Statistical inference
by George Casella · first published 1990
76% recommend19% neutral5% critical
Why HN recommends it
Rigorous, readable graduate-level text that builds statistics from probability theory; its many exercises, online solutions manual and distribution chart suit self-study and first-year grad courses.
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…https://www.amazon.com/Econometric-Analysis-Cross-Section-Pa... Greene is a really useful reference text: https://www.amazon.com/Econometric-Analysis-8th-William-Gree... For advanced stats theory, I recommend Casella and Berger https://www.amazon.com/Statistical-Inference-George-Casella/... Hope that helps! The more specific a model can be made to the problem at hand, the better it'll perform. Supervised ML models are great starting / baseline models.
on “Time Series Prediction Using LSTM Deep Neural Networks” ↗Depends where you are starting from and what you want to learn. The linked book is a first year introduction, and does a good job of that. If you want to go further there are many other options: * Statistical Inference by Casella and Berger. This book has a very good reputation for building statistics from first principles. I won't link to them, but you can find full PDF scans online with a simple search. Amazon reviews:…
on “Introduction to Modern Statistics” ↗…that everyone in machine learning should be (completely) familiar with essentially all of the material in the following intermediate-level statistics book: 1.) Casella, G. and Berger, R.L. (2001). "Statistical Inference" Duxbury Press. For a slightly more advanced book that's quite clear on mathematical techniques, the following book is quite good: 2.) Ferguson, T. (1996). "A Course in Large Sample Theory"…
on “Learning About Statistical Learning” ↗I've said this elsewhere, but I recommend Casella & Berger's Statistical Inference. It will take you from probability theory to statistics... all the basics. I found it to be a very readable text, and it is used for many first graduate courses in stats - for me it was used for a 2…
on “Statistics for Hackers” ↗I've been enjoying the struggle through Statistical Inference by George Casella as a foundational text. This was the introductory text for stats graduate students at Arizona State University a few years back. The Mathematical Methods of Statistics by Harald Cramér…
on “Ask HN: What are your favorite statistics and probability textbooks?” ↗…Spivak's Calculus is hands down the best intro Calc book if you want to learn math for its own sake. His book on manifolds is also amazing but definitely not intro. If you want stats I highly recommend Statistical Inference by Casella & Berger -- it's extremely dry but so many stats books out there try to "make it easy" but the simplification means that you can't actually grok what's really going on. HOWEVER if you want…
on “Why won’t anyone teach me math?” ↗Yeah just the books I used in school: Ross - A First Course in Probability Rice - Mathematical Statistics and Data Analysis Casella - Statistical Inference
on “Ask HN: Good book about statistics and probability?” ↗When I was learning undergraduate mathematical statistics, my professor made it a point to connect the links between linear models and many different tests. In the back of Statistical Inference by Casella and Berger, there is a great chart making similar connections between the most common statistical distributions. There is a lot of rhyming in statistics.
on “Common statistical tests are linear models” ↗Statistical Inference by Casella & Berger, is the canonical first year phd stats textbook. I like it.
on “Ask HN: Recommend Books on Statistics” ↗For frequentist statistics, I'd recommend Statistical Inference by Casella and Berger. For Bayesian statistics, I'd recommend Bayesian Data Analysis by Gelman et al.
on “Good statistic book for CS post-graduate?” ↗Casella & Berger's "Statistical Inference" is a nice introduction to basic probability theory and statistics. I found it pretty readable, and it's used for many 1st year graduate stat programs. Duda & Hart's "Pattern Classification" is one of…
on “USA tops International Math Olympiad for first time in 21 years” ↗My favorites are Casella and Berger: https://books.google.com/books/about/Statistical_Inference.h... and Hogg, McKean and Craig: https://www.pearsonhighered.com/program/Hogg-Introduction-to... They are both good books. The first one is more rigorous, but the second one covers more breadth and…
on “All of Statistics, by Larry Wassserman (2013) [pdf]” ↗I find this to be fairly involved but a good follow-up to introductory texts. Casella, George, and Roger L. Berger. Statistical Inference. 2nd ed. Duxbury Advanced Series. Australia ; Pacific Grove, CA: Duxbury/Thomson Learning, 2002.
on “The Probability and Statistics Cookbook” ↗If you like proofs and rigor, take a look at "Statistical Inference" by Casella and Berger.
on “The Data Science Process” ↗Statistical Inference by Casella is great for self learning, not only because of the main text but because it has a huge number of exercises and a detailed solutions manual can be found online.
on “Machine Learning books suggested by Michael I. Jordan from Berkeley” ↗