All of Statistics
by Larry Wasserman · first published 2004
67% recommend28% neutral5% critical
Why HN recommends it
Concise, math-based tour of statistical inference and probability, written for people in CS and machine learning. Good as a reference, with plenty of well-chosen exercises; terse chapters suit readers with calculus.
Common criticism: Not a gentle starting point; heavy on theory and terse for newcomers
Summarised by Claude from recommending comments
"This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining, and machine learning." "This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear alge
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…better served going with more introductory texts and really understanding them. Maybe Blitzstein and Hwang's "Introduction to Probability" and then McElreath's "Statistical Rethinking" or Wasserman's "All of Statistics" for people who need more stats. I'm not even sure what to recommend for developing good software judgment and habits. There doesn't seem to be a shortcut for that. Maybe "Fluent Python" or "Effective…
on “Best Data Science Books According to the Experts” ↗All of Statistics by Larry Wasserman is the book I recommend for anyone who knows calculus and linear algebra and wants to learn statistics.
on “Ask HN: What are your favorite statistics and probability textbooks?” ↗…4 books covering real, complex and functional analysis by Stein and Shakarchi, which should serve your purpose Applied Math : 3) Probability - Grinstead and Snell, Durrett both have good books. 4) All of Statistics by Larry Wasserman for a more ML bent to it 5) Optimization by Boyd and Vanderberghe 7) There's no single topic called "Computer Science", but going with the theme of the topics you are looking at,…
on “Ask HN: Mathematicians, what textbooks are best for learning these math topics?” ↗…Machine Learning (https://smile.amazon.com/Pattern-Recognition-Learning-Inform...) * Machine Learning: A Probabilistic Perspective (https://smile.amazon.com/Machine-Learning-Probabilistic-Pers...) * All of Statistics: A Concise Course in Statistical Inference (https://smile.amazon.com/gp/product/0387402721/) * Elements of Statistical Learning: Data Mining, Inference, and Prediction (https://smile.amazon.com/gp/product/0387848576(…
on “Machine Learning for Software Engineers” ↗"All of Statistics" by Larry Wasserman is very good. It is traditional, fairly mathematical statistics, but intended for a general audience. (It is particularly popular with computer science people.)
on “Elements Of Statistical Learning: now free pdf” ↗I'm not a big fan of the percentile bootstrap, but that reference is a little too cavalier with material that deserves to be treated more rigorously. Chapter 8 of Wasserman's "All of Statistics" is much more careful about outlining the conditions under which the percentile bootstrap will work. Moreover, he works through a specific example that demonstrates that the percentile bootstrap does…
on “Bootstrapped – A Python library to generate confidence intervals” ↗What a beautiful presentation! Tangentially: I am really enjoying the book "All of Statistics" as a reference for better understanding things like histograms, kernel density functions, etc, and their parameters. https://www.amazon.com/All-Statistics-Statistical-Inference-...
on “What's so hard about histograms?” ↗Reading 'All of statistics' by Wasserman would be a much better bet than diving deep into measure-theoretic probability though.
on “Probability Theory for Scientists and Engineers” ↗All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman You can find in PDF by typing it into your favorite search engine.
on “Ask HN: Recommend Books on Statistics” ↗All of Statistics by Larry Wasserman is a great introductory book from the frequentist tradition that includes some sections on Bayesian methods. It's definitely not frequentist propaganda - more like a sober look at the…
on “Statistical Rethinking (2022 Edition)” ↗…Analysis (Pugh) - Mathematics and its History (Stillwell) - An Introduction to Manifolds (Tu) - Gauge Fields, Knots and Gravity (Baez) - A First Look at Rigorous Probability Theory (Rosenthal) - All of Statistics (Wasserman) There are some authors I trust and am happy to buy so long as the topic vaguely interests me: VI Arnold, Tristan Needham and John Stillwell. I really like the list put out by @enriquto in…
on “Ask HN: Math books that made you significantly better at math?” ↗…probability using the foundation of measure theory, and a mathematician would probably want to understand probability first before statistics. That said, although I have not tried to read it, the book titled "All of Statistics: A Concise Course in Statistical Inference", by Wasserman, looks to me like a fast-track to clearly understanding statistics from a mathematical perspective, if there ever was one. I'd still recommend…
on “Ask HN: How or where to begin learning mathematics from first principles?” ↗I strongly recommend "All of Statistics", by Larry Wasserman. It lives up to its title pretty well. It is very concise in its explanations of various topics. I like this, but you might want a traditional book if some topic gives you trouble.…
on “Ask YC: Best book to learns statistics?” ↗All Of Statistics by Larry Wasserman. The material is presented both very succinctly and rigorously, and overall it's the best statistics book I have come across.
on “Ask HN: Proof Based Book on Statistics” ↗…stats-heavy compsci papers". The MacKay book, "Information Theory, Inference and Learning Algorithms," already referenced by benm is quite good, but I'd suggest on top of it Larry Wasserman's amazing book, "All of Statistics". If the level of calculus and linear calculus in that book is too much for you, you might need to review that material first before moving on to anything sophisticated in statistics. In the interim,…
on “Ask HN: the road to learning useful math” ↗