Probability For Dummies (And We’re All Dummies)

Sometimes it feels like probability was made up just to trip you up. My undergraduate advisor Persi Diaconis, who started out as a magician and often works on card shuffling and other problems related to randomness, used to say that our brains weren’t wired right for doing probability. Now that I (supposedly!) know a little more about probability than I did as a student, Persi’s statement rings even truer.

I spent a little time this weekend thinking lately about why probability confuses us so easily. I don’t have all the answers, but I did end up making up a story that I found pretty illuminating. At least, I learned a few things from thinking it through. It’s based on what looks like a very simple example, first popularized by Martin Gardner, but it can still blow your mind a little bit. I actually meant to have a fancier example, but my basic one ended up being more than enough for what I wanted to get across. (Some of these ideas, and the Gardner connection, are explored in a complementary way in this paper by Tanya Khovanova.) Here goes.

Prologue. Say you go to a school reunion, and you find yourself at a dimly-lit late evening reception, talking to your old friend Robin. You haven’t seen each other for years, you’re catching up on family, and you hear that Robin has two children. Maybe the reunion has you thinking back to the math classes you took, or maybe you’ve just been drinking too much, but for some reason, you start wondering whether Robin’s children have the same gender (two boys or two girls) or different genders (one of each). Side note: if you’ve managed to stay sober, this may be the point at which you realize that you’ve not only wandered into a reunion you’re barely interested in, you’ve wandered into a math problem you’re barely… um, well, anyway, let’s keep going.

The gender question is pretty easy to answer, at least in terms of what’s more and less likely. Assuming that any one child is as likely to be a girl as a boy (not quite, but let’s ignore that), and assuming that having one kid be a girl or boy doesn’t change the likelihood of having your other kid be a girl or boy (again, probably not exactly true, but whatever), we find there are four equally likely scenarios (I’m listing the oldest kid first):

(Girl, girl)      (Girl, boy)     (Boy, girl)     (Boy, Boy)

Each of these scenarios has probability 25%. There are two scenarios with two kids of the same sex (total probability 50%), and two scenarios with two kids of opposite sexes (total probability also 50%). Easy peasy.

But things won’t stay simple for long, because you’ve not only wandered into a school reunion and a math problem, you’ve also wandered into a…


Really. So you’re at the reunion, still talking to Robin, only you might be sober, or you might be drunk. Which is it?

Sober Version: You and Robin continue your nice lucid conversation, and Robin says: “My older kid is a girl.” Does the additional information change the gender probabilities (two of the same vs. opposites) at all?

This one looks easy too, especially given that you’re sober. Now that we know the older kid is a girl, things come down to the gender of the younger kid. We know that having a girl and having a boy are equally likely, so two of the same vs. opposite genders should still be 50-50. In terms of the scenarios above, we’ve ruled out the last two scenarios and have a 50-50 choice between the first two.

But now let’s turn the page to the…

Drunk Version: You and Robin have both had more than a little wine, haven’t you? Maybe Robin’s starting to mumble a bit, or maybe you’re not catching every word Robin says any more, but in any case, in this version what you heard Robin say was, “My umuhmuuh kid is a girl.” So Robin might have said older or younger, but in the drunk version, you don’t know which. What are the probabilities now? Are they different from the sober version?

Argument for No: Robin might have said, “My older kid is a girl,”in which case you rule out the last two scenarios as above and conclude the probabilities are still 50-50. Or Robin might have said, “My younger kid is a girl,” in which case you would rule out the second and fourth scenarios but the probabilities would again be 50-50. So it’s 50-50 no matter what Robin said. It doesn’t make a difference that you didn’t actually hear what it was.

Argument for Yes: Look at the four possible scenarios above. All we know now is that one of the kids is a girl, i.e., we’ve only ruled out (Boy, Boy). The other three are still possible, and still equally likely. But now we have two scenarios where the kids have opposite genders, and only one where they have the same gender. So now it’s not 50-50 anymore; it’s 2/3-1/3 in favor of opposite genders.

Both arguments seem pretty compelling, don’t they? Maybe you’re a little confused? Head spinning a little bit? Well, I did tell you this was the drunk version!

To try to sort things out, let’s step back a little bit. Drink a little ice water and take a look around the room. Let’s say you see 400 people at the reunion that have exactly two kids. I won’t count spouses, and I’ll assume that none of your classmates got together to have kids. That keeps things simple: 400 classmates with a pair of kids means 400 pairs of kids. On average, there’ll be 100 classmates for each of the four kid gender combinations. One of these classmates is your friend Robin.

Now imagine that each of your classmates is drunkenly telling a friend about which of their kids are girls. What will they say?

  • The 100 in the (Boy, Boy) square would certainly never say, “My umuhmuuh kid is a girl.” We can forget about them.
  • The 100 in the (Girl, Boy) square would always say, “My older kid is a girl.”
  • The 100 in the (Boy, Girl) square would always say, “My younger kid is a girl.”
  • The 100 in the (Girl, Girl) square could say either. There’s no reason to prefer one or the other, especially since everyone is drunk. So on average, 50 of them will say “My older kid is a girl,” and the other 50 will say, “My younger kid is a girl.”

All together, there should be 150 classmates who say their older kid is a girl, 150 who say their younger kid is a girl, and 100 who don’t say anything because they have no girl kids.

In the drunk version, where we don’t know what Robin said, Robin could be any of the 150 classmates who would say “My older kid is a girl.” In that case, 100 times out of 150, Robin’s two kids have opposite genders. Or Robin could be any of the 150 classmates who would say, “My younger kid is a girl,” and in that case again, 100 times out of 150, Robin’s two kids have opposite genders.

This analysis is consistent with the Argument for Yes, and leads to the same conclusion: there is a 2-in-3 chance (200 times out of 300) that Robin’s kids have opposite genders. But, it seems to agree with the spirit of the Argument for No as well! It looks like knowing Robin was talking about the older kid actually didn’t add any new information: that 2-in-3 chance would already hold if Robin had soberly said “My older kid is a girl” OR if Robin had just as soberly said “My younger kid is a girl.”

But now something seems really off. Because now it’s starting to look like our analysis of the sober version, apparently the simplest thing in the world, was actually incorrect. In other words, now it seems like we’re saying that finding out Robin’s older kid was a girl actually didn’t leave the gender probabilities at 50-50 like we thought. Which is just… totally… nuts. (And not at all sober.) Isn’t it?

Not necessarily.

Here’s the rub. In the sober version, the conversation could actually have gone a couple different ways:

Sober Version 1.

YOU: Tell me about your kids.

ROBIN: I’ve got two. My older kid is a junior in high school, plays guitar, does math team, runs track, and swims.

YOU: That’s great. Girls’ or boys’ track? The girls’ track team at my kids’ school is really competitive.

ROBIN: Girls’ track. My older kid is a girl.

Sober Version 2.

YOU: I teach math and science, and I’m really interested in helping girls succeed.

ROBIN: That’s great! Actually, if you’re interested in girls doing math, you might be interested in something that happened to one of my kids. My older kid is a girl, and…

Comparing Versions. In both versions, it looks like you ended up with the same information (Robin’s older kid is a girl). But the conclusions you get to draw are totally different!

Let’s view things in terms of your 400 classmates in the room. In Sober Version 1, the focus is on your classmate’s older kid. The key point is that, in this version of the conversation, in the 100 scenarios in which both of your classmate’s kids are girls, you would hear “my older kid is a girl” in all of them. Of course in the 100 (Girl, Boy) scenarios, you would hear “my older kid is a girl” as well. That makes for 200 “my older kid is a girl” scenarios, 100 of which are same-gender scenarios. The likelihood that both kids are girls is 50-50.

Whereas in Sober Version 2, the focus is on girls. In the 100 scenarios in which both of your classmate’s kids are girls, you should expect to hear a story about the older daughter about half the time, and the younger daughter the other half. (Perhaps not exactly, because the older kid has had more time to have experiences that become the subject of stories, but I’m ignoring this.) Combining this with the 100 (Girl, Boy) scenarios, we get 150 total “my older kid is a girl” scenarios. Only 50 of them are same-gender scenarios, and the likelihood that both kids are girls is only 1-in-3.

Why Probability Makes Us All Dummies. Probability is about comparing what happened with what might have happened. Math people have a fancy name for what might have happened: they call it the state space. What we see in this example is that when you talk about everyday situations in everyday language, it can be very tricky to pin down the state space. It’s hard to keep ambiguities out.

Even the Sober Version, which sounds very simple at first, turns out to have an ambiguity that we didn’t consider. And when we passed from the Sober Version to the Drunk Version, we got confused because we implicitly took the Sober Version to be Version 1, with a 200-person state space, while we took the Drunk Version to be like Version 2, with a 150-person state space. In other words, in interpreting “My older kid is a girl” vs. “One of my kids is a girl,” we fell into different assumptions about the background. I think this is what it means that our brains aren’t wired right to do probability: it’s incredibly easy for them to miss what the background assumptions are. And when we change the state space without realizing it by changing those background assumptions, we get paradoxes.

Note: while I framed what I’ve been calling the Drunk Version (one of my kids is a girl) in a way that makes Version 2 the natural interpretation, it can also be reframed to sound more like Version 1. In that case, the Argument for No in the Drunk Version is fully correct, and the probabilities are 50-50. From a quick online survey, I’ve found this in a few places, including Wikipedia and the paper I linked at the start. I haven’t seen anyone else note that what I’ve been calling the Sober Version (my oldest kid is a girl) can be also framed in multiple ways. Just more proof that it’s really easy to miss background assumptions!

Another point of view on this is in terms of information. The Sober vs. Drunk versions confused us because it looked like we had equivalent information – one of the kids is a girl – but ended up with different outcomes. But in fact we didn’t have equivalent information; in fact in the Sober version, there was an essential ambiguity in what information we had! The point here is that just knowing the answer to a question (my oldest kid is a girl) usually isn’t the full story when it comes to probability problems. We need to know the question (Is your oldest kid a girl vs. Is one of your kids a girl) as well. The relevant information is a combination of a question and a statement that answers it, not a statement (or set of statements) floating on its own.


Do The Right Thing (with a Crosspost from

In the Soviet Union, the big winter holiday was New Year’s. The idea was to replace Christmas, which the authorities outlawed because it was a religious holiday, with a secular version. The basic traditions and symbols (Santa Claus, gifts, and, yes, the New Year’s tree) carried over with only minor changes. I have very nice memories of New Year’s trees, both from the Soviet Union, where I lived until age 7, and after, in Boston, where for many years my parents would take me to festive New Year’s Eve gatherings complete with Russian food and drink, marathons of top 40 music videos while you waited for midnight to arrive, and the smell of the tree.

Now that I have kids, we’ve revived the idea of a Russian-themed gathering celebrating the New Year. We mostly stick to traditional Russian food, though sometimes we have to improvise a bit to accommodate gluten-free diets, as well as current events:


Oh right, Putin. So much for holiday cheer: his government came up with its own twist on the traditional New Year’s celebrations. As the Russian opposition planned large rallies to protest the trial of anti-corruption crusader and dissident Alexey Navalny, as well as his brother Oleg, on trumped-up charges, the authorities moved up the Navalnys’ sentencing date at the last minute. Instead of waiting till the scheduled date of January 15th, already targeted for demonstrations by the opposition, the court rushed to read the verdict just a couple days before New Year’s, so that the least number of people possible would be paying attention. Recalling the Stalinist tradition of sending relatives of imagined opponents to labor camps, the government’s version of a Solomonic decision was to give Alexey Navalny, the actual dissident, a suspended sentence (let’s not risk turning him into a martyr), but to throw his brother Oleg in jail for three and a half years. Happy New Year to all.

You can and should read all about this in the Times. But, like Dostoyevsky, it’s even more powerful in the original Russian, in this case Navalny’s excellent Twitter feed and blog, where it feels like you’re watching and feeling events unfold in real time. To give you a feel for it even if you don’t speak Russian, I’ve translated Navalny’s New Year’s Eve post (published a day after he watched his brother carted away to Butyrka prison in the morning, and tried and failed to reach a rally supporting both brothers in the evening) into English below. It is a message of keeping hope alive and doing the right thing during what feels like a dark time, which is a good way to start the New Year. Best wishes to all, and now here’s Navalny in his own words:

Happy New Year

Many thanks to everyone who came out into the street yesterday in Moscow, St. Petersburg, Ekaterinburg, and other cities, across Russia and worldwide.


Participating in these kinds of actions, each of which usually looks hopeless at the time, is an important moral choice for anyone. And our moral choices are more important right now than ideological or political ones.

After all, what criteria can guide how we live our lives, which today are being turned into a dystopia based, literally, on the principle “lies = truth”? Only right and wrong.

It’s even worth it, if you’ll forgive my primitive understanding of philosophy, to follow our countryman (born in Kaliningrad!), old Immanuel Kant, and ask, “Am I acting in a way that can become a universal law for everyone?”

“The categorical imperative is ours.” There’s the right slogan for modern times.


Returning to yesterday: without morally right but hopeless actions, there can be no triumphant and invigorating ones. Without the few who are desperate, those who are more cautious, and can only walk an already cleared path, won’t turn up. Without individuals there can be no masses, and I’m glad that yesterday I could be one of those individuals, however briefly.

I think our next step has to be organizing and executing a set of truly large, simultaneous actions in Moscow and five or ten other large Russian cities. Definitely in St. Petersburg and Ekaterinburg, which were both magnificent yesterday. This has to be planned and organized diligently and well, so we have tens of thousands people participating.

The organizing themes should be fighting corruption, the justice system, the right to vote, and direct elections of governors and mayors across the country. That is, those issues on which 85% of the population supports us.

Yesterday I was riding in a police van by fighters from the 2nd regiment, and we talked about the same things as always. I tell them about Suchin’s salary and theft at Russian Railways, and they say, “Sure, and I’m stuck with my family and two kids in 200 square feet in Lyubertsy.

We’ll have to wait and see who ends up with more percentage points.

665acd6a57f245ec90445c876482807fPutin has now been in power for exactly 15 years, elevated to the top by the drunken head of the village committee, in exchange for a guarantee of safety for his corrupt family.

I wish everyone a Happy New Year, and wish for us to never lose faith that Russia isn’t a deficient country, and that people who live in Russia aren’t deficient people. They don’t need a king. They too can build a society where power changes through elections, and monarchs, Boyars, feudal lords, attendants, and serfs are encountered only in history books.

There has been no contact with Oleg so far (though MK News somehow already managed to interview him in Butyrka), but I’m sure that he also sends everyone his regards, thanks, and best wishes for the New Year.

Why Math and Music are Friends

When I started this blog, I figured I’d mostly write about math topics, but lots of other things have crept in. A big one is music.

There’s general agreement that math skills and music skills overlap in some deep way, but for a long time I had a hard time putting my finger on exactly where (perhaps because I have pretty good math skills, but am very deficient in music skills). The applications of math in music theory (arithmetic mod 12; going up an octave = doubling the frequency of a sound wave = cutting the length of a vibrating guitar string in half on a fretboard) are very nice, but I never felt like they were getting to the heart of the matter.

Here’s what finally got me there. It’s hard to define exactly what math is, but here’s one definition I’ve gotten to like over the years (I believe it’s due to Andy Gleason):

Mathematics is the science of order and mathematicians seek to identify instances of order and to formulate and understand concepts that enable us to perceive order in complicated situations.

I.e., it’s not just about numbers! There’s also geometry (finding order in space), functions and correspondences (finding order by finding rules that relate one kind of thing to another), and a lot more. It’s an inclusive, generous definition, by which I mean that it lets many notions in, and helps explain how, and to what extent, those notions are actually mathematical.

Not accidentally, it echoes Varese’s equally generous definition of music:

Music is organized sound.

Finding order, organizing things, organizing sound. When you think about it that way, of course music is mathematical.