Q: How does a non-binary person commit homicide?
A: They slash them.
This is a story about campus insanity.
A friend of mine teaches statistics on the college level. He shared this story with me a couple of hours ago, and gave me permission to write about it.
I am truly amazed at how much worse it’s gotten since I graduated just a few years ago. We laughed while we discussed it, but it was very much the laughter of a particular sort that so many of us know so well: the laugh-so-you-don’t-cry kind of laughter.
To give you the proper context for the story, I’ll need to give you some background information about statistics. Don’t worry; this will be an easy, intuitive, non-rigorous, “get the gist of it” explanation, and it won’t hurt.
Statisticians, data scientists, and others who work in these arenas use a mathematical concept called “distributions” to make predictions and calculations.
Some things fit into what we call the “normal” distribution. One example of this would be heights. The average American woman is 5’5” in height, with a standard deviation of 2.8 inches. This means that:
68% of women are between 5 feet, 2.2 inches and 5 feet, 7.8 inches.
95% of women are between 4 feet, 11.4 inches and 5 feet, 10.6 inches.
99.7% of women are between 4 feet, 8.6 inches and 6 feet, 1.4 inches.
Why can we be confident of these numbers? Normally distributed values follow the rule of the bell curve. 68% of values are within 1 standard deviation, 95% are within 2 standard deviations, and 99.7% are within 3 standard deviations.
By applying this rule, we can calculate things like how rare a woman of a certain height is. I did that here to calculate the rarity of WNBA player Brittney Griner’s height. You can follow it yourself, clicking play on each block as you go down the page. Do this on a tablet or computer; it’ll be wonky on a phone. (BTW, Google will give you a scary warning when you view the page, but that’s just a CYA on their part and you can ignore it — I wrote the code myself and there’s nothing in it but some math.)
You already have an intuitive understanding of the normal distribution. That is why if you see a woman who is 6’2” you will probably remember her. She’s rare. She’s not “whip out your phone and text your friends immediately” rare, but she’s probably “stick in the mind for much of the rest of the day” rare.
But if you see a man who is 6’2” you likely don’t remember him at all, or at least not on account of his height. Men who are 6’2” are statistically far more common, even though there are about 116,000 women in the United States who are 6’2” or taller. There is significant overlap between male and female heights, but the averages are quite different.
There are other distributions for other types of values.
The binomial distribution is what applies when something has only two possible values: yes or no, approve or disapprove, etc. (In a saner world, calculation about sex ratios in various situations would be done this way—back when we recognized that everyone is male or female. I shudder to imagine how bad the data is in our world of “non-binary” and “gender fluidity”.)
For example, if you roll a fair dice ten times, the binomial distribution allows us to calculate the probability of getting exactly two 2’s. (It’s .29, meaning that if you conduct this experiment 100 times, you can expect to get exactly two 2’s in 29 out of your 100 experiments.) That’s a binomial distribution calculation because for our purposes every roll has two outcomes: it either IS or IS NOT a 2.
So normal distributions and binomial distributions are very different, but they both have many mathematical tools available to help statisticians and mathematicians make predictions and calculations.
Now that you understand the context, here’s what happened.
My friend made a joking comment in class.
He said that statisticians hate the binomial distribution so much that they try to shove everything into the normal distribution, even though there’s a lot less normal distribution in the world than we want to think.
What he meant by that was simply that binomial distribution calculations tend to be tedious and annoying, and normal distribution calculations are both more intuitive and the math is easier, so people tend to knee-jerk to doing calculations based on the normal distribution—even, sometimes, when they shouldn’t.
Here are the first two steps of the calculation I mentioned about getting two 2’s out of 10 rolls of a fair dice:
Coding makes it easier, of course, but still, it’s a lot of steps and it’s easy to make a mistake.
That was all he meant.
My friend faced an internal investigation based on a student complaint.
Why?
Because a student complained about this comment. He asserted that my friend’s comment about the “binomial distribution” being hated by statisticians made him uncomfortable and made him, as a student with bipolar disorder, feel unsafe.
He had to go through bullshit with the DEI office even though his comment should have made the bipolar student (if he was determined to take it personally) feel better, not worse — because it implied that “normal” is a lot less common than most people think.
That was a male STEM student in a highly ranked university.
This is where we are.
It’s a little startling to imagine that things are this bad, but they are, and these kids are not changing when they get jobs and enter the real world. They are changing the real world to fit their own sensibilities.
I have a feeling that we’re in for a really rough next few years.
Thanks for reading, and have a great weekend, y’all!
Oh my fucking god.
Maybe the bigger problem is how the administration treats the complainants. Can you imagine, back in the 1950s, what those in charge would have said to a student claiming to feel “unsafe” because of a joke like that?