The course intends to meet two goals. It provides tools for empirical work with time series data and is an introduction to the theoretical foundation of time series models. Much of statistical methodology is concerned with models in which the observations are assumed to be independent.  However, many data sets occur in the form of time series where observations are dependent.  In this course, we will concentrate on univariate time series analysis, with a balance between theory and applications.  In order to emphasize the application of theory to real (or simulated) data, we will use R. 

NOTE: Students must have basic-level statistics knowledge such as taking the expectation of a given process, finding the covariance function, and hypothesis testing concepts.