Today's topic is one of the most famous stories in statistics,
uh, it's also about where babies come from. Um, and I know you know where babies come from, but there used to be this tale,
that's what I grew up with, that babies come from storks.
If a child is asking awkward questions of his or her parents, the parents would say well, you know, the stalks bring the baby
in - draped from their bill in a blanket,
that's where your baby brother or your baby sister came from. - (Brady: Have you figured out where that came from?)
(Why storks were associated with babies at all?)
So there's a theory it's something to do with um stalks being a traditional symbol of fertility, a religious symbol of fertility. And another theory
is that storks when they go fishing they're looking for embryonic life forms in the water,
so that is, that is two theories. Um,
I don't know. I'm, I'm an economist, you know, I'm not a,
not a sort of a studier of mythology and ritual. Anyway, anyway, to get back to the important stuff, which is the statistics. So
storks deliver babies. This is the old story.
Let me try to prove that to you statistically. I've got my, I've got my paper here.
So,
and this is just going to be a um illustrative plotting, if you imagine two axes.
And here, this is babies per year,
and here
we have the number of storks. And if you just take a a bunch of European countries, and I have actually seen the data,
what you find is
Turkey, if I remember, and this is Poland. And then you might have Germany here and then you've got a whole bunch down here, a
couple there. And it's not the world's best correlation, but it's, it's not the world's worst correlation.
Loads down here with not many babies, not many storks. You've got these big outliers here. You've got nothing here. You've got no places
with um loads of babies and no storks,
you've got no places with loads of storks and no babies, and you can draw a best fit line and it goes like that,
and there is actually an academic paper, about 20 years ago, with the title storks deliver babies p equals
0.008. And without going into the technical details, you probably know that according to the conventional standards of statistical significance
that means this relationship is not a coincidence. There is definitely a
correlation between storks and babies. Now, you're probably thinking to yourself, okay
so what's the trick? Because surprise surprise storks don't actually deliver babies.
Um, email me if you actually want me to explain where babies do come from.
(Brady: Will they get a reply?) [both laugh]
Well, maybe.
So what's going on here? What's going on here is basically, as I said, I think this is Turkey, this is Poland.
There's, there's Monaco, there's Luxembourg, there's Lichtenstein down here. Lots and lots of places with very small amounts of land,
there are no storks and there are no kids, basically. And here are places that are really big, lots of storks,
lots of babies. And that's what's going on, that's enough
to drive that statistical correlation. The amount of land is the hidden, uh is the hidden factor,
yeah, it's the secret thing that's driving both a large population, which means a lot of babies,
and it is driving the large number of storks. Because bear in mind I'm not - I didn't say birth rate,
I'm sure there's, well I expect there's no correlation for the birth rate,
what i'm talking about is the the number of babies born each year in this,
in these countries. Which is very closely correlated to the population. - (Brady: So you would also perhaps expect a correlation with trees?)
Yeah, yeah, probably number of trees versus number of babies a year? Trees also deliver babies,
I mean you could, you could go in all kinds of places like this. And there are lots of these,
um, these spurious correlations out there. Actually, there's a website maintained by a guy called Tyler Vigen,
I think, called spurious correlations; full of all kinds of fun stuff like this.
But I said at the beginning that this is one of the most famous stories in statistics.
And it was made famous by a fellow called Darrell Huff and,
here for me is where this gets really interesting. So Darrell Huff was a journalist. And in 1954
he published a book
with the title "How to lie with statistics". It got a rave review in the New York Times,
it became, many people say, the best selling book about statistics ever written. And I loved it when I was a teenager,
reading about all of these tricks, all of the different ways you could be deceived. He's got the storks and babies in there,
it's got loads and loads of great examples. It's got dodgy maps, it's got dodgy graphs, it's got
all sorts of great, great examples. It's a very funny book.
Um, I'm not the only person who likes it, Ben Goldacre, who wrote bad science and many other great books about numbers,
he praised Darrell Huff. Charles Wheelan, who wrote a book called naked statistics; he said it was an homage to Darrell Huff.
There are loads of fans of Darrell Huff out there. - (Brady: This book is in praise of statistics, though.)
(This, this book is supposed to be doing a service to statistics, presumably?) - So that, I think, is where
the important question, uh lies.
It, it is loved by nerds,
but it is not really in praise of statistics because what Darrell Huff is doing
is in chapter after chapter; example after example, he's debunking
dodgy statistics. And he just doesn't have a lot of positive examples of statistics being used to illuminate the world.
And that's where I
start to get a little bit queasy. Because that book was published in 1954, and you know, what else happened in 1954? Two great statisticians,
epidemiologists, Richard Dole and Austin Bradford Hill, provided some of the first solid evidence that smoking cigarettes
might well give you lung cancer.
Because the same year, two different visions of what you can do with statistics. Darrell Huff is saying it's a bit of a joke,
it's a bit of fun - I'll tell you the story about the storks and the babies. Um, but don't don't ever take statistics, too
seriously because they're just a way for people to lie to you.
Austin Bradford Hill and Richard Dole
are using this vital tool to find out the answer to one of the key
medical questions of the 20th century. And when you think about it,
they couldn't have done that in any other way than using a, the statistical lens.
So even to notice that lung cancer cases were on the increase, and they were massively,
you need to be
systematically counting cases of lung cancer.
I mean you, maybe there'd be some anecdotes, but you know, you need the numbers, you need the data. And then to show, compellingly,
that uh, there's, there's evidence of causation
you really need to work hard with the statistics.
A lot of people at the time thought it was something to do with cars, which is not crazy,
you think about it, between the beginning of the 20th century and the 1950s,
lung cancer's on the increase, so are cars - loads of cars. Maybe it's something in the tarmac?
Maybe it's uh something, you know coming out of the exhaust? It's not a crazy idea.
But it turns out it wasn't the cars,
it was the cigarettes.
This is so important. This is such a key fact. Understanding that this thing is true,
this has saved literally tens of millions of lives. Possibly hundreds of millions of lives.
And you've got Darrell Huff in, remember this the the best-selling book ever
published about statistics, saying
'don't ever take statistics too seriously' because they're basically,
liars will use them to lie to you. There's a twist in this story. Because in the
1960s, the US Senate held hearings to decide
whether cigarette
packets should have warning labels on them. Should smokers be warned, you know,
maybe this is going to kill you. And they got all these expert witnesses in to discuss the evidence and one expert witness came in
and he told the senators:
'Look, don't worry too much
because
there are a lot of funny correlations out there.
Let me tell you about storks and babies.'
And he sat there and he told the senators all about how you could demonstrate this correlation
between
babies and storks, he used a slightly different example, but the same basic argument.
And it's the same with, with cigarettes and lung cancer. And the senator who was chairing the commission said:
'Do you seriously mean to tell me
that
there is as as casual a relationship between smoking and lung cancer
as there is between storks and babies?'
And the expert witness says 'yeah, they seem to me to be about the same.' And his name,
you may have seen it coming,
Darrell Huff, the guy who published
'How to lie with statistics'. He was actually working on a sequel, which was never published, called how to lie with smoking statistics.
So he'd taken
this, you know, this, you know, funny, witty
skepticism
about statistics, in this great little book, and he'd soured it into this nasty cynicism
that everything out there is fake news. You can't believe a single thing you're told,
and he'd then gone to work for the tobacco lobby. Who found him to be the perfect
witness for their case.
If you'd like more great stories like this from Tim Harford, check out his book "How to Make the World Add Up".
This is what it looks like, just in case you need to know.
The links in the description include a chance to get yourself a signed copy.
You can also catch Tim talking with Matt over at Standupmaths, again links in all the usual places.