« Primer on Regression Adjustments 1 | Main | Round 2: 10 Ways to Rank the Rio Summer Olympics »


Feed You can follow this conversation by subscribing to the comment feed for this post.

John Hall

These past two posts focus a lot on the "regression doesn't know". I think what you needed to spell out more clearly is that the naive process is to estimate the regression and then use the estimate of the intercept to infer the population average. You're obviously right that this is mistaken when the groups in the population are unbalanced. It would make for a good introduction to posterior predictive checks or Gelman's Mr. P. (multi-level regression with post-stratification)


JH: Yes, one of the next posts will explain what regression is good for and why we do what we do.

"You're obviously right that this is mistaken when the groups in the population are unbalanced." Couldn't have said it better - and when in the real world do we have populations that are balanced?

And yes, what is in this post directly relates to Mr. P.


Thanks again for this well-explained post. It would be nice if you could make a post in this serie on multi-level regression with post-stratification. So far I have not been able to develop a good intuitive understanding of it. I am asking you that because I really like how you explain difficult ideas, by using examples that directly show the mistakes we make if we don't have a good understanding of how it works. Your examples are simple and yet very powerful. You are really gifted for explaining all this!

The comments to this entry are closed.

Get new posts by email:
Kaiser Fung. Business analytics and data visualization expert. Author and Speaker.
Visit my website. Follow my Twitter. See my articles at Daily Beast, 538, HBR, Wired.

See my Youtube and Flickr.


  • only in Big Data
Numbers Rule Your World:
Amazon - Barnes&Noble

Amazon - Barnes&Noble

Junk Charts Blog

Link to junkcharts

Graphics design by Amanda Lee

Next Events

Jan: 10 NYPL Data Science Careers Talk, New York, NY

Past Events

Aug: 15 NYPL Analytics Resume Review Workshop, New York, NY

Apr: 2 Data Visualization Seminar, Pasadena, CA

Mar: 30 ASA DataFest, New York, NY

See more here

Principal Analytics Prep

Link to Principal Analytics Prep