Math/Stat courses to take for Stat/Math MS applications

[Jaded Salaryman]

Hi everyone,

I'm preparing to apply to MS programs in stats or applied math next year (2022-2023). 

Undergrad: Top 100 undergrad private (US News) 

Major(s): Economics & Political Science
GPA: 3.899

Background: International Male Asian

 

Courses taken: 

Undergrad class: 

• Calculus I-II, Intro Stats, Econometrics, Game Theory, Intro Programming for Science and Engineering
  • Grades: all A 
  • Taken at my alma mater
• Linear Algebra and Real Analysis I
  • Grade: waiting (at least B+, expecting A- or A)
  • Taken at Harvard Extension (Math E-23a) while working full time
  • Course is an integrated, proof-based treatment of linear algebra, multivariate and elementary real analysis (but not as rigorous as Harvard Math 25 sequence)
  • Textbooks: Ross (for analysis) and Hubbard (for linear algebra & multivariate calculus)

 

Courses planned: 

• Linear Algebra and Real Analysis II (Math E-23b)

GRE: 163Q, 164V, 4.5W (taken in December 2017, may have to retake to boost Q)

 

Programs Applying: All MS. Some offer both Math and Stats MS (such as Wake Forest)

• Stats: Kentucky, Ohio State, UGA, Idaho, Colorado State
• Math: Alaska Fairbanks, Arizona, Bowling Green, Boise State, Wake Forest, South Dakota State, UMass Amherst

Research Experience: None.

 

Other Experience:

• Industry experience (working full-time since 2018) for a big e-commerce firm in Asia. Department: production support, now moving into business intelligence
• Some MOOC certificates: Andrew Ng's ML course on Coursera, WorldQuant University Applied Data Science
• Python, R, SQL
   

Letters of Recommendation:  mostly from undergrad econ professors

 

Need your advice

• In addition to Linear Algebra and Real Analysis II above, I can only take at most 2 additional courses before application deadlines. What other courses should I take? My options are limited because I am outside the US and thus can only take online courses at Harvard Extension or UIUC NetMath. I'm deciding between:
  • Abstract Algebra: Most MS in Math programs require this, but if I apply to MS in Statistics, this seems unnecessary
  • Differential Equations: a math professor at my alma mater recommends this over abstract algebra if I cannot take both
  • Probability Theory: I don't want to take this course since it is CAS-ILE based and has no lectures. It also doesn't seem to involve proofs. Is this class a must if I apply to stats MS programs?
  • Intro Theoretical Computer Science (cross-listed as Harvard CS 121): the course involves writing proof so I think it may send a good signal
  • Stochastic Methods for Data Analysis, Inference, and Optimization (cross-listed as Harvard APMTH 207): seems very computational and little theory
• Is my lack of research experience and LOR from stats/math professors a big problem?
• Do I have a good chance of getting TAships from these MS programs? 
• Is my profile strong enough for unranked/low-tier stats PhD programs?
  • My goal is to work in industry after graduation, so prestige is not an issue

Many thanks!

Edited December 20, 2021 by Jaded Salaryman