Good Reads, etc.

Why study Statistics?

  1. Megan Yu's PLOS ECR blog entry. 2016-05-31.
  2. Weissgerber et al.'s PLOS Biology article. 2016.

 

AI (ChatGPT, etc.) and Statistics

  1. AMSTAT News 2023-09-01: Judea Pearl, AI, and Causality: What Role Do Statisticians Play?
    • Pearl is like a father of causal modeling (establishing causation from observational data). In this interview, he says, "I used to feel safe about AI. What’s the big deal? [...] Once in a while we make a mistake and [...] the world suffers. But most of the time, education works. But with AI [...] teenagers are now a hundred million times faster than you, and they have access to a hundred million times larger space of knowledge. Never in history has there been such an acceleration of the speed of evolution. For that reason, we should worry about it, and I don’t know how to even begin to speak about how to control it."
  2. Elena Naumova: Artificial intelligence and data analytics competencies for public health professionals. 2024-06-26.
    • Naumova's discussion is cross-cutting and not specific to public health professionals.

 

Some popular-science blogs/podcasts by statisticians:

  1. Statisticians React to the News (published by the International Statistical Institute)
  2. Stats + Stories
  3. Practical Significance (published by the American Statistical Association)
  4. [more to come]

 

Some (fun) statistical literature for a popular-science audience:

  1. Nate Silver's The signal and the noise: why most predictions fail -- but some don't. 2012.
  2. Alex Reinhart's Statistics done wrong: the woefully complete guide. 2015.
  3. Edward Tufte's data viz# "tetralogy/box set":
  4. Nathan Yau's data viz# books:
  5. Jeff Rosenthal's popular science exposé on probability theory and random phenomena:
  6. Aubrey Clayton's Bernoulli's Fallacy: Statistical illogic and the crisis of modern science. 2021.
  7. Sharon Bertsch McGrayne's The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy. 2011.
    • thanks to Rob Isdell for suggesting this
  8. An article from The Guardian on Julian Baggini's How to Think Like a Philospher (2023), and statistical principles show up there!
  9. [more to come]

 

 

 

 

# Check out Elena Naumova's guide on the principles of data visualization from 2024-04-15.