List of Figures List of Tables Acknowledgements 1 Introduction to ITSA 2 ARIMA Algebra 3 The Noise Component: N(at) 4 The Intervention Component: X(It) 5 Auxiliary Modeling Procedures References Index

Selling point: Provides tools for researchers whose data consist of a long sequence of observations measured before and after a treatment, intervention, or other significant change Selling point: Integrates the statistical issues of design, estimation and interpretation with foundational validity issues Selling point: Provides a unique focus on time series experiments Selling point: Emphasizes graphical aspects of time series analysis, including more than 130 figures and an equal number of tables Selling point: Includes over forty example analyses that instructors could assign as problems to students

David McDowall is Distinguished Teaching Professor at the University at Albany, State University of New York. He serves on the faculty of Albany's School of Criminal Justice, where he also co-directs the Violence Research Group. His research interests involve the social distribution of criminal violence, including trends and other temporal features in crime rates. Richard McCleary is a professor at the University of California, Irvine. In addition to faculty appointments in Criminology, Law and Society, Environmental Health Sciences, and Planning, Policy and Design, he directs the Irvine Simulation Modeling Laboratory. His research interests include population forecast models, time series models, and survival models. Bradley J. Bartos is a doctoral candidate in the Department of Criminology, Law and Society at the University of California, Irvine. Through his work with the Irvine Simulation Modeling Laboratory, he has developed discrete-event population projection models for various criminal-justice and corrections systems in California. His research interests include mass incarceration, policy evaluation, time series models, and synthetic control group designs.

Selling point: Provides tools for researchers whose data consist of a long sequence of observations measured before and after a treatment, intervention, or other significant change Selling point: Integrates the statistical issues of design, estimation and interpretation with foundational validity issues Selling point: Provides a unique focus on time series experiments Selling point: Emphasizes graphical aspects of time series analysis, including more than 130 figures and an equal number of tables Selling point: Includes over forty example analyses that instructors could assign as problems to students