Recreational Quantification

On my recent post about hot drinks and esophageal cancer, Gringo made a comment about how quickly his Yerba Mate cooled down in the summer (30 minutes) vs winter (10-15 minutes). I was struck by this, because I find random numerical trivia about people’s daily life quite fascinating. I think this is mostly because many people don’t actually keep track of stuff like this, or if they notice it they don’t remember it.

While this phenomena is obviously probably related to numerical aptitude, I also think it’s probably related to something John Allen Paulos talks about. In an article about Stories vs Statistics, he posits that about 61% of people (update: he may have been joking with this number, there’s no source for it) see numbers as “rhetorical decoration” to stories, whereas the other 39% see numbers as “clarifying information”.

This reminded me of an exchange I had with my father last week when we were discussing how cold it was:

Dad: How are you surviving the cold down there?
Me: It’s been pretty chilly. I could tell it was cold because my walk from the train normally takes me 30 minutes, and this week I noticed it was taking 26 minutes without me consciously increasing my speed.
Dad: wow, that’s cold.
<5 more minutes of back and forth on walking speeds during various weather patterns, and how traffic lights/street crossings make the 4 minute time saving even more impressive>

I have come to understand that most people do not reach for anecdotes like this when they are trying to explain how cold it is, but it’s one of the best ways of communicating information like that to my Dad.

Interestingly, Paulos attributes this communication preference to our feelings towards Type 1 vs Type 2 errors. He posits that those who want to hear numbers are doing so because they are focused on avoiding Type 1 errors (seeing something that’s not there), and those who prefer stories are more interested in avoiding Type 2 errors (failing to see something that is there). I have no idea if he’s right about this, but personality typing based on statistical approaches is a thing I am totally on board with.

Anyway, I find myself counting and/or finding ways of quantifying all sorts of things as I go through life. Some of these are straightforward (I tracked my gas mileage for quite some time, I track my steps and resting heart rate, I have a particular obsession with hours of daylight), but some are a little more complex.

For example, every time I go to a concert, I always take note of the relative frequency of mixed gender groups vs male only groups vs female only groups. I started this because I attend a lot of concerts with my husband, and we got in a running discussion about “guy bands” vs “girl bands”. As I tried to quantify which was which, I realized that a strict gender breakdown sometimes hid information about the band’s core audience. AC/DC for example: the crowd there is 30-40% women, but almost all of the women are there with men. The number of male only groups was 3 to 4 times the number of female only groups. Interestingly, in many of the mixed gender groups there were more women than men, which is why the proportion was so high despite women not attending alone. Thus I put AC/DC in the category of a “guy band” that appeals to women, as opposed to a gender neutral band. In other words, it appears women are happy to attend, but only if someone else suggests it.

Since I started tracking this, I have seen two bands who appear to have truly equal gender appeal: Tom Petty and the Heart Breakers and Aerosmith.

The most male dominated concert I have ever been to was Judas Priest. The most female dominated concert was Ani Difranco. At neither of these concerts could I find a member of the minority gender unaccompanied by a member of the majority gender.

Another interesting breakdown is “couples concerts” or “date concerts” where you see very few people attending in mono-gender groups. TV on the Radio and a few other hipster bands I’ve seen appear to be like that. On the other side, when I went to see a Drag Queen Christmas, it was entirely the opposite. The audience was half male and half female, but since most of the men were (presumably) gay the groups that attended were mostly mono-gender.

All that being said, I’d be interested in hearing about random things that readers count/track/note when out and about, or your band examples. I understand I have rather idiosyncratic tastes in music, so I’d be interested in other examples.

Proof: Using Facts to Deceive (Part 5)

Note: This is part 5 in a series for high school students about reading and interpreting science on the internet. Read the intro and get the index here, or go back to part 4 here.

Okay! So we’re almost half way done with the series, and we’re finally reaching the article!  Huzzah! It may seem like overkill to spend this much time talking about articles without, you know, talking about the articles, but the sad truth is by the time you’ve read the headline and looked at the picture, a huge amount of your opinion will already be forming. For this next section, we’re going to talk about the next thing that will probably be presented to you: a compelling anecdote. That’s why I’m calling this section:

The Anecdote Effect

Okay, so what’s the problem here?

The problem here isn’t really a problem, but a fundamental part of human nature that journalists have known for just about forever: we like stories. Since our ancestors gathered around fires, we have always used stories to illustrate and emphasize our points. Anyone who has even taken high school journalism has been taught something like this. I Googled “how to write an article”, and this was one of the first images that came up:

Check out that point #2 “Use drama, emotion, quotations, rhetorical questions, descriptions, allusions, alliteration and metaphors”. That’s how journalists are being taught to reel you in, and that’s what they do. It’s not necessarily a problem, but a story is designed to set your impressions from the get go.  That’s not always bad (and pretty much ubiquitous) but it is difficult when it leaves you with an impression that the numbers are different than they actually are.

What should we be looking out for?

Repeat after me: the plural of anecdote is not data.


Article writers want you to believe that the problem they are addressing is big and important, and they will do everything in their power to make sure that their opening paragraph leaves you with that impression. This is not a bad thing in and of itself (otherwise how would any lesser known disease or problem get traction?), but it can be abused.  Stories can leave you with an exaggerated impression of the problem, and exaggerated impression of the solution, or an association between two things that aren’t actually related.  If you look hard enough, you can find a story that backs up almost any point you’re trying to make.  Even something with a one in a million chance happens 320 times a day in the US alone.

So don’t take one story as evidence. It could be chance. They could be lying, exaggerating, or mis-remembering.  I mean, I bet I could find a Mainer who could tell me a very sad story about how their wife changing their shopping habits to less processed food led to their divorce.  I could even include this graph with it:


Source.  None of this however, would mean that margarine consumption was actually driving divorce rates in any way.

Why do we fall for this stuff?

Nassim Taleb has dubbed this whole issue “the narrative fallacy”, the idea that if you can  tell a story about something, you can understand it. Stories allow us to tie a nice bow around things and see causes and effects where they don’t really exist.

Additionally, we tend to approach stories differently than we approach statistics. One of the most interesting meditations on the subject is from John Allen Paulos in the New York Times here. He has a great quote about this:

In listening to stories we tend to suspend disbelief in order to be entertained, whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled.

I think that sums it up.

So what can we do about it?

First and foremost, always remember that story or statistic that opens an article is ultimately trying to sell you something, even if that something is just the story itself.  Tyler Cowen’s theory is that the more you like the story, the more you should distrust it.

Even under the best of circumstances, people can’t always be trusted to accurately interpret events in their own life:


Of course, this almost always works the opposite way. People can be very convinced that the Tupperware they used while pregnant caused their child’s behavior problems, but that doesn’t make it true. Correlation does not prove causation in even a large data set, and especially not when it’s just one story.

It also helps to be aware of words that are used, and to think about the numbers behind them. Words like “doubled” can mean a large increase, or that your chances went from 1 in 1,000,000,000 to 1 in 500,000,000. Every time you hear a numbers word, ask what the underlying number was first.  This isn’t always nefarious, but it’s worth paying attention to.

One final thing with anecdotes: it’s an unfortunate fact of life that not everyone is honest. Even journalists with fact checkers and large budget can totally screw up when presented with a sympathetic sounding source. This week, I had the bizarre experience of seeing a YouTube video of a former patient whose case several coworkers worked on. She was eventually “cured” by some alternative medicine, and has taken to YouTube to tell her story.  Not. One. Part. Of. What. She. Said. Was. True. I am legally prohibited from even pointing you in her direction, but I was actually stunned at the level of dishonesty she showed. She lied about her diagnosis, prognosis and everything in between. I had always suspected that many of these anecdotes were exaggerated, but it was jarring to see someone flat out lie so completely. I do believe that most issues with stories are more innocent than that, but don’t ever rule out “they are making it up”, especially in the more random corners of the internet.

By the way, at this point in the actual talk, I have a bit of break the fourth wall moment. I point out that I’ve been using the “tell a story to make your point” trick for nearly every part of this talk, and that they are most certainly appreciating it more than if I just came in with charts and equations. The more astute students are probably already thinking this, and if they’re not thinking it, it’s good to point out how it immediately relates.

Until next week!  Read Part 6 here.