top of page
Writer's pictureAila Bandagi

I suck at math, but I love data



I am dyscalculic. I cannot read and analogue watch, I cannot catch a ball if you throw it at me (I might, by fluke). And obviously, I suck at mathematics. I don't remember if I was always bad at it or I became bad over time. I do know that I never learnt the multiplication table, I made the stupidest dumbest mistakes in exams (thank you ICSE for having marks for the process!), and while I can roughly figure out what 50% off on 1799 means, if it's 40% off, I will not even try the dress!


My condition was so bad that for my undergrad first year math exam (yes, liberal arts has math and science as mandatory subjects), I sat outside the exam hall, crying, having a panic attack so bad that I could not breathe. My math teacher got to know about my little incident, and half way through the exam, she walked into the room and added a 20 mark question to the exam paper - “Should math be a mandatory subject at the high school level? Discuss


My fear of math is very visible to everyone in my life. I never hid it. Even though I know that there is a reason why I cannot do math (finally identified by my psychology teacher in 2nd year of college), I never got over my fear of the subject. I studied social sciences, so of course after the first year, I did not have to do math. But come third year of college, we started statistics and quantitative research. I was preparing for my usual anxiety and fear, but it never came. On the contrary, I was fascinated by this world of numbers. Maybe it was the amazing math teacher who taught me that there was more to math than calculation, or maybe it was that I had stayed away from the subject long enough to see it in a different light, I don't know, and frankly, I did not care.


I actually ended up doing a mixed methods research (using primary data collection and analysis) for my masters thesis. I collected and analysed primary quantitative data across all the central prisons in Telangana for a project, using stata. I also went on to work as a data journalist, fact checking BJP government claims during the 2019 elections. I was never great at any of these. My guide helped me immensely during my thesis, a colleague guided me on how to use stata for big data analysis, and I had the most amazing editor and boss when I was writing fact check articles. I made a lot of mistakes, silly ones sometimes and big ones some times. But for some reason, I never gave up. Because I felt an unexplainable joy every time I saw a pattern in the data or found an explanation for a correlation.


In my last job however, my mistakes were not tolerated, I was told by my boss that “knowing a software does not mean you know data.” My manager told me “If you are making so many mistakes, then maybe you should not pursue it.” My colleagues expected perfection and I had no guidance or mentorship of any kind. So I gave up on everything ‘data’ and took myself off projects that I really wanted to work on. I could never be perfect when it comes to data and I knew it. I needed excel to do the calculations for me and I needed computer generated graphs to find the patterns for me. Numbers would not automatically make sense to me, they never did and they never will.


It's been months now since I have touched anything to do with quantitative data. I have not opened an excel sheet or imported it into stata or Q-GIS, in months. When I was asked to write a piece that involved data analysis, I told them, I will do the qualitative part but that they have to get someone else to deal with the numbers. I met a data analyst who argued that gender need not be a variable, in some cases, and I did not say a word.


I never claimed to be an expert on data, just that I know a little bit and that I enjoyed dealing with it. It gave me a sense of power because I could prove to myself that even someone as bad at math as me, can deal with numbers. I knew the power of data in advocacy and planning and I wanted to use it to build a better world. Unfortunately I let it all go in response to something someone said.


Today someone asked me if I could help with some data analysis and I almost said no again.

The thing is, these people who know math, the ones who see numbers as their friends are not question data the way someone like me (dumb enough not to understand it) will. These people are claiming that 90% of the women in Indian cities depend on sustainable modes of transportation while they fully know that mobility data is only collected for those who work outside the house and travel for more than 500 meters on a daily basis. They also know that 87% of these women report that they do not travel outside the house at all, but they chose to ignore these points (or maybe they don't think it matters). In a world manipulating and misunderstanding and wrongly analysing data to prove selective interests right, isn't it the responsibility of those of us who do understand these problems, to try and fix it? Even though we might not be great at it!


I am not good at analysing or visualising or mining data but I am going to keep working on it. Because those who are really good at analysing, visualising and mining data are leaving me and people like out of data all together. You only need to look at how much data exists on women’s issues in the global south and how good that data is to know that I am right. So I am deciding today to take up the data project. I will find the right mentors and reviewers and editors and guides to help me through it, but I won't give up, because we deserve better data systems. If I fail, I will take solace knowing that I at least started a conversation.


27 views0 comments

Recent Posts

See All

Comments


bottom of page