Applied Statistics MSc

Organisation
University of Southampton
Start - End
5 Sep
Study Options
Full Time
Fee
GBP 9250 - 9250
Fee International
GBP 21000 - 21000

MSc Applied Statistics provides postgraduate instruction in the theory and methods of applied statistics. The programme is for students whose interests lie in the theory and application of statistical methods, and in methods for designing, collecting and analysing large –scale data.

You will benefit from the cutting-edge research conducted in the research centres in which professors from our department hold leading positions: the Southampton Statistical Sciences Research Institute and the ESRC National Centre for Research Methods. Our main areas of expertise include sampling, small-area estimation, census and administrative data and the analysis of 'big data'.

Flexible study

If you prefer, you can apply to study this course as:

  • a part-time master's - study the same course content over 2 or more years

Your modules and fees may vary if you choose a different study option.

Course lead

Your course leader is Dr Olga Maslovskaya, Lecturer in Social Statistics and Demography within Economic, Social and Political Sciences. Her research interests include survey research, survey methodology, social statistics, quantitative research methods and demography. Read Dr Maslovskaya's staff profile to find out more about her work.

Course structure

You’ll study for a full 12 months, from September to the following September.

In the week before the start of semester 1, you’ll attend a 4-day induction course which will introduce you to our computer and library facilities.

For the first 9 months (semesters 1 and 2) you’ll study the taught part of the course. This is made up of modules that everyone on the course takes and modules that we’ll ask you to choose from a list of options.

Exams take place at the end of semesters 1 and 2.

You’ll spend the last 3 months of the course working independently on your research project and dissertation.

Want more detail? See all the modules in the course.

Learning and assessment

Learning

The learning activities for this course include the following:

  • lectures
  • seminars
  • group work
  • projects
  • independent learning (studying on your own)

Assessment

We’ll assess you through:

  • essays
  • a dissertation
  • presentations
  • seminar discussions
  • written exams

Dissertation

You’ll start your supervised research in June and submit a 15,000-word dissertation in September. This will be on a subject of your choice, to be agreed with your tutor.

The dissertation is a chance for you to show in-depth knowledge of a chosen topic.

Past topics include:

  • statistical methods for social networks
  • multilevel models of class context on voters at the 1983 General Election
  • estimation of pay distributions from new earnings survey data
  • comparing asset with money metric-based measures of poverty in Malawi

You’ll have regular support meetings with your supervisor throughout the process.

Academic Support

You’ll be assigned a personal academic tutor and have access to a senior tutor.

Careers

This degree will qualify you to work as a statistician in a range of sectors, including:

  • government
  • medicine
  • social research
  • private sector data analytics

You’ll also be in a great position to continue your studies at PhD level.


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