Econometrics Operations Research and Actuarial Studies postgraduate personal statement example

Personal statement example

Every Saturday from May to September I sit in a wooden hut beside a village cricket pitch with a pencil and a scorebook. Scoring is unglamorous work, but it taught me early that a column of numbers is a record of decisions: when a captain changes the bowling, the run rate moves, and the book shows whether the decision paid off. I started keeping simple spreadsheets of our club's seasons, comparing averages that rested on very different numbers of innings, and my curiosity about how much a small sample can honestly tell you has followed me through my degree.

I have just completed a BSc in Mathematics with a 2:1. My strongest modules were probability, linear algebra and a second-year course in statistical inference, where I first worked properly with maximum likelihood estimation and saw how confidence intervals depend on the assumptions behind a model. A final-year optimisation module introduced linear programming and the simplex method, and I enjoyed the shift from describing data to choosing the best action under constraints. That combination, of estimating something uncertain and then deciding what to do about it, is why a programme spanning econometrics, operations research and actuarial science appeals to me more than a narrower course.

My final-year project studied the phone line of a medium-sized GP surgery, using an anonymised summary of call volumes by half-hour period that the practice manager agreed to share. I modelled the line as an M/M/c queue and calculated expected waiting times for different numbers of receptionists. The Poisson arrival assumption looked reasonable within short intervals but clearly failed across the morning, when demand rose sharply at opening. I therefore wrote a discrete-event simulation in Python with time-varying arrival rates and compared its results with the analytical formulas. The simulation suggested that moving one receptionist's break by forty minutes would cut average morning waits more than adding staff in the afternoon. I was careful to present this as a scenario rather than a recommendation, because I had no data on call abandonment, but the practice manager found the comparison useful, and I learned how much modelling depends on knowing which assumptions to relax.

Alongside my studies I have worked for three years at a local cinema, where I am now a shift supervisor. Part of my role is building weekly staff rotas around students' availability, expected ticket sales and legal break requirements. It is a small, practical scheduling problem, and I have come to appreciate how often the hardest constraints are human rather than mathematical. Supervising has also made me calmer when things go wrong on a busy Friday evening, and better at explaining a decision clearly to colleagues who did not make it.

Outside the degree I have worked through parts of Wooldridge's Introductory Econometrics, particularly the chapters on omitted variable bias and heteroskedasticity, because my own coursework had not covered regression with observational data in depth. I also completed an online introduction to R so that I am not reliant on a single programming language. I recognise that my economics background is thinner than my mathematics, and I expect to work hard on that side in the early months.

At postgraduate level I want to build rigorous foundations across all three areas before choosing a specialism. I am currently drawn towards operations research applied to health and public services, but I am interested in actuarial modelling of risk and would welcome the chance to test that interest properly. I can offer a solid mathematical grounding, programming experience gained on a real if modest problem, and the steadiness that comes from years of balancing work and study. I am ready for a demanding, quantitative course, and I would approach it with the same patience I bring to a long innings in the scorebook.