A Biostatistics PhD Application Notebook [with Statement of Purpose]


Katherine Hoffman


August 14, 2023

A minor life update – I applied to Biostatistics PhD programs last fall! And, a major life update– I’m moving to Seattle to attend the University of Washington (UW)’s program next month. I’m super excited (and nervous) to begin. Since applications are opening up for next year, I thought I’d share what the process of deciding to apply, actually applying, and deciding on a program was like for me.

Background and FAQs

I was in a somewhat uncommon situation when I applied in Fall 2022 for Fall 2023 matriculation to Biostatistics PhD programs. I received my MS in Biostatistics in 2018 and have been working in academic medical research since. Because of this, I had many academic biostatistician colleagues and friends to consult about my application. Since not everyone has this opportunity, I thought I’d pass on what was told to me, especially the advice I was given on writing my statement of purpose (SOP). I found the SOP advice so helpful that I’ve publicly shared mine in this Google Doc and added advice I received in the comments.

I am by no means an expert at what biostatistics graduate programs are looking for, and this is not a comprehensive post on applying to (biostatistics) graduate school. For more general and thorough information, I recommend Lucy Lai’s post on applying to graduate programs and Simon Couch’s post on applying to statistics and biostatistics graduate programs. Nonetheless, perhaps some of you might find my experience useful, or you might be able to pass it on to a future applicant who will find it useful!

Do you need a PhD to be successful in biostatistics?

A question I’m frequently asked from students and early-career biostatisticians is whether I feel a PhD is necessary because of a “ceiling” in biostatistics. My answer was and still is: a PhD is absolutely not necessary. In fact, for a while, I was resistant to the idea of pursuing one. It’s a huge financial and personal commitment, and it’s worth carefully examining whether it’s the right decision for you, now or ever.

I wholeheartedly believe I could have been fulfilled intellectually and financially in Masters-level statistician/data science jobs forever. There are many interesting roles in both industry and academic research. Some are heavily programming related, some are much more statistics-heavy, and other roles involve supervision/management as the primary form of career progression. A (bio)statistics degree is extremely versatile because you can pivot to areas such as data engineering, software writing, data reporting/querying/interpreting, and more. There have been multiple times over the past five years that I’ve seriously considered trying out data journalism and/or data visualization roles.

However, I really love studying and teaching causal inference and statistics. Beginning around Spring 2022, I had a nagging feeling that it might be the right time in my life to deeply learn many concepts I’ve struggled to learn for years without formal coursework and training. I wanted to learn these concepts not because I particularly want to develop new methods as an academic researcher, or to make lots of money in industry, but rather because I see huge gaps in the statistical and epidemiological methods which are available and what are actually being used in applied research. I know I will feel fulfilled the rest of my career if I can work on improving these gaps, either through education, scientific communication, or mentorship.

Should you take time off before starting your PhD?

The other questions I’ve been asked are (1) whether it was intentional to take “so much time” off and/or (2) whether I’m glad I waited to go back for my PhD. My answer to the first question is that, no, it wasn’t intentional, because five years ago I was not planning to get a PhD. The second question is somewhat difficult to answer before I start my program (it might be really hard to go back to school, I have no idea!), but at the moment, I am super happy I took a break between finishing the MS and starting the PhD. I had plenty of time to narrow and pursue my interests without any pressure and while making good money. I also had the chance to learn work-life balance, which I wasn’t great at until a few years ago. I was able to build up my application through an abundance of research and teaching opportunities, and this allowed me to be a far more competitive applicant than I would’ve been out of my MS. Finally, I learned a lot about myself! I feel so much more emotionally mature and resilient than I was five years ago.

The Application Process

I’ll try to be as honest as possible about my personal experience in applying. I hope none of the information I provide deters anyone from applying to any schools because they have a different background than me. I’ve been working full-time for five years, so I necessarily have a different background than someone applying during their undergraduate or Masters degree. However, PhD programs accept many, many students directly out of undergraduate and Masters programs, so my successes and failures should not be considered to be predictive of someone else’s.

Assessing which schools to apply to

I gauged my competitiveness for applying to PhD programs by asking biostatistics faculty I knew from working in the field and/or who taught me during my MS. I also searched Reddit for relevant content (r/biostatistics) and used Gradcafe. (Be wary of anonymous forums on the internet, though!)

From these sources, I gathered that my strengths were probably:

  • having a MS in Biostatistics already
  • five years of full-time work as a biostatistical consultant
  • experience as the lead data analyst/statistician on many applied projects
  • leading some of my own research papers
  • participating in statistical methodology papers

I decided the main weakness of my application would be my lack of mathematics background. Even though I had good grades in my Biostatistics MS program, I had only the minimum math requirements to apply to that program originally (Calc I-III and linear algebra), and my Calc III and linear algebra grades were mediocre, albeit from 10 years ago.

Of note, when I read posts on GradCafe, the general consensus was that U.S. citizens (which I am) have a higher chance of being admitted to programs in the U.S. I don’t have much insight on this, but I think it has to do with funding opportunities. There are many government sponsored funding opportunities which are unfortunately only available to domestic students.

In the end, I applied to eight schools: two schools in New York City (where I currently live) and six other schools which are consistently considered to be top programs for biostatistics. Although I’m well-aware that rankings are imperfect measures of the quality of programs and there are many excellent biostatistics programs that are not top-ranked, I also knew I would only consider leaving NYC and my full-time salary for a few opportunities.

Application organization

I kept track of all my applications and notes on a Notion page. I made several tables with information about each school’s requirements and created to-do lists for various tasks (e.g. send transcripts). I also wrote out my letter of recommendation (LOR) writers’ names, emails, and titles so that I would have an easier time copying and pasting.

Application Components


All the schools I applied to required me to submit unofficial transcripts and then manually enter all relevant (science, math, statistics, etc.) coursework into their own application system. I had to enter the course name, course number, number of credits, semester I took it, and grade for each course. This is super time consuming, and I recommend beginning to work on this as soon as applications open. Many of the application portals were glitchy, and this would have been hard to complete at the last minute.

GRE Scores

My GRE scores expired a few years back, but thankfully all the schools I applied to haven’t required them since the pandemic, so I didn’t retake the test. Of note, a few schools said they required them on their website, but did not actually when I inquired with admissions. For one school I only had to self-report my old scores.

Letters of Recommendation

All schools required three LORs, and most accepted up to four or five. The people I asked to write my LORs were:

  1. A long-time colleague and mentor who could speak to my research potential for both methods and applied work. They are mid-career and known within the field of causal inference statistical estimation methods, which is what I want to continue studying.

  2. A long-time physician collaborator who I’d also worked with on applied projects for 4 years who could talk about my skill set in applied projects.

  3. My current boss, an academic epidemiologist with strong training in statistical methods. At the time I’d only worked with them for a few months, but they seemed comfortable writing about my scientific potential.

  4. (Extra letter) My former professor1 from my applied capstone course during my MS. They are late-career and well-known within the field of biostatistics. They confirmed they could speak to my discipline and aptitude for completing coursework.

  • 1 Some schools explicitly request a LOR from a former professor.

  • I think this is general LOR advice, but I only asked individuals who I was pretty sure would write strong letters on my behalf. I tried to strike a balance in people who were recognizable names within the field of biostatistics and who worked with me enough to write about me. Remember to ask your letter-writers early, as well as register early with the schools’ application systems so the writers have plenty of time to upload their letters.

    Curriculum Vitae

    All of the schools required me to submit a Curriculum Vitae (CV) document. This is the version I submitted for applications. Depending on your background, sections will look different. I recommend having someone within academia, preferably (bio)statistics or related, review your CV. If you are a student, you should also take advantage of your university’s career center resources to review.

    Additional feedback I received for this which may be relevant to someone else:

    • List out all details/roles for classes you served as Teaching Assistant.

    • List out blog posts under “Scientific Communication” and try to illustrate their impact. I’ve been blogging for years and have a Google Analytics attached to my site, so I was told to add the number of views.

    The Statement of Purpose (SOP)

    This was by far the hardest part of the application for me! There’s a lot of opinions surrounding the statement of purpose for Biostatistics PhDs, from, “it’s very important and the only way to set yourself apart to the application committee,” to, “nobody reads it and it won’t affect your application.” I opted to believe the first set of opinions and took my SOP seriously.

    I received a lot of advice on my statement. The most helpful piece of advice I received was that the SOP is not about highlighting qualifications – that’s what the CV does – and qualifications alone do not equate to success in academia. You need drive and motivation, and your SOP is the chance to show that you have it. It is more about your philosophy and research goals than stating what you’ve done so far. Every time you bring up an accomplishment, you should explain to the committee exactly why that’s relevant to your overall goal of pursuing a PhD in biostatistics. If something is not directly relevant to why you want to pursue a PhD or why you’ll be a successful researcher, you should not include it.

    I ended up receiving so much advice for this that I decided to publicly post my UW SOP on a Google Doc with comments. Some other resources I found helpful include these California State Example Essays and Lucy Lai’s Personal Statement for her Neuroscience PhD applications. These tweet threads were also useful:

    If you take only one thing away from my SOP advice: start writing your SOP early and ask at least one person who has served on an academic application committee, preferably for Biostatistics PhDs, to read your draft to make sure you’re on the right track. This is the easiest part of your application to control!

    The Personal Statement

    Only a few schools required this, and the prompts were related to why your background uniquely adds to your scientific potential. This statement is, of course, very personal to your own background! I wrote about how growing up in a rural Midwest town with my family in blue-collar jobs shaped my understanding of public health and access to education. I also wrote about my work and volunteer experience in low income areas and with underrepresented groups, and how my motivations for improving diversity in the field are driven by my experiences as an underrepresented gender in STEM. This will obviously look very different for any given applicant. I am not posting my personal statement publicly, but if you have a reason you think it’d be helpful to see my personal statement, please email me.

    Application Fees

    Almost every school had an $80-130 application fee, paid upon the time of submitting. Make sure to reach out to schools if you have any justification for receiving a fee waiver!

    Pre Application Review Service (PARS)

    I sent all my application materials in November to UW’s Pre Application Review Service (PARS) for review by current students. This is an excellent service available to underrepresented genders and minority groups. Not only was I able to get feedback on my application, but I made connections with a statistics PhD student who reviewed my application and a biostatistics PhD student who he subsequently introduced me to via email.

    Interviews and visit days

    Applications were due December 1, and I began hearing about interviews the first week of December. My first interview was mid-December (a virtual half-day). The first in-person interview was in mid-January. My last interview was late February (virtual) and in-person visit days for admitted students continued through early April. All in-person visits except for one school were fully funded. I did not attend the unfunded visit day.

    I found the interviews stressful to plan around because each was announced only a few weeks before the day(s) of the interview. I had a lot of anxiety leading up to each interview, however, the questions themselves were easy to answer (with the caveat that I’ve done many interviews and interviewed several biostatistician job candidates over the years, so I had an idea of what to expect). The questions I received were generally along the lines of:

    • Tell me about why you want to do a PhD. Why do you think you need it? What are you hoping to accomplish during and after your PhD?
    • Why [this school]? Why [city the school is located in]?
    • Tell me about a time when you had to collaborate with others to get a project done.
    • What questions do you have about our program or [location of the school]?

    For many of my answers, I reiterated (sometimes verbatim) sentences from my statement of purpose. I also brought up different research projects I’d done over the years, depending on where the conversation went. The people interviewing you are, above all, trying to assess your fit with the program. I know it is easier said than done, but my takeaway was that it was best to just let the conversation flow. The interviews were usually 30 minutes long, so make sure you have lots of questions prepared for when the interviewer flips the question-asking to you. If you run out of questions about the program, start asking the interviewer about their research or what their favorite things to do are around the university.

    Despite the interview questions feeling straightforward to me, the days were EXHAUSTING, both physically and mentally. You essentially have 8am-9pm day(s) with other applicants, students, and faculty, and you have to be “on” the entire day. This experience can be really overwhelming, so go easy on yourself. I recommend writing notes down after each interview day/visit – I kept a long running note on my phone.

    Decision time

    Of the eight schools I applied to, I interviewed at five and was accepted to five.2 My acceptances and rejections didn’t make a ton of sense to me either way, meaning I was surprised to receive certain acceptances while also receiving rejections from schools I thought I may have a higher chance of getting into. This supported a phrase I heard a lot, “PhD admissions are a bit of a black box.” There are many qualified applicants, and it is hard to discern between applicants by a CV, transcript, and a statement of purpose. Different application committee members will have biases in what they’re looking for (e.g. strong mathematics background vs. research experience) and it’s best not to dwell too much on any particular outcome.

  • 2 If you are applying and think it would be helpful to know which schools I applied to and/or what my experiences were at each, please email me.

  • It was a difficult decision for me to choose between programs. I was extremely torn over the idea of leaving the community I have in NYC. However, I could not shake the feeling that my visit to UW had felt overwhelmingly “right.” After a lot of pro-con lists, I decided to go with this gut feeling.

    The major choices which affected my decision were location, overall fit of the program/coursework, current students’ relationships within and between cohorts, perceived work-life balance of students and faculty, funding/teaching/research requirements, stipend amount, and number of faculty working on what I wanted to work on (non-parametric causal inference). After I finished my visit days, I set follow-up meetings with professors and the graduate program directors from multiple schools to make sure I understood my options correctly. I made my decision to attend UW at the end of March, about two weeks before the April 15th decision deadline.

    Miscellaneous notes

    A few miscellaneous details I learned and thoughts I had throughout the application process:

    Admission rates

    I found it difficult to find admission rates online, but the numbers given at some of my interview/admit days (if I remember correctly) were approximately:

    • 250 or so applicants
    • 15-25 interview spots
    • 7-20 spots in the cohort offered

    The final number of spots in the cohort and process for obtaining that number varied quite a bit by school. A few schools ranked candidates and could only offer a spot to the top 6-7 candidates. Once someone rejected their offer, they moved down the list to offer the next candidate. Other schools accepted a large (~20) number of applicants with the expectation that only a certain percentage would accept their offer. Finally, at least one school I applied to could only offer a fixed number of spots (12), and could not re-offer to another applicant if someone turned down their offer. That school was careful to only give offers to those they really thought might attend.


    Most Biostatistics PhD programs will only admit students if they know they can fund them, i.e. pay for tuition and a stipend, for 4-6 years. For the programs I was admitted to, the stipend offers ranged from $36-46,000 per year, pre-tax. A PhD stipend is often described as “enough to live, but not enough to save,” although this will obviously vary by the city’s cost-of-living and the student’s personal financial situation.

    I said earlier that a PhD is a huge financial commitment, and the stipend is the main reason why. Even though the amount of money might seem like a lot (it did to me when I was going through my MS degree!), the time you’ll spend earning your PhD is undoubtedly a short-term loss of potential earnings. If you have a strong quantitative background (as most Biostatistics PhD applicants do), a conservative estimate is that this loss could accumulate to over $400,000 in pre-tax income.3 This estimate is not accounting for the compounding interest you will miss out on in retirement savings (assuming you would put money towards retirement if working full-time). Although the earning potential is higher with a PhD than with an MS, it will still take some time to counteract the short-term loss.

  • 3 My calculation for this is (potential salary - stipend) * expected years in PhD.

  • On that note, if you have multiple funded offers, it is worth asking each program what their policies are regarding internships, part-time work, and freelance consulting work, because all of these are supplemental sources of income. Are any of these types of work allowed or encouraged, and does participating in them affect the stipend amount you receive (beyond potential differences in tax brackets)? The answers vary by program, and sometimes even by student due to differences in funding sources.

    Reaching out to professors in advance

    I did not email any professors before applying, so I unfortunately don’t have much to share on this topic. I doubt it would’ve helped me get into any additional programs, but who knows! It definitely has the potential to be informative and a good networking experience. Lucy Lai includes a template for reaching out to professors in her blog post, as does John Muschelli in his post, “Some things I wish I knew about Grad School”.

    Looking ahead, preparing for my PhD coursework

    UW is on the quarter system, so I’ll start classes with a cohort of eight other students at the end of September. This summer I’ve been working, enjoying life sans homework, and trying to remember all the math I’ve forgotten over the years.

    I’m refreshing myself on linear algebra using a combination of Khan Academy (I love Sal’s visualizations – I listen on 1.5-2x speed and slow down when he says something that I don’t understand) and Linear Algebra Done Right by Sheldon Axler. The latter is a small textbook which is meant to be a second learning of linear algebra (it’s quite abstract compared to the usual sequence of teaching the subject). This Github repo with solutions to Axler’s exercises is also helpful. I am also brushing up calculus using a mix of Khan Academy, random YouTube videos, and the textbook Advanced Calculus by Patrick M. Fitzpatrick. This is what I wish I would’ve done before starting my MS degree. 🙂

    If you’d like to know more about what my work looked like as an applied biostatistician in medical research, please see my Day in the Life of a Biostatistician post. I answer common email questions stemming from that post in this Follow-up post. As always, feel free to email me with questions, clarifications, or suggestions for additional resources to include.

    Until next time!



    Deciding to start a PhD program was a huge decision for me, and I am grateful to so many for encouragement and advice over the years. Thank you to my colleague Iván Díaz, who has taught me an enormous amount over the past five years and who has been instrumental in my development as a researcher. Thank you also to my former professors, especially Tom Braun for convincing me not to drop out of my Biostatistics MS program during my first semester :), and Bhramar Mukherjee for consistently vocalizing her belief in my potential. Finally, thank you to Elizabeth Sweeney, Sam Adhikari, David Lenis, Kara Rudolph, Alejandro Schuler, and Seth Temple for helpful conversations which contributed in various ways to information I’ve shared in this post.