MSc Social Research Methods and Statistics with Computational Social Science

University of Manchester

Course overviewLearn from elite academics at one of the UK’s top 5 universities for social sciences.Train in advanced quantitative methods, including applied statistics for complex data.Use innovative computational techniques to analyse real-world problems.Course descriptionData skills are invaluable across the social sciences. Used responsibly, big data can help you to interpret the myriad factors at play in the study of social phenomena.Mastering computational methods will greatly expand your ability to process, analyse and draw conclusions from data.Each core module on this programme has been designed to equip you with a strong foundation in both statistical theory and advanced computational techniques, ensuring you graduate with a versatile toolkit for analysing complex social phenomena.Some of the key skills you’ll learn are:Advanced data analysisSurvey designStatistical modellingAgent-based modelling for understanding complex systems.Upon course completion, you’ll have developed a highly valued skillset, preparing you for doctoral research and enhancing your employability across countless sectors.Career opportunitiesThere is an increasing need for well-trained social scientists who are able to apply advanced methods of analysis to complex data.You will gain relevant marketable skills that will put you in a good position to obtain jobs in:the academic sector;central and local government;commercial consultancy;voluntary research sector.We have excellent links with ONS and government departments, local authorities and many commercial organisations and we are well placed to assist you in finding jobs.A number of our students already hold research positions (typically in local government or overseas) taking the MSc as part of a career development programme. The course is ideal preparation if you wish to pursue doctoral study, and is a formal component of our 1+3 PhD training model. You are offered support to apply for PhD funding.