Think Stats

What Hacker News says

1. staplungMay 2026
   Allen Downey (author of the above) has a number of books on computer science-y things. You can buy hardcopies but I think all of them are also just freely available.

   Here's a few:

   Think Complexity

   https://github.com/AllenDowney/ThinkComplexity2

   Think DSP

   https://github.com/AllenDowney/ThinkDSP

   Think Stats

   https://github.com/AllenDowney/ThinkStats/

   Think Bayes

   https://github.com/AllenDowney/ThinkBayes2/

   Show morethread
2. nosioptarMay 2026
   Seconded, not only is Downey quite generous, his books are every bit as good, if not better, than expensive counterparts. Think Stats bailed my ass out of failing a stats class because it was so much clearer than the assigned book.
   thread
3. esafakFeb 2026
   Get a book on applied statistics, such as

   Think Stats: Probability and Statistics for Programmers (https://allendowney.github.io/ThinkStats/)

   Computer Age Statistical Inference (https://hastie.su.domains/CASI/)

   Statistical Rethinking (https://xcelab.net/rm/)

   An Introduction to Statistical Learning (https://www.statlearning.com/)

   Obviously maths is going to be involved to do the subject justice. These recommendations are more about applied statistics, but that's the foundation. From there it is a small transition to statistical process control.

   Show morethread
4. westurnerApr 2025
   I took AP Stat in HS and then College Stats in college unnecessarily. In HS it was TI-83 calculators, and in college it was excel with optional minitab. R was new then

   I remember ANOVA being the pinnacle of AP Stat. There are newer ANOVA-like statistical procedures like CANOVA;

   "Efficient test for nonlinear dependence of two continuous variables" (2015) https://pmc.ncbi.nlm.nih.gov/articles/PMC4539721/

   Estimators:

   Yellowbrick implements the scikit-learn Estimator API: https://www.scikit-yb.org/en/latest/

   "Developing scikit-learn estimators" https://scikit-learn.org/stable/developers/develop.html#esti... :

   > All estimators implement the fit method:

     estimator.fit(X, y)
   

   > Out of all the methods that an estimator implements, fit is usually the one you want to implement yourself. Other methods such as set_params, get_params, etc. are implemented in BaseEstimator, which you should inherit from. You might need to inherit from more mixins, which we will explain later.

   https://scikit-learn.org/stable/modules/generated/sklearn.pi...

   Sklearn Glossary > estimator: https://scikit-learn.org/stable/glossary.html#term-estimator

   https://news.ycombinator.com/item?id=41311052

   https://news.ycombinator.com/item?id=28523442

   What is GridSearchCV and what are ways to find optimal faster than brute force grid search?

   IRL case studies with applied stats and ML and AI:

   - "ML and LLM system design: 500 case studies to learn from" https://news.ycombinator.com/item?id=43629360

   Additional stats resources:

   - "Seeing Theory" Brown https://seeing-theory.brown.edu/

   - "AP®/College Statistics" Khan Academy https://www.khanacademy.org/math/ap-statistics

   - "Think Stats: 3rd Edition" notebooks https://github.com/AllenDowney/ThinkStats/tree/v3

   And physics and information theory in relation to stats as a field with many applications:

   - "Information Theory: A Tutorial Introduction" (2019) https://arxiv.org/abs/1802.05968 .. https://g.co/kgs/sPha7qR

   - Entropy > Statistical mechanics: https://en.wikipedia.org/wiki/Entropy#Statistical_mechanics

   - Statistical mechanics: https://en.wikipedia.org/wiki/Statistical_mechanics

   - Quantum Statistical mechanics: https://en.wikipedia.org/wiki/Quantum_statistical_mechanics

   Statistical procedures are inferential procedures.

   There are inductive, deductive, and abductive methods of inference.

   Statistical inference: https://en.wikipedia.org/wiki/Statistical_inference

   Statistical literacy: https://en.wikipedia.org/wiki/Statistical_literacy

   Also, the ROC curve Wikipedia sidebar: https://en.wikipedia.org/wiki/Receiver_operating_characteris...

   What is the difference between accuracy, precision, specificity, and sensitivity?

   Khan Academy has curriculum alignment codes on their OER content, but not yet Schema.org/about and or :educationalAlignment for their https://schema.org/LearningResource (s)

   Show morethread
5. ranc1dMay 2024
   I like Alan Downeys books Think Stats, Think Bayes. He introduces topics in Statistics using python:

   https://greenteapress.com/wp/think-stats-2e/ https://greenteapress.com/wp/think-bayes/

   thread
6. yellowstuffJan 2021
   Think Stats is a very good book aimed at Python programmers who want a broad overview of practical statistical techniques: https://greenteapress.com/thinkstats/html/index.html
   thread