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PaperclipPerfector  1mo ago (text post)   2804 thread views

Small-Scale Question Sunday for October 20, 2024

Do you have a dumb question that you're kind of embarrassed to ask in the main thread? Is there something you're just not sure about?

This is your opportunity to ask questions. No question too simple or too silly.

Culture war topics are accepted, and proposals for a better intro post are appreciated.

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Meet Bob. He's in his late twenties, and has not done any math since high school, where he was a B- student in STEM-related subjects and moderately disliked most of them. Bob is of above average intelligence, but not exceptionally bright (think +1 SD, midwit extraordinaire territory). One day Bob decides to renounce his wordcel ways and try to learn enough math in his spare time to leave his fake e-mail job and join a rigorous quantitative PoliSci program.

How many hours of intensive study do you estimate it would take Bob to get to the level of mathematical prowess of an average incoming first-year grad student in such a program?

Claude seems to ballpark that number at 600-800 hours (200-300 to relearn math up to Calculus, and 400-500 hours for undergrad math). To me this feels like a real lowball (there are like half a dozen videogames where I have twice as many hours, surely learning an extremely valuable skill must take a lot more time and effort – otherwise everyone would do it, right?), but maybe math is that easy, and Bob, like many people, just never really tried.

Mental fatigue is a real thing. If you only count hours spent actually running then training for a marathon doesn't seem that impressive.

Spending 2 hours a night and 6 hours a day on weekends learning math is going to be exhausting. But it's pretty easy to do that with video games.

Meet TollBooth - graduate of a quantitative PoliSci undergrand program at an Ivy.

Math is important, but you're going to have to be more specific with your end goal. If you want to be a professional academic then you'll need to have a transcript with math courses on it. Community colleges are fine up to multivariable calculus, then you probably need to pay for your local state school's courses (a lot of these programs are online). But then you'll also need to show a reasonable polisci ability as well. That's actually harder. Not because of the courser material (lol) but because those programs run on prestige and credentialism. An online PoliSci degree from some no name school is worse less than zero because they'll charge you tuition. And Top-50 PoliSci undergrads aren't usually in the habit of bringing in curious almost 30 year olds (although so might be if you show you hustled on your math, idk). There are some Continuing Education programs that are actually legit, but you have to be a careful. Harvard Extension school is pretty much Coursera.

But do you want to be a professional academic? That seems lame as hell. If you want to do quant geopolitics for a living - build a GitHub portfolio where you apply your mathematical ability to real world data using code. You're showing off a full-stack of skills there; hard math, PoliSci concepts, and moderate software engineering capability. You can probably get a job with one of the research firms (think Cambridge Associates). From there you can build a professional network and work your way to a think tank or one of the smaller (and less known) research firms who do risk analysis for bank etc. I mean, this is a 10+ year progression, but its doable.

But again, what's the goal? A quantitative polisci masters is kind of weird degree to get unless you're already in that industry (risk analysis, geopolitical analysis, military-industrial capacity analysis (probably filed under Operations Research a lot)).

What insanely complex math do you use in ‘quantitative political science’ on a regular basis? Even most reputatable geopolitical think tanks are running what is essentially babby’s first ML / journeyman python data science and combining it with undergrad lukewarm political science level commentary. At the best places it’s combined with academic prof tier commentary churned out with low motivation and contributed to by ex military and state department people retiring where the easy money is.

What insanely complex math do you use in ‘quantitative political science’ on a regular basis?

Zero, for 95%+ of the industry. Please don't confuse me for OP, however. I wasn't trying to imply you need high level math to be a geopolitical/risk practitioner. That's why I said "lol just spin up github" in my response.

If you don’t mind me asking, what do you do with your degree?

I know one guy who studied PoliSci, presumably because he grew up in a State Department household on the other side of the planet. We met because he was switching to engineering. As far as I know he’s at a major defense contractor now.

I don't use my degree at all.

First few years after graduating, I did startup land stuff. Back then, it was like being paid to be a YouTube podcast bro. I hated it. So I started consulting because it was prestigious and good old fashioned work. I hated it. Went to a F500. Way better, but I realized success there was 20+ years of politicking. Hooked back up with some solid engineers I knew from wayback. We built a thingy (won't get into details because it's too specific and I'd risk a doxx) and made a bunch of money.

Now, I still don't use my degree at all.

Can Bob afford a tutor? The instructional and executive functioning value there is huge (with a good tutor).

In particular, I think they could really help you know what is worth studying. E.g. probably you can skip trig identities, and you can certainly skip Kramer's rule.

Even better, find someone in the polisci program and ask them what you actually need to know. There is probably a big difference in what you need to know to get the job, and what you need to know to do the job. I'd focus on the former.

surely learning an extremely valuable skill must take a lot more time and effort – otherwise everyone would do it, right?)

Absolutely not. People procrastine and are lazy as hell. There are many skills that are relatively easy to learn but the learning is unpleasant enough most people just don't do it

Are you Bob?

It’s impossible to give a universal estimate, people learn math at such wildly different rates that there’s no point in speculating. If Bob has all the prereqs met for whatever the program is then Bob should be good. Bob can just learn things as Bob goes. Perhaps Bob should just read the sorts of journal articles that quantitative political scientists tend to read, and if Bob encounters a mathematical concept that Bob is unfamiliar with, then Bob can go look it up and do a deep dive on that particular concept. That would give Bob a series of concrete, relevant goals to focus on.

Ok, so college algebra at my local community college is 5 hours a week for a sixteen week semester, and let’s approximately double that time for homework/out of class study/whatever. That’s 160 hours to get through high school minimum math, minus geometry. Precalculus is a four hour/week class, so that’s 96 hours. So for everything up to but not including calculus that’s 256 hours, towards the high side of Claude’s estimate. If we assume that calculus is approximately the same amount as getting ready for it, we’ve blown Claude’s estimate out of the water. But, Claude’s estimate seems reasonably accurate for solely class time, so that’s probably what it counted.

I find your estimate fair, if you take into account that Bob is not at the level of a skilled mathematician or programmer, for whom advanced math is bread and butter. A STEM graduate working in the profession can spend about 3-6 hours a day on math before getting tired, but for Bob two hours a day would probably be his limit. Time estimate is not as important as ability to use this time efficiently and meaningfully.

About 95% of programmers never use math beyond basic arithmetics. Exception is when you have to deal with physics and such (games, simulations, etc.) and crypto (but regular programmer would never ever roll their own crypto, they'd use a pre-made library), or maybe financial calculations. Of course, if you consider algorithms, computation theory and things like graph theory "advanced math", it's different but it's not the same kind of math as calculus or linear algebra are, I think.

Yes, graph theory is math, or at least the math department that gave me a doctorate for a dissertation in graph theory seems to think so :)

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