Seeking Advice After All Rejections

[NotEvenWrong]

Hi All, 

I am recently rejected by all 20 Ph.D. programs (mainly in statistics) to which I applied. Though a few considered me for their master programs after Ph.D. rejection, none ended up extending me a master admission. Unfortunately, I did not separately apply to other master programs.

I am still quite interested in pursuing a Ph.D. in statistics (or related areas) to prepare for a research career (not necessarily in academia). I am looking for advice on what to do for the upcoming year(s) to better prepare for another round of application. Below are some of my stats. 

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Undergrad Institution: US Large State School (US News Ranked Top 50)
Major(s): Mathematics, Statistics, Finance, Accounting
Minor(s): Computer Science, Computational Science and Engineering
GPA: 3.98/4.00 (Overall), 4.00/4.00 (Math + Stat)

Type of Student: International Asian Male 

GRE General Test:
Q: 170/170 (97%)
V: 158/170 (80%)
W: 4.0/6.0 (60%)
GRE Subject Test in Mathematics:
M: 860 (88%)

TOEFL Score: (116 = R29/L30/S29/W28)

Grad Institution: N/A
 

Programs Applying: Statistics (14) + Applied Math (4) + Operations Research (2) = 20 Ph.D. programs

 

Research Experience: 

No publications. No REUs. Several research projects and independent study projects at my institution. My senior thesis/project won a college-level research award of $1,000 ($500 for research grant, $500 for scholarship). 
Awards/Honors/Recognitions: 

- Within institution: Overall GPA < 3% of graduating class. Dean's list every semester. Student president of an honor society. A few small amount scholarships. 

- Outside institution: A 2nd place price of a midwest local data science competition. A leadership award by the national chapter of an Asian student org. 
Pertinent Activities or Jobs: 

- Internships: one consulting, one actuarial

- worked ~ 15 hours/wk at various university offices (as tutor, accounting intern etc.) during my sophomore and junior years

- Some student org involvements 

Letters of Recommendation: 

- 4 letters: 2 from professors with whom I did research/independent study, the other 2 from professors with whom I took advanced classes

- Pretty sure at least 3 out of the 4 letters are (very) strong

- not sure if well-known, but 2 recommenders are department director/grad chair respectively at my institution

Math/Statistics Grades:  

- All A/A+ for Mathematics, Statistics, Computer Science, Computational Science and Engineering

- Relevant Undergrad Classes

• Real Analysis (honor, A), Analysis on Manifold (honor, A+), Applied Complex Variables (A+)
• Abstract Linear Algebra (A+), Intro to Abstract Algebra (A+)
• Intro PDE (A)
• Linear Programming (A+), Nonlinear Programming (A+)
• Foundations of Data Science (honor, A+), Advanced Data Science (A+)
• Statistical Computing (A+), Artificial Intelligence (A+)
• Time Series (A), Regression and Experiment Design (A+)
• Probability Theory (A+)

- Grad Classes (My school has many classes that enroll both master and Ph.D. students)

• Microeconomic Theory I (PhD, A), Theory of Asset Pricing (PhD, A+)
• Mathematical Statistics I (Master/PhD, A)
• Statistical Learning (Master/PhD, A+)
• Numerical Analysis (Master, A)
• Applied Stochastic Prosses = Markov Chain (Master/PhD, A+)
• Models of Dependent Risks (Master/PhD, A+)
• Concurrent (Spring 2018) in Machine Learning, Statistical Learning Theory, Mathematical Statistics II

Any Miscellaneous Points that Might Help Hurt: 

- International Asian Male

- Interested in statistical learning 

- No noticeable research experience 

Research Interests:

Want to learn statistics and mathematics and do some applied work. On the technical side, interested in statistical learning, computational statistics, and some traditional topics (e.g. model selection). On the application side, interested in mathematical finance, risk management, and econometrics. 

 

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Any advice on programs to apply, strategies to prepare, or other pertinent points will be much appreciated. 

 

Edited April 20, 2018 by NotEvenWrong
fixed typo

[statff]

You seem to be strong enough to be admitted to at least one decent program unless you aimed only at top 10. Could you specify the programs you were denied admission? Then we could give you more helpful advice.

[Stat Assistant Professor]

Did the programs you applied to request only three recommendation letters? Sending four might have been seen as excessive, and it's really best to only send three of them (the strongest ones you think you can muster) if you reapply to programs in the future. How was your statement of purpose? I know that having an amazing statement of purpose isn't the most important thing for admissions, but a sloppy SOP or one that contains "red" flags can also hurt an application (e.g. one where you indicate that you have *no* intention of even considering an academic career, one that comes across as overconfident or one where you try to make it seem as though you have more expertise than you really do, etc., etc.).

Based on your test scores and grades, I cannot imagine that you were denied admission because of your raw numbers, which are very good. I would try to work on strengthening other aspects of your application and make sure to read the applications instructions carefully and follow them to a T.

Edited April 20, 2018 by Applied Math to Stat

[bayessays]

Mostly agreed with above - get rid of your weakest letter, work on your SOP, and forget about the top 10 and just reapply next year. Make sure to apply for schools in the 20-30 range. 

[NotEvenWrong]

14 hours ago, statff said:

You seem to be strong enough to be admitted to at least one decent program unless you aimed only at top 10. Could you specify the programs you were denied admission? Then we could give you more helpful advice.

Statistics (2018 US News Ranked)

• 1, Stanford
• 2, UC Berkeley
• 3, Harvard
• 6, U Chicago
• 8, CMU
• 8, University of Washington
• 12, UPenn Wharton 
• 12, Duke
• 12, U Michigan, Ann Arbor
• 16, Columbia
• 19, UNC, Chapel Hill
• 20, Cornell
• 31, UCLA
• 31, Yale

Applied Math/Computational Math

• CalTech, Computing and Mathematical Sciences
• U Chicago, Computational and Applied Mathematics
• U Penn, Applied Mathematics and Computational Science
• Notre Dame, Applied and Computational Mathematics and Statistics

Operations Research/Industrial Engineering

• 4, Northwestern 
• 7, MIT

Though I didn't solely rely on US News to choose the programs, it turned out that the statistics programs I applied covered a wide range up to around my undergrad institution's ranking. For non-statistics programs, I didn't expect a high chance but some of these programs have admitted students from my school in recent years and I heard wonderful things from them. I was really serious about my statistics applications, but the results were not successful. 

 

9 hours ago, Applied Math to Stat said:

Did the programs you applied to request only three recommendation letters? Sending four might have been seen as excessive, and it's really best to only send three of them (the strongest ones you think you can muster) if you reapply to programs in the future. How was your statement of purpose? I know that having an amazing statement of purpose isn't the most important thing for admissions, but a sloppy SOP or one that contains "red" flags can also hurt an application (e.g. one where you indicate that you have *no* intention of even considering an academic career, one that comes across as overconfident or one where you try to make it seem as though you have more expertise than you really do, etc., etc.).

Based on your test scores and grades, I cannot imagine that you were denied admission because of your raw numbers, which are very good. I would try to work on strengthening other aspects of your application and make sure to read the applications instructions carefully and follow them to a T.

Thanks for the comments on letters. I did send out 3 letters to almost all schools but I prepared 4 because I have different collections for different programs. In particular, I swapped one letter (which speaks more of my pure math skills I suppose) for applied math programs. So in total, there are 4 recommenders and 4 letters, but schools get 3 each (unless otherwise required). 

My SOP was obviously not stellar. I kind of just followed the convention to described what I did in undergrad, what I am passionate about, and what topics/research that I want to explore further. I definitely have mentioned that I want to become a research faculty after getting a PhD. If required, I also dropped a few names and briefly discussed why I am interested in certain professor/lab's work. In addition, I also explained my academic history a bit. I started college as a business student and was stuck in the program due to various reasons for two full years. So essentially I only had three semesters to take courses (in math and stat) and participate in research projects by the time I sent in my applications. 

 

8 hours ago, bayessays said:

Mostly agreed with above - get rid of your weakest letter, work on your SOP, and forget about the top 10 and just reapply next year. Make sure to apply for schools in the 20-30 range. 

I'll definitely cast a wider net next time. I am actually also thinking about non-statistics programs that do research in similar areas. How about Ph.D. programs in econometrics? biostat? Would these be valid alternatives? 

 

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For better or worse, I will graduate in a couple weeks. Since I am an international student, I kind of have to find a job if I still want to physically stay in the US for the upcoming year. I am wondering if anybody has experience or thoughts on how work experience will affect future admissions (within the next couple years)? Do certain types of work be viewed +/- in evaluation? 

 

 

Edited April 20, 2018 by NotEvenWrong

[Stat Assistant Professor]

Thanks for the clarification. It seems like your application was very strong. It's just hard for most everyone (especially international students) to get admitted into top stat PhD programs. There may also be a bit of "elitism" at top schools, for better or for worse. For example, there was an American (*NOT* international) student in the combined Bachelors/Masters in Statistics program at my school who had a 4.0 GPA, took basically all pure math and statistics PhD level courses in his last two years, did legitimate research on measure theoretic probability theory in the mathematics department, and was STILL rejected from most of the top stat PhD programs. Now, my school is by no means bad (it is in the top 10 public universities, according to USNWR), but it does seem like the more prestigious your undergrad pedigree (Ivy League, MIT, Stanford, etc.), the better your chances are for being admitted to a prestigious PhD program if you were a top performing student.

As for econometrics and biostat, I would say to take some time to reflect on what you really want to do. The culture of a top stat department in theory would probably differ quite a bit from the culture of a more applied statistics dept, an econ dept, or a biostat dept that is focused heavily on say, genomics (all will train you in theory and have some research in theory, but the *predominant* research focus will likely have a specific "nature" to it). If your interests lie more in applied machine learning and computational statistics, I would target departments that are especially strong in those areas.  

Re: work experience. It is unlikely to sway your application either way. You can of course mention in your SOP that it helped to shape your interests and passions (for instance, in my statement of purpose, I mentioned that working on Monte Carlo simulations and doing statistical analysis on analog signals while I was working as an engineer led me to want to pursue statistics). But playing it up *too* much as if it gives you solid preparation for a grad program is probably unrealistic and would be viewed negatively.

Edited April 21, 2018 by Applied Math to Stat

[StuartLittle]

I am surprised that you didn't get admitted to any one of those universities as well.

 

Have you ever considered Canadian Institutions?

Toronto, UBC, Waterloo, and McGill have very strong statistics department. 

[NotEvenWrong]

On 4/20/2018 at 7:03 PM, Applied Math to Stat said:

Thanks for the clarification. It seems like your application was very strong. It's just hard for most everyone (especially international students) to get admitted into top stat PhD programs. There may also be a bit of "elitism" at top schools, for better or for worse. For example, there was an American (*NOT* international) student in the combined Bachelors/Masters in Statistics program at my school who had a 4.0 GPA, took basically all pure math and statistics PhD level courses in his last two years, did legitimate research on measure theoretic probability theory in the mathematics department, and was STILL rejected from most of the top stat PhD programs. Now, my school is by no means bad (it is in the top 10 public universities, according to USNWR), but it does seem like the more prestigious your undergrad pedigree (Ivy League, MIT, Stanford, etc.), the better your chances are for being admitted to a prestigious PhD program if you were a top performing student.

As for econometrics and biostat, I would say to take some time to reflect on what you really want to do. The culture of a top stat department in theory would probably differ quite a bit from the culture of a more applied statistics dept, an econ dept, or a biostat dept that is focused heavily on say, genomics (all will train you in theory and have some research in theory, but the *predominant* research focus will likely have a specific "nature" to it). If your interests lie more in applied machine learning and computational statistics, I would target departments that are especially strong in those areas.  

Re: work experience. It is unlikely to sway your application either way. You can of course mention in your SOP that it helped to shape your interests and passions (for instance, in my statement of purpose, I mentioned that working on Monte Carlo simulations and doing statistical analysis on analog signals while I was working as an engineer led me to want to pursue statistics). But playing it up *too* much as if it gives you solid preparation for a grad program is probably unrealistic and would be viewed negatively.

Thanks for the thoughts and advice. I definitely agree that I should take this extra time to reflect on my research interest before next round of application. 

 

On 4/21/2018 at 9:14 PM, kelsia said:

I am surprised that you didn't get admitted to any one of those universities as well.

 

Have you ever considered Canadian Institutions?

Toronto, UBC, Waterloo, and McGill have very strong statistics department. 

Not this year. I will apply to a couple of Canadian schools next time. Do you have any recommendations or any insights into these programs? I have no experience with Canadian system and don't have a clue about their relative strength and preferred type of students. 

[Stat Assistant Professor]

Yes, I would apply to a wider range of schools and target ones that are more aligned with your personal interest. It may also help to look at programs that have a reputation for accepting students from more varied backgrounds (you mentioned your background in finance/accounting). Actually, one of the Statistics PhD alumni from my current program had a Bachelor's degree in Finance (only had a minor in Statistics), but switched to Stats for his PhD. He is now an Assistant Professor in Statistics at an R1, doing very well. Some of the top 10 programs, on the other hand, may be more likely to accept students from the most prestigious undergrad schools who have the strongest mathematical backgrounds.

You stated that you are interested in statistical learning. This is quite broad, so again, you should target programs that are most aligned with your interests. For example, Yale has some very strong faculty working on statistical learning (Barron, Lafferty, Zhou), but it is heavily theoretical. So they may be looking to recruit students who are particularly interested in theory. If you want to do less theory, then perhaps look at programs in statistics and biostatistics that also have research in the area of machine learning but from a more applied/computational angle. 

[NotEvenWrong]

On 4/25/2018 at 9:53 AM, Applied Math to Stat said:

Yes, I would apply to a wider range of schools and target ones that are more aligned with your personal interest. It may also help to look at programs that have a reputation for accepting students from more varied backgrounds (you mentioned your background in finance/accounting). Actually, one of the Statistics PhD alumni from my current program had a Bachelor's degree in Finance (only had a minor in Statistics), but switched to Stats for his PhD. He is now an Assistant Professor in Statistics at an R1, doing very well. Some of the top 10 programs, on the other hand, may be more likely to accept students from the most prestigious undergrad schools who have the strongest mathematical backgrounds.

You stated that you are interested in statistical learning. This is quite broad, so again, you should target programs that are most aligned with your interests. For example, Yale has some very strong faculty working on statistical learning (Barron, Lafferty, Zhou), but it is heavily theoretical. So they may be looking to recruit students who are particularly interested in theory. If you want to do less theory, then perhaps look at programs in statistics and biostatistics that also have research in the area of machine learning but from a more applied/computational angle. 

2

Would you mind sharing which program you are from? It's quite rare to see someone with only a business degree and a minor in statistics switching to Statistics Ph.D. Is this alum still doing research with an angle in finance? Very interested in the mix. 

 

As for learning, I have become more interested in the theory side after taken a statistical learning theory course. Nonetheless, I would say I still don't know much about the field in general. I will try to figure out more things before I reapply. 

[Stat Assistant Professor]

22 hours ago, NotEvenWrong said:

Would you mind sharing which program you are from? It's quite rare to see someone with only a business degree and a minor in statistics switching to Statistics Ph.D. Is this alum still doing research with an angle in finance? Very interested in the mix. 

 

As for learning, I have become more interested in the theory side after taken a statistical learning theory course. Nonetheless, I would say I still don't know much about the field in general. I will try to figure out more things before I reapply. 

I attend University of Florida (graduating in August though). And for what it is worth, the UF Statistics Dept seems to be a bit more "open-minded" in the applicants that it admits (as in, we have admitted students who attended very little-known undergrad institutions, students who didn't major in math or stat as undergrads but then later switched, etc.). My undergrad major was Economics (my Masters is in Applied Math though), and there is even one alumnus who's currently an Associate Prof of Statistics at an R1 who majored in Journalism for his undergrad (but then he got a Masters in Math, so I think that helped).

As for the alumnus that I mentioned, he is doing research on Bayesian nonparametrics, and I believe that he approaches it from both applied and theoretical angles (having several publications in top theoretical and top applied journals). I think our program does a fine job preparing graduates for their future careers, even if it is not ranked in the tip-top tier. In academia, we place grads in prestigious postdocs (Duke, Stanford, Carnegie Mellon, UPenn, etc.) who have gone on to get Assistant Professorships, or occasionally, alumni get TT jobs right after graduation (I suppose at a "lower" ranked school, it's tougher to pull this off than if you graduate from say, Stanford or Berkeley). But for the most part, anyone who wants an academic job can get one, even if most of us have to spend some time postdoc'ing after we finish the PhD.

Edited May 17, 2018 by Applied Math to Stat