameters, and there might be different possibilities for estimating some of the key quantities involved in a given selection criterion. Some of these issues are illustrated in this chapter, which is concerned with data analysis and discussion only; for the methodology we refer to earlier chapters.