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MS/PhD evaluation (Statistis/Data Science)


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I'm interested in pursuing a Masters in Statistics, and am playing with the idea of a pHd. 

Undergraduate: American University (one year study abroad at Waseda University), graduated Spring 2016

Major: Statistics

Minor: Mathematics

GPA: 3.63 (3.76 in major, 3.48 in last 2 years)

Honors: Dean's list 3 times, graduated cum laude

Type of Student: Half white, half asian, raised in US, bilingual

GRE: Haven't taken yet, but from practices expecting 168-170 Q and 155-160 V


  1. Statistics Professor (taken her class 3 times, currently auditing a class of hers as an alum)
  2. Probability Professor (took his class twice as a senior with an A and A-, would remember me)
  3. My supervisor where I work as a data analyst/consultant (not very knowledgeable in stats but could speak more to my work ethic)

Relevant Courses:

Calc 1-3, Regression, Foundations of Mathematics, Linear Algebra, Real Analysis, Discrete Mathematics, Differential Equations, Coding Theory, Categorical Data Analysis, Design of Experiments, Non parametric Statistics, Probability, Intro to Math Stat

Programming: Taken classes with SAS but not very comfortable with it. I'm ok with R (self-taught). Most of my classes used SPSS. Took a CS class in Python but still beginner level.

Experience: No real research experience. Been working as a data analyst at a non-profit since June 2016. 


Schools/Programs I'm interested in:

Univ. of Pittsburgh


Texas A&M




In addition, what are some things I should look into when deciding which schools to apply to (there's so many).



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It's helpful for those that evaluate profiles if you list the grades in your math classes. If you're looking at this cycle for PhD programs take the GRE ASAP as priority funding deadlines are closing soon!

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