---
product_id: 347778238
title: "An Introduction to Statistical Learning: with Applications in R"
price: "Bs.2354"
currency: BOB
in_stock: true
reviews_count: 5
url: https://www.desertcart.bo/products/347778238-an-introduction-to-statistical-learning-with-applications-in-r
store_origin: BO
region: Bolivia
---

# An Introduction to Statistical Learning: with Applications in R

**Price:** Bs.2354
**Availability:** ✅ In Stock

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- **What is this?** An Introduction to Statistical Learning: with Applications in R
- **How much does it cost?** Bs.2354 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.bo](https://www.desertcart.bo/products/347778238-an-introduction-to-statistical-learning-with-applications-in-r)

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## Description

Buy An Introduction to Statistical Learning: with Applications in R by James, Gareth, Witten, Daniela, Hastie, Trevor, Tibshirani, Robert online on desertcart.ae at best prices. ✓ Fast and free shipping ✓ free returns ✓ cash on delivery available on eligible purchase.

Review: The authors Hastie and Tibshirani are legends in the stats world, creating GAM and LASSO respectively. Their other textbook "The Elements of Statistical Learning" is geared for PhD students. This textbook is very accessible, with figures and lots of sample code. The target audience is any aspiring data scientist who can learn to code and wants to actually understand what the code/models are doing (but doesn't need to be able to derive all the original math by hand). In addition to teaching different analyses, this book does a great job on explaining key statistical analysis concepts, like bias vs variance tradeoff, k-fold cross-validation, bootstrapping, finding the right balance in model complexity for your dataset, etc. There is both an R and a Python edition. The 2nd edition includes 3 new chapters on survival analysis, multiple testing, and neural nets. There is a free Stanford MOOC that uses this text.
Review: It was the same thing I ordered for

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #111,533 in Books ( See Top 100 in Books ) #170 in Computer Software #204 in Applied Mathematics #569 in Computer Science |
| Customer reviews | 4.6 4.6 out of 5 stars (412) |
| Dimensions  | 16.51 x 3.18 x 24.13 cm |
| Edition  | 2nd ed. 2021 |
| ISBN-10  | 1071614177 |
| ISBN-13  | 978-1071614174 |
| Item weight  | 1.19 Kilograms |
| Language  | English |
| Print length  | 607 pages |
| Publication date  | 30 July 2021 |
| Publisher  | Springer-Verlag New York Inc. |

## Images

![An Introduction to Statistical Learning: with Applications in R - Image 1](https://m.media-amazon.com/images/I/61XlRprVVML.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Review
*by M***Z on 30 January 2024*

The authors Hastie and Tibshirani are legends in the stats world, creating GAM and LASSO respectively. Their other textbook "The Elements of Statistical Learning" is geared for PhD students. This textbook is very accessible, with figures and lots of sample code. The target audience is any aspiring data scientist who can learn to code and wants to actually understand what the code/models are doing (but doesn't need to be able to derive all the original math by hand). In addition to teaching different analyses, this book does a great job on explaining key statistical analysis concepts, like bias vs variance tradeoff, k-fold cross-validation, bootstrapping, finding the right balance in model complexity for your dataset, etc. There is both an R and a Python edition. The 2nd edition includes 3 new chapters on survival analysis, multiple testing, and neural nets. There is a free Stanford MOOC that uses this text.

### ⭐⭐⭐⭐⭐ Review
*by E***H on 11 June 2025*

It was the same thing I ordered for

### ⭐⭐⭐⭐⭐ Review
*by R***S on 25 April 2024*

wonderfull book, I am currently studying a master in Bionformatics and needed to brush my forgotten lessons of Statistics. Amazed how the authors are able to explain the most advanced and difficult concepts skiping the mathematics below, for example the subject of hyperplanes is so amazingly exposed that it should be given as an role model of teaching and turning a difficult subject into an accesible one.I recommed this book with all my heart¡¡

## Frequently Bought Together

- An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
- An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)

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*Product available on Desertcart Bolivia*
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*Last updated: 2026-01-24*