Introduction to Statistical Inference
by Jack Kiefer · first published 2011
3mentions
2recommended by
3HN commenters
2014–2022first – last mentioned
67% recommend33% neutral
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…Statistics' is the best introduction I know of to issues of causality as we understand them today. For actual inference, the basis is one player game theory (aka, decision theory). I learned it from Kiefer's 'Introduction to Statistical Inference,' which sets out the theory very nicely in the first few chapters. That's a starting point at least. There are some interesting courses[^3] that try to teach statistics via resampling that seem pedagogically…
on “We will never have enough software developers (2020)” ↗Bear in mind Elements of Statistical Learning is a grad-level text. I would never recommend that to a beginner to the field over an Introduction to Statistical Inference, by the same authors. Geron Aurelien's Oreilly book is great - Hands-On Machine Learning with Scikit-Learn and TensorFlow. Get the second edition which covers Tensorflow 2.
on “Ask HN: Full-on machine learning for 2020, what are the best resources?” ↗…some texts that cover this? A friend suggested: * Data Analysis: A Bayesian Tutorial by Devinderjit Sivia, John Skilling * Bayesian Data Analysis, by Andrew Gelman, John B. Carlin, Hal S. Stern * Introduction to Statistical Inference by Jack C. Kiefer, Gary Lorden Currently I am working my way through this. Pattern Recognition and Machine Learning by Christopher M. Bishop These books are expensive and very time-consuming so it…
on “Don't become a scientist (1999)” ↗