Advice for course selection

[Fancyfan10]

Hi everyone!

I am currently in one of the top universities in China and will enter my junior year in September. I am posting this for seeking some advice on course selection. Since I am going to apply for Statistics/Biostatistics PhD program, I have arranged my course schedule last two years for preparation. Here are some courses and grades related to application.

 

Mathematical analysis 123 (A,A,A-) 

(FYI, in China almost every school combines calculus and analysis together, so these courses can be viewed as “calculus+intro to analysis”.)

 

Linear Algebra 12(C+,

 

Probability based on calculus (A-)

 

Mathematical statistics (A,definitely ace it, rank 1/75)

 

Numerical analysis(A-)

 

Real analysis(A)

(The content includes basic topology, Lebesgue measure and integration, some introductions to Lp space like Holder inequality)

 

I plan to take following courses next semester but there are still some options to make.

 

Nonparametric statistics(proof-based)

 

Topology 

 

Applied stochastic process

 

PDE

 

Here are some questions:

1. There is still one option between applied regression and functional analysis. In order to achieve the goal to a decent stat/biostat PhD program, which course is better?

2. Because of the personal reason, the Linear Algebra 1 I took in the first semester of freshman year definitely damaged my profile. So if I have chances to take an advanced algebra course that will cover all the content of it and also include more advanced topic like QR decomposition and SVD, is it a good idea to take it?

3. Do I need to take measure theory? Any other courses that can be helpful for the application and future research?

Any advice will be much appreciated.?

 

 

 

 

 

Edited July 28, 2019 by Fancyfan10
Typo

[bayessays]

1. Math courses will generally help more than applied stat courses.

2. Definitely take the advanced linear algebra. In fact, prioritize it over the two courses above. Even if you did well in your first linear algebra course, things like SVD are used all the time in statistics.

3. You don't absolutely need it, but if you will do well, take it.

My ranking of priority for those 4 courses would be

1. Advanced linear algebra

2. Measure theory

(Large gap)

3. Functional analysis/applied regression

[Fancyfan10]

Just now, bayessays said:

1. Math courses will generally help more than applied stat courses.

2. Definitely take the advanced linear algebra. In fact, prioritize it over the two courses above. Even if you did well in your first linear algebra course, things like SVD are used all the time in statistics.

3. You don't absolutely need it, but if you will do well, take it.

My ranking of priority for those 4 courses would be

1. Advanced linear algebra

2. Measure theory

(Large gap)

3. Functional analysis/applied regression

Thanks so much！Could you please recommend me some other courses that are helpful?  Do you think my math background is sufficient to apply for Statistics PhD program?

[bayessays]

Yes, you have plenty of math. I think the ones you listed are a good start. A course on optimization may be useful as well.

[Fancyfan10]

31 minutes ago, bayessays said:

Yes, you have plenty of math. I think the ones you listed are a good start. A course on optimization may be useful as well.

Yeah, actually there is another optimization class that I will take next semester. I just omitted it in the post. Your advice is very much appreciated, bayessays. And since I am also interested in optimization, I am doing a research about creating an R package using optimization method to estimate the coefficient under the extreme value distribution model. Ideally, this project will lead a paper published in a decent journal like JCGS, Technometrics,etc. Do you think this kind of research experience can be viewed as a big plus? (Also, I might apply for several OR PhD next year.)

[bayessays]

It would be very rare for undergrads to publish in journals like that, so it would definitely be impressive and help.