It’s finally Thanksgiving Week of 2009; a chance to take my nose out of my books. I’ve neglected this site, yet again.
If you haven’t heard from me in a while, it’s probably because of my full-time load as a MA candidate in Economics at San Francisco State. It might not be the big leagues quite yet, but it’s graduate study, and it’s been quite a ride so far. I know I was a good student in undergrad–still, the start of graduate-level economic theory and methods ain’t no joke. I never thought all my calculus, engineering, and computer science coursework from 10 years ago (that never amounted to a major; another story, another time) would come in handy in economics. It’s been a steep learning curve, but I feel I’ve disciplined myself into a studying routine that’s working this semester. Well, almost working…I’m confident about three of my classes, but feeling questionable about my fourth.
So, if you’re reading this page, and if you are considering studying Economics (or something related) at the graduate level, some advice:
- Take a FULL calculus sequence. Not the business calculus courses either. Take Calculus I–II–III with the science and engineering kids. It may feel like the stages of hell getting through it, but you’ll be set.
- Take MORE mathematics. You wince, my youngling, but it will ease the pain of further graduate study. Linear algebra, probability theory and statistics, differential equations, proof, real analysis…they’ve been recommended to me by other students.
- Use your professor’s office hours. USE THEM! Like your life depends on it. (In a sense, it does!)
- Work with your comrades-in-arms in all your classes. Don’t work alone all the time. Everyone thinks about problems differently; having multiple avenues of attack on a problem helps immensely.
- Make time for some relaxing activities, because all the Latin and Greek-letter variables will make your head spin. I actually enjoy math, and it makes MY head hurt.
References: UC Berkeley’s Economics PhD applicant page
A few math resources to help you in your journey, wherever it may lead:
- Wolfram MathWorld (math reference site)
- Wolfram Alpha (“computational knowledge engine”)
- Khan Academy (YouTube tutorial videos for free!)
Happy Thanksgiving, everyone! Back to the front line next week.