It should be noted that an M.A. in statistics will require aptitude in both the calculus and algebra. Moreover, a generalized applied degree will require prelim

It should be noted that an M.A. in statistics will require aptitude in both the calculus and algebra. Moreover, a generalized applied degree will require preliminary knowledge of ordinary differential equations and real analysis. I’ve also heard from professors that some competency in scientific computation (i.e. familiarity with both a well-used computer algebra system and statistical package) is usually expected. I haven’t pursued either, but I suspect that I will--I’m still an undergraduate studying general mathematics. But my assumption is that a generalized applied program is more useful than statistics. I’ve found breadth to be more important than depth in curriculum. That is, if you have a rigorous foundation in probability and mathematical statistics, then you could conceivably learn sampling theory, Bayesian statistics, or linear models outside of the classroom. Likewise, a rigorous foundation in differential equations might enable you to pursue chaotic or dynamical systems independently. I can’t speak to computer graphics specifically, but some of my peers work in quantitative finance, and they’ve echoed my sentiments on breadth. I’ve also heard from professors that one unexpected occurrence about students who enter either program is that many enter with a specific research interest, say quantitative finance, but realize they prefer to work in a different field, say biological statistics. I find the mobility and flexibility attractive.