« Science in the Age of Covid-19, Part 3 | Main | Instant Classic for Science Communications Students »


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


"In other words, if X causes Y, then X and Y must be correlated.
That statement is true if there is nothing else in the system but X and Y."

This only holds if by correlation you/they mean more generally any relationship or association. If you are using the narrower statistical meaning of linear relationship than it is trivially falsifiable with a variety of nonlinear relationships, even in the absence of other variables.


Mike: Good point. I generally think of "correlation" as admitting any functional relationship revealed in a scatter plot of X and Y, in parallel with thinking "regression" is more general than fitting a straight line. It's a good reminder that the typical correlation printed by a software measures linear correlation, just like the basic regression assumes a linear model.


I have been following your blog for a while now (and also Andrew's one) but I have never written a comment... until now. I am doing it to let you know that I am very happy you took the time to explain in simple words what Andrew talked about. I don't have an advanced education in math or stats but I enjoy learning more about those topics. But sometimes it's hard to follow Andrew's post and the comments there. So your post written in simple terms with simple and more in depth explanations is very welcome. Thanks again. 


Clur: thank you for leaving the kind note. It's gratifying to hear I'm having the desired effect on my readers.

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