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I’m an Economics/Philosophy double major, for those who haven’t read my super-sweet biography on this blog yet. I fell into the Philosophy major as a wayward sophomore (not that majoring in Philosophy makes you wayward, per se…); I actively pursued the Economics major as — not only a more “practical” option — but a field that I was genuinely interested in, and always have been. However, I was initially scared away from Economics because I’m not, ah, exactly numbers-oriented.

So if you have taken an Economics class at Cornell — or anywhere — you know that the math is easy. Super-easy. Review the first month of a basic calculus course and you’ve got the gist of it. What is REALLY hard — and really tests the mettle of all those qualitative, artsy, would-be Economics majors out there — is making the synergistic connections between the economic concepts and the mathematical models, regressions and equations that help you reach those concepts. An example: finding the derivative of a basic total cost equation is easy. However, learning to really understand the importance and application of this “marginal cost” derivative to different aspects of economics has driven many introductory macroeconomic students to near insanity.

But what I realized when I was accepted to the economics major is that, like anything in life, it’s not a good idea to get bogged down in the numbers. Certainly the numbers are incredibly crucial — to my grade point average, for instance — but the fact is, I was fascinated by what made the markets tick, what made certain businesses and industries successful, and overall, learning why the heck the economy does what it does. And hey, if Cornell accepted me, I figured I must be at least good enough for the most popular major in the College of Arts and Sciences. 

If I could tell you how many hours I've spent studying this single graph...