Describes ARIMA or Box Tiao models, widely used in the analysis of interupted time series quasi-experiments, assuming no statistical background beyond simple correlation. The principles and concepts of ARIMA time series analyses are developed and applied where a discrete intervention has impacted a social system. ‘…this is the kind of exposition I wished I had had some ten years ago when venturing into the world of autoregressive, moving-average (ARIMA) models of time-series analysis…This monograph nicely lays out a method for assessing the impact of a discrete policy or event of some importance on behavior which can be continuously observed…If widely used, as I hope, it will save a generation of social scientists from the labor of having to learn this methodology the hard way…’ – Helmut Norpoth, State University of New York