Data Analytics and Social Statistics (online) MSc postgraduate personal statement example

Personal statement example

Every Monday at the housing association where I work, I export the previous week's repair requests into a spreadsheet so my team leader can see how long tenants have waited. A few months into the job I noticed that the average wait looked healthy while the phone calls I took suggested otherwise. When I sorted the data by job type, the reason was obvious: hundreds of quick jobs, such as replacing a lost key fob, were pulling the mean down, while damp and mould cases often stayed open for weeks. I started reporting medians alongside means and splitting the figures by category. It was a small change, but it altered which cases were discussed in our weekly meeting. It also showed me how much I still had to learn. I want to study data analytics and social statistics so that I can move from tidying spreadsheets to analysing social data properly.

My first degree was in geography, and the most useful part was my dissertation. I compared how residents of two estates in east Leeds used buses after a route was cut back. I designed a short questionnaire, collected 140 responses at bus stops and a community centre over three weekends, and used chi-square tests to compare reported changes in travel between the estates. The results suggested that older residents on the estate that lost a direct service were more likely to say they had stopped making some trips. Writing it up, I had to be honest about the limits: my sample was a convenience sample, skewed towards people who were already out and waiting for buses. My supervisor's comments on non-response bias stayed with me, and they are part of why I want formal training in survey methods and sampling.

Since graduating, I have built on the basic statistics module from my degree on my own. I worked through an introductory R course in the evenings and have since used R to reproduce some of my work reports, which means I can rerun them each week instead of rebuilding charts by hand. I have also been reading Tim Harford's How to Make the World Add Up. His point that we should look at our own emotional reaction to a statistic before judging it matches what I see when colleagues seize on a single month's figures. I know that applied work needs more than careful habits. I want to understand regression modelling, how to handle missing data, and how to work responsibly with administrative records about people's lives.

My job has taught me that behind every row is a household. Tenants who report damp several times are often also the ones in arrears or caring for someone, and I have become aware that linking datasets can help target support but also raises real questions about consent and fairness. I would like to study these issues alongside the technical methods rather than treat them as an afterthought.

Outside work, I am the volunteer scorer for a local cricket club's second team. Keeping a scorebook accurate over a long Saturday requires concentration, and I enjoy the small arguments in the pavilion afterwards about whether a batter's average flatters him because of not-outs. I also do the weekly shop and hospital-appointment lifts for my grandmother, who lives nearby, so I have learned to plan my time carefully.

An online course suits me because I can keep working while I study, and my job gives me a constant supply of practical questions to test new methods against. I am organised, comfortable with independent learning, and used to explaining figures to people who did not ask to see them. I hope to develop the statistical skills to analyse social data rigorously, and eventually to work as an analyst in housing or local government research.