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  • Practical Time Series Forecasting with R: A Hands-On Guide [2nd Edition] by Kenneth C., Jr. Lichtendahl book cover
  • Practical Time Series Forecasting with R: A Hands-On Guide [2nd Edition] by Kenneth C., Jr. Lichtendahl book cover
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Practical Time Series Forecasting with R: A Hands-On Guide [2nd Edition]

by Kenneth C., Jr. Lichtendahl

Forecasting methods grounded in business applications

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AlbakiReads Editorial

Forecasting methods grounded in business applications

This second edition connects time-series forecasting with practical work in business analytics, using the open-source R software as its working environment. It introduces methods including smoothing algorithms, regression models, and neural networks, then addresses how to evaluate forecasting performance and relate analytical work to business goals. Guided cases with real data and end-of-chapter problems give the material an applied structure. The companion site is described as providing datasets, R code, learning resources, and instructor materials.

Good fit for readers who enjoy

  • Students in upper-undergraduate, graduate, or MBA courses in forecasting, data science, or business analytics.
  • Practitioners in operations research, supply chain management, marketing, economics, finance, or management.
  • Readers seeking applied instruction in time-series methods using R.

Themes

Time-series forecastingBusiness analyticsForecast evaluationR programmingApplied learning with real data

Based on publisher information and book metadata.

Book overview

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 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, 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 for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management.For more information, visit forecastingbook.com
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