Statistical inference

What Hacker News says

1. noelwelshOct 2023
   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: https://www.amazon.com/Statistical-Inference-Roger-Berger/dp...

   * Statistics by Freedman, Pisani, and Purves has similarly very good reviews and can be easily found online. Amazon reviews: https://www.amazon.com/Statistics-Fourth-David-Freedman-eboo...

   * The majority of the Berkeley data science core curriculum books are online. This is not purely statistics but 1) is taught in a modern style that makes use of computation and randomization and 2) uses tools that may be useful to learn about.

   1. https://inferentialthinking.com/chapters/intro.html (Data 8)

   2. https://learningds.org/intro.html (Data 100)

   3. http://prob140.org/textbook/content/README.html (Data 140)

   4. https://data102.org/fa23/resources/#textbooks-from-previous-... (Data 102; this gets into machine learning and pure statistics)

   The Berkeley curriculum is not the only one; there are tens, possibly hundreds, of online courses. The Berkeley curriculum is just 1) quite extensive and 2) the one I happened to read the most about when I was recently researching how data science is currently taught.

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2. sudoankitOct 2023
   I particularly like Statistical Inference by George Casella and Roger Lee Berger.

   You could also look at Introduction to Probability by Joseph K. Blitzstein and Jessica Hwang (available for free here: http://probabilitybook.net (redirects to drive)).

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3. in9Oct 2023
   Statistical Inference Berger and Casella. There are better options, but the exercises and notataion are fun.
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4. SpivakFeb 2022
   My username comes to mind. 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 to actually apply anything in this book you'll need to grab something more practical as well. Going through an applied stats book after having done SI is like having superpowers.

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5. natalyarostovaApr 2020
   Statistical Inference by Casella & Berger, is the canonical first year phd stats textbook. I like it.
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6. loudenMar 2019
   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.

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