---
product_id: 7510106
title: "Forecasting: principles and practice"
price: "₨2371"
currency: SCR
in_stock: true
reviews_count: 13
url: https://www.desertcart.sc/products/7510106-forecasting-principles-and-practice
store_origin: SC
region: Seychelles
---

# Forecasting: principles and practice

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## Description

Forecasting: principles and practice [Hyndman, Rob J, Athanasopoulos, George] on desertcart.com. *FREE* shipping on qualifying offers. Forecasting: principles and practice

Review: Outstanding practical book on forecasting - This book is an excellent resource for anyone trying to master practical nuts and bolts of forecasting or who is just starting to study the field. The authors explain the practical issues needed to forecast. If you want to know about the distribution of the Durbin-Watson statistic, or other recondite details, this is not the right resource. The text is tightly integrated with R examples which make it easy to start applying immediately what you have learned. Note: I read the free web version before the text was released. An index, however, would have been helpful.
Review: Understand and implement forecasting algorithms - While working on forecasting (understand “time series analysis”) I found several interesting and state of the art articles from Rob J. Hyndman. He is the co-author, with George Athanasopoulos of Forecasting: Principles and Practice. This is an excellent, concise and comprehensive text explaining concepts behind forecasting, common algorithms and how to implement them in R (for a business view of forecasting, I advise "Future Ready"). The book presents key concepts of forecasting. From judgemental forecasting (which can be useful when you have no or few data) to simple/multiple regression, time series decomposition, exponential smoothing (ETS), ARIMA and a few more advanced topics such as Neural Networks. I would suggest to the author to add Support Vector Regression (SVR) and ensemble learning for the next edition of the book. Each concept of the book is covered through examples with real data. What is most appreciable about the book is how concise and readable it is. Each sentence is useful to understand the described concept, nothing superfluous. The book contains good overview and schema about each technique and how to set their meta-parameters. The R codes are well presented and easy to implement and test. The book can easily be used to teach forecasting since each chapter contains exercises. In conclusion, Forecasting: Principles and Practice is THE book to learn time series analysis algorithms and how to implement them in R.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #3,534,440 in Books ( See Top 100 in Books ) #1,068 in Business Planning & Forecasting (Books) |
| Customer Reviews | 4.3 4.3 out of 5 stars (51) |
| Dimensions  | 6.69 x 0.61 x 9.61 inches |
| ISBN-10  | 0987507109 |
| ISBN-13  | 978-0987507105 |
| Item Weight  | 1.03 pounds |
| Language  | English |
| Print length  | 292 pages |
| Publication date  | October 17, 2013 |
| Publisher  | OTexts |

## Images

![Forecasting: principles and practice - Image 1](https://m.media-amazon.com/images/I/5156fOHNvxL.jpg)
![Forecasting: principles and practice - Image 2](https://m.media-amazon.com/images/I/516cqMsvzmL.jpg)
![Forecasting: principles and practice - Image 3](https://m.media-amazon.com/images/I/81vneQG5sTL.jpg)
![Forecasting: principles and practice - Image 4](https://m.media-amazon.com/images/I/81xgM9qYIML.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Outstanding practical book on forecasting
*by L***E on May 1, 2014*

This book is an excellent resource for anyone trying to master practical nuts and bolts of forecasting or who is just starting to study the field. The authors explain the practical issues needed to forecast. If you want to know about the distribution of the Durbin-Watson statistic, or other recondite details, this is not the right resource. The text is tightly integrated with R examples which make it easy to start applying immediately what you have learned. Note: I read the free web version before the text was released. An index, however, would have been helpful.

### ⭐⭐⭐⭐ Understand and implement forecasting algorithms
*by S***A on May 21, 2017*

While working on forecasting (understand “time series analysis”) I found several interesting and state of the art articles from Rob J. Hyndman. He is the co-author, with George Athanasopoulos of Forecasting: Principles and Practice. This is an excellent, concise and comprehensive text explaining concepts behind forecasting, common algorithms and how to implement them in R (for a business view of forecasting, I advise "Future Ready"). The book presents key concepts of forecasting. From judgemental forecasting (which can be useful when you have no or few data) to simple/multiple regression, time series decomposition, exponential smoothing (ETS), ARIMA and a few more advanced topics such as Neural Networks. I would suggest to the author to add Support Vector Regression (SVR) and ensemble learning for the next edition of the book. Each concept of the book is covered through examples with real data. What is most appreciable about the book is how concise and readable it is. Each sentence is useful to understand the described concept, nothing superfluous. The book contains good overview and schema about each technique and how to set their meta-parameters. The R codes are well presented and easy to implement and test. The book can easily be used to teach forecasting since each chapter contains exercises. In conclusion, Forecasting: Principles and Practice is THE book to learn time series analysis algorithms and how to implement them in R.

### ⭐⭐⭐⭐⭐ If I have to buy one book on forecasting, it will be this one
*by P***H on May 13, 2019*

Excellent book with very broad coverage. Depth may be lacking some times and you may have to resort to the academic papers cited. There is no coverage of recent deep learning models like RNN and LSTM for forecasting.

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*Last updated: 2026-03-06*