Time Series Analysis

This course presents both theory and applications of linear time series and an introduction to stochastic processes at a level accessible to a wide variety of students and pratictioners in statistics, economics and finance, science, engineering and quantitative social science. Stochastic processes quantify dynamic relationships of sequences of random events; time series modelling is one part of stochastic processes. Emphasis is placed on model choice and development, and how to estimate model parameters and forecast future values. Stochastic models play an important role in analysing the variability inherent in biological, medical and engineering processes, and in dealing with the uncertainties affecting managerial decisions and the complexities of psychological and social interactions.