Introduction to Statistical Learning by Gareth James et al.
Covers core concepts like regression, classification, and model selection, all with a focus on practical applications..
Naked Statistics: Stripping the Dread from the Data by Charles Wheelan
This book makes statistics approachable and fun. Teaches you to think critically about data and avoid common misinterpretations.
Think Stats: Probability and Statistics for Programmers by Allen B. Downey
Ideal for those with some programming experience. Teaches statistical concepts through real-world Python examples.
The Elements of Statistical Learning by Trevor Hastie et al.
Explores complex topics like Machine Learning and statistical inference, making it a valuable resource for experienced data scientists.
Practical Statistics for Data Scientists by Peter Bruce et al.
Bridges the gap between statistics and data science applications. Focuses on using R and Python to implement key statistical techniques commonly used in data analysis.
Statistics for Data Science: An Introduction to Probability, Statistics, and Data Analysis by James Miller
It Provides a strong foundation for further learning and practical application.