Publisher's Synopsis
Practical Time Series Forecasting: A Hands-On Guide, Third 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 Excel(R) add-in XLMiner(R) to develop effective forecasting solutions that extract business value from time-series data.Featuring improved organization and new material, the Third Edition also includes:
- Popular forecasting methods including smoothing algorithms, regression models, and neural networks
- A practical approach to evaluating the performance of forecasting solutions
- A business-analytics exposition focused on linking time-series forecasting to business goals
- Guided cases for integrating the acquired knowledge using real data
- End-of-chapter problems to facilitate active learning
- A companion site with data sets, learning resources, and instructor materials (solutions to exercises, case studies, and slides)
- Globally-available textbook, available in both softcover and Kindle formats