<p>If I intend to go for graduate school in Economics, which major besides Econ would be a better choice - Math or Statistics? And which one would be easier?</p>
<p>I remember Sakky had a post about this, but I can't find it.</p>
<p>And what's the difference between normal math and applied math?</p>
<p>Also, if Math and Statistics are the majors with the lowest GPAs in campus, why is that other majors like EECS and Chem E are considered harder?</p>
<p>howabout … ECONOMICS</p>
<p>for grad school in econ, i would guess that stats is a little more useful…but i have no idea. stats is a little more practical, math gets abstract and proof-based. i have no idea which would be easier, it depends on your intrinsic talent and abilities.</p>
<p>normal math = abstract shizz to further the subject of math itself. applied math = stuff like physics and stats. math that’s applied to other topics.</p>
<p>math and stats are highly talent based (you have to have talent to do it and succeed, flat out). math requires a brand of abstract thinking ability, combined with creativity and problem-solving abilities. so you’ve got the high and the low, and very few people doing it. courseload-wise, it’s just math and whatever L&S breadths. and maybe a little physics.</p>
<p>EECS and the college of chem majors are considered harder largely because of the workload. EECS kids have to take breadths, engineering, basic chem, physics, CS, math, etc. College of chem kids have to take breadths, assorted chem classes, math, physics, and depending on major, bio or engineering and more.</p>
<p>this might help:
[berkeleyclassesirecommend</a> (markborgschulte)](<a href=“http://sites.google.com/site/markborgschulte/berkeleyclassesirecommend]berkeleyclassesirecommend”>Mark Borgschulte, University of Illinois - berkeleyclassesirecommend)</p>
<p>Upper div EECS courses tend to have one or more large projects that take 100+ hours.</p>
<p>If you have no preference, my suggestion would be to double major in statistics. Take a look at the [major</a> requirements](<a href=“http://www.stat.berkeley.edu/94]major”>http://www.stat.berkeley.edu/94). You can choose to take courses from a math option. So you can do the statistics major and as part of that take Math 110 (linear algebra), Math 104 (real analysis), Math 128A (numerical analysis), and perhaps Math 105 (second course in analysis). You’ll be fine if you take all of that, though more will certainly not hurt you.</p>
<p>If you are more interested in economic theory, I would suggest delving even further into mathematics. Aim to take Math 202A and 202B, the graduate level analysis sequence. But if you are more interested in applied economics, I would suggest emphasizing statistics and econometrics. dogglefox posted Mark Borgschulte’s advice which I consider extremely useful. You’d do well to read that too.</p>
<p>thanks for all the help.</p>
<p>Take some of both. But taking graduate economics classes is probably what will help the most and what you should find to be most interesting if you are interested in economics. Best combination would be economics, math, statistics, and computer science, but that’s not practical. Some people say take math plus psychology or math plus philosophy but why do that if you are really interested in economics.</p>
<p>In microeconomics, calculus on matrices and optimization theory is important (what it means for a matrix to be negative semi definite, the implicit function theorem, young’s law, etc.) Real analysis is useful here, especially in regards to properties of functions. </p>
<p>In macroeconomics and asset pricing (finance), dynamic programing is what is used a lot so use differential equations, ordinary, partial, linear, and nonlinear. Majoring in physics would probably be good preparation and there are a lot of economists who were physics majors in college, after all physicists are the ones who invented differential equations. Stability of systems of differential equations gets used a lot. Dynamic programing also uses functional analysis, functional operators (like the bellman equation). </p>
<p>In econometrics, linear algebra is important and you want more theory than whats in a intro type linear algebra class (ex. properties of a positive semidefinite matrix). Statistics would be important here too obviously. You want a statistics class that uses calculus, like CDF = integral of PDF and expectations using integrals.</p>
<p>Game theory uses a lot of high level math in the existence proofs. You don’t need much to solve simple games but that’s not what game theory is really about. </p>
<p>In math there are theorems called fixed point theorems and these are important for proving stuff about equilibria, which is a lot of what economics is about. </p>
<p>Knowing about probability theory is important for all of these topics. </p>
<p>Like anything you can always know more math and statistics.</p>
<p>CCNewbie, I think the obvious choice for you would be economics + applied math, with your “applied” electives focusing on economics and statistics. I think having no fundamental mathematics and only statistics would not be good for graduate school in economics – after all, if mathematics is emphasized, it usually means it’s a staple, not an optional thing. </p>
<p>Kemkid has a good post. Normal math electives focus on fundamental notions, usually abstract, while applied things will consider the interaction with other fields like engineering, CS, economics, etc.</p>