Self-Study Questions Thread

TylerJay

There are a lot of autodidacts on LessWrong and many of us hold scholarship to be a virtue. Learning things on your own can be tricky for a number of reasons, but there is a lot of good material on LessWrong on how to do it efficiently. We know that it's usually best to build small skills in the right order, but sometimes it's difficult to figure out just what that order is, especially across disciplines. University programs have strict prerequisites that are supposed to ensure that you can handle a course before you take it, but taking a college course catalog's prerequisites to be absolute is an easy way to get demotivated before you learn anything you're actually interested in.

I've seen a lot of people run into trouble with self-study when they really want to study topic x, but know that they have to study topic y first as a prerequisite. (For example, I once saw someone on LW who wanted to start learning programming, but thought he couldn't get started without learning a bunch of math first.) For progress to be by accumulation and not by random walk, it is sometimes necessary to do this, but it can be hard to tell.

I wanted to create a thread where would-be autodidacts with limited knowledge of their target domain can ask these kinds of questions so that they can better plan their courses of study. Whether it's questions about specific texts, recommended prerequisites, MOOCs, course overlap, whatever.

Any general discussion about self-study is welcome too.

"Probability theory" is an extremely broad term. You don't need any calculus to understand discrete random variables (and if your motivation is directed towards MIRI research, this is mostly the kind of probability that's relevant). You'll want to know some one-variable calculus to understand continuous random variables (so you can manipulate probability density functions and maybe characteristic functions). It would be helpful to be comfortable with some multivariable integral calculus for the purpose of understanding collections of continuous random variables, but something like Stokes' theorem won't be particularly relevant.
My impression is that most traditional statistics courses are very bad (not even because of anything to do with frequentism, they're just very bad). Don't take one.
Can you clarify what you mean by this?

Thanks, that's really helpful.

For #3, I was basically looking for some feedback on this text. It was recommended in the best textbooks on every subject thread, but I've heard mixed reviews about it. The top rated review on amazon claims

Students will need a very strong mathematical background and a strong arm to even think about picking up this book because the it is heavy (both physically and metaphorically). Mastery of discrete math is a must, graph theory, programming, and, combinatorics will also help.

and another review by a Comp Sci professor cal... (read more)

0ThrustVectoring12y

That's my impression as well. I've had to take a statistics course, and I wound up memorizing procedures enough to vomit it up on tests on homework. There wasn't really a coherent framework, so the least work method of passing the course was memorizing the teacher's passwords. If you have to take a traditional statistics course, don't expect to get a solid understanding of statistics out of it. Perhaps you'll know how to use certain orthodox analysis methods.

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