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Posted (edited)

Hey everyone, I'm here for some advice about applying to Stats MS programs next year.

 

School: Top 5 Public

Cumulative GPA: 3.70

Major: Mathematics

Math Courses: Single Variable Calculus (A), Multivariable Calculus (B), Intro Linear Algebra (B+), Intro Differential Equations (A), Linear Algebra I (B-), Linear Algebra II (A-), Ordinary Differential Equations (C+), Real Analysis I (B+), Real Analysis II (A), Complex Analysis (B), Partial Differential Equations (A-), Optimization (A)

Statistics Courses: Intro Statistics (A+), Statistical Programming (A-), Mathematical Statistics (B-), Probability Theory (A), Regression Analysis (A),  Experiment Design (A-), Intro Computational Statistics (A),  Linear Models (A), Statistical Modeling (B+)

GRE: 169 V / 170 Q / 5 AW

Letters: 2 Stats Profs (1 probably lukewarm, other great), 1 Math Prof (great, from my Real Analysis II Class).

 

Should I address the C+ in ODEs? Honestly, I have no reasons other than I didn't understand the material well and I didn't have enough time to fully prepare for my final, which I likewise did poorly on. Is that all I need to say? I'd hope my grades in Real Analysis would be a good indicator of my ability for grad courses.

Should I try to take the Math GRE and do well on it? Would I get any bonus for that?

Also, what range of MS programs can I be competitive for? Top 10? Top 20?

 

Thanks in advance!

Edited by Extroram
Forgot some classes + Extra Question
Posted

I think you're wasting your time to take the Math GRE for MS admissions, unless you think you want to do a PhD later and will remember more in a couple of months than in a couple of years. It's just a lot of review for someone who took computational level calculus years ago. It's also pretty hard to get a good score, because most people who take it are applying to math PhD programs (I know this doesn't seem align with my previous sentence haha) . That said, it would be impressive if you did well. I just think there are better uses of your time.

I'd apply to a range of places, but definitely take a couple swings at the top places (Stanford, Berkeley, Chicago). I'd be pretty surprised if schools ranked around 20 rejected you. Keep in mind what you want out of this degree, as it will inform specific school choices. If you look at previous posts I've made similar to this one, you'll get a rundown of what I mean by this. 

Posted (edited)

I would not address the C+ directly as it's really not an outlier in your math grades so there's no reason to call attention to it.  The advice that I'd heard is that it's usually only necessary to discuss things that are a big deviation from your profile that have an explanation that can't be inferred from your transcript.  For instance if you had one quarter where you went through something personal and racked up 2 D's, but you have all A's otherwise, that merits a brief explanation.  This will become more clear as you start to apply I think, for instance U of Chicago flat out says not to discuss grades in your statement.

Additionally, ODEs is not one of the "core" mathematics courses that they'll give extra scrutiny to.  I'm sure you know this already but that set is roughly linear algebra, calculus, probability and real analysis, with analysis being less important at the masters level.

I also wanted to comment because I had a very similar profile in terms of big metrics ("top 10 public" school, same major, similar GRE, identical GPA) and was admitted for an MS at 3 out of 4 of the top 10 schools I applied for (biost/stat combined ranking).  So I would encourage you to shoot for that range and be sure to include some safeties that are a good fit for your interests.  You may be a candidate for a funded MS at a lower ranked school if that interests you.

I'm going to offer a different take than robben did on the subject test:   Taking the Math GRE and doing well will help you (of course!), and I can't see any reason that reviewing calculus is not in your best interest.  You don't have to send it if it goes badly, so why not give it a shot?  If you have to choose between that and getting good grades, then get good grades.  

 

Edited by Innominate
Posted
2 hours ago, Innominate said:

I'm going to offer a different take than robben did on the subject test:   Taking the Math GRE and doing well will help you (of course!), and I can't see any reason that reviewing calculus is not in your best interest.  You don't have to send it if it goes badly, so why not give it a shot?  If you have to choose between that and getting good grades, then get good grades.  

Don't you think it's overkill though? you got into a bunch of places OP would presumably like to go with a similar profile as OP currently has (i.e. without it).

Posted

Of course it's overkill.  OP asked if it would give him a bonus, the answer is yes (I'm sure you'll agree).  Whether he can spare the time is his decision.

Posted

I definitely think the OP can get into a top-10 stats program as-is. Top-5 public schools include Berkeley, UCLA, Michigan, UNC, and UVA, all of which have good math departments. Secondly, ODEs isn't even really necessary for statistics. I would wager the majority of students applying to master's degrees don't have a lot of math courses under their belt, which is why they're going for Master's than PhD. I seriously doubt the majority of students applying for master's degrees have taken Analysis I and this person has taken Analysis II (getting an A) and Complex.

I wouldn't waste time taking the math GRE. I'm pretty confident you can get into a top-10, but apply to the 11-20 range to be safe.

Posted (edited)

Thanks everyone for the advice!

 

Since my interests are in Machine Learning, I know that, at least for the Top 10, I'll be applying to Stanford and CMU, with Stanford being the harder of the two to crack I assume. Would Berkeley also be a good choice for ML or is the program more on the theoretical side? Or does specialty really matter as the Masters level?

 

Also, does anyone have recommendations for ML in the 11-20 range?

 

Thanks!

Edited by Extroram

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