Foundations of Statistics for Data Scientists: With R and Python

The textbook Foundations of Statistics for Data Scientists: With R and Python is a comprehensive introduction to mathematical statistics for students training to become data scientists. It covers probability distributions, descriptive and inferential statistical methods, and linear modeling, with an emphasis on using software to implement statistical methods and conduct simulations. The book includes nearly 500 exercises and introduces modern topics such as Bayesian inference, generalized linear models, and regularized model fitting.

Format: Hardback
Length: 468 pages
Publication date: 30 November 2021
Publisher: Taylor & Francis Ltd

This comprehensive textbook is meticulously crafted to serve as a foundational guide for students embarking on a one- or two-term introduction to mathematical statistics, with a specific focus on its applications in data science. It delves into the core principles and topics of statistical science, providing a thorough and in-depth exploration of the field. The book assumes a foundational understanding of basic calculus, allowing it to delve into the theoretical underpinnings while emphasizing practical implementation and software usage.

In contrast to traditional mathematical statistics textbooks, this book places greater emphasis on utilizing software to execute statistical methodologies and conduct simulations to elucidate key concepts. All statistical analyses presented in the book are conducted using the powerful R software, with an appendix providing equivalent implementations in Python.

The textbook offers a well-structured and organized approach, dividing its content into two main sections: Data Analysis and Applications and Methods and Concepts. Within these sections, the book covers a wide range of topics essential for data scientists, including probability distributions, descriptive and inferential statistical methods, and linear modeling. It provides detailed explanations and examples to facilitate a deep understanding of these concepts.

One of the notable features of this textbook is its extensive exercise coverage. With nearly 500 exercises, students are provided with hands-on opportunities to apply and reinforce their knowledge. These exercises are thoughtfully categorized into Data Analysis and Applications and Methods and Concepts, allowing students to focus on specific areas of interest. Additionally, appendices introduce R and Python, providing a solid foundation for those who wish to explore these programming languages further.

Furthermore, the book's website (http://stat4ds.rwth-aachen.de/) offers valuable resources, including lecture slides, code snippets, and solutions to odd-numbered exercises. This additional support enhances the learning experience and allows students to delve deeper into the topics covered.

In summary, Foundations of Statistics for Data Scientists: With R and Python is an exceptional textbook that caters to the needs of students aspiring to become data scientists. It provides a comprehensive and rigorous introduction to mathematical statistics, emphasizing practical applications and software usage. With its extensive exercise coverage, appendices, and online resources, this textbook equips students with the skills and knowledge required to excel in the field of data science. Whether you are a novice or an experienced student, this book is an invaluable resource for your statistical education.

Weight: 1168g
Dimension: 182 x 260 x 32 (mm)
ISBN-13: 9780367748456