- Careers & Employability
- Politics and International Studies
- Preparing for University
- Social Studies
Social Analytics: A Review
When selecting optional modules for your course, it is always difficult and you often wonder if the outlines and information provided on the website equivalate those in real life. Thus, for the benefit of many of you under the social sciences faculty and specifically those of you who are studying Sociology or Politics and International Studies, I have decided to construct a review of the Social Analytics course – or what is better known as QS104. Our final results regarding this module have been recently released and while I alongside many of my friends were fortunate enough to secure a first, I thought it would prove to be interesting to review what this module was like as a whole since it was the first official module I have completed at University.
As a Politics and International Studies student, Social Analytics was not a core module; hence, it is referred to under my first year as an optional module. I decided to select this module because despite the inclusion of mathematics in it, the module director had assured me that this was not demanded at an excessively challenging degree and was in short ‘doable’. Moreover, he also stressed how gaining data interpretation and analysing skills will inevitably prove to be beneficial in the long run as it is currently demanded by many employers. Now that I have completed and received feedback for this module, I can confidently conclude that I highly recommend it!
I would be lying if I said this module was easy; indeed, there were moments where I found myself questioning if I could transfer to another module, but after having completed the exam, I was very glad I did not do so. I was very shocked on the first day of the lecture when we were told we needed to purchase a calculator as I didn’t think this was something I would ever have to do as a politics student. But, the module and exam have been constructed in a way that provides us with equations which therefore means that we are not required to remember any complicated math equations. As I look back and reflect on the module’s description on the Warwick website, I can with high confidence say that this module has helped me understand the importance of conceptualisation and measurement in conducting quantitative research; understand basic elements of core descriptive statistics; conduct basic quantitative analysis using secondary survey data, and begin to critically engage with quantitative findings in social science journal articles.
Additionally, the one hour of lecture a week entwined with the 2 hours of seminar time per week grants us with flexibility and ensures that our schedule is not too demanding, allowing us to focus on self-study and reflection. However, just like every other course in Warwick, Social Analytics is what you make of it – I strongly believe that there is no such thing as an ‘easy’ course and that if you continue to put in the hard work and dedication to your modules, results will accordingly follow.
In conclusion, I cannot deny that I have learned essential and transferable skills from this module and therefore would highly recommend it to all those considering it!