Eleri is a student on the Social Sciences with Quantitative Methods* BSc, class of 2020. She talks to us about all the possibilities of quantitative skills.
* From the 2020/21 academic year onwards, this degree has been renamed as the Social Sciences with Data Science BSc.
Hi Eleri! What made you choose your particular subject area?
This degree really drew my eye because it allowed me to study a range of social sciences and also had the quantitative element. That was really important to me because I wanted to have the training to prove that what I was saying was rigorous and applicable.
I am from Sheffield and not many people come down to London to study but it is the capital city and there are a lot of things going on here so I was excited to come. UCL is obviously a really good university, it has great rankings which was really appealing to me. UCL's Institute of Education (IOE) especially drew my attention – it has been ranked first in the world for education for six years in a row.
What have you found most valuable about your degree?
The thing I have found most valuable is probably the thing I have found most frustrating as well because it is difficult to learn: quantitative methods and the more rigorous application of statistics. I think a lot of social scientists shy away from that because they are scared of numbers or they don’t think they can do it. But actually it is really important to have an understanding of how research can be rigorous and quantitative and how that can actually support your findings and make them more viable and more accurate. Even though it is a steep learning curve it is very possible to learn the skills as long as you put in the effort and you do the reading.
In a world where we have so many different data sources and we are using things like big data and the possibilities are infinite for data analysis, the ways in which these can be applied to social problems are also endless. Employers are looking for people that have that dual mind-set – who can understand what they are looking at in terms of data and can understand what the limitations are but can also understand the more qualitative aspects, the reasoning behind it, and can also identify where the data might be flawed. I think a lot of people that just focus on quantitative methods think data is king and that everything can be explained by numbers, but anyone that does any kind of qualitative methods know that is definitely not the case.
Have you lived in UCL accommodation?
Yes I lived in Connaught Hall which is University of London hall of residence. I loved my halls experience, I wouldn’t swap it for anything! I was in catered accommodation and I found that it was really nice to come back and have your food made for you because it was one less thing to think about.
As I lived in University of London accommodation, I was living with students not just from UCL but lots of other University of London institutions. I really liked being able to interact with students from different universities because you are all going through the student experience and it broadens your circle of friends. It is a really good way of fostering community, getting to know people and having that shared experience.
What is the biggest challenge you face while studying?
I think the biggest challenge is knowing what you need to know and what is not necessary. Sometimes when you get enthusiastic about a subject, it is difficult to know where to stop. Equally when you are not so enthusiastic about a module, which will happen, it is difficult to know where you should go. I have found it useful to take notes on everything and then later on when you are doing essays or revising for exams you can look back and work out what is important and relevant. That is a really important skill and it takes time to develop. Of course in the beginning you make mistakes but eventually it becomes clearer.
Tell us what it is like to live and study in London.
It is really expensive but not in the ways I thought it would be. Students are hustlers so we get discounts everywhere we can and we are always able to find a cheap pint or a cheap night out. UCL always has events on and societies are always holding events so you can always find a way to have fun cheaply.
It is really great being able to have everything at your fingertips. When I was in Sheffield I’d see all of these events like a Guardian talk or politician giving a talk and they would always be in London out of my reach but that is not the case anymore. Now, all of these events are only 20 minutes away by tube.
“When applying for internships, especially for the roles using quantitative methods in start-ups or prestigious companies, so many of them are in London so having a base here is fantastic. It is just a really cool place to live basically.
What do you do when you’re not studying?
Last year I was really involved in the debating society. I loved the community. It really gave me some skills in terms of public speaking and developing an argument. My school didn’t do debating so it was really nice to come to UCL and be given the opportunity to try something new. I know a lot of other universities don’t offer those opportunities; unless you have debated for ten years you won’t get a look in when it comes to doing competitions but that is definitely not the case here. I took part in lots of competitions last year and I really enjoyed them. I went to the Cambridge Women’s Open, which was really fun.
What would you say to somebody thinking of applying to the IOE?
Firstly, know what you want. If you want to have a grounding in different social science disciplines and you want to be able to use quantitative evidence to support what you find and make your results more insightful then this course is definitely for you. If you are interested in developing those quantitative skills and gaining new skills that you didn’t even think were possible then this course is definitely for you. But if you are looking for a maths and statistics course with just a tiny bit of social science then this isn’t the course for you. The main emphasis here is the use of quantitative methods to support research; not doing maths for the sake of it.