<p><b>Praise for the <i>First Edition<br><br></i></b>&quot;…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics.&quot; -<i>MAA Reviews</i><b><br><br></b>Thoroughly updated throughout, <i>Introduction to Time Series Analysis and Forecasting, Second Edition</i> presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. <br><br>Authored by highly-experienced academics and professionals in engineering statistics, the<i>Second Edition</i> features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting.<i>Introduction to Time Series Analysis and Forecasting, Second Edition</i> also includes:<br><br></p><ul><li>Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance</li><li>More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data</li><li>New material on frequency domain and spatial temporal data analysis </li><li>Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions</li><li>A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems</li></ul><br><i>Introduction to Time Series Analysis and Forecasting, Second Edition</i> is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.