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Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time-series data. Featuring improved organization and new material, the Second Edition also includes: Popular forecasting methods including smoothing algorithms, regression models, and neural networksA practical approach to evaluating the performance of forecasting solutionsA business-analytics exposition focused on linking time-series forecasting to business goalsGuided cases for integrating the acquired knowledge using real data End-of-chapter problems to facilitate active learningA companion site with data sets, R code, learning resources, and instructor materials (solutions to exercises, case studies)Globally-available textbook, available in both softcover and Kindle formats Practical Time Series Forecasting with R: A Hands-On Guide, Second Edition is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed