Statistical Practice for Data Science: R by Nalini Ravishanker (.PDF)
File Size: 13.4 MB
Statistical Practice for Data Science: With Hands-On Illustrations Using R by Nalini Ravishanker, Asha Gopalakrishnan, Haim Bar
Requirements: .PDF reader, 13.4 MB | True PDF
Overview: Statistical Practice for Data Science: with Hands-on Illustrations using R is a comprehensive guide designed to equip students from diverse fields―engineering, science, and the biological, physical, and social sciences―with the statistical tools and techniques essential for Data Science. This book bridges the gap between theoretical concepts and practical applications, offering a clear and accessible introduction to statistics with minimal mathematical prerequisites. With a focus on real-world datasets and hands-on implementation using R, it empowers students to analyze, interpret, and communicate data effectively.
The book begins with foundational concepts in probability and statistics, ensuring that students with only college-level algebra can grasp the material. It progresses through key topics such as data visualization, hypothesis testing, regression modeling, and modern Machine Learning methods like random forests and gradient boosting. Each chapter is enriched with practical examples and coding exercises in R, making it an invaluable resource for students embarking on a data science program.
Genre: Non-Fiction > Tech & Devices
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