Studying Applied Statistics and Network Analysis at HSE Moscow
Felipe Vaca Ramirez and Paco Arevalo Reyes, both from Ecuador, are second-year students in HSE’s Master’s programme in ‘Applied Statistics with Network Analysis’. Having heard about Russia’s rich mathematical tradition and the high academic standing of HSE, they both decided to study in Moscow despite how far away from home it is. Felipe and Paco share a background in economics, and the HSE programme’s focus on statistics and data and network analysis was a huge draw for them. Affordable tuition fees and a multicultural environment were additional bonuses.
Now, in their final year of studies at HSE, they are confident they have made the right choice. ‘I have found the active involvement in data analysis projects and the constant exposure to research to be very useful,’ says Felipe Vaca Ramirez, who plans to pursue a PhD after completing his Master’s and thus enjoys the research focus of the programme. Felipe also praises the outstanding team of professionals teaching in the programme. He particularly enjoyed courses taught by Vladimir Batagelj and Vladimir Panov which focused on establishing the mathematical foundations of a method, explaining the intuition behind them, and presenting applications of the methods. Networks and Non-Parametric Statistics courses were some of Felipe’s favourites due to their content and the way they were presented. ‘They have opened my mind!’ he says.
‘Professor Batagelj’s lectures are very challenging and funny,’ adds Paco Arevalo Reyes. ‘In one session he can both brilliantly explain a bit of abstract algebra and share curious and interesting applications of network modelling. For example, if you have forgotten the Monte Carlo method you can take advantage of Prof. Batagelj’s lectures.’
Paco liked all of the courses related to network analysis because they considered totally new concepts and tools for obtaining results through data analysis. ‘The courses really showed how several branches of mathematics work together in reality modeling: combinatorics, graph theory, probability, algebra and statistics.’ In addition, he found the Contemporary Data Analysis course quite interesting because it introduced the newest statistical techniques, which was very motivating. ‘In that course I discovered a large variety of approaches that are useful in different contexts, depending on the nature of data, its quality, characteristics and availability.’
Now both students are working on their Master’s theses while doing internships at the University of Ljubljana, one of the programme’s partners. Felipe is researching urban spatial networks. He is characterising cities by means of some topological attributes of their road networks and then analysing the patterns that emerge, using spatial statics and machine learning methods. Paco is trying to model data from a national survey in order to discover the relationships between the decisional autonomy self-perception, the balance of resources inside couples, and the perception on the decisional participation in dual-earner households. He is considering two approaches for modelling the data: the first one is related to structural equation modelling, and the second one uses techniques and concepts of envelopment data analysis.
As Paco Arevalo Reyes concludes, ‘at MASNA I have found a variety of courses which have strengthened my knowledge of the theoretical foundations of statistics. Besides, a variety of courses on this programme showed me the diversity of contexts and fields where different methods are useful for solving real life problems.’
Academic Supervisor of the programme and Head of the International Laboratory for Applied Network Research