The talk discusses new insight into the statistical inference for data arising in discrete stationary time series: From the Neyman-Pearson test, via maximum likelihood procedures to time series (e.g. GARCH-models). Emphasis will be put on new techniques of theoretical nature (for example for Gibbs distributions) and computational innovations in data analysis.