Practical Time Series Forecasting with R 
and Practical Time Series Forecasting provide an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. 

Balancing theory and practice, the books introduce popular forecasting methods and approaches used in a variety of business applications, and are ideal for Business Analytics, MBA, Executive MBA, and Data Analytics programs in business schools.
Practical Time Series Forecasting with R

Practical Time Series Forecasting

News & Announcements

  • New R Edition at USC Marshall Happy learning to Profs. Gabrys & Abbass course "Applied Time Series Analysis For Forecasting" at USC Marshall Masters of Science in Business Analytics using the new R version of Practical Time ...
    Posted by Boaz Shmueli
  • Book Adopted at Amrita University Happy learning to Professor Vivek Menon at Amrita University's MBA Program!
    Posted Sep 21, 2016, 2:13 AM by Boaz Shmueli
  • New Edition of Practical Time Series Forecasting with R Practical Time Series Forecasting with R, Second Edition is now in print (a Kindle version is also available; an Indian Edition is coming soon). Here is a summary of the ...
    Posted Jul 27, 2016, 11:22 PM by Boaz Shmueli
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Why choose Practical Time Series Forecasting?

The ideal forecasting textbooks for business analytics.
  • A new business-analytics approach to time-series forecasting
  • A good balance between theory and practice
  • Plenty of real-world examples
  • Hands-on exercises
  • Affordable and globally available
  • Paperback and Kindle editions
  • Written by author of top-selling Data Mining Book for Business Analytics
  • The perfect companion for data scientists

Praise for the Books

"The book is a little gem" 
— FORESIGHT, The International Journal of Applied Forecasting 

"An excellent primer"
— John Seymour, "John the Math Guy"

"This book was the perfect resource!"
— Debra Hunter 

"One of the best intro books on time series and forecasting I have ever seen" 
— Dr. Ron S. Kenett

See all Praise for Practical Time Series Forecasting.