If you are a data science enthusiast or a student looking to delve into the world of statistical science, the book Foundations of Statistics for Data Scientists: With R and Python is a valuable resource to consider. Authored by Alan Agresti and Maria Kateri, this textbook offers a comprehensive introduction to mathematical statistics tailored for individuals aspiring to become data scientists.
Key Features of the Book:
- Provides a deep understanding of statistical concepts essential for data scientists.
- Covers Bayesian and regularized fitting of models, classification, clustering, and practical implementation with R and Python.
- Includes nearly 500 exercises to enhance learning and reinforce key concepts.
- Introduces modern topics like Bayesian inference, generalized linear models, and regularized model fitting.
About the Authors:
Alan Agresti is a Distinguished Professor Emeritus at the University of Florida and the author of several acclaimed books on statistics. Maria Kateri, a Professor of Statistics and Data Science at RWTH Aachen University, brings her expertise in teaching statistics to a diverse range of students.
Frequently Asked Questions (FAQs)
Q: Can this book be used for self-study purposes?
A: Yes, this book is suitable for self-study as it provides in-depth explanations of statistical concepts along with exercises to practice and reinforce learning.
Q: Does the book require prior knowledge of calculus?
A: The book assumes a basic understanding of elementary calculus to help readers grasp the concepts effectively.
Q: Are the exercises in the book accompanied by solutions?
A: Yes, the book includes solutions for the odd-numbered exercises to aid in self-assessment and learning.
Conclusion
Foundations of Statistics for Data Scientists: With R and Python is a valuable textbook that bridges the gap between mathematical statistics and practical implementation for aspiring data scientists. With a focus on key concepts, modern applications, and hands-on exercises, it equips readers with the essential skills needed to excel in the field of data science.
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