Life tip: If you want to study X but aren't sure if you need to study Y first, just start studying X.

If you read a textbook is too hard, you will quickly discover and correct your mistake. If you read a textbook is too easy, you risk wasting months on material below your capabilities, and you won't find out until you move on to the textbook you should have started with in the first place.

As a strategic note, I am increasingly skeptical of the idea of trying to learn a bunch of skills that you may or may not use, especially advanced math skills. The key problem with learning is that skill ability decays over time unless you invest a lot of time on maintenance. So if you invest X hours learning a skill, you will have an asset whose value decays over time, while if you spend the same amount of effort making money, you will have an asset that grows exponentially in value over time.

A few questions that I've had recently:

1. Do you really need multivariable calculus for probability theory?
2. Would taking a traditional statistics course be a good place to start learning statistics and probability theory, or do they tend to teach a "bad frequentist mindset" that later has to be unlearned?
3. Is Cormen et al. suitable as an introductory algorithms text?

I've seen differing opinions on this one, so I wanted to make it a poll:

Is Jaynes suitable as an introductory probability theory textbook? [pollid:594]

Autodidacts beware.

Does anyone have an idea of the prerequisites necessary for Information Theory, Inference, and Learning Algorithms or Introduction to Economic Analysis?

I am an aspiring autodidact in math who's having motivation issues and would like to identify their cause. I've been, embarrassingly, stuck at basically the same high-school, introductory level for a few years now in all of the material I've begun studying so far, and this is because I've been studying with a frequency ranging from one week per month, to once every three months or something. My chosen study methods are slow and thorough.

I often feel frustrated about the material I'm studying, and find it rather tedious. I suspect that one reason for this is the fact that I'm a freshman undergrad in a STEM field, so I've already gone through all of what I'm studying now and more (albeit more superficially), have been acquainted with more difficult math and would really like to get into the meat of things -- however, I'm aware that I don't have a solid grasp on the basics and need to practice even the easy exercises until it becomes second nature to me.

I often wonder whether my struggles with finding the motivation to go through my textbooks are an ordinary part of the life of people who eventually overcome them (through better study plans, or increased conscientiousness or whatever) and go on to become good mathematicians, or whether it just means that I'm simply naturally disinterested in math, and will always be so, and consequently I'll never raise above the level of a mediocre STEM undergrad. I mean, if I were cut out for math, then I'd be naturally curious and enthusiastic about studying it, right? Or at least I'd have the conscientiousness / work ethic to study diligently even when it doesn't feel exciting. So far none of these conditions apply; does it mean that they never will? (I expect this feeling of tediousness to go away once I start to become good at college-level math. But maybe there's a selection effect at play here: only people who are naturally good at math master the undergrad level; people who naturally suck at math give up by the end of high school.)

I've also noticed that my lack of motivation is not domain-specific: I fail to habitually study every other field I've ever meant to study. In fact, I've been comparatively successful in studying math (and, to a lesser extent, physics and programming). This leads me to thinking the issue is a lack of study habits. The funny thing is that I constantly -- habitually, even -- fret about lacking study habits, yet so far (3 years or so) this has never translated into the instillation of said study habits.

Have any LessWrongers had similar issues and managed to overcome them?

I'm looking for a non-language specific book on proper computer programming techniques.

People vary quite a bit, so this may only apply to a subset of readers. It definitely applies to me. I learn by working backwards much better than by finding a path from basics to an end result.

Also, for a whole lot of topics, "learn X" or even "study X" is not a well-formed intent. There are often an incredibly wide range of activities you could undertake that seem to be leading to your goal(s), but are actually part of a completely different result that happens to share the same name "know X".

Don't attempt to study machine learning. Pick an outcome you want (perhaps building a LessWrong comment classifier), and study enough to get that done. Then pick another outcome, and do that.

Don't attempt to study quantum mechanics. Instead, try to figure out why you should care about the many-worlds interpretation.

My newest interest is to become a winning poker player. I have recently recented advice doing so professionally isn't quite feasible, since the sanity waterline has risen in the online poker world. However, I am not fully discouraged and I wish to pursue the skills needed to become an above average player, if not a professional one. Also, I am considering brick and mortar poker games in addition to online games.

I have been having some trouble calculating pot odds and implied odds. I grasp what they are conceptually, but actually calculating them has been a bust for me. These skills are needed for value betting, and what I have found online so far has been difficult to understand.

As I mentioned here, I am engaged in self-study to become a software engineer. I now have a (tentative) 3 year (roughly 2^10 hour) plan for learning the relavent skills. You can take a look at what I'm doing and track my progress here.

Currently, it includes learning touch-typing, math, logic, computer science, Java, C, Ruby, Haskell, SQL, HTML/CSS, Unix, and getting a degree in computer science with a concentration in software engineering.

The idea is to read and do all the exercises in the texts listed under each goal and move onto small personal and open source projects for the remainder of the time.

I'm open to and would appreciate constructive criticism of the plan, book suggestions, relevant anti-akrasia techniques, etc... Also, before I get any comments about the "slow" pace, keep in mind I own my own business, have an almost 1 year old son, and am going to school full-time.

Somehow, the way my education jumped about, I got through high school, acing advanced topics in physics, astrophysics, and scoring high enough on the advanced placement calculus exam to skip some college courses, all without learning the cross or dot products.

I didn't do so well in college physics.

(I tried researching these online, but everything I found was either impenetrably technical or used an inaccessible format for mathematic notation. I finally got a hold of javascript functions, but I still wouldn't know when to use them.)

What background material is prerequisite for Artificial Intelligence: A Modern Approach?

I'm having the exact problem that you're describing. I want to study computer science in a university here in Greece but to do that I have to give exams in subjects that are irrelevant to a computer science curriculum (anatomy,biology etc.) because in High School I was in a "medical" department. So now because I don't want to spend a year of my life studying those courses I can't study computer science in a university and I became autodidact , which is very challenging so far...