Correlation vs Causation: A Brief Guide To Communicating Research

Using causal language when reporting research that only provides evidence of a correlation is one of the most common errors in science reporting.

Professor David Spiegelhalter explains why correlation is not the same as causation - and what language you can use to clearly and accurately communicate observational vs experimental research.

David Spiegelhalter is a statistician, author and broadcaster. His book THE ART OF STATISTICS is a worldwide bestseller. He was the Winton Professor for the Public Understanding of Risk at the University of Cambridge for many years, and served a term as the President of the Royal Statistical Society.

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[jayalalkj]

What a great explanation. An increase in educated internet users will cause additional subscribers to this channel.

[GodwillhandleIT]

Thank you! I appreciate you going over this.

[Anikanoteven]

Thank you for the clarity you bring to these terms.

[philipherlihy]

Diamond clear. And a set of "go-to" explanations that really fill a gap!

[alexcoutoalves]

Excellent communicator and communication :)

[senditall]

This explanation is by far the best. (if you ask me)
Thank you!

[ndipagbor]

Please, what is his name? I really love watching his videos. Pure knowledge here.

[Haze_Loto]

I have been finding papers where they use first the word impact and then the word related like if it were synonyms. It's confusing to read it.

[pustakarileks]

SEM PLS os for correlation right? Not for causation