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Stats PhD Hopeful Evaluation

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When it comes to applying to graduate schools and jobs, I always struggle to get advice tailored to my situation, which is admittedly uncommon (at least from what I have gathered).

Background: I originally flunked out of a UC school after my freshman year. I was an electrical engineering major and in ROTC, and was in over my head. Not knowing what to do with my life, I ended up getting a degree from a diploma mill for-profit university while I worked full time (albeit doing well, but let's just say I wasn't challenging myself the way I should have). Since then, I got got committed to academics again and began re-teaching myself a lot of the math and programming that I once new, as well well as working on data-related projects. Eventually I studied for the GRE and applied to Data Science and Statistics masters degrees, and was fairly surprised when I got in to most of them. Since attending, I have developed a really keen interest in statistical theory, especially applications to outlier analysis and anomaly detection. I have completed projects and independent research related to these subjects, and I would like to do more research in these subjects through a PhD.

However, despite having good relationships with my professors, I feel like they don't take me seriously when it comes to considering me as someone on the "phd track". To be honest I don't blame them-- I don't have an academic remotely similar to any of them, let alone the students in my program. I feel like I was able to compensate for my prior faults enough to get into a Masters program, but is that the ceiling for me?

I guess what I am wondering is: what more can I do to make myself a more competitive potential PhD candidate? Should I take Real Analysis as a non-degree student despite doing well in analysis-heavy stats classes? Should I hunker down and study for the GRE math subject test? I know top 20 schools are out of the question, but what about the 50-100? 

Any advice would be greatly appreciated. More specific details below:

Degrees: BS Environmental Science at Online for-profit university, MS in Statistics East Coast private school (US news rank ~50, Stats Department ranked similarly)

Type of student: American (non-international)

GRE: 168 Verbal, 168 Quant, 5 Analytical Writing. 

Programs applying: Statistics

Graduate Level Stats Coursework: Probability and Statistical Theory (2 semesters), Linear Models, Categorical Data Analysis, Time Series Analysis, Machine Learning, Data Science, Data Mining, Applied Multivariate Analysis, Bayesian Stats, Statistical Deep Learning, Computational Stats.

Other Coursework: Multivariable Calculus, Linear Algebra, Undergrad Stats, about 5 computer science courses.

Graduate GPA: 3.92 -All As and 1 B

Jobs and Research:

  • Machine Learning and Data Science internships
  • TA for Data Science courses
  • Applied Stats Research (Econ and Operations Research oriented)


Edited by buccsbandwagon
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