creed_the_third

I don't think MIT has a stat PHD..though they have op research, did you apply to that?

The only one I've read about is Wisconsin: http://www.stat.wisc.edu/FAQ "PhD students are expected to have had an introduction to measure and integration theory with proofs (similar to UW's Math 629). Books that cover Measure & Integration Proofs are Royden (Real Analysis) and Ash (Real Analysis and Probability)."

Is 110 graduate real analysis at harvard?

Thanks for the input My math grades are good. One of my interests is in stochastic processes so I guess this course would help in that area? I don't know if I'm gonna apply to super theoretical departments like Chicago though... Looked at the syllabus of previous years for the course and it does not seem like the grade cutoffs are that much different than any other course... also the final is worth 50% which does seem like a lot for a course here (though in Sweden most course grades are only based off the final exam heh, I'm an exchange student). Also, is it a "waste of time" taking a lot of stat courses in stuff like anova and regression since you'd still have to retake them in a PhD program? Or could you skip over them if you've already taken them?

The thing is that there is another course, a grad course in mathematical statistics, that is in the same section as this one. So if I don't take measure theory I'd take that one instead I think.

I'm thinking about taking a graduate level course in real analysis (measure theory). I took undergrad analysis during the fall and did well, but I still feel intimidated by the thought of taking a grad level course in math. Would it look bad/neutral/good on an application to a stat phd program if I got lets say a B in the course? How much does the difficulty level vary between upper level undergraduate courses and grad courses (stupid question since it depends on school and the specific course but what has been your experience)? The alternative to taking measure theory would be to take more stat courses or maybe some other undergrad course in math such as abstract algebra or complex analysis. Thanks Also, regardless if I'm taking the course or not I plan on reading up a bit on my own on measure theory

I'm currently doing my year as an exchange student at a US university and doing okay so far (btw, glad I read up a bit on my own on writing proofs since I wasn't able to register for the prereq for real analysis). I'm pretty clueless how I should go about getting LORs from professors here at this university in the US, since when I'll be applying for phd programs I'll be back in Sweden. Should I just email them when I apply? I doubt they will remember me... Or would it be appropriate for me to go and speak to them after I finnish my courses and explain my situation? Also, I'm think it would be good for me to get some research experience here, so how does one go about contacting professors if they need help with their research? Email or office hours?

Thank you guys for the input. I'll think I'll read up a bit on my own during the summer and try to take the course directly. The book they use is Kenneth Ross: Elementary Analysis: The Theory of Calculus.

It does also state under prerequisites "or consent of instructor" so maybe I can talk my way out of that requirement?

It does also state under prerequisites "or consent of instructor" so maybe I can talk my way out of that requirement?

Maybe I wasn't very clear in my opening post but I will do a student exchang (as part of my engineering program) next year at a US university and it is during this exchange that I plan to take real analysis. My question was if I would be able to take real analysis during my exchange year abroad, because one prereq for it was a proof writing course. That question had nothing to do with PhD programs. So when I apply to PhD programs after I get my MSc in engineering I will have real analysis (again, if I'm allowed to take it).

Thanks for the reply. How strict are they in US colleges with prerequisits? I looked at the real analysis course at the college where I'm going to study at next year, and one prereq is a course in how to write proofs. I haven't taken such a course. Do you think that will be a problem? The optimization course I have taken covers KKT theory, linear and nonlinear programming, convex optimization etc.

I'm a Scandinavian student currently in a 5 year MSc in industrial engineering program (you go into it directly from high school, first 3 years = bachelor, 2 last years = master). I'm in my third year now and I've started thinking about pursuing graduate school. Unfortunately it is a little to late to switch major, but I'm planning on taking as many math classes I can and my masters concentration will be in financial engineering. Starting in the fall I will do a year abroad at a top 10 US engineering school. Currently I've taken the following math courses: calculus in one variable, calculus in several variables, linear algebra, mathematical statistics basic course, analytic functions, systems and transforms, optimization (will take stochastic processes and numerical analysis before summer). Also of course engineering courses and a few finance courses. My grades so far are 4,6/5,0 with top grade in all but one math course. Okay given my background, what courses should I take to prepare me for graduate studies? I've read a lot about real analysis being necessary. As part of my concentration in financial engineering I will plan to take financial statistics, Monte Carlo and empirical methods for statistical inference, statistical modelling of extreme values, econometrics and a few more. What I'm worried about is that my math background isn't as rigorous as someone who majored in math. For example I have no discrete mathematics, topology etc. Will this be a big problem? Should I apply directly to a PhD or to a MS in statistics/math first? Also my university has a master in math statistics which I can take and count some of my credits from my MSc in engineering. Though it would mean that my graduation would be prolonged by a year. Would really appreciate some insight on the topic