We should teach intro stats students about relative vs. absolute risk

Do you know what bugs me? How much time different intro stats textbooks spend talking about probability, lots of A not B stuff*, lots of probability associated with the normal distribution, etc. But we don't take advantage of the discussion to warn their students about the evils of relative vs. absolute risk. #statsliteracy

Relative risk is the most clickbaity abuse of statistics that there is. Well, maybe the causal claims based on correlational data are more common. But I think the relative risk is used to straight-up scare people, possibly changing their behaviors and choices.

I thought of it most recently when The Daily Mail (bless) used explained the difference in COVID-19 risk between dog owners and non-dog owners.  

Here is the data described in the headline, straight from the original paper:

Really, Daily Mail? How dare you.

I think the most clever, trickiest, sneakiest ways to mislead with data are by not lying with data at all. Most truncated y-axes display actual data. Data sets with sampling error are still data sets. And relative risk and absolute risk express the same data, but relative risk sounds scary while absolute risk doesn't sound scary. 

Another example I like involved Gerd Gigerenzer, the well-known cognitive psychologist. In this video, he describes an instance when relative risk headlines scared women away from oral contraceptives, and then there was a rise in abortions. All of these could have been avoided totally if women have been given absolute risk information about birth control pills.

You can take issue with Gerd's claim that abortion negatively affects women, but I think that most people would agree that women being scared out of taking their birth control pills is a bad thing. And that newspapers need to be responsible, and editors must avoid using relative risk to scare readers.

I know we have a lot of ground to cover in Intro Stats. But we are doing our students a disservice if we aren't preparing them to deal with oft-encountered dirty data in real life. This topic doesn't take too long to explain. You already have to talk about probability. The video is short. It is easy to explain. 

*And probability has its time and place. Go read The Drunkard's Walk. You'll love it. But I just sit and think a lot about how we should use our precious Intro to Stats time. And I think we should point out how classroom topics play out in real life.