Priya Nair

Um, okay. So I think it started with cricket, actually. I was watching a match and the commentator said some bowler had a really good average, and I thought, wait, how do they even calculate that, and what does it really tell you? So I started looking at the numbers, and then I realised maths was the thing that made the numbers make sense.

Hmm. I think they work with messy data, like, a lot of it, and they clean it first, because it's never clean. Then they build models to find patterns, and then they have to explain the results to people who are not mathematicians. I think that last part is important, but I'm not totally sure how it works in real jobs yet.

Okay, yes. For my blog I wanted to know if strike rate at the death overs was actually more useful than economy rate for predicting who wins. So I pulled about four seasons of match data, and I had to fix a lot of missing entries first. I ran a simple regression, and the result was kind of surprising, so I wrote a whole post about why, and I think that was my favourite thing I did.

So besides the blog, I run the math circle at my school. We meet every week and we do problem sets, but also like, small projects. Last term we did a project on probability in board games, which was honestly a lot of fun, even though some people got bored with it.

Honestly, getting people to show their working. Some students just want the answer, and they skip the reasoning. So I started asking everyone to explain their method out loud, and at first it was awkward, like really awkward, but after a few weeks people got better at it.

Um, a few reasons. It's a research university, and I like that the work is connected to real problems, not only theory. Also it's in Abu Dhabi, which is a place I've never been, so that's exciting for me. I also want to be somewhere that has a diverse group of students, and I think that matters for data science too.

Yes, okay. In my school, the maths department didn't have any data analysis course, so I wrote a proposal for a short workshop on Python for statistics. Nobody asked me to. I was nervous to present it to the teachers, because I thought they would say no, but they said yes.

It went okay, I think. Only about eight people came the first time, and my code had a bug in the first session, which was embarrassing. But by the end, a few of them were making their own small projects. What I learned is that I should check my examples before the session, not during it.

Hmm, yeah. I think I'm a bit of a perfectionist, which can be good, but also I spend too much time on small details. I'm working on that. I just want the committee to know that I really care about getting things right, and I'm willing to keep learning.