Request for Widely Applicable Quantitative Methods
post by atucker · 2011-02-20T04:08:11.357Z · LW · GW · Legacy · 7 commentsI'm going to be competing in the Moody's Mega Math Challenge, and I was wondering if there was anything in particular I should brush up on.
If you look at previous problems, you can see that they're pretty varied. I want to know if there's any widely applicable math that we could study (in a fairly short amount of time) to maximize the odds of us knowing something useful for the competition.
Our math backgrounds include:
- Statistics (taught by a frequentist, mostly just probability theory and p, z, chi-squared, etc. tests)
- Calculus (single variable and multivariable)
- Linear Algebra
- Numerical Methods
Currently we're looking into Causality by Judea Pearl, and Linear Programming. Should we look at these? Anything else we should know?
Edit:
I suppose we could also use a genetic algorithm, but those don't seem particularly suited to the competition.
7 comments
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comment by jsalvatier · 2011-02-20T17:12:51.580Z · LW(p) · GW(p)
If you're not terribly concerned about speed, I would try to understand a bit of optimization in general instead of linear programming (which is a special case).
Replies from: atucker↑ comment by atucker · 2011-02-21T02:05:47.827Z · LW(p) · GW(p)
I should probably do that sometime in my life, if not for this.
Any suggestions for how? Would the wikipedia page be enough?
Replies from: jsalvatier↑ comment by jsalvatier · 2011-02-21T04:49:11.534Z · LW(p) · GW(p)
I'm not sure what the best way is; I do recommend playing around in excel. Excel has some pretty decent optimization functionality built in (not hard to use either) and it's quite visual. The wikipedia page is a good start, you probably just need to know how to use some tools and some idea about how they work.
The two most traditional approaches to optimization are approximating the function of interest locally as 1) a hyper-plane 2) a quadratic function.
Replies from: atuckercomment by Daniel_Burfoot · 2011-02-20T14:44:31.888Z · LW(p) · GW(p)
Boosting methods, particularly AdaBoost, are very effective and easy to understand.
Replies from: atucker