The course starts with an overview of variable cosmic phenomena and characteristics of astronomical time series. Classical time series analysis in the time and frequency domain for evenly spaced data will be reviewed. This includes Gaussian and Poisson processes, smoothing and interpolation, autocorrelation and autoregressive modeling, Fourier analysis, and wavelet analysis. The class then proceeds to treatments of unevenly spaced time series commonly found in astronomical datasets, again in both the time and frequency domain. Guest lectures by expert SAMSI scholars developing advanced techniques for unevenly spaced data will be featured. Throughout the course, methods will be exercised using the public domain R statistical software environment using contemporary astronomical datasets. Students will complete R-based homeworks and a personal project in time series analysis involving a dataset of their choice.