Hey guys, this is the second history of statistics video I'm making and it's going to be called
(Don't Call Them) Joy Plots. Let's go ahead and get started with the video. Here is a picture of
an English rock band from the late 1970s called Joy Division. They were a band for just a few
years in the late 70s. I think the lead singer of the band ended up passing away right after they
became famous, so they don't have that much music together as a complete band but their most famous
song was called Love Will Tear Us Apart according to Spotify. I'm mentioning this band in a history
of statistics video because they made what I would consider a pretty significant contribution
to the field of data visualization. In 1979, they released their debut studio album called Unknown
Pleasures and they picked a data visualization as their album cover. In this slide, I have the
album cover shown here and this is basically just a black background with a white data visualization
on it. This album cover became very, very famous. I think it's a very recognizable cover, so when
people see this, they immediately know that it's a Joy Division album or a reference to Joy Division.
I think it's honestly one of the reasons that Joy Division is still talked about today as a rock
band because so many people know this album cover and can recognize it as a Joy Division album.
And I think it's safe to say that this was the most famous use of a data visualization
for an album cover. Even today, I think it's the most famous example. And it's also a very famous
example of a data visualization used as art. Here I just have some examples of how famous this data
visualization became. You very, very commonly see it on rock band t-shirts. A lot of people have
gotten tattoos with the album cover from this Joy Division album and there's other merchandise as
well. And in this video I kind of wanted to talk a bit about this data visualization and this plot
that was chosen as album cover. First I wanted to talk about what is this data visualization
actually showing. What is the data and what is this visualization that's on this album cover?
The data visualization is an example of a ridgeline plot. A ridgeline plot is really a plot
that shows multiple density functions or density plots stacked on top of each other. They're really
just showing the probability distributions for different levels of a variable or a factor.
And usually ridgeline plots have some degree of overlap. I have in these two examples ridgeline
plots with overlap but the separateness is usually a parameter so you can also have ridgeline plots
where there is no overlap and there's complete separation across the different factor levels.
And these plots are usually just used to make general comparisons. For example in this plot,
this plot is showing the temperatures in Lincoln, Nebraska for the different months and you can see
predictably that in the summer months it tends to be hotter and in the winter months it tends to be
colder. You can make these types of relative comparisons very easily in a ridgeline plot.
Now the actual data visualization was created by this graphic designer named Peter Saville
and there's a video of him that I will link in the description box below where he discusses
in the video the creation of that album cover and where the data came from, what was the inspiration
behind that data visualization. And basically, to summarize what he said, that data visualization
was something that the band found in a book called The Cambridge Encyclopedia of Astronomy, which
came out in 1977 and they had a copy of it. And on one of the pages there was the data visualization
that they ended up using as the album cover. I couldn't find a PDF of this book online but there
are several screenshots of people having the book and showing the page that was actually used as the
inspiration for the album cover. In the original textbook or encyclopedia that they used, the image
is white with black lines and basically what the graphic designer did was invert it. He made it
a black background with white lines. And since this is The Cambridge Encyclopedia of Astronomy,
this dataset came from an astronomical study and it actually is a very interesting and important
research study that was performed. This printing in the encyclopedia was a reprint from a paper
and so the paper I could find online, called The Nature of Pulsars by Jeremiah P. Ostriker. I'm not
sure how you pronounce that last name. But this was published in the American Scientific in 1971
and this paper discusses the discovery of pulsars, which is what this data visualization actually
displays. Basically, researchers at the University of Cambridge one day were studying radio waves in
space and trying to find signals in space using radio waves and they discovered this irregular
pattern of radio waves coming from the universe somewhere these were signals that they could not
explain and they didn't know what it was and where it was coming from and why. And so the paper kind
of talks about at first people were thinking are these aliens trying to talk to people on Earth?
What are these signals that we're seeing? They didn't know how to explain it at first but
basically what the paper talks about is they were seeing these irregular pulses of radio waves that
they called pulsars, initially they didn't know what pulsars were, so they could have been aliens
for all they knew, but basically they discovered that the pulsating radio waves that they could
record from Earth were the result of neutron stars. And so neutron stars in other galaxies
not in the solar system were rotating and as they rotated they would emit radio waves kind of like a
light coming out of a lighthouse. And so when the rotation would line up with hitting Earth if there
was a radio dish that was receiving radio signals, these pulses of radio waves could be recorded.
And so this is the original data visualization in this 1971 paper and this is a recording of 80
pulses from a neutron star and this was the first pulsar that was ever recorded. Some interesting
facts about this data visualization and this data is that the first pulsar that created this data
visualization that became very famous was recorded and first analyzed by a female radio astronomer
named Jocelyn Bell. And so she was a graduate student at the University of Cambridge at the time
and she helped create the radio satellite and she was the one managing the satellite,
she found these weird signals that they were not expecting at all--the research team was
not expecting the signals--she didn't know how to interpret them, she took them to her advisor
and her advisor at the time was Tony Hewish. He told her multiple times that it was just
interference and he was basically convinced that this was just noise and it was not important. And
basically she was the one who helped discover pulsars. It was a female graduate student to
discover the first pulsar and actually the New York Times has a short documentary on YouTube on
Jocelyn Bell and how she didn't get the fame and the glory for her discovery like she should have.
It's actually a really well made video. I will put a link to it in the description box below but in
the video she says she actually discovered the first two pulsars. When they discovered this and
realized it wasn't just noise, this was obviously a very important discovery, so she discovered a
second one to show that it wasn't just random noise and that was also her contribution. And
something that I found when I was doing research for this video was that a few years later in 1974
they awarded the Nobel Prize to basically two astronomers from Cambridge and basically they gave
the Nobel Prize, especially to Tony Hewish, her advisor, for the discovery of pulsars and they
never credited her as a co-winner of the Nobel Prize. She never won the Nobel Prize even though
she made very significant contributions to the discovery of pulsars and basically was the true
discoverer of pulsars. I've seen her say that she thinks it's okay that she didn't win the Nobel
Prize because she was a graduate student and she also thinks that it was because she was a woman as
well. In the documentary that the New York Times did, they had a short little interview with Tony
Hewish that they showed and in that video he seems very ungrateful for her contributions and
basically wants to take all credit for the work that was done in that lab, which is really gross.
And that actually makes me think that she should be awarded the prize even more because not only
did she make the discovery but she also had to put up with an annoying advisor while she was doing
it. But anyway, I thought that that was just an interesting thing that I should make sure to point
out in the video that this data visualization actually comes from a female scientist who
probably should have been awarded the Nobel Prize for her work. And in the last part of the video I
wanted to talk about the term "joy plots". I said that this type of data visualization was called
a ridgeline plot, which is correct, but they're also very, very commonly called joy plots. And
when I was looking up the history of where did that term first come from, because when I first
read joy plot out in the wild I had no idea what that was and what that was a reference to. Joy
plots is a play on this data visualization. It's a play on the band name of the English rock band
Joy Division. Internet historians have dug up the origin of who first came up with the term "joy
plots" and it was actually invented on twitter. Someone posted a data visualization of ridgeline
plots showing the elevation, I guess in Europe. And so a lot of times these plots where the lines
are very, very close to each other on a ridgeline plot, these tend to be called joy plots more than
they tend to be called ridgeline plots. This is a very good example of a plot that tends to be
called a joy plot. And in reply to this image in 2017 this woman named Jenny Bryan said as a joke,
"I hereby pose that we call these joy plots." And this tweet, I checked, it's still up online
and it only has 33 likes but everyone who has done like internet history on the origins of joy plots
says that this is where the term joy plots came from, so this 33 liked tweet is the origin
of that term and now thousands of people use that term, by the way, so I would think that this tweet
would be more viral but this is the origin of the conversation that created the term joy plot.
However, as you note from the title of this video, this video is saying do not call them joy plots.
I just want to end the video by saying that right after she made this tweet there have been very
many people who have come out and said to not call them joy plots. I didn't know anything about this
until I started doing research for this video but in reply to her tweet someone right away
said to not call them joy plots because the name Joy Division is problematic, you could say.
I had no idea about this but "joy plot" obviously is a reference to the name or phrase Joy Division,
which I had no idea what that was, but apparently this is a real expression or phrase and it comes
from a book about the Holocaust called House of Dolls, which was written by a Holocaust survivor.
And for the sake of keeping it PG on YouTube I'm not going to say what joy divisions are but it's
kind of gross. If you look up House of Dolls, you can learn right away what that expression means
but it's about something pretty gross from the Holocaust and it's a very weird thing that that
English rock band decided to name themselves after that expression or after that phrase.
I did some research into this and apparently the members of the band had some weird interest
in World War II history for whatever reason and so that's why they named themselves Joy Division
but by today's standards it's definitely a bad name for a band. And so I think just like the
first history of statistics video where a bunch of people are trying to move away from naming things
after Ronald Fisher, I would say that I've seen multiple people say to move away from calling them
joy plots. And so I definitely am going to end this video by recommending that people call them
ridgeline plots instead. And that's all I have for this video and thank you guys for watching!