Stats Students: My R top tips!
If you’re interested in an degree within Statistics, especially at Warwick, then you’ll probably become familiar with R. R is a programming language used particularly within Data Science and Applied Statistics.
Currently all first year Statisticians at Warwick take compulsory modules which have assignments based in R. Like any kind of code, getting familiar with the language is a learning curve. After 4 years familiarising myself with R, I’m ready to share my tips and experiences.
Do some *free* courses!
DataCamp is an online Data Science learning platform and has great online courses for all types of coding languages including R and Python. I used it over the summer and really liked the style of learning. You can choose a specific area of R to learn about, from beginners courses to more experienced areas. After completing courses you receive certificates which you can use for your CV or LinkedIn.
Like most learning platforms, there’s a paywall for most courses BUT if you sign up for GitHub Education you can get 3 months of DataCamp for FREE! Can you tell I’m excited to tell you that?
GitHub is a cloud based git repository allowing people to work on code together wherever you are. GitHub Education is a platform to access tools and events to support your coding journey and it’s free – all you need is to be at least 13 and have an education based email.
GitHub Education: https://education.github.com/students
DataCamp with GitHub Education: https://www.datacamp.com/github-students
Google is your friend
When you have a problem with R it’s likely that someone else has too. Whenever I am really stuck on some code I google it. I usually head to Mathematics Stack Exchange (a mathematics forum) to see if anyone in the community has had a similar problem.
However, as my lecturers say, some techniques used online may have subtleties which make it unusable for your situation. Therefore, I would suggest sticking to lecture notes for your assignment techniques. On the other hand for small fixes Google is great.
Run parts of your code
Especially when you are creating functions which have multiple layers of code, if the whole function does not seem to run try running each line separately. This could help pin down the error-causing line which saves time. It can also make sure the other lines are running as expected.
Write it down on paper first
When you are creating functions, like a function to write a number in binary, your task can initially seem overwhelming. Try writing down your method by hand first so you really know what you want to do. Then convert each step into a line of code.
Do some R Courses at Warwick
Currently both the Warwick Statistics Society and Warwick Data Science Society run R courses to support you with modules or just to help you gain extra know how. Having completed both R courses on offer I would really recommend them. The training is quite flexible and it’s a cool way to meet other students with similar interests too. I would recommend keeping up with the societies Social Medias for more information.
In fact, Warwick Data Science Society have all their course materials freely available on their website so you can even check out their courses now: https://education.wdss.io/
Don’t get frustrated
Like anything, R may not come easy. Friends and I still joke about my tutor’s frustrated remarks on my first R assignment and safe to say, 4 modules in, I am slowly getting the hang of it. If you have time in the Summer I would certainly recommend downloading R and having a play with it. Like any language it’ll take a while to get comfortable with, it’s safe to say you’ll probably be using it more than you think you will.
If you’d like more information about downloading R and RStudio see this useful page: https://rstudio-education.github.io/hopr/starting.html
