2025-26 Grad School Application Cycle
Now that enough time has passed after hearing back from most programs, I’ve found other threads exceedingly helpful in preparing for graduate applications and wanted to pass on the favor. I hope that this post will help any aspiring grad students that want to pursue Statistics in the near future.
Before I proceed, I’d like to start with several acknowledgements. I’ve largely been inspired from Daniel Posmik’s post and profited from his feedback, especially how we’ve had similar trajectories in undergrad (Both initally wanting to pursue Economics PhDs and pivoting to Statistics / Biostatistics). I would also like to give a sincere thank-you to my recommendation letter writers (Who were bombarded with many electronic requests) as none of this would have been possible without their support. I am also indebted to the various friends and professors at UofT who provided me with invaluable feedback and support in both my coursework and graduate applications. Finally, to my girlfriend and family, thank you so much for the sacrifices you have made for me during my undergraduate studies.
Please note that the opinions in this post are my own and do not represent the views of any external parties mentioned in this blog. My advice can only be so helpful as an incoming graduate student and I strongly recommend pairing it with other resources if possible. Take anything I say here with a heap of salt.
Trivia + Background Information
Ironically, I hated the idea of research for most of my life until the end of my first year in undergrad, and this definitely showed in my grades (More on that later). I was in a rough spot by the end of Year 1 and I had to retake my economics courses to make the program I wanted at the time (Economics and Mathematics Specialist, one of my current programs). From that Summer onwards, I was forced to reverse my study habits which reflected in my grades as well. After my second year of advanced calculus and the honors core sequence in both economics and statistics, I changed my tune on grad school and wanted to push further into academic research, as I started to genuinely enjoy the content I learned. For a good chunk of my undergrad I wanted to pursue a PhD in Economics and I started with a Statistics minor intended to complement this decision. By my third year I realized I had the necessary credits to pursue a Statistics major instead (Given that I was going to take courses in probability and statistical inference anyways). In my final year I committed to another Specialist in Statistics instead as I was wrapping up my program requirements for Econ Math and I was only two courses away from finishing, so I bulked up my course selection to avoid senioritis. This lead me to a spot where I could apply to both Economics and Statistics PhDs; I threw some wild-card programs (Engineering and OR) into the mix as well. In hindsight my application process was a bit scatterbrained and I plan to only apply for Statistics and Biostatistics PhDs for the 2026-27 cycle.
My initial research interests were very broad across Health Economics and Biostatistics, with some applications including Electronic Health Records, Hospital Operations, Healthcare Engineering and Discrete Choice Modelling. This decision was in large part driven by my personal faith, as a career in Public Health would incorporate Christian values such as taking care of the sick and poor and affirming the inherent God-given dignity that resides in each person (i.e. Imago Dei).
“If anyone has material possessions and sees a brother or sister in need but has no pity on them, how can the love of God be in that person? Dear children, let us not love with words or speech but with actions and in truth.” (1 John 3: 17-18).
I am also a Canadian citizen, so I was very much privileged in the admissions process and had access to government-funded opportunities (I did not apply to these positions in time). Unfortunately, the international pool for most Canadian programs is much more competitive as many cohorts are predominantly domestic, so the larger application pool, higher tuition and less funding opportunities creates a tighter bottleneck (E.g. you can check historical trends on the UofT PhD Admissions Tableau). This is why you usually see international applicant profiles being stronger on average than their domestic counterparts.
Grades
The Good:
- With the exception of Year 1, my Year 2 - 4 GPA was around a 3.9 and > A- for all courses except one (Topology, real analysis, probability, etc) which gave me an easier narrative to write about in my Statement of Purpose.
- Most Canadian programs only use grades from the final year or final 2 years as a benchmark, so students who struggled early on can still remain competitive for grad school (Me!).
The Bad:
- My cumulative GPA was significantly pulled down as a result of my first year (I started university in the 2.0s). While Canadian programs are only concerned with grades in the last two years, many US programs (Anecdotally) use CGPA as an initial filter so there is a risk of being screened out when it comes down to hundreds of applications for a few spots.
- My only questionable grade in upper year courses (Low B in Data Analysis I) might’ve hurt for US PhDs, considering it’s a core course in most Statistics curriculums.
Courses
I’ve been told by professors that course selection is more important than the grades you receive in them. At the time of applying to Direct-Entry PhD programs I wanted to stand out by taking more rigorous courses (E.g. topology, PDEs, ML) especially to compensate for my GPA as well. This is especially important for Economics PhDs since I did not have a predoc at the time of application which is usually a filter at competitive programs. Generally, it’s a better idea to take hard courses and do average in them (~ B range) over not taking them at all.
Recommendation Letters
Arguably the most important part of the entire PhD admissions process. Students with mediocre academic track records are still able to be admitted if they have superstar letters. Conversely, an outright bad LOR can tank an otherwise strong applicant. In general, research letters dominate course letters but at least 1R + 2C should be okay. For Economics programs, all of my letter writers were Economics professors, and for Statistics programs, I went with a combination of 2 Econ profs + another letter from my Real Analysis instructor. It’s also a good idea to have backup letter writers in case of emergencies, and to avoid burnout if your writers have a limit. Make sure to be very grateful throughout the entire process as it can be very mentally intensive (A lot of programs require an additional questionnaire section along with the standard LOR) and the time investment on their behalf can really add up. This is also a chance to bring up any exceptional circumstances to your writers (E.g. unusual grades, life events) other than in the SOP if applicable.
Test Scores
I only submitted GRE scores for programs where it was mandatory to do so as I one-shotted it with only two weeks of studying (Not recommended!). For most STEM programs, 155V 168Q 4.0AWA should be the minimum acceptable score.
Research Experience
Please refer to the other sections in my website. Note that I did not have any publications at the time of application; this is less desirable for Statistics programs but normal in Economics, even amongst some applicants who did a predoc.
Application Materials
I’m not sure if I’m the best person to ask for CV and SOP advice as there are better threads online for doing so. However you should tailor your SOP to each school and mention one thing that’s unique about the program (For example, I mentioned how UofT’s Statistics PhD has the MDoc program which allows you to be co-supervised by a professor outside your home department). You should also mention 1-3 professors and their research area you’d like to work with and mention publications when applicable. If you’d like a copy of my material as inspiration for your own writing, please send me an email. It goes to say that please do not copy anything that I wrote verbatim.
Decisions
After a very long application season, here is my list and the corresponding results:
| Program | Result |
|---|---|
| UC Berkeley PhD Biostatistics | Rejected |
| Duke PhD Economics | Rejected |
| UMich PhD Economics | Rejected |
| UMich PhD Industrial and Operations Engineering | Rejected |
| UMich PhD Biostatistics | Rejected - Offered MS, without funding |
| Waterloo PhD Biostatistics | Rejected |
| Waterloo PhD Statistics | Rejected |
| UofT PhD Economics | Waitlisted -> Withdrew |
| UofT PhD Statistics | Interviewed -> Rejected |
| UofT Rotman PhD Management | Ghosted |
| UofT PhD Mechanical and Industrial Engineering | Ghosted |
| UCLA Master of Quantitative Economics | Interviewed -> Waitlisted -> Admitted from waitlist |
| UBC MA Economics | Admitted with full funding |
| Waterloo MMath Statistics | Admitted with full funding |
| UofT MA Economics | Admitted with full funding + Scholarship |
| UofT MSc Biostatistics | Admitted |
| UofT MSc Statistics | Admitted -> Accepted! |
My final decision came down to picking between 4 offers (UofT MSc, Waterloo MMath, UCLA MQE, and UMich MS). Michigan has a very strong Biostatistics program but I was worried about the lack of funding and research opportunities + high tuition, and there isn’t any guarantee of me placing into the PhD by the end of Year 2, especially as an international student. UCLA’s MQE program has a high ROI, but it would likely pidgeonhole me into industry rather than a future in academia. I ended up staying at UofT due to its flexibility in taking electives outside of the department, elite research output (E.g. affiliation with Vector Institute), familarity with the faculty, and being able to stay in Toronto. Waterloo was a close 2nd as they offered me a very generous funding package of $27,000, and probably more if I opted into the thesis route by the end of Year 1. The tiebreaker came down to UofT’s having stronger course offerings, being able to stay close to my girlfriend, and tuition being affordable enough to cover with several TAships despite the lack of funding. I ended up pursuing Statistics as I honed in my research interests during my final semester of undergrad. I really love my field and looking back, I believe that I made the right choice.
Final Thoughts
At first, I was slightly bummed out about not being admitted to any PhD programs, but this was the best possible outcome for me. Hindsight 20/20 I just finished undergrad at the time of writing this, and my entire perspective on academia was very naive (And I’m sure it will remain so after my Master’s as well). A PhD is more than just doing well in courses, but it depends on being able to create new knowledge in a field as opposed to absorbing it. Doing a Master’s would really help me familarize myself with academic research, especially if I can get a publication or two under my belt before next cycle. I’m very happy and grateful for my offers and I’m looking forward to whatever else is on the horizon. I’m planning to reapply for PhDs during the 2026-2027 academic year, so I’ll make another blog post as an update to this.
Soli Deo Gloria