Foundations of Statistics for Data Scientists: With R and Python (Chapman & Hall/CRC Texts in Statistical Science)
$66.26
Description
Book Synopsis: Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.
Key Features:
- Shows the elements of statistical science that are important for students who plan to become data scientists.
- Includes Bayesian and regularized fitting of models (e.g., showing an example using the lasso), classification and clustering, and implementing methods with modern software (R and Python).
- Contains nearly 500 exercises.
The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website (http://stat4ds.rwth-aachen.de/) has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.
Details
Are you passionate about data science? Ready to take your skills to the next level? Look no further than Foundations of Statistics for Data Scientists: With R and Python! This comprehensive textbook is the perfect resource for students training to become data scientists. With its in-depth coverage of probability distributions, descriptive and inferential statistical methods, and linear modeling, this book ensures that you will have a solid foundation in statistical science. And don't worry if you're not a math whiz - the book focuses on "why it works" rather than complex mathematical theory, making it accessible to all. Get your copy now and become a master of statistical analysis!
But what sets this book apart from others? It goes beyond traditional textbooks by emphasizing the practical application of statistical methods using modern software. All statistical analyses in the book are performed using R software, with an appendix demonstrating the same analyses with Python. With a focus on software implementation and simulations, you'll gain hands-on experience and learn how to effectively utilize these tools in real-world scenarios. Whether you're interested in Bayesian inference, regularized model fitting, or classification and clustering, this book covers it all.
As a data scientist, it's important to have a deep understanding of statistical concepts. Foundations of Statistics for Data Scientists: With R and Python provides just that, with nearly 500 exercises to reinforce your learning. These exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts," allowing you to practice and apply your knowledge. Plus, the book's website offers additional resources, including expanded appendices for R, Python, and Matlab, as well as all the data sets from the examples and exercises. Don't miss out on this invaluable learning tool!
Ready to take your data science skills to the next level? Don't wait - get your copy now and become a master of statistical analysis!
Discover More Best Sellers in Programming Languages
Shop Programming Languages
Programming Languages - Web Development with Blazor: A practical guide to start building interactive UIs with C# 11 and .NET 7, 2nd Edition
Programming Languages - Pretrain Vision and Large Language Models in Python: End-to-end techniques for building and deploying foundation models on AWS
Python Programming: An Introduction to Computer Science, 3rd Ed.
Programming Languages - Python Programming: An Introduction to Computer Science, 3rd Ed.
Python for Data Science: A Hands-On Introduction
Programming Languages - Python for Data Science: A Hands-On Introduction
Programming Languages - Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Programming Languages - Learn React with TypeScript: A beginner's guide to reactive web development with React 18 and TypeScript
MATLAB For Dummies (For Dummies (Computer/Tech))
Programming Languages - MATLAB For Dummies (For Dummies (Computer/Tech))
