Essential Statistics for Data Science: A Concise Crash Course by Mu Zhu is a comprehensive resource that delves into the foundational statistical concepts crucial for data science. This edition emphasizes a three-part structure:
 
Part I: Talking Probability – Introduces the statistical approach to analyzing data, beginning with probability models to describe data-generating processes.
 
Part II: Doing Statistics – Focuses on statistical inference, guiding readers through learning unknown quantities in models from the data they generate.
 
Part III: Facing Uncertainty – Discusses the importance of quantifying uncertainty about model parameters and incorporating that into decision-making.
 
By integrating robust research, evidence-based practices, and compelling narratives, the text fosters a deeper understanding of topics such as probability models, random variables, frequentist and Bayesian approaches, interval estimation, and significance testing. It is an invaluable resource for students and professionals seeking to enhance their knowledge in data science.
 
This high-quality PDF eBook features a professional design and interactive content, allowing you to easily navigate between chapters and sections through clickable links.
 
Essential Statistics for Data Science: A Concise Crash Course by Mu Zhu, published by Oxford University Press in 2023, is available in interactive PDF format, with Print ISBN: 0192867741, 9780192867742 and eTextbook ISBN: 0191959844, 9780191959844. This edition is categorized under Applied Mathematics and Mathematical Education, making it an invaluable asset for those aiming to excel in statistical applications within data science. Purchase this eBook and save up to 80% at Ebookworm.
 
About the Author:
 
Mu Zhu: Professor in the Department of Statistics & Actuarial Science at the University of Waterloo and Fellow of the American Statistical Association. He received his AB magna cum laude in applied mathematics from Harvard University and his PhD in statistics from Stanford University. He is currently Director of the Graduate Data Science Program at Waterloo.