There's this great cliché, which is that
when you go to watch a film that has been adapted from a novel
the film is never, ever as good as the book.
You know, it generally - it kind of feels like it's true right?
Like Hitchhiker's Guide to the galaxy,
amazing book, terrible film.
Northern Lights, amazing book, terrible film.
Harry Potter and the Deathly Hallows Part 1.
I mean, that was just,
everyone should be embarrassed about that, really.
The book was amazing, obviously.
The film not quite so good.
And I started thinking, maybe, maybe
Hollywood takes good books and just makes them into bad films, maybe a good book equals a bad film.
Especially when you think about actually there are some books that aren't quite so good, that do make good films, like Bridget Jones's Diary.
All right book, but actually pretty good film. The Martian as well,
I think, you know, the film probably
was a bit better than the book, but it was an ok book - an ok book, amazing film.
So maybe there is this thing that Hollywood ruins good books, but also maybe
it just appears that way because of a
statistical fallacy called Berkson's Paradox. Go with me on this for a second,
let's imagine that there is no connection whatsoever.
Of all of the possible stories in the world
if you plotted them on this as to how good a film they make, and how good a book they make, actually there's no connection
whatsoever. You've just got this, this kind of
mishmash of dots, right?
Like this.
Now the slight problem here, when you're looking at the data or you're thinking about films that,
that sort of answer this question, is that you are only considering a very small
subsection of all of the possible stories, right? So you're only thinking about
films that were good. So we're kind of up here,
so this is where all the good films are. Or you're only thinking about good books, right? So books that are kind of down here.
So generally speaking the only ones that are sort of in your consciousness
are gonna be above this line here, all of these dots here.
So either very good films or very good books
(Brady: Why Hannah? Why aren't we considering what's below that line?)
Well because either a book is so bad that it never gets made into a film, or a
film that's been made from a book is so bad that you've never heard of it. You know, like
Count of Monte Cristo, anyone seen that film? No, it was terrible.
Absolutely atrocious. So it just isn't really in your consciousness because the film is kind of so, is so bad.
(Brady: So bad films we don't know about, bad books we don't know about or they don't even get made into a film so we don't know about them?)
Exactly right, exactly right.
But the end result is that you're only ever
considering a very small subsection of this. On this you've got films like, maybe
Harry Potter is down here, Harry Potter and the Deathly Hallows.
You've got, maybe the Martian is gonna be over here; Godfather that kind of thing. But you're not considering any of this stuff.
So if you just redraw this graph with all the data that you can see, all the data that's sort of available to you.
So bearing in mind all of these stories here aren't really in your consciousness,
it almost looks like there's this negative correlation.
If you were to draw a trend line through this data
it looks as though Hollywood really is
ruining books, because it takes the best books and
makes them into bad films. If these are the stories that you think about, all the books that are really good,
the ones that are over here, if you kind of think about the average
goodness of film of all of the books that are really good. It's kind of going to be around about here,
it's like a mediocre film.
Whereas if you're over here, these kind of mediocre books, and you look at the average
goodness of the film that they make, actually they make pretty good films, right?
So it almost looks as though the goodness of the book is negatively related to the goodness of the film. As though,
if you're a Hollywood exec you want to try and find books down here,
not very good books basically, to make those ones into films because
statistically they'll make your better films. Sort of doesn't make any sense, and it's because you're only considering a really small
subsection of the population. So this here is Berkson's paradox.
It was discovered by a guy called Joseph Berkson
after he was working in hospitals and trying to collect data on the different diseases that people had. And found these negative correlations between
things that you wouldn't,
you know, you wouldn't necessarily expect. So let's say that you had diabetes
and
severe ingrown toenails, for instance. He went into hospital and found
this kind of negative correlation, right? So here are your toenails, and here are your diabetes.
So this is kind of like how extreme your cases are. So more extreme cases are gonna be out here.
So there were some people who had bad cases of both, but it looked as though, if you had diabetes
you were less likely to have bad toenails. People with most diabetes, the worst diabetes,
tended to have the best toenails. And likewise people with the worst toenails, down here, tended to have, you know,
alright diabetes. But it's this negative correlation that actually isn't really there. Because, of course, in the whole population
actually, there are all those people down here
who have kind of not very bad toenails or not very bad diabetes, but they're just not the ones who are in hospital.
So if you're only considering the people who are in hospital, who are there because they have
either bad toenails or bad diabetes, you end up getting this sort of spurious
correlation between things that isn't really there. My favourite example of this is in Jordan Ellenberg's book: How Not to be Wrong. And
he talks about - there's that sort of old adage that very beautiful people are arseholes? And that's another example of Berkson's paradox,
but you kind of take this one step further because on that example here, so this is sort of good-looking,
so the prettiest people going to be over here. And this here is niceness,
so the nicest people are gonna be up here. And you've got - sort of again you've got all of this data like this.
In the real population, actually
there's no connection between them. You get nice people all across the spectrum and you get good-looking people all across the spectrum of niceness.
The thing is, is that if you are
dating
people, the people that you're considering, there's sort of a level of good-lookingness that you, you
generally don't go below; and there's a level of niceness that you generally don't go below. So even though this is the whole population,
when you're talking about the people that you would date,
there is this line here. You're only really considering the people to this side of this line.
So it looks like there's a negative between niceness and good-looking-ness.
If you're talking about very, very good-looking people, the range that they have in terms of niceness is kind of the full spectrum.
But the average niceness that they have is like somewhere in the middle, as in not very nice.
But meanwhile the ugliest people that you would consider going out with
are actually only the people at the very top of this line, so they're only the very nicest people. So it looks like there's this
downward trend right? So sort of the average here is up here, and the average down here is kind of somewhere about there.
So it looks like there's this downward trend. And with this example in particular, if you also add to this
that the very sort of most attractive people of all are gonna be up here, in this other triangle up here,
so the very nicest and most good-looking people are actually gonna be in this triangle over here. And
probably they're not gonna want to go out with you. So these people are off-limits to you
anyway, all you're left with is this very, very narrow channel of people who you'd be willing to date,
and who'd be willing to date you. And that is
definitely a negative correlation - or at least it looks like one.
So just to prove that there isn't this negative correlation, this sort of secret negative correlation that, that Hollywood are
ruining good books. I spoke to a journalist called Walter Hickey, who has done some analysis where
he has downloaded the data for all of the films that he could find
which were both
made into a film, and were released as a novel.
So he got the Metacritic score, which is kind of like a posher version of Rotten Tomatoes, essentially.
And he also got the Goodreads score, which is again similar sort of thing - a user-generated score.
So you've got the goodness of the book along the bottom, and the goodness of the film along the top. And when you look at
it first, it looks very heavily skewed. Which isn't necessarily fair because
scores on Goodreads tend to be quite good,
tend to be quite high. People are quite positive about things. The scores there ranged between naught and 5, whereas on
metacritic they - it's a percentage between naught and 100. And the thing is is that if you do
finish a book, and then take the time to review it
you're probably gonna have enjoyed the book a little bit,
right? If it's a really rubbish book, you just would put it down before you got to that stage.
So this graph here doesn't totally represent the data very well. Instead
what you can do is you can use something called a Z score,
which is a little statistical trick that gives you a score of how good something is compared to all of the other data.
And it kind of normalises everything for you, gives you a slightly more accurate picture of what's going on.
So this here then, this is the real data here.
You've got your goodness of your book along the bottom and the goodness of your film along the top. And
actually, you can see that if anything - I mean, there's almost like a positive correlation, right?
You've got lots of films over here that make both good books and good films;
you've got some that make, I think this one is Up in the Air?
I've never seen that film, have you? Dunno whether it's very good, but apparently critics loved it.
Godfather I think is one of these. The data's generally actually quite spread out,
you certainly haven't got this, this negative trend. The only thing that you don't see here,
there's thes- sort of these, these gaps over here. And that is because, of course, very bad books never get made into films.
Whereas with the good looking example, you wouldn't date people who you didn't consider either nice or good looking, you know,
people don't read bad books, but they do watch terrible films.
So if the book was better than the movie, then you would want your data to be all down on this side, right?
So if you had a diagonal line
anything on that side of the line would be the movies better than the book, and anything on that side of line would be the
book is better than the movie.
And actually - so there's the line there. I mean, it's maybe a bit skewed that often
the book is better. Thing is at the very beginning, when we're thinking about that sort of almost
negative correlation,
people just don't remember all of these films
or all of these books that, I mean the ones in this - I've gone through the data, I didn't, I've never even heard of most
of them.
(Brady: So when it comes to famous films and famous books, that's when you get more of the book is better than the film?)
Yeah, I think so. I think so. Or at the very least when you get famous books and famous
films,
it's like, Hollywood ruined the good book.
But they didn't.
There's a lot of bad books out there.
(Brady: Yeah, not yours though.) - No
You know, the debate about books versus movies is
irrelevant to me because I think the perfect compromise is an audiobook. And Hannah, who you just watched,
she's got a brand new book out;
she's recorded it as an audiobook and I went along as she recorded some of it!
The book is called 'Hello world, How to be Human in the Age of the Machine' [Preview] "People are less tolerant of an algorithm's mistakes
than of their own,
even if their own mistakes are bigger' - Hannah's book's already getting great reviews,
it's been nominated for a really amazing prize as well.
And I'll tell you what, it really comes to life when you hear it read by the author herself,
Hannah's got such a great voice and gives it so much personality. [Preview] "The algorithms that silently follow us around the internet,
the ones that are harvesting our personal information."
The best place of course to get your audiobooks is Audible, and they are the supporter of today's episode. If you go to audible.com/numberphile
or text the word numberphile to 500 500, you can start their 30-day trial.
With that you can download a free book. You can download any book, but of course, I'm gonna recommend Hello world, Hannah's new one.
Definitely worth getting. - [Hannah] Well, the thing is, actually, you don't really read your own book. I mean the first time I read my own book
was when I was doing the audiobook 'cause - I mean you you're sort of like doing little bits here and there,
and then, you know,
you don- never have a chance to sort of sit down and read it all in one go.
So that was quite nice, quite reassuring to know that actually as a book it does work rather than just these
disparate chunks of text that are mashed together.
Audiobooks are great when you're lying in bed, going on a long road trip,
walking the dog. I love listening to them, and I think you're gonna really enjoy Hello world.
audible.com/numberphile for the trial, for the free book which can be Hello world if you want it to be. Or
text numberphile to 500 500. Our thanks to them for supporting this episode.