What topics are covered in 'An Introduction to Statistical Learning'?

The book covers a wide range of topics including linear regression, classification, resampling methods, shrinkage methods, tree-based methods, support vector machines, and more. Each chapter offers theoretical concepts followed by practical applications using R. This makes it ideal for students and professionals looking to enhance their statistical modeling skills, providing both foundational knowledge and advanced analytical techniques for real-world data. The application of R in examples ensures that readers gain hands-on experience with statistical learning.

Who is the target audience for this book?

This book is aimed at data scientists, statisticians, and graduate students in statistics and related fields. It provides a comprehensive introduction to statistical learning, making it suitable for beginners to intermediate users who wish to deepen their understanding. By combining theoretical aspects with practical examples, it enhances the learning experience for educators and practitioners alike. Readers can utilize the text as a course textbook or a self-study guide to navigate the world of statistical learning.

How does this book differ from other statistical learning texts?

Unlike many statistical learning texts that can be dense and overly complex, this book emphasizes clarity and practical application. It provides straightforward explanations of concepts, alongside practical examples and R code snippets. Such an approach makes statistical learning accessible and easier to comprehend, catering to both theoretical insights and practical application. This makes the book a go-to resource for those looking to bridge the gap between theory and real-world usage.

Can I use R packages with the examples in the book?

Yes, the book is designed to work seamlessly with various R packages, which enhance the practical learning experience. Each chapter includes code examples that illustrate how to implement statistical techniques using popular R packages, such as 'caret', 'randomForest', and 'ggplot2'. This integration allows readers to directly apply what they've learned in R, making it ideal for practicing data analysis and visualization in a hands-on manner.

Is there any supplementary material available for this book?

Yes, accompanying the second edition, there are various resources available online including datasets used in the examples, R code snippets, and additional exercises. These resources can typically be found on the publisher's website or related academic repositories. This supplementary material enriches the learning experience, enabling readers to further engage with the content and apply their knowledge to practical problems in statistical learning.

What is the importance of statistical learning in data science?

Statistical learning is crucial for data science as it underpins many popular machine learning algorithms. It provides the methodologies for understanding and predicting patterns in data, which is essential for actionable insights. By mastering statistical learning techniques, data analysts and scientists can build predictive models, perform data-driven decision-making, and uncover trends that inform strategic business choices. This skill set is increasingly valuable in various industries, from healthcare to finance.

Is this book suitable for self-study?

Absolutely! The book is structured to facilitate self-study, featuring clear explanations, illustrative examples, and exercises at the end of each chapter. Readers can learn at their own pace, utilizing the practices alongside explanations to develop their skills in statistical learning. It serves as a complete guide for individuals interested in independently enhancing their knowledge base and technical skills in the field, leveraging R for practical applications.

What prior knowledge is needed to read this book?

While the book can be approached with a basic understanding of statistics and R, it is beneficial for readers to have a foundational knowledge of linear algebra and probability theory. This background allows readers to more effectively grasp the content and context of statistical learning techniques. However, the book also introduces concepts progressively, making it accessible for those willing to learn and engage with new material along the way.

Are there case studies included in the book?

Yes, 'An Introduction to Statistical Learning' includes real-world case studies that illustrate the application of statistical methods to complex problems. These case studies help readers understand the relevance and effectiveness of statistical learning techniques in various fields. By examining these cases, readers can see how to implement theoretical concepts in practice, enhancing their ability to tackle real datasets and derive meaningful conclusions from their analyses.

How to Shop An Introduction to Statistical Learning: with Online From Ubuy?

It’s easy to shop An Introduction to Statistical Learning: with online from Ubuy. You just have to search for the product, choose your shipping method while checking out and get it delivered to your location.

Is An Introduction to Statistical Learning: with Available to Shop Online in South Africa?

Yes, at Ubuy South Africa this product is available for you to shop at a reasonable price. The An Introduction to Statistical Learning: with is not available locally but you can trust us with our express shipping services.

How Long Does It Take to Get Product After Placing the Order?

The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning with relevant applications and tutorial on implementing analyses and methods in R, targeted at statisticians and non-statisticians alike.

Item #: 59936510

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Q: Where can I buy 'An Introduction to Statistical Learning: with Applications in R'?

You can purchase 'An Introduction to Statistical Learning: with Applications in R' on Ubuy. Ubuy offers access to a variety of textbooks including this one, providing a convenient platform to browse and order the title directly from the comfort of your home. With a user-friendly interface, Ubuy simplifies the process of acquiring educational materials for those looking to enhance their knowledge in statistical learning.

Item #: 59936510

ZAR 1126

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

^{*All items will import from US}

Availability : In stock

Imported from USA store

QTY:

Order now and get it around Wednesday, July 29

Secured transaction

Our Top Logistics Partners

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning with relevant applications and tutorial on implementing analyses and methods in R, targeted at statisticians and non-statisticians alike.

U-Care Warranty:

None

Select a Plan

Fast
Shipping

Free
Return^*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

Note: Step Down Voltage Transformer required for using electronics products of US store (110-120). Recommended power converters Buy Now.

What Stands Out

Comprehensive Coverage

Offers an extensive introduction to statistical learning techniques, integrating theoretical foundations and practical applications, making it ideal for both beginners and experienced practitioners.

R Integration

Incorporates R programming for hands-on data analysis, empowering readers to apply learned concepts directly in real-world scenarios, enhancing understanding of statistical methods.

Updated Content

The second edition includes updated examples and new applications, ensuring relevance and alignment with current trends in data science, preparing readers for contemporary challenges.

Product Details

Accessible overview of statistical learning for analyzing complex datasets
Covers important modeling and prediction techniques with real-world applications
Includes tutorials on implementing analyses and methods in R
Written for statisticians and non-statisticians interested in statistical learning
Second edition features new chapters on deep learning, survival analysis, and multiple testing
R code updated for compatibility

Item Weight

2.6 lbs (1.18 kg)

Who Should Buy?

Data Scientists
Ideal for data scientists seeking to gain practical statistical knowledge and apply it using R programming.
Graduate Students
Suitable for graduate students in statistics or related fields who need an introduction to statistical learning concepts.
Statistical Analysts
Helpful for statistical analysts aiming to deepen their understanding of statistical methods and their applications in R.

Beginners in Statistics
Not suitable for complete beginners, as prior knowledge in statistics and R programming is recommended.
Advanced Statisticians
May not meet the needs of advanced statisticians looking for in-depth, specialized statistical methodologies.
Non-technical Users
Individuals without a technical or statistical background might find the content challenging and less applicable.

Product Description

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Have any Query? Chat with us

Customer Questions & Answers

Question: How to Shop An Introduction to Statistical Learning: with Online From Ubuy?

Answer: It’s easy to shop An Introduction to Statistical Learning: with online from Ubuy. You just have to search for the product, choose your shipping method while checking out and get it delivered to your location.
Question: Is An Introduction to Statistical Learning: with Available to Shop Online in South Africa?

Answer: Yes, at Ubuy South Africa this product is available for you to shop at a reasonable price. The An Introduction to Statistical Learning: with is not available locally but you can trust us with our express shipping services.
Question: How Long Does It Take to Get Product After Placing the Order?

Answer: The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.

Intelligence & Semantics Editorial Review

"An Introduction to Statistical Learning: with Applications in R" is a well-balanced book for beginners who want to learn about machine learning. It strikes a good balance between containing enough detail to help grasp theory but not becoming a slog to get through. The book explains the rationale of different models in an easy-to-understand way. Although the book uses R, its concepts and theories can be applied to other programming languages. This book is an amazing resource for understanding many different methods in line.

Customer Reviews & Ratings

4.0

1 customers ratings

5 Star

0%
4 Star

100%
3 Star

0%
2 Star

0%
1 Star

0%

Review this product

Share your thoughts with other customers

Pros

Well-balanced between proper depth and easy-to-understand
Contains enough detail to help grasp theory without becoming a slog
Explains the rationale of different models in an easy-to-understand way
Amazing resource for understanding many different methods in line

Cons

Uses R, which may not be preferred by some readers

Top selling Statistical Learning in {{COUNTRY_NAME}}

Product Image	Product Details
Product Image	Product Name	Brand
	An Introduction to Statistical Learning with Applications in Python Springer Texts in Statistics
	An Introduction to Statistical Learning with Applications in Python Springer Texts in Statistics	-
	An Introduction to Statistical Learning with Applications in R Springer Texts in Statistics
	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
	The Elements of Statistical Learning Data Mining, Inference, and Prediction, Second Edition Springer Series in Statistics	-
	Statistics The Art and Science of Learning from Data, Global Edition
	Statistics The Art and Science of Learning from Data, Global Edition	-
	Statistics The Art and Science of Learning from Data
	Statistics The Art and Science of Learning from Data	-
	Building Statistical Models in Python Develop useful models for regression, classification, time series, and survival analysis
	Building Statistical Models in Python Develop useful models for regression, classification, time series, and survival analysis	-
	Probability and Statistics for Computer Science
	Probability and Statistics for Computer Science	-
	Statistics Every Programmer Needs Practical Python implementations and quantitative methods
	Statistics Every Programmer Needs Practical Python implementations and quantitative methods	-
	Statistics for the Social Sciences A General Linear Model Approach
	Statistics for the Social Sciences A General Linear Model Approach	-
	STAT2 Modeling with Regression and ANOVA
	STAT2 Modeling with Regression and ANOVA	-

Last Updated on Juli 13, 2026

Product Price History

Important information

Limitations : For products shipped internationally, please note that any manufacturer warranty may not be valid; manufacturer service options may not be available; product manuals, instructions, and safety warnings may not be in destination country languages; the products (and accompanying materials) may not be designed in accordance with destination country standards, specifications, and labeling requirements; and the products may not conform to destination country voltage and other electrical standards (requiring use of an adapter or converter if appropriate). The recipient is responsible for assuring that the product can be lawfully imported to the destination country. When ordering from Ubuy or its affiliates, the recipient is the importer of record and must comply with all laws and regulations of the destination country.
Not all the products listed on Ubuy are for sale, as Ubuy is a global search engine. Products are subject to export/trade regulations.

ZAR 1126

Order now and get it around Wednesday, July 29

QTY:

Secured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners

Fastest cross-border delivery

Features & Benefits

Accessible overview of statistical learning
Relevant applications and tutorial on implementing analyses and methods in R
Targeted at statisticians and non-statisticians alike
New chapters on deep learning, survival analysis, and multiple testing
Expanded treatments of naïve Bayes and generalized linear models
R code updated for compatibility

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns ^*, and secure packaging on every order.

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

ZAR 1126

Fast Shipping

Free Return*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

What Stands Out

Product Details

Who Should Buy?

Product Description

Customer Questions & Answers

Intelligence & Semantics Editorial Review

Customer Reviews & Ratings

Review this product

Pros

Cons

Top selling Statistical Learning in {{COUNTRY_NAME}}

Product Price History

Important information

ZAR 1126

Features & Benefits

Ubuy Assurance

Fast
Shipping

Free
Return^*