STA 525: Time Series Analysis
Stationary and non-stationary models. Autocorrelation and partial autocorrelation functions. Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA), and Autoregressive Integrated Moving Average (ARIMA) models. Models for seasonal time series. Identification, estimation, diagnostic checking and forecasting. Use of computer package such as SAS or Minitab.<p>STA 432: Applied Regression Analysis
Matrix approach to regression models, least square estimation, correlation, multiple regression, transformation of variables, analysis of residuals, multicollinearity and auto- correlation. Use of computer packages for applied problems.<p>STA 420: Nonparametric Statistics
Common nonparametric tests such as permutation tests, sign tests, Wilcoxon test, chi- square test, and rank correlation tests. Null distributions and their approximations.<p>MAT 470: Combinatorics
Study of enumeration techniques, permutations, combinations, principle of inclusion and exclusion, finite fields, combinatorial designs, error-correcting codes.
Combinatorics is some classic computer science-ish material, showing up in a lot of Knuth's writings.<p>The other topics may well be useful for specific applications, but having no idea about what you intend to do with this knowledge, I would vote for combinatorics as "most useful to a programmer".