Skills You Can Work On if Skipping the 2021 Cycle

[THS]

I know that the pandemic has really messed things up for a lot of you. Your dream program might have cancelled admissions this year or you are looking at an even more competitive market because there will be fewer programs accepting students. This might mean that you choose to take this year off and wait to apply next year OR that you want improve your skills and increase your chances of success in a program. I am writing this post to suggest skills you can develop on your own, without being in a program, but that will make your life better when you get there if you learn them beforehand.  They will also make you more attractive to programs that expect their students enter with certain kinds of skills/knowledge. 

The first thing you should do is learn to use R. If you don't know where to start a really good textbook is Discovering Stats Using R by Field, Miles, and Field. This text is great because it will give you a refresh on your stats knowledge and will teach you to use a free stats program. The learning curve for it is pretty big, you have to learn to speak its language- but if you can teach yourself how to use this your life will be so much easier later. A lot of people might say that learning R first is a bad idea, but if you learn to use R then using state, SPSS, or SAS later is a breeze. Plus the R community is amazing and there are so many free tutorials out in the world if the book is confusing. 

The second skill you can develop on your own is practice regression models (learning the code to run them, to interpret them, learning what you use various types of models for...). This is super important if you want to be a qualitative person. What? You might be asking. Yes, I am serious. Many programs will expect you to be competent in every method so going in knowing how to do quant work will mean less push back for your qual dreams. There are lots of textbooks you can use, my program uses Regression Models by Example by Chatterjee and Hadi. But anyone can teach themselves to do this as well. Download free data (CPS is pretty easy to work with if you are just starting out) and play. 

The third skill you can develop on your own is the ability to use python. There are lots of online programs that my peers have used to learn this skill (I, honestly, have not). I do know that as you progress in your quant skills that eventually this becomes something you'll want to know how to use. I work with survey data/not crazy huge datasets so I've been able to avoid it, but this might be something to think about. 

A lot of posts on here suggest doing things like learning theory, but from my experience you have no idea what theory will be covered in the program you end up accepted to. You could spend an entire semester learning Talcott Parsons or you could get a general overview or you might just cover Marx/Weber/Durkheim. My point there is I wouldn't bother. I would download as many pdfs of peer reviewed research articles on the area you are interested in writing your thesis on NOW while you still have access to your undergrad institution and to start building a literature review. Make sure to do specific searches of major journals (AJS, ASR...) If you don't have access get your hands on as many "free" sources as possible and make it your goal to read at least a couple books in your interest area. Make sure to save the citation information, the gist of the article, and any quotes you think you might later use (I do this in excel spreadsheets). Even just saving them to a PDF is a good starting place though. This will help you when you finally do get to that point in your career. Your interests might change, but it never hurts to have a solid lit review started. You will be able to pull from that for class papers if you don't use it for your thesis someday. 

I know that not being able to apply is going to be super stressful for many of you and that it will probably mean working a job during this time which is why I gave a list but with varying levels of commitment or time attached to the tasks. I'd suggest doing ANY of these things- but if you don't do anything that is ok too. We are living through a global pandemic and it is ok to not be ok. The thought here is that these are good ways to build on your skills while you figure things out (let's be real knowing how to do statistics or use python are great skills to have on a resume anyways anymore).

I am so sorry this is happening to everyone who is at this point in your grad school journey, I login to this site like idk every 4 or so months so if you DM me I won't answer for a while, but I promise I will eventually reply if you have any questions about what grad school is like or about how to go about any of these suggestions I have made. I did this because after advising a student from my summer class I realized that she is far from the only person thinking "what now" so I hope this helps. 

A side note: obviously polishing your application materials will help too. An extra year to craft the perfect letter of intent might be a blessing for someone who is still wrapping up their BA. 

Also I hope other current grad students share their insights. I am ABD in my program and nearly done so people earlier in the process might remember some things I don't or have insights from their programs or other books to recommend

Edited August 16, 2020 by loves2hike
Call for more people to suggest.

[whooshboosh]

I'd like to add to, second, and comments on a few points loves2hike made. 

1. Learning R is hard. If you have the opportunity to learn Stata or SPSS first, you should do it. They'll help you understand the process of coding and computerized analysis and are far easier to learn. That said, they're far more expensive than R, which is free. When you do get to R, take your time with it. The best advice I've seen is to only learn a few things at a time. These can be regression, management, visualization, or even just finding the mean of a variable, but there is too much possible for any one person to learn, especially starting out. Learn one thing well and everything else will follow. The key is to know enough for your basic work and then learn how to search for the answer to your questions that will come up. (And don't be afraid to ask the internet for help. Everybody has questions about R.)

2. I agree with practicing regressions, especially if you aren't great at them. That said, you'll have stats classes your first two years that will teach you everything, so this isn't your priority. UCLA IDRE's website (https://stats.idre.ucla.edu/) has a ton of resources on how to run and interpret various models on different software. It's free and a great place to turn when you have questions.

3. Python is up and coming within sociology. If you learn it, great! If not, you won't be missing out on much UNLESS you want to use computational methods.  R and Stata are still the workhorse programs for quant analysis, so it's more important to get good at these first.

4. I wholeheartedly agree with not reading theory outside of a course. It's dry, boring, and complex. Instead, read more exciting sociology that will exercise your sociological imagination and make your life easier. University presses will usually have a huge discount this time of year, and you may even be able to get some books from your library, either university or local. Journal articles are also great places to start, but they can also be pretty dry and typically have a very narrow scope.