4. Don’t Say Her Name - Lords of Serendipity

Six hundred students sat in a gully of light brown hard-backed chairs, thirty rows deep, filling the lecture hall at a modest incline. On the wall behind the lectern was a series of Nelson Mandela quotations. The students were mostly international eighteen-year-olds, newly enrolled in a low-ranking urban American university. While Jack was writing his lecture and Allard was arranging his latest set of guaranteed B’s, they had been in five days of orientation to university—a kind of extended kindergarten gym class, corporate wellness retreat, and sexual violence seminar, interleaved with nightly orgiastic hives, noodle slurping, die-ins for Palestine or smaller counterprotests for Israel, texted breakups with high school beloveds, and weepy video chats with family. At this, the start of their first class in university, the students were very quiet.

Good morning and welcome to STA 105, Jack said.

He called up slide one.

It read, Professor Bayern’s Opening Slide.

A small number of the students laughed. Their first sound in university. But in the otherwise silent lecture hall the effect was like an old balloon popping: a sudden bit of noise that immediately disappeared.

STA 105 is Introduction to Statistics for Non-Majors. My name is Professor Bayern. The purpose of this course is to provide you with an introduction to statistics. In this field, we convert very large amounts of information into numbers and statements that increase our understanding of life. This specific course is intended to provide the data literacy that you are expected to have in pursuing your own fields of study when you apply to your programs at the end of freshman year. I’d like to begin by learning a little more about you. How many of you intend to go into social sciences?

No one raised their hand.

Life sciences?

No one raised their hand.

Are you all planning to go into the humanities? he asked.

Nothing.

Let me try again, he said. How many of you want to go to med school someday?

Half the class raised their hands.

He nodded.

And how many of you want to go to law school or business school or . . . some other kind of school someday?

The other half raised their hands.

And how many of you want to go into classics, English, philosophy, history, or theology?

No one raised their hand.

What do you call a data scientist who reads Shakespeare? he asked.

No hands went up.

Boss, he said. And what do you call a data scientist who’s never read Shakespeare?

No hands went up.

Boss, he said.

A hand went up. It belonged to a young Asian woman.

Yes? said Jack.

Is this going to be on the final exam? she asked in halting English.

Jack sagged for a moment, but even Katrina would care about what was on an exam. He pressed on.

Now that you’re at college and taking courses like this one, you’re going to hear from your other professors, from your academic counselors, and from old people at alumni events that the reason to study things like classics and English is that this will make you a more interesting person during a job interview and more open to different experiences and perspectives when you’re part of a team or leading a team. Maybe that’s the case. Even, I’ll allow, probably. In fact, we could even research the number of people with humanities backgrounds leading publicly traded companies to determine whether there is a positive or negative correlation between studying the humanities and succeeding in a data science–related field or profession, and, as you all know, all fields and professions are now data science related. My assumption is that, in aggregate, there’s a positive correlation, but if we were to run the same sets in, say, five-year periods, we’d see that positive correlation turn negative the closer we get to the present. Which means what, then, for you?

A student raised his hand.

Yes? said Jack.

There is no statistical advantage to studying the humanities.

Correct, Jack said to the student, a young Black man with a Caribbean accent wearing a navy blazer and white shirt over matching navy shorts, white socks, and oxblood loafers.

So then, if I may, Professor, why aren’t we studying statistics yet, you know, in this statistics course? he said, grinning. He looked around and nodded at the other students, some of whom were also nodding and smiling.

Jack smiled.

Agreed. Let’s begin studying statistics. So, the other day, I noticed a bloody pigeon’s wing on the ledge outside my office window. A gust of wind sent it into the air, and as it was falling to the ground, an eagle swooped down and caught it and landed on top of the building across the street. What should a statistician do with an event like that?

I saw that on Instagram! said a young woman from a middle row while another young woman, a few rows higher, got up and left.

Okay, Jack said. He noticed that many students were now looking more intently at their phones than normal, tapping away.

Everyone, you can look this up afterward. Let’s stay focused, please.

Actually, looks like it’s been removed from Insta, said another student, with many others nodding.

You can probably find it in a cache somewhere. Try searching up—

Try searching up later, please, said Jack. Let’s return to the question—how should a statistician respond to this event?

Well, that’s not a normal everyday thing to see, said another student, so I guess a statistician would figure out how strange it is to see it?

Very good. And everyone notice the wording. The statistician would figure out how strange it is. They would establish, in other words, probability, beginning with the reasonable assumption that it is strange to see a bloody pigeon’s wing on the ledge outside your office, and then to see it fall, and then to see an eagle catch the wing in its beak.

Another student got up and left. Like the last one who’d departed, she was in baggy cargo pants and had fuchsia hair and was wearing an N95 mask.

But before we talk about what a statistician would have to do, to figure out how strange this is, I’m curious. What do you think an English professor would do with this experience?

Write a poem about it.

Everyone laughed.

And a historian?

Figure out the history of pigeons and eagles?

More laughter.

A philosopher?

The young man in the matching blazer and shorts stood up and turned around to face the rest of the class.

What does it all mean? he said dramatically, gesturing with his hands and arms to emphasize each word, then turned back and, to laughter and a little applause, took a bow before returning to his seat.

And, finally, a theologian?

Silence.

Any guesses what a theologian would do?

Is that like a religion philosopher?

Yes, a religious philosopher, said Jack.

Everyone was looking at the young man in the blazer and shorts, who nodded and stood up again.

What does it all mean, God?

Jack joined in the applause. He was enjoying himself in a lecture for the first time in years. Enjoying the feeling in the room that they were in this thing together, thinking out loud together, figuring things out, together. He felt a warmth inside, a kindling, a good crackling fire.

In other words, Jack continued, those other disciplines respond to unexpected events by trying to make them mean something, or, arguably, mean something more, something else. An English student responds with artful words; a historian, by searching the past; a philosopher, by asking what it means; and a theologian, yes, by asking God what it means. In statistics, we don’t try to make an unexpected event mean something, or mean something more, or mean something else. Certainly not that last one. Instead, in statistics, we make what seem like unexpected events make sense. We figure out how expected, or not, they actually are. What we do is establish probabilities, which we describe in percentages and other forms of mathematical language that don’t depend on whether you believe in God or know history or like poetry to make sense.

Jack paused. He smiled.

I see a lot of relieved faces out there. Good. Let’s continue then. So, in this case, to establish the probability of seeing an eagle catch a pigeon’s wing in midair, in the downtown core, we will make inferences at the outset and figure out what data points or data we need. Eventually, we’ll determine what’s called a correlation coefficient for the variables of eagles and pigeons in the downtown core. To get there, let’s start with those initial inferences and data points and data sets. Any suggestions?

A student raised her hand.

Yes?

Is this kind of like a Thestral situation, Professor?

Do you mean a kestrel? And I think the bird was actually an eagle, not a kestrel.

No, Thestral. As in, wasn’t it, like, really bad that you saw that?

I’m sorry, I’m not sure what you mean, said Jack.

In book five, Thestral sightings are bad omens, she said.

Book five? said Jack.

That’s debatable, said another student.

What’s debatable? said Jack.

Whether a Thestral sighting is a bad omen. I think the correct interpretation is that Thestrals are unfairly treated as bad omens, but in fact they are helpful creatures to Harry and the others throughout the series. Think about book seven.

Listen, I’m on Team Hagrid too, but there’s no perfect, correct interpretation of Thestrals, any more than there’s a perfect, correct interpretation of the good and bad of drinking unicorn blood. Book one.

Don’t say her name! said a turquoise-haired student.

Drinking unicorn blood? Can someone inform me what we’re talking about? asked Jack.

The turquoise-haired student was violently thumbing her phone, shaking her head.

Maybe, like, you’ve seen death, professor? a student said to Jack.

Excuse me?

In Order of the Phoenix—

Don’t say her name!

I know. Trust me, I won’t. Anyway, in Order of the Phoenix people can only see the winged creature called the Thestral if they’ve seen death first. I guess it’s a rule or whatever. So I think what we are discussing is whether your seeing that pigeon wing means you’ve seen death.

Actually, I think it means, Professor, there is a high probability that you’ve seen death, correct? said the young man in blazer and shorts. Professor, are you all right?

Yes. My slides are now finished.

Jack left the lectern and sat down in a front-row seat. Allard went to the lectern and started his presentation.

Introduction to Academic Integrity with Allard Hamburger, Head TA.

Jack closed his eyes. He did not see death. He saw life. A past life. A gone life. He was remembering a field with a stand of trees at its far end. Early morning. They had just come in from their dawn walk around the neighborhood. Hot tea. A reading chair meant for one, holding the three of them. Jack, Elizabeth, and baby Katrina. Looking out a picture window at the mists. The baby was sleeping. Elizabeth hadn’t been diagnosed yet. Looking at the mists rising from the green at the break of day, she told him that there would come a time when once more all three of them would be together like this, and that would be heaven, not just heaven on earth. How Jack had wanted that to be true. He still did, sitting in the front row of the lecture hall. Because that student was wrong. Jack had not seen death. He had seen Elizabeth’s death. Which had left him in ashes, years ago. And while Allard explained the importance of academic integrity to the students, Jack was left in ashes again.