[This article was first published on Revolutions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Norm Matloff points us to a pithy example that sums up Simpson's Paradox perfectly, captured in the title of a medical paper: "Good for Women, Good for Men, Bad for People". He explains how Simpson's Paradox isn't a paradox at all, but just the consequence of including a minor variable in a model ahead of a more significant variable, and illustrates this with an R analysis of the UCB admissions data. You can also see an interactive analysis of the same data here.
To leave a comment for the author, please follow the link and comment on their blog: Revolutions.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.