The End 2016 Mathematics A To Z: Hat

I was hoping to pick a term that was a quick and easy one to dash off. I learned better.

Hat.

This is a simple one. It’s about notation. Notation is never simple. But it’s important. Good symbols organize our thoughts. They tell us what are the common ordinary bits of our problem, and what are the unique bits we need to pay attention to here. We like them to be easy to write. Easy to type is nice, too, but in my experience mathematicians work by hand first. Typing is tidying-up, and we accept that being sluggish. Unique would be nice, so that anyone knows what kind of work we’re doing just by looking at the symbols. I don’t think anything manages that. But at least some notation has alternate uses rare enough we don’t have to worry about it.

“Hat” has two major uses I know of. And we call it “hat”, although our friends in the languages department would point out this is a caret. The little pointy corner that goes above a letter, like so: $\hat{i}$. $\hat{x}$. $\hat{e}$. It’s not something we see on its own. It’s always above some variable.

The first use of the hat like this comes up in statistics. It’s a way of marking that something is an estimate. By “estimate” here we mean what anyone might mean by “estimate”. Statistics is full of uses for this sort of thing. For example, we often want to know what the arithmetic mean of some quantity is. The average height of people. The average temperature for the 18th of November. The average weight of a loaf of bread. We have some letter that we use to mean “the value this has for any one example”. By some letter we mean ‘x’, maybe sometimes ‘y’. We can use any and maybe the problem begs for something. But it’s ‘x’, maybe sometimes ‘y’.

For the arithmetic mean of ‘x’ for the whole population we write the letter with a horizontal bar over it. (The arithmetic mean is the thing everybody in the world except mathematicians calls the average. Also, it’s what mathematicians mean when they say the average. We just get fussy because we know if we don’t say “arithmetic mean” someone will come along and point out there are other averages.) That arithmetic mean is $\bar{x}$. Maybe $\bar{y}$ if we must. Must be some number. But what is it? If we can’t measure whatever it is for every single example of our group — the whole population — then we have to make an estimate. We do that by taking a sample, ideally one that isn’t biased in some way. (This is so hard to do, or at least be sure you’ve done.) We can find the mean for this sample, though, because that’s how we picked it. The mean of this sample is probably close to the mean of the whole population. It’s an estimate. So we can write $\hat{x}$ and understand. This is not $\bar{x}$ but it does give us a good idea what $\hat{x}$ should be.

(We don’t always use the caret ^ for this. Sometimes we use a tilde ~ instead. ~ has the advantage that it’s often used for “approximately equal to”. So it will carry that suggestion over to its new context.)

The other major use of the hat comes in vectors. Mathematics types do a lot of work with vectors. It turns out a lot of mathematical structures work the way that pointing and moving in directions in ordinary space do. That’s why back when I talked about what vectors were I didn’t say “they’re like arrows pointing some length in some direction”. Arrows pointing some length in some direction are vectors, yes, but there are many more things that are vectors. Thinking of moving in particular directions gives us good intuition for how to work with vectors, and for stuff that turns out to be vectors. But they’re not everything.

If we need to highlight that something is a vector we put a little arrow over its name. $\vec{x}$. $\vec{e}$. That sort of thing. (Or if we’re typing, we might put the letter in boldface: x. This was good back before computers let us put in mathematics without giving the typesetters hazard pay.) We don’t always do that. By the time we do a lot of stuff with vectors we don’t always need the reminder. But we will include it if we need a warning. Like if we want to have both $\vec{r}$ telling us where something is and to use a plain old $r$ to tell us how big the vector $\vec{r}$ is. That turns up a lot in physics problems.

Every vector has some length. Even vectors that don’t seem to have anything to do with distances do. We can make a perfectly good vector out of “polynomials defined for the domain of numbers between -2 and +2”. Those polynomials are vectors, and they have lengths.

There’s a special class of vectors, ones that we really like in mathematics. They’re the “unit vectors”. Those are vectors with a length of 1. And we are always glad to see them. They’re usually good choices for a basis. Basis vectors are useful things. They give us, in a way, a representative slate of cases to solve. Then we can use that representative slate to give us whatever our specific problem’s solution is. So mathematicians learn to look instinctively to them. We want basis vectors, and we really like them to have a length of 1. Even if we aren’t putting the arrow over our variables we’ll put the caret over the unit vectors.

There are some unit vectors we use all the time. One is just the directions in space. That’s $\hat{e}_1$ and $\hat{e}_2$ and for that matter $\hat{e}_3$ and I bet you have an idea what the next one in the set might be. You might be right. These are basis vectors for normal, Euclidean space, which is why they’re labelled “e”. We have as many of them as we have dimensions of space. We have as many dimensions of space as we need for whatever problem we’re working on. If we need a basis vector and aren’t sure which one, we summon one of the letters used as indices all the time. $\hat{e}_i$, say, or $\hat{e}_j$. If we have an n-dimensional space, then we have unit vectors all the way up to $\hat{e}_n$.

We also use the hat a lot if we’re writing quaternions. You remember quaternions, vaguely. They’re complex-valued numbers for people who’re bored with complex-valued numbers and want some thrills again. We build them as a quartet of numbers, each added together. Three of them are multiplied by the mysterious numbers ‘i’, ‘j’, and ‘k’. Each ‘i’, ‘j’, or ‘k’ multiplied by itself is equal to -1. But ‘i’ doesn’t equal ‘j’. Nor does ‘j’ equal ‘k’. Nor does ‘k’ equal ‘i’. And ‘i’ times ‘j’ is ‘k’, while ‘j’ times ‘i’ is minus ‘k’. That sort of thing. Easy to look up. You don’t need to know all the rules just now.

But we often end up writing a quaternion as a number like $4 + 2\hat{i} - 3\hat{j} + 1 \hat{k}$. OK, that’s just the one number. But we will write numbers like $a + b\hat{i} + c\hat{j} + d\hat{k}$. Here a, b, c, and d are all real numbers. This is kind of sloppy; the pieces of a quaternion aren’t in fact vectors added together. But it is hard not to look at a quaternion and see something pointing in some direction, like the first vectors we ever learn about. And there are some problems in pointing-in-a-direction vectors that quaternions handle so well. (Mostly how to rotate one direction around another axis.) So a bit of vector notation seeps in where it isn’t appropriate.

I suppose there’s some value in pointing out that the ‘i’ and ‘j’ and ‘k’ in a quaternion are fixed and set numbers. They’re unlike an ‘a’ or an ‘x’ we might see in the expression. I’m not sure anyone was thinking they were, though. Notation is a tricky thing. It’s as hard to get sensible and consistent and clear as it is to make words and grammar sensible. But the hat is a simple one. It’s good to have something like that to rely on.

Reading the Comics, February 11, 2016: Apples And Pointing Things Out Edition

I didn’t expect quite so many mathematically themed comic strips so soon after the last round. Most of them just highlight one or another familiar joke. So this edition is mostly just noting that yeah, the joke is there and has been successfully made. There’s an exception, though. Enjoy.

Zach Weinersmith’s Saturday Morning Breakfast Cereal for the 7th of February is a cute chart. It’s got an unusual label to the x-axis. Now that I’ve seen it, I’m surprised not to see more jokes constructed this way.

Ruben Bolling’s Super-Fun-Pak Comix for the 7th of February was this essay’s Schrödinger’s Cat mention. I’m considering putting a moratorium on Schrödinger’s Cat strips, at least for a little while. I need to find something fresh to say about them.

Russell Myers’s Broom Hilda for the 8th of February inspires a Fermi problem. These are named for the great physicist Enrico Fermi, who often asked problems of estimation and order of magnitude. Given a few pieces of information, can you say about how big something might be? In this case, how many hours of work are spent peeling labels off grocery store apples? If we had the right information it would be easy to answer. How long does the average label take to peel off? How many apples get peeled each year? I admit not knowing either offhand. I would guess the average label-peeling time to be under five seconds, but if I wanted to be exact I’d get a bag, a stopwatch, and a sheet of paper for notes.

How many apples get peeled each year? That’s tougher. We might be able to get the total number of apples sold. But not every apple is sold with a label on it. A bag of apples doesn’t need individual labels, after all. But we might estimate what fraction of apples are sold loose and thus with labels by looking in local supermarkets. That requires assuming the turnover of apple stock is about the same whether the apple’s labelled or unlabelled. It also assumes our local supermarket is representative of the whole nation’s. But if we’re just looking for an idea of how big the number should be, or if we’re looking for what further information we have to determine, that’s good enough.

Wikipedia says the United States produced 4,100,046 metric tons of apples in 2012, the last year they have records for. If an apple is about a fifth of a kilogram, then, that implies something like 2,050,230,000 apples got sold in the United States that year. Let’s guess that three-quarters of them go right to industrial uses, into the hands of the Apple Pie Trusts and other corporate uses that don’t need labelling, while the remaining quarter go to consumers. That’s a wild guess on my part, but, industry is big. And of those, I’ll guess two-fifths get sold individually, with labels on. The rest can be sold in bags or whatnot. I’m basing that on what I kind of remember from my last trip to the farmer’s market with the free coffee bar and the bag-your-own candies.

So this implies something like 205,023,000 apples could be sold with labels. And if each label takes an average of five seconds, then this implies a total of 17,085,250 minutes spent unpeeling apple labels. That sounds like a big number, but it’s really only over 284,754 hours, or not quite 11,865 days. Of course, divided up among all the apple-eaters it’s not so much per year.

My number is wrong. I picked important bits of information out of thin air. But if I want to be more precise, I have an idea of what I need to learn. And I have an idea of how big I should expect the right answer to be. I can go from this to a better estimate, if I think now it’s worth being more exact.

Stephan Pastis’s Pearls Before Swine tries picking a fight with mathematicians on the 8th of February, with Rat boasting how he’s never used algebra. I’m not sure why bragging about not using algebra is supposed to be funny. The strip says it’s cathartic. I suppose. But it’s a joke that’s been told many times over and this doesn’t feel like a fresh use.

Rick Stromoski’s Soup To Nutz for the 8th of February is a fractions joke. Royboy perceives a difference between one-half of an orange and four-eighths of an orange. I can’t say there isn’t a difference in connotation between the two representations.

Percy Crosby’s Skippy for the 9th of February (a rerun from sometime 1928) shows Sookie with a ball. Well, a ball with a hole in it. A topologist would agree. If you’re interested in how the points on, or inside, an object connect to each other then a hoop like this is the same as a ball with a hole through it or a doughnut or bagel. This is my favorite for this group, because of the wonderful convergence of kid logic and serious mathematics.

Larry Wright’s Motley Classics for the 10th of February (a rerun from that date in 1988) is a joke about the terrors of word problems. I’m not convinced an authentic child would have trouble adding up all those cookies.

Hector D Cantu and Carlos Castellanos’s Baldo for the 11th of February reveals they have a week’s more lead time than most of the comics on the page.

How Many Grooves Are On A Record’s Side?

One. OK. We know that.

Every person who ever suffered through that innocent-looking problem where you’re given the size of a record and data about how wide the groove is and asked how many are on the side of the record and then after a lot of confused algebra handed in an answer and discovered it was a trick question has that burned into their brain, and maybe still resents the teacher or book of math puzzles that presented them with the challenge only to have the disappointing answer revealed.

This may be a generational frustration. I think but don’t know that compact discs and DVDs actually have concentric rings so that the how-many-grooves equivalent would be a meaningful, non-trick question; to check would require I make the slightest effort so I’ll just trust that if I’m wrong someone will complain. In another thirty years the word problem may have disappeared from the inventory. But it irritated me, and my Dearly Beloved, and I’m sure irritated other people too. And, yes, we’ve all heard of those novelty records where there’s two or three grooves on a side and you don’t know until fairly well into the performance which version you’re listening to, but I’ve never actually held one in my hand, and neither have you. For the sake of this discussion we may ignore them.

But the question we plunge into answering before we’ve noticed the trick is more like this: If we drew a line from the hole in the center straight out, a radial line if I want to make this sound mathematical, then it crosses some number of grooves; how many? Or maybe like this: how many times does the groove go around the center of the record? And that’s interesting. And I want to describe how I’d work out the problem — in fact, how I did work it out a few nights ago — including a major false start and how that got me to a satisfactory answer.