I’d never heard of that site! Thanks
Your answer uses a fair amount of analysis and knowledge in order to avoid this kind of large charge. Maybe perversely, I was asking for methods that do not require analysis or knowledge about contract types. I also doubt that most customers of the Texas company had a good sense of the risk they were exposing themselves too—many might have followed the “scan list for lowest rate, then pick that one” method that I use sometimes.
Thanks—that’s even better separation than using separate accounts at the same bank. More work, but something I hadn’t thought of.
Ahh—of course! Thanks!
Nice story! All the little details made it fun to read.
I’ve never! Not even close.
Python, actually! (Who would have guessed?). The camera zooms in on Do-San writing correct Python every now and then. I mean, he keeps writing a function called sigma_prime, which, like, maybe he should import? But it is tech literate even there!
This isn’t a textbook, but Dataclysm by Christian Rudder was a major inspiration to me when I was new to data analysis. The book is like a long data analysis project around dating on OKCupid (Rudder founded the site), and has a lot of good graphs made just for the book. Unlike some of the popular examples made famous by e.g. Tufte, the graphs in Dataclysm are of the type an analyst in 2020 might typically make in their day-to-day work. Lots of scatter plots and bar plots, but created thoughtfully enough to really be something. Rarely in this book did I think “ah, beautiful”—much more often, I thought “ah, yup, I see the relationship he’s saying exists.”
Interesting—I can’t count the points on a star either (my imagination insists on zooming way in on one point when I try to count it, so zoomed-in that the other points are no longer in “sight”). But I consider myself a pretty visual thinker, and rarely do things I imagine seem fake. One of my big accomplishments this year has been learning a lot more math, and that learning started being really successful when I began trying to visually picture as many concepts as I could (like probability regions in 2d and 3d, for example).
Thanks for investigating, this is helpful—I added a link to this comment to the post.
Yes, the thing about the age is totally dependent on the actual state of the universe (or, put more mundanely, dependent on the actual things I know or think I know about cows).
In regard to the short laws of the universe… I am saying that, if you’re already in the framework of probability theory, then you know you can’t gain from random guessing. Like how the optimal strategy for guessing whether the next card will be blue or red, in a deck 70% red, is “always guess red”. A hypothetical non-Occam prior, if it doesn’t tell you anything about cards, won’t change the fact that that this strategy is best. To convince someone who disagrees that this is true, using real examples, or actually drawing actual cards, would help. So again there I’d use empirical information to help justify my claim. I guess what I’m trying to say is: I didn’t mean to argue that everything I said was devoid of empiricism.
I’ve seen the words “simulated annealing” I don’t know how many times, but always figured it was some complicated idea I’d have to actually sit down and study. So this post is actually the first time I got the idea and see how it is useful. I also didn’t know that 2-year-old brains had more synapses than adult brains. Good post!
Great post! I moved a lot toward a rare-earth view when I learned of the Sandberg paper, and this post has me back to unsure. Glad I read this.
Love this! Very much agree. I do work on improving pricing methods in my day job, but I hadn’t been equipped with the emotional lens that this post describes—so this is useful to me (and just nice!). I’m gonna share it with people at work.