What are the most important statistical ideas of the past 50 years? [pdf]

Re:What are the most important statistical ideas of the past... by mindcrime on Monday March 08, 2021 @02:28PM (#26390364)

Depending on the context, I'm a fan of the work of Douglas Hubbard, in his book How to Measure Anything[1]. His approach involves working out answers to things that might sometimes be done as a "back of the napkin" kind of thing, but in a slightly more rigorous way. Note that there are criticisms of his approach, and I'll freely admit that it doesn't guarantee arriving at an optimal answer. But arguably the criticisms of his approach ("what if you leave out a variable in your model?", etc.) apply to many (most?) other modeling approaches.

On a related note, one of the last times I mentioned Hubbard here, another book came up in the surrounding discussion, which looks really good as well. Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin[2] - I bought a copy but haven't had time to read it yet. Maybe somebody who is familiar will chime in with their thoughts?

[1]: https://www.amazon.com/How-Measure-Anything-Intangibles-Busi...

[2]: https://www.amazon.com/gp/product/0691129495/ref=ppx_yo_dt_b...

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Re:What are the most important statistical ideas of the past... by ingqondo on Tuesday March 09, 2021 @04:16AM (#26396897)

How to Measure Anything is a fantastic book. Here are the most significant insights you learn in the book

- how to measure anything; Hubbard actually comes through on the promise of the title - after finishing the book you will truly feel that the scope of what you can measure is massive. He does this by a change in the definition of what it means to measure something, but you realize his definition is more correct than the everyday intuitive one.

- value of information; Hubbard gives a good introduction to the VOI concept in economics, which basically lets you put a price on any measurement or information and prioritize what to measure

- motivation for 'back of the napkin' calcs; through his broad experience he has seen how a lot of the most important things that affect a business go unmeasured, and how his approach to 'measuring anything' can empower people to really measure what matters.

Reading this book provided one half of what I have been searching for for a long time - a framework for thinking about data science activities which is not based on hype, fundamentally correct and still intuitive and practical.

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Re:What are the most important statistical ideas of the past... by dr_dshiv on Monday March 08, 2021 @03:01PM (#26390743)

Let me second "How to measure anything." I think it should be required reading for human beings.

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Re:What are the most important statistical ideas of the past... by alex_anglin on Monday March 08, 2021 @03:19PM (#26390945)

I would add that "How the Measure Anything in Cybersecurity Risk" should be a core part of Infosec literature.

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