HackerTube.dev

Jake Vanderplas - Statistics for Hackers - PyCon 2016.mp4

PyCon 2016 · 92.9K views · 2016-06-17 · 40:45

Open on YouTube ↗

If playback is restricted in your region, try opening the original video. Use Mark watched to add it to your marked videos.

Overview

Jake Vanderplas's PyCon 2016 talk shows how sampling-based methods such as simulation, shuffling and bootstrapping make statistics intuitive. His pitch is that if you can write a for-loop, you can do statistics.

On Hacker News

It is recommended to programmers who want to learn statistics through simulation rather than memorized formulas.

Recommended by 3 HN people across 3 months · HN mentions 2017–2025

Topics

Data science & statisticsPython, Ruby & scripting languages
Search by tags
bootstrappingresamplingpythonsimulationhypothesis testing

What people said

armanboyaci · 2025-03 · Recommendation

>Being able to apply statistics is like having a secret superpower. I totally with this sentence. BUT If you ask for my opinion, merely knowing a list of statistical formulas is not very helpful. Most of the time, people don’t remember the underlying assumptions, so there is a fair chance they will use them in inappropriate situations. I recommend watching these two YouTube videos. The presenters advocate using simulation/bootstrapping/shuffling methods instead of memorizing formulas. Jake Vanderplas - Statistics for Hackers [VIDEO] John Rauser - Statistics Without the Agonizing Pain [LINK]

Read the original HN comment ↗
auxym · 2020-06 · Recommendation

You might enjoy this talk "statistics for hackers" (in case statistics is not included in your data science knowledge): [VIDEO] For structural beam analysis (ie, from mechanical and civil engineering) check out this textbook on the direct stiffness method: [LINK] Unfortunately, the accompanying code (MASTAN2) is not open source and runs in Matlab. Still, it's a decent first step if you want to move to full-on Finite Element methods, which require much heavier math (real analysis) to really grasp.

Read the original HN comment ↗
pixelmonkey · 2017-08 · Recommendation

We're using this book for a "book club" at work. Doing 1 chapter every 2 weeks. Chapter 1 covers Jupyter, 2 covers numpy, 3 pandas, 4 matplotlib, and 5 machine learning. We just made it through the first 4 chapters and it lays a good foundation for those libraries. I suspect chapter 5 is the meatiest and most interesting chapter, which covers scikit-learn and machine learning techniques. It is a long chapter so we will spend a month on it. I recommend combining this book with McKinney's Pandas book[1] and the author's excellent YouTube presentations at PyCon and PyData. Start with "Statistics for Hackers"[2] by Jake VanderPlas and then look for his others. [1]: [LINK] [2]: [VIDEO]

Read the original HN comment ↗

Sources

Video by PyCon 2016, played through YouTube.

Data and selection notes

HN summaries and labels may contain AI errors. HN dates refer to discussions, not video publication.

HN Library: HackerTube export (2026-10-31) and open-index/hacker-news. Upstream summaries and classifications may contain AI errors.

Views, duration and playback status refresh separately from the published catalog. When an update fails, existing data remains visible.

Selection checks
  • SaaS & AI candidates: Matches the configured criteria
  • Editor-approved picks: Editorial review is required

Rule matches identify candidates. They do not guarantee video quality or financial results.

About the library and its sources