3 HN users recommended this talk3 months2015–2025score 3.5
Years with an HN recommendation, 2007–2026
HN recommends it as an excellent programmer-friendly explanation of p-values and statistical thinking.
John Rauser's Strata 2014 keynote argues that programmers can learn statistics quickly by simulating random processes and shuffling data. He explains p-values through resampling rather than formulas.
“This is an excellent talk I attended a while ago that explains it very well from a programmer's perspective” (HN, 2015)
I have a talk in which I argue that if you can program, you have a huge advantage in learning statistics because you can simulate random processes and tinker with them to get an intuitive sense of the statistics involved. At Data Driven NYC: [link] Keynote at Strata+Hadoop World 2014: [this video]
Programmers can learn statistics by simulating random processes
>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 [link] John Rauser - Statistics Without the Agonizing Pain [this video]
Advocates simulation and shuffling over memorizing formulas
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