Abstract: The influenza virus infects approximately 500 million individuals each year. Owing to its RNA makeup, influenza mutates extremely rapidly, allowing the virus population to evade the pressure of the human immune system. A single individual may be infected year after year by antigenically distinct strains. The timescale of influenza evolution is consequently a human timescale - we get the chance to observe the process of evolution in action. And yet, a time series of sequence data is hardly interpretable on its own. In this talk, I show how placing sequence data in a phylogenetic context can uncover otherwise-hidden patterns of biological importance. Using flexible Bayesian statistical models, I address pressing questions of the global circulation and antigenic evolution of the influenza virus. In these analyses I use the virus population's phylogenetic tree as a foundation on which to build and test evolutionary hypotheses. This approach allows the data to speak for itself, while properly accounting for statistical and phylogenetic uncertainty. I also place this work in the context of developing inclusive evolutionary models, which explore how mutations create phenotype and phenotype results in fitness. The aim is to illuminate the mechanics of not only 'survival' but also 'arrival of the fittest.'