Analysis of epidemic time series is a large endeavor because of the richness of dynamical patterns and plentitude of historical data (Rohani and King 2010). A wide range of tools are used, some of which are borrowed from mainstream statistics other of which are “custom made.” The classic “mainstream” methods belong to two categories: the so-called time-domain and frequency-domain methods. The autocorrelation function and ARIMA models belong to the former class and spectral analysis and the periodogram belong to the latter. Hybrid time/frequency methods have become increasingly prominent in the form of wavelet analysis because it allows the study of changes in disease dynamics through time (Grenfell et al. 2001). This chapter discusses a variety of “mainstream” methods using a variety of time-series data.