6 ms·
Ask HN: Recommend Books on Statistics
My PhD in information systems will start this September. Even though I took a class of statistics during Master's, I think I should familiarize myself with probability, stochastic processes, mathematical statistics, and multivariate analysis. Any advice for self studying books regarding these areas would be greatly appreciated.
- sova 7y agoTry and visualize everything https://github.com/piermorel/gramm https://github.com/piermorel/gramm
- lunarcea 7y agoNice thanks!
- s1t5 7y agoHarvard's Stat110 by Joseph Blitzstein and the accompanying book Introduction to Probability - https://projects.iq.harvard.edu/stat110/youtube https://projects.iq.harvard.edu/stat110/youtube
- lunarcea 7y agoAwesome
- jtcond13 7y agoMy personal favorite is Richard McElreath's "Statistical Rethinking", which covers regression and multilevel modeling from a Bayesian approach but doesn't assume too much formal math background.
- BOOSTERHIDROGEN 7y agois there any introduction before this books, I've read first chapter (looking from first chapter, I already have a feeling this is a good book) and author saying there is a substantial idea that is missing from a lot of introduction statistics books (isn't necessarily wrong).
- lunarcea 7y agoThanks!
- lunarcea 7y agoThank you, jtcond13!
- Mxtetris 7y agoJames, Witten, Hastie, and Tibshirani, "An Introduction to Statistical Learning." Available for download: http://faculty.marshall.usc.edu/gareth-james/ISL/ http://faculty.marshall.usc.edu/gareth-james/ISL/ Taylor and Karlin, "An Introduction to Stochastic Modeling"
- natalyarostova 7y agoStatistical Inference by Casella & Berger, is the canonical first year phd stats textbook. I like it.
- lunarcea 7y agoThanks
- xelxebar 7y agoProbability Theory: The Logic of Science (2003) by E. T. Jaynes This is a treatise on modern probability theory. In the first few chapters, Jaynes quite succinctly derives the theory as what would seem at first blush like a mild extension of binary logic. The whole thing is a bit of a tome but the chapters are not ordered in a strict logical manner, so you can skip around after the first derivation part. The whole book is gold, though. In my experience, a lot of texts are organized as "statistical toolbags" whereas Jaynes hammers in the point that there are solid principles underlying the theory that, when kept clearly in mind, quickly empower you to approach even tricky problems. There is even an entire chapter devoted to dispelling "probability paradoxes" which arise from the (mis)use of infinite sets. Jaynes clears these up neatly, making a strong case for always using clearly-defined limiting processes when dealing with non-finite systems. The foundations presented in this book do stand in opposition to the standard approach using Kolmogorov Axioms. Jaynes' approach is inherently finitistic, which IMHO, makes the reasoning a whole lot more obvious.
- lunarcea 7y agoThanks for your help, xelxebar!
- toto444 7y agoAll of Statistics: A Concise Course in Statistical Inference by Larry Wasserman You can find in PDF by typing it into your favorite search engine.
- lunarcea 7y agoThanks, toto444!