R for data analytics has been a tool I’ve been keen to learn since my first year here at Srishti. Having been aware of the power that language holds for computing and mining through large volumes of data has always interested me to know more about it. Even the general aspect of visualising quantitative data to see up front how our study is behaving says a lot more than going through numbers and making sense of them. Visual language is more implicit to us all. But even to draw inferences and insights the real question that arises is, where is the proof? Where is the data?

Perhaps that was why I chose to sign up for this course, my assumption behind taking this up was to learn how things around data analysis work. However, the class offered a large variety of tools and approaches to both collect and analyse data. Frequency and thematic analysis was an interesting take on observing the relevance of themes in our broader problem. Anything and everything that adds to understanding a problem before thinking about its solution fascinates me. There were times it felt like an information overload, because I wasn’t able to make direct connections between the methods prescribed and their relevance with my own project’s dataset. I feel like the class was a great head start towards being open to finding information and backing our thoughts and ideas. It gives us the power to prove things right and wrong, and I think that’s valuable and applicable for everything I do. This class has given me a new perspective to look at research studies and it seems to have met its goal for me.