Best Probability & Statistics Books of 2025

The Princeton Review AP Statistics Prep, 2023 is an extensive study guide that includes everything needed to score a perfect 5 on the AP Statistics Exam. It comprises five full-length practice tests with answer explanations, content reviews for all topics, strategies for every question type, and access to online extras. The book is fully aligned with the latest College Board standards for AP Statistics and offers tried-and-true strategies to help avoid traps and beat the test. The engaging activities and step-by-step walk-throughs for setting up box plots, dot plots, and other statistics graphics make this book unique. Overall, this book is a valuable resource for anyone preparing for the AP Statistics Exam.

How the World Really Works: The Science Behind How We Got Here and Where We're Going is an instant New York Times bestseller that offers a reality check on the modern science and technology that makes our twenty-first century lives possible. In this thought-provoking book, the author explains seven fundamental realities governing our survival and prosperity, from energy and food production to risks, the environment, and its future. This interdisciplinary guide finds faults with both extremes and offers a much-needed perspective on the facts. Overall, this book is a compelling and highly readable analysis that leaves readers with the fundamental grounding needed to help solve the world’s toughest challenges.

Statistics for People Who (Think They) Hate Statistics by Neil J. Salkind and Bruce B. Frey is an excellent guide for students who find statistics intimidating. The book provides a humorous, personable, and informative approach to teaching basic and advanced statistical procedures. The Seventh Edition includes real-world examples, additional coverage on multiple regression, and a robust interactive eBook. The authors' instruction in SPSS® makes the book a valuable resource for students who want to understand statistical analyses without feeling intimidated. Overall, this book is an exceptional resource for anyone who wants to learn the principles of statistics in an approachable way.

The Freakonomics Revised and Expanded Edition, written by Steven Levitt and Stephen J. Dubner, presents a brilliant and entertaining account of how incentives drive behavior in ways that challenge conventional wisdom. Levitt, a renowned economist, uses the principles of economics to examine daily life phenomena, such as baby-naming patterns and sumo wrestling. This edition includes an exclusive discussion between the authors and bestselling professor of psychology Angela Duckworth. The book is politically incorrect in the best, most essential way, and provides bracing fun of the highest order. This edition is a must-read for anyone interested in the theory of economics.

Factfulness: Ten Reasons We're Wrong About the World--and Why Things Are Better Than You Think by Hans Rosling is a must-read book for anyone interested in cognitive psychology. The book reveals the ten instincts that distort our perspective and offers a radical new explanation of why we systematically get the answers about global trends wrong. Rosling teaches readers how to see progress clearly and how to work off facts rather than our inherent biases. The book is a hopeful reminder that the world is in a much better state than we might think. Overall, Factfulness is an insightful and eye-opening read that challenges readers to re-examine their worldview based on facts.

This comprehensive guide, "Essential Math for AI", is a must-read for anyone interested in the AI field. It provides a comprehensive understanding of the underlying mathematics necessary to build successful AI systems, focusing on real-world applications and state-of-the-art models. The book is written in an immersive and conversational style, making it easy for anyone to learn and understand. It covers topics such as regression, neural networks, convolution, optimization, probability, graphs, random walks, Markov processes, differential equations, and more. The author has done an exceptional job of making math fun and engaging, making this book stand out from other math textbooks.

Barron's AP Statistics Premium: 2023-2024 is a comprehensive review book that includes nine full-length practice tests and online practice. It covers all units on the AP Statistics Exam and provides detailed answer explanations and expert advice. The book is written and reviewed by AP experts, providing students with tips, strategies, and study advice for exam day. With a diagnostic test to target studying and timed test options, students can simulate the exam experience. Dr. Martin Sternstein, a long-time College Board consultant, wrote the book. Overall, this book is an excellent resource for students preparing for the AP Statistics Exam.

Essential Math for Data Science is a comprehensive guide for mastering the mathematical concepts required to excel in data science, machine learning, and statistics. The book covers a range of topics from calculus to linear algebra, statistics to neural networks, all presented in plain English and with minimal mathematical jargon. It also provides practical insights into the state of data science and how to use those insights to maximize your career. Thomas Nield's relatable approach to technical content makes this book a must-read for anyone looking to improve their skills in data science.

Discovering Statistics Using IBM SPSS Statistics: North American Edition by Andy Field is a comprehensive guide for students to learn statistics in a fun and accessible way. The fifth edition incorporates IBM SPSS Statistics© version 25, taking students from initial theory to regression, factor analysis, and multilevel modeling. The book offers a unique combination of humor and step-by-step instruction. It also provides a research roadmap to navigate projects and fascinating examples throughout. The text has received positive reviews from students and professors alike for its captivating writing style and practical guides for reporting results and findings. Overall, this book is an excellent resource for those who want to learn statistics in an engaging way.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition is a comprehensive guide to statistical learning that covers a broad range of topics, from supervised learning to unsupervised learning. The book is well-organized and includes many examples, with a liberal use of colour graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The second edition has been updated to include new material on graphical models, random forests, ensemble methods, and more. Overall, this book is highly recommended for anyone looking to deepen their understanding of statistical learning.