To give better advice, it would be helpful to know what you are currently aiming to focus on. I don’t have good advice if you plan on going into a STEM field.
But if you aren’t going that route, I highly recommend taking enough statistics courses to get a good grip on the technical points of correlation, causation, power, population distribution, and regression.
Slightly more controversially, I think that a Philosophy of Science course would be helpful for you to acquire your own concept of what Science is and what purpose it serves. (If it doesn’t cover Kuhn, then it isn’t what I’m talking about, and ideally it would discuss something from Feyerabend).
And I think that some basis in On the Genealogy of Morals is essential to any discussion comparing value systems, but if the professor is not sympathetic to Nietzsche, then you might not get much value from it. In fact, if you have no exposure to Greek moral theory (esp. Aristotle), then I’m not sure that you will find Nietzsche interesting. And he writes in playful hyperbole, which means teasing out his meaning is a lot harder than understanding straightforward assertions.
One of the best courses I took in terms of taking a step back and looking at how science and knowledge actually work was a history of science since the enlightenment.
We read Kuhn’s Structure of Scientific Revolutions and studied Popper. Learned about phlogiston theory, and the development of gas theory. We studied Darwin, as examined by his contemporaries, by reading the essays other scientists wrote about him and his works. Back then the big debate wasn’t that evolution was “atheist” but rather on Darwin’s methodology (deductivism v inductivism, basically)
tl:dr- History and Philosophy of Science is extremely worthwhile.
The program I got accepted into is proprietary to the university, and although somewhat STEM, it’s as un-STEM as you can be while still being tangentially related.
In other words, a designer. This is the program overview from the faculty. In addition to the courses they mention here, I have to supplement with a STEM subject background, so doing something like statistics or computer programming is not out of line. Also, given that this is first year university, I get to sprawl over subjects outside of the faculty.
My fantasy was to do something like a Comprehensive Anticipatory Design Scientist, but that isn’t necessarily a goal, per se, or an ends; more of a lifestyle of learning and finding the best ways to apply that learning to help people.
I have non-mathematically inclined tendencies (note: that needs to be tabooed), which is a source of shame for me. It severely limits my options. I’ve been taking up numerous nootropics and finding other solutions to compensate. But… I don’t know. Is there a “math-sense” that you either have, or have not? Does anyone have an inspiring math success story?
If it’s math-sense that you seek, take statistics courses until you think you could explain statistics to literature majors at a cocktail party. That’s vastly more math-sense than most people have.
Also, classes in game theory (aka decision theory) could develop a different kind of quantitative thinking. But I don’t think that is what most people mean when they say “Math-sense”
The meme that liberal arts majors are almost always terrible at mathematics is incredibly dangerous to raising the sanity line. The meme is part of the same cluster of ideas as “Liking/Being good at math is weird and not for normal people.” Sorry if I’m overreacting to the joke, but I really believe the meme is that dangerous.
If you weren’t joking, sorry for misinterpreting you. The answer to your question, you want enough statistics training that you can deduce the really basic concepts (population, sample, null hypothesis) by yourself. Depending on the person, the focus of the professor, and the quality of the class, that could mean one really good class or a year long sequence. As I said above, your goal is to be able to explain a concept like regression to an interested lay audience.
To give better advice, it would be helpful to know what you are currently aiming to focus on. I don’t have good advice if you plan on going into a STEM field.
But if you aren’t going that route, I highly recommend taking enough statistics courses to get a good grip on the technical points of correlation, causation, power, population distribution, and regression.
Slightly more controversially, I think that a Philosophy of Science course would be helpful for you to acquire your own concept of what Science is and what purpose it serves. (If it doesn’t cover Kuhn, then it isn’t what I’m talking about, and ideally it would discuss something from Feyerabend).
And I think that some basis in On the Genealogy of Morals is essential to any discussion comparing value systems, but if the professor is not sympathetic to Nietzsche, then you might not get much value from it. In fact, if you have no exposure to Greek moral theory (esp. Aristotle), then I’m not sure that you will find Nietzsche interesting. And he writes in playful hyperbole, which means teasing out his meaning is a lot harder than understanding straightforward assertions.
Upvoted, and ditto.
One of the best courses I took in terms of taking a step back and looking at how science and knowledge actually work was a history of science since the enlightenment.
We read Kuhn’s Structure of Scientific Revolutions and studied Popper. Learned about phlogiston theory, and the development of gas theory. We studied Darwin, as examined by his contemporaries, by reading the essays other scientists wrote about him and his works. Back then the big debate wasn’t that evolution was “atheist” but rather on Darwin’s methodology (deductivism v inductivism, basically)
tl:dr- History and Philosophy of Science is extremely worthwhile.
Besides Formal Logic and Statistics, Philosophy of Science was the best class I took during my time at university.
The program I got accepted into is proprietary to the university, and although somewhat STEM, it’s as un-STEM as you can be while still being tangentially related.
In other words, a designer. This is the program overview from the faculty. In addition to the courses they mention here, I have to supplement with a STEM subject background, so doing something like statistics or computer programming is not out of line. Also, given that this is first year university, I get to sprawl over subjects outside of the faculty.
My fantasy was to do something like a Comprehensive Anticipatory Design Scientist, but that isn’t necessarily a goal, per se, or an ends; more of a lifestyle of learning and finding the best ways to apply that learning to help people.
I have non-mathematically inclined tendencies (note: that needs to be tabooed), which is a source of shame for me. It severely limits my options. I’ve been taking up numerous nootropics and finding other solutions to compensate. But… I don’t know. Is there a “math-sense” that you either have, or have not? Does anyone have an inspiring math success story?
If it’s math-sense that you seek, take statistics courses until you think you could explain statistics to literature majors at a cocktail party. That’s vastly more math-sense than most people have.
Also, classes in game theory (aka decision theory) could develop a different kind of quantitative thinking. But I don’t think that is what most people mean when they say “Math-sense”
Is that supposed to be a lot or a little statistics?
The meme that liberal arts majors are almost always terrible at mathematics is incredibly dangerous to raising the sanity line. The meme is part of the same cluster of ideas as “Liking/Being good at math is weird and not for normal people.” Sorry if I’m overreacting to the joke, but I really believe the meme is that dangerous.
If you weren’t joking, sorry for misinterpreting you. The answer to your question, you want enough statistics training that you can deduce the really basic concepts (population, sample, null hypothesis) by yourself. Depending on the person, the focus of the professor, and the quality of the class, that could mean one really good class or a year long sequence. As I said above, your goal is to be able to explain a concept like regression to an interested lay audience.
Here’s your audience.
(that’s a parody, just making sure you know)
A hilarious parody, with a link to its amazing inspiration!