New Blog Post on Thinking Bayesian and Thinking Frequentist

The MEAP (early previews of our data science book) will launch very soon! We’ve also been working on the next few chapters of the book; it’s been slightly slower going, which is normal in the writing process.

It’s also slowed down my blogging rate. But I’ve managed to get another post out for Win-Vectors Statistics To English Translation series: a discussion of bayesian versus frequentist thinking, and when each is appropriate.

Post withhf

I’m not going to get into the “Bayesian versus Frequentist” war; in my opinion, which style of approach to use is less about philosophy, and more about figuring out the best way to answer a question. Once you have the right question, then the right approach will naturally suggest itself to you. It could be a frequentist approach, it could be a bayesian one, it could be both — even while solving the same problem.

You can read the whole article at the Win-Vector blog.


About nzumel
I dance. I'm a data scientist. I'm a dancing data scientist. In my spare time, I like to read folklore (and research about folklore), ghost stories, random cognitive science papers, and to sometimes blog about it all.

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