Lessons learned & advice from a 1st year PhD Student

[Paulcg87]

I just finished the first term/semester of the first year of my political science PhD. Just a few things for next year's incoming cohort:

Learn how to code in R. Don't fight the inevitable, just learn it. 

- This is the most important advice I can give to anyone entering a PhD program next year who doesn't have a strong computer programming/coding background. In the past, users on here have emphasized how important quant methods are ad nauseam, and this is true and I don't want to take away from it. You do need to understand undergraduate algebra based statistics. You do need to know basic concepts like hypothesis testing, linear regression and p values, ordinary least squares, t-tests and average treatment effects. What you also need to know that is as important as a basic knowledge of stats is a basic knowledge of coding in the 'R' language. R is a computer coding language similar to Python but a bit more customizable and complex. It has become the gold standard for a lot of social science PhD programs. Python is also important and used more than R outside of polisci specifically so try to learn that too if you can. 

Polisci PhD students (in North America at least) are no longer doing stats on paper or in Stata or in SPSS; almost everything is being done in R. My entire first year PhD quant methods framework uses the R language, as did my master's degree quant courses. It's no longer enough to have a basic intro to stats; you need to know how to do those stats in R. If you aren't familiar yet with R or with coding in general, take an online class and download R Studio and learn how to code in R markdown and then practice applying quant analysis to sample datasets/data frames. Learn how to code functions, plots and tables. It will make the first year of your PhD so much easier. You can learn R during your first year and some in my cohort are doing that right now, but they are struggling because of the extra workload. It's enough to be dealing with all of the other pressures of the first year and the required coursework; also learning how to code from scratch simultaneously is just one extra thing that you don't need. And for those who are thinking "It's ok, I plan on doing mostly qualitative/ethnographic etc research and I don't need to know R", trust me, unless you are a theory student, you will be using R. It isn't possible anymore to avoid R or computer coding in the majority of North American polisci PhD programs if you are a non-theory student. So much of the field has moved from observational to experimental and from qualitative to quantitative that even if it isn't what you plan to do professionally, ever, you still have to learn how to do it. I think the logic is that if you're going to be competitive in applying for academic/TT jobs some day, you at least need to know enough about quant methods and coding in particular to be able to explain it to your students even if you avoid doing it yourself. 

 

Don't stress if you don't like your field(s)/subfield(s)

What most North American polisci PhD programs have in common is that you have to choose one or two fields/subfields (comparative, IR, theory, development, policy, American, etc). Some people, including myself, go into a polisci PhD sure of the field we are interested in studying and then change our minds a few weeks or months in. Sometimes it even happens after the first year. Fields are NOT set in stone when you are starting out and it's ok if you want to change. The tradeoff is that if you change fields after you start your PhD, depending on how long you wait, you could be adding an extra term or an entire extra year to your PhD that might not be funded if you received a fixed amount of funding. I, for example, received 5 years of guaranteed funding, so if I stay past that for whatever reason, I'm on my own when it comes to money. It is what it is, but don't stress about being locked into a field/subfield. Also note that changing fields/subfields within a political science PhD program is different from changing your PI/advisor/supervisor. The size, culture, funding and other attributes of your PhD program will determine how much flexibility, or lack thereof, you'll have, but nothing is usually impossible if you have a change of heart after starting. 

 

Don't stress about online education

My department/school started off this past fall semester in a hybrid with in-person and online courses and then switched to entirely online for everything once the second wave started a few months ago. Yes, online classes are not as good as in-person classes in just about every way, including networking with your cohort and in-person learning. I found it so much harder to do the weekly labs for my stats/coding course when everything went online because we were not together in the computer lab and I couldn't just ask the TA what a line of code meant in person. Personally, I'm not a fan of online education and I don't like Zoom. When we switched over to online only, one of my classes was in Zoom, one was in an Adobe program, one was in Microsoft Teams and a lab was in Blackboard Collaborate. Literally, every single one of my classes/labs used a different online learning program/method and it was very frustrating. It was a lot harder to do do these things this way, but it was not the end of the world. We got through it as a cohort, we commiserated over Zoom study sessions and on our cohort facebook page/group, and life went on. I'm happy to say that we didn't have any of the first term curriculum delayed because of COVID, and you won't either, whether everyone is vaccinated and everything is in-person in the fall of 2021 or it is still online. Hopefully it's the former, but if it's the latter, your department will make it work. 

 

If anyone who is still on here from last year is also just finishing the first term and has anything to add, please do. The single biggest piece of advice I have is to learn R as soon as possible. Even if you can't take a class on it, try some of the free online learning modules, download R Studio, use the sample datasets and start practicing with the mean function in R markdown. Also, I highly recommend one of the interactive texts we are using this year for our 3-course stats/R coding sequence, which is available in paper, PDF and Kindle formats: Kosuke Imai. Quantitative Social Science: An Introduction. Princeton: Princeton University Press, 2017. 

Edited December 21, 2020 by Paulcg87
Added QSS ref

[guest789]

I am only an applicant (in AP/methods, but I've been working in data science for years), but I agree - learn R. It's useful as a computing tool, but for applicants it also serves as signal that we know what research in political science involves. This signal is likely compounded by writing your writing sample and CV in R Markdown. If you have time and you want to learn more, start coding your own things and create R packages related to what you research. They don't have to end up on CRAN, but if they do it counts as a statistical software publication and should go on your CV. Knowledge of R should go in the technical skills section as well.

 

Edited December 21, 2020 by timeseries

[kestrel18]

8 hours ago, Paulcg87 said:

I just finished the first term/semester of the first year of my political science PhD. Just a few things for next year's incoming cohort:

Learn how to code in R. Don't fight the inevitable, just learn it. 

- This is the most important advice I can give to anyone entering a PhD program next year who doesn't have a strong computer programming/coding background. In the past, users on here have emphasized how important quant methods are ad nauseam, and this is true and I don't want to take away from it. You do need to understand undergraduate algebra based statistics. You do need to know basic concepts like hypothesis testing, linear regression and p values, ordinary least squares, t-tests and average treatment effects. What you also need to know that is as important as a basic knowledge of stats is a basic knowledge of coding in the 'R' language. R is a computer coding language similar to Python but a bit more customizable and complex. It has become the gold standard for a lot of social science PhD programs. Python is also important and used more than R outside of polisci specifically so try to learn that too if you can. 

Polisci PhD students (in North America at least) are no longer doing stats on paper or in Stata or in SPSS; almost everything is being done in R. My entire first year PhD quant methods framework uses the R language, as did my master's degree quant courses. It's no longer enough to have a basic intro to stats; you need to know how to do those stats in R. If you aren't familiar yet with R or with coding in general, take an online class and download R Studio and learn how to code in R markdown and then practice applying quant analysis to sample datasets/data frames. Learn how to code functions, plots and tables. It will make the first year of your PhD so much easier. You can learn R during your first year and some in my cohort are doing that right now, but they are struggling because of the extra workload. It's enough to be dealing with all of the other pressures of the first year and the required coursework; also learning how to code from scratch simultaneously is just one extra thing that you don't need. And for those who are thinking "It's ok, I plan on doing mostly qualitative/ethnographic etc research and I don't need to know R", trust me, unless you are a theory student, you will be using R. It isn't possible anymore to avoid R or computer coding in the majority of North American polisci PhD programs if you are a non-theory student. So much of the field has moved from observational to experimental and from qualitative to quantitative that even if it isn't what you plan to do professionally, ever, you still have to learn how to do it. I think the logic is that if you're going to be competitive in applying for academic/TT jobs some day, you at least need to know enough about quant methods and coding in particular to be able to explain it to your students even if you avoid doing it yourself. 

 

Don't stress if you don't like your field(s)/subfield(s)

What most North American polisci PhD programs have in common is that you have to choose one or two fields/subfields (comparative, IR, theory, development, policy, American, etc). Some people, including myself, go into a polisci PhD sure of the field we are interested in studying and then change our minds a few weeks or months in. Sometimes it even happens after the first year. Fields are NOT set in stone when you are starting out and it's ok if you want to change. The tradeoff is that if you change fields after you start your PhD, depending on how long you wait, you could be adding an extra term or an entire extra year to your PhD that might not be funded if you received a fixed amount of funding. I, for example, received 5 years of guaranteed funding, so if I stay past that for whatever reason, I'm on my own when it comes to money. It is what it is, but don't stress about being locked into a field/subfield. Also note that changing fields/subfields within a political science PhD program is different from changing your PI/advisor/supervisor. The size, culture, funding and other attributes of your PhD program will determine how much flexibility, or lack thereof, you'll have, but nothing is usually impossible if you have a change of heart after starting. 

 

Don't stress about online education

My department/school started off this past fall semester in a hybrid with in-person and online courses and then switched to entirely online for everything once the second wave started a few months ago. Yes, online classes are not as good as in-person classes in just about every way, including networking with your cohort and in-person learning. I found it so much harder to do the weekly labs for my stats/coding course when everything went online because we were not together in the computer lab and I couldn't just ask the TA what a line of code meant in person. Personally, I'm not a fan of online education and I don't like Zoom. When we switched over to online only, one of my classes was in Zoom, one was in an Adobe program, one was in Microsoft Teams and a lab was in Blackboard Collaborate. Literally, every single one of my classes/labs used a different online learning program/method and it was very frustrating. It was a lot harder to do do these things this way, but it was not the end of the world. We got through it as a cohort, we commiserated over Zoom study sessions and on our cohort facebook page/group, and life went on. I'm happy to say that we didn't have any of the first term curriculum delayed because of COVID, and you won't either, whether everyone is vaccinated and everything is in-person in the fall of 2021 or it is still online. Hopefully it's the former, but if it's the latter, your department will make it work. 

 

If anyone who is still on here from last year is also just finishing the first term and has anything to add, please do. The single biggest piece of advice I have is to learn R as soon as possible. Even if you can't take a class on it, try some of the free online learning modules, download R Studio, use the sample datasets and start practicing with the mean function in R markdown. Also, I highly recommend one of the interactive texts we are using this year for our 3-course stats/R coding sequence, which is available in paper, PDF and Kindle formats: Kosuke Imai. Quantitative Social Science: An Introduction. Princeton: Princeton University Press, 2017. 

Good advice! 
And yeah...-R is a really cool research tool!
I would also mention some knowledge about random variables distributions (e.g., Poisson, Bernoulli) would make life much easier at the end of the semester

[Muan1]

Theory students be reading this like, yeah uhuh.

[guest789]

14 hours ago, Muan1 said:

Theory students be reading this like, yeah uhuh.

I don't know how this works across all departments, but don't political theory students, in general, take the core methods sequence along with the other students in their cohort?

[Theory007]

1 hour ago, timeseries said:

I don't know how this works across all departments, but don't political theory students, in general, take the core methods sequence along with the other students in their cohort?

It depends on the department. Some places require theory students to go through the entire methods sequence and others do not have any requirement like that.

[politolog]

I just finished my first semester as well, and I agree with the OP. I'd recommend Siegel and Moore's A Mathematics Course for Political and Social Research for those looking to brush up on their math skills. It helped me make it through the first course in my department's methods sequence. 

[Theoryboi]

8 hours ago, timeseries said:

I don't know how this works across all departments, but don't political theory students, in general, take the core methods sequence along with the other students in their cohort?

1st-year Theory/IR PhD student here: no quant for me.

 

My advice for theory folks is: 1. get ready to read 2. pre-reading before you start is a great idea 3. Even if you think you have a really strong base in theory going in, you probably don't. Most of my theory cohort came in super ill-prepared and it showed.

[kestrel18]

At the end of the first semester, I'm feeling like a coalminer returning to the surface...-It has been so exhausting! 

[needanoffersobad]

Great advice! Thanks! May I ask if you wanna share how is the interaction with faculty and your cohort? Do u find it sufficient? As I am taking a gap year (deferment), I am concerning whether we will have “normal” conversations with professors. Cuz I currently work as RA and talk with people on zoom. I find conversation on zoom is extremely short. Many thanks! 

[Paulcg87]

On 12/23/2020 at 9:09 PM, needanoffersobad said:

Great advice! Thanks! May I ask if you wanna share how is the interaction with faculty and your cohort? Do u find it sufficient? As I am taking a gap year (deferment), I am concerning whether we will have “normal” conversations with professors. Cuz I currently work as RA and talk with people on zoom. I find conversation on zoom is extremely short. Many thanks! 

@needanoffersobad Not going to lie, it's tough being relegated to Zoom. Especially office hours and feeling like everything takes longer (including lab questions) when we are trying to do it over Zoom. With that said, my cohort had the advantage of (mostly) being together in person when classes started since we had in-person classes at the beginning of the term that switched over to online only once the second wave got bad, so many of us had met each other in person before we were forced to go online. Some schools/departments weren't so lucky.

I think the answer to your question really depends on your life situation right now. The interaction is sufficient enough for me, but I'm also a bit older and I've got a lot of competing time demands from outside of school so my time is already taken up with my partner or visiting family/friends rather than going to the pub with classmates or spending extra time with faculty. My cohort is fairly large and consists of people everywhere in life from straight out of undergrad (direct entry PhD, without even a masters) and just 22 years old, to a few students in their 40's and quite a few like me who are in between those two extremes (a few years work experience, a master's degree, in many cases a spouse/partner and in some cases kids). I think it's harder for the foreign students and the younger students because they have different needs than those of us who are a bit older and have more going on outside of school. 

 

On 12/22/2020 at 2:05 PM, timeseries said:

I don't know how this works across all departments, but don't political theory students, in general, take the core methods sequence along with the other students in their cohort?

@timeseries I think @Theory007 already answered this but in terms of my program/department, we do not require theory students to take anything quant but they are of course allowed to take our 3-course quant sequence if they would like to, as electives. Quant is purely optional for theory students but it is required for all other fields (development, IR, comparative, American, public policy). I'm in a larger political science department with a separate master's degree program and about 30 students in my 1st year PhD cohort and none of the theory students elected to take quant this fall with the rest of us. 

 

On 12/23/2020 at 5:01 PM, kestrel18 said:

At the end of the first semester, I'm feeling like a coalminer returning to the surface...-It has been so exhausting! 

@kestrel18 +1. For my specific program, I took three of the hardest courses this past fall all at once to get it out of the way. I kind of regret the effects this will have on my GPA when it is posted in January; I might have bitten off more than I could chew. But, as one of my professors said this fall, "you're PhD students. Grades no longer matter". Not entirely true because they do matter for fellowships and post docs, but they sure do matter a lot less to me now than when I was getting a masters degree and still had another degree program I had to apply to! 

 

On 12/22/2020 at 10:43 PM, Theoryboi said:

1st-year Theory/IR PhD student here: no quant for me.

 

My advice for theory folks is: 1. get ready to read 2. pre-reading before you start is a great idea 3. Even if you think you have a really strong base in theory going in, you probably don't. Most of my theory cohort came in super ill-prepared and it showed.

Great advice @Theoryboi. I am not theory for either of my fields but theory transcends every single field of polisci in my opinion. Even my non-theory (non-quant) core courses this fall went into theory in such depth and it was a struggle. And I have to say, the first year of the PhD was infinitely more difficult than my master's degree; significantly more reading than my master's in polisc and pressure from the department to start preparing for the thesis proposal pretty much from day one. 

[gradpumpkin]

Thank you all for this great advice! I'm wondering if any of you could comment on what the typical schedule, workload, and "day in the life" would be for a first-year PhD student. I know it will vary a lot based on programs/fellowships, but just trying to get a general idea and advice on how to manage it as best as possible. 

[Theoryboi]

On 12/26/2020 at 9:37 AM, gradpumpkin said:

Thank you all for this great advice! I'm wondering if any of you could comment on what the typical schedule, workload, and "day in the life" would be for a first-year PhD student. I know it will vary a lot based on programs/fellowships, but just trying to get a general idea and advice on how to manage it as best as possible. 

I think my schedule was maybe a bit unorthodox compared to what others have experienced, but I will share anyways. As part of my program I am employed as an instructor of record for an undergraduate class (meaning I am THE instructor, not an assistant). So I taught an IR class twice a week for an hour and fifteen minutes each session, and had 3 graduate classes which were once a week for two hours and fifty minutes, also this of course involved prep time, grading, etc. Teaching was awesome and my students really helped keep my spirits up as the semester wore on. I don't think most programs will involve this sort of work, particularly in the first semester, so it probably won't apply to many reading this post. 

Basically, like I said above, I had to do a ton of reading week in and week out as we would expect for a PhD program. One class, on Theory, mandated we read at least one book a week, sometimes two. Another, a security studies class, involved one book with a few related articles a week. The third, a methods class, was more like 4-5 articles a week. The first class I mentioned also mandated a short paper be written every week (750-1000 words) on the book(s) we read. Otherwise, there were not really week-to-week assignments for the other two classes, though they each had a presentation at one point in the semester. Two classes had book review essays (about 2000 words each), and Final papers ranged from 4000 words in one case and two called for 6000 words. 

Of course, much of this occurred online, so I was mostly isolated in my room. On a non-work note, but related to the day-to-day, I found it difficult to connect with people generally speaking, and I wouldn't say this is for lack of social grace, but rather just the Covid situation really complicating things. I have one close friend from my cohort and we made it a point to hangout once a week so we had some form of human interaction. Hopefully for those reading, this will be less of a concern by the time you start your programs. So there isn't a great sense of cohort comradery at the moment, but hopefully that will improve as time goes on and conditions improve.

I found I had great flexibility with my schedule overall, as I had no obligations on Fridays generally speaking. Still, I was working pretty much seven days a week, and only took a few full days off here and there. I know many of my colleagues felt very overwhelmed by the workload/schedule demands, though I can say I was able to manage it well enough. As others have said, my experience was more demanding overall than during my masters work, and it was both the most challenging, yet rewarding semester of school I have experienced. But, the stakes are high: my cohort has already had one drop out and it remains an open question if one or two others will return after winter break, so I don't know if I had the typical case of people, even in my own program. So, if your number gets called, don't take the opportunity lightly! When it gets tough I always remind myself how many people would love to have the opportunity and the funding I am fortunate to have. Maybe that thought can help when things inevitably get tough; after all if a PhD was easy, why would we all covet it as such? 

 

[sloth_girl]

On 12/26/2020 at 9:37 AM, gradpumpkin said:

Thank you all for this great advice! I'm wondering if any of you could comment on what the typical schedule, workload, and "day in the life" would be for a first-year PhD student. I know it will vary a lot based on programs/fellowships, but just trying to get a general idea and advice on how to manage it as best as possible. 

I was pretty busy (though I do have 2 kids!). My schedule itself was fairly flexible in what exactly I had to be doing at a specific time of day (other than classes, office hours, etc.), but it was still pretty busy. My program front loads a lot (not all do this), and I was taking two substantive field (CP & AP) as well as Methods and a required social science research course, so we're pretty busy this year. For a lot of weeks, I pulled one all-nighter (or ran on 3-4 hours of sleep) per week getting my reading/Methods homework done.

For me, Zoom was really, really tough. We've got two kids + my working spouse in the background all the time, so I constantly was getting interrupted and distracted. I still managed to do pretty well, but I can't wait to have an actual school/learning space and office. I think if I had that, I wouldn't have had to pull so many late nights!

I knew a good amount of R before, though of course debugging can take a bit regardless. I'm also a bit of a perfectionist ;). Definitely brush up on this! I also wish I'd brushed up on my math skills beforehand, but the pandemic changed a lot of my plans. Math Camp was like drinking out of a fire house. 

I also tried to make time to work on some projects in the pipeline -- better to start on publications earlier rather than later! 

This year is really weird (obviously), so keep that in mind. But overall, it's a really, really busy time, but very rewarding!

[Paulcg87]

41 minutes ago, sloth_girl said:

I knew a good amount of R before, though of course debugging can take a bit regardless. I'm also a bit of a perfectionist ;). Definitely brush up on this! I also wish I'd brushed up on my math skills beforehand, but the pandemic changed a lot of my plans. Math Camp was like drinking out of a fire house. 

Same. Our pre-fall math camp was called "Data Analysis Bootcamp" and it was pretty much designed for people who already have a math background so if you don't, spend the summer before your first year doing a stats review. Seriously. I did my master's in a quant heavy program and I was a little shocked to find calculus and linear algebra in our basic intro "Statistics for Political Scientists" course last fall. The level and complexity of the math will depend heavily on your department/instructor but polisci is trending more data/quant intensive (for every subfield besides theory), not less. Can't emphasize enough how important math and R are these days at the PhD level if you're doing AP, CP, IR and/or public policy. 

[icemanyeo]

Thank you to everyone who shared on the thread -- I truly appreciate it!

[icemanyeo]

Also, thank you to those who recommended some prep texts, those were really helpful. I know quite a bit of Java and MySQL but have yet to learn R. Do you have any specific courses/books you recommend for that as well?

[Barry B. Benson]

I'm an applicant too, but I really like Hadley Wickham's R for Data Science (https://r4ds.had.co.nz/) and Urdinez & Cruz's R for Political Data Science (https://www.routledge.com/R-for-Political-Data-Science-A-Practical-Guide/Urdinez-Cruz/p/book/9780367818890)

Hope it helps!

[icemanyeo]

15 hours ago, Barry B. Benson said:

I'm an applicant too, but I really like Hadley Wickham's R for Data Science (https://r4ds.had.co.nz/) and Urdinez & Cruz's R for Political Data Science (https://www.routledge.com/R-for-Political-Data-Science-A-Practical-Guide/Urdinez-Cruz/p/book/9780367818890)

Hope it helps!

Thanks!