1. MSc Social Statistics and Social Research Why study social statistics and social research? Social research methods are used in the public, private, voluntary and academic sectors. Now is a particularly interesting time for social statistics, with the development of new forms of data and new analytical techniques producing innovative ways of understanding the social word. This course equips individuals with the technical and theoretical skills to explore this data. Who is the course for? This course is for graduates of social science disciplines (e.g., sociology, education, geography, management and so on). A strong statistical background is not required, just a willingness to learn. This particular programme is designed for people specifically interested in quantitative research, including as part of mixed methods. What’s involved? Five core modules (focusing on quantitative methods, data management and research design); two option modules from across the Applied Social Research programme (including on Big Data and on Data Management); & a 15,000 word dissertation. The course can be taken on a full- or part-time basis with most classes held on 1 or 2 days per week. Why Stirling? Research at the School of Applied Social Science was deemed ‘internationally excellent or world leading’ (99%) in the last REF. The School has a reputation for excellence in teaching research methodology, and includes a large and successful quantitative methods research group. New MSc programme School of Applied Social Science Social science research with a focus on quantitative methods This MSc delivers an understanding of social research, with a particular focus on social statistics and quantitative methods. The course includes orientation material on social research methods as a whole, and detailed training on a wide range of statistical methods, with advanced modules on data management and emerging priority research areas, such as big data and social network analysis. Teaching covers the theories behind the methods, and the practical work in using datasets and analysing them with statistical software. Students will gain a variety of highly marketable skills in the areas of social research and social statistics. This course will provide: A strong understanding of social research, including designing, refining and addressing theoretically informed research questions. A theoretical and practical overview of a range of quantitative methods, including linear and non-linear regression, multilevel modelling, causal analysis and selection models. Knowledge of emerging methods, including social network analysis, big data, and using secure and administrative data environments. Training in a range important social statistics software, developing advanced knowledge of Stata, and a strong working knowledge of R, SPSS, Pajek and UCINET. Reflections on quantitative practices, such as variable operationalisation and graphing.

2. Course structure Students undertake five core modules, two option modules and complete a 15,000 word dissertation. In the full time programme, 3 modules are completed during the Autumn semester, 3 in the Spring, and the dissertation submitted in the summer. Modules either cover wider topics in social research, or focus on understanding and implementing advanced quantitative methods. Core modules Research Design and Process Students will be taken through all stages of designing a research project, including developing a research idea, performing a literature review, identifying a theoretical framework and refining the research question and methods. They will explore common qualitative and quantitative methods and reflect on research ethics. Quantitative Data Analysis This module introduces quantitative data analysis, covering a wide range of statistical techniques, with a focus on analysing data collected in large-scale social surveys. Students will learn a range of methods, covering introductory descriptive statistics and commonly used strategies of statistical modelling, and training in using software. Advanced Data Analysis This module follows on from Quantitative Data Analysis covering more advanced statistical issues, such as sensitivity analysis, complex multilevel modelling and dealing with troublesome data. This will expand students knowledge of using software, particularly using Stata. Advanced Data Management This module covers issues central to social statistics that are rarely covered in standard training. These include operational issues such as using ‘workflows’ and linking datasets; methodological challenges such as using administrative data and using secure data environments; and theoretical issues, such as variable operationalisation. This module will prepare students for practical issues they might encounter in their own, independent, research careers. Using Big Data in Social Research This module introduces students to using ‘Big Data’ in their research, from a social science perspective. They will learn the practical methods for analysing and linking data and also gain understanding of the theoretical debates around big data and how to construct research questions which are centred around social science issues. Option modules Students will also select two option modules from Stirling’s MRes in Applied Social Research programme. Particularly recommended is: Social Network Analysis Social network analysis is an emerging methodology in the social sciences. Students will receive training in network theory and learn a range of software packages, including Pajek and UCINET. Other modules available include options on ‘Comparative social research’, ‘Policy analysis and evaluation research’, ‘Qualitative data analysis’, ‘The nature of social enquiry’ and ‘Research methods in Criminology and Socio-Legal Studies’. These modules may be particularly suitable for students with an interest in mixed methods research. Exploring the results from a ‘correspondence analysis’ An output from a ‘social network analysis’

3. Entry requirements A minimum of a second class honours degree (2.1 preferred) or equivalent in a relevant social science subject. Applicants without such qualifications but with significant appropriate/relevant work/life experience are encouraged to apply. A willingness to learn advanced statistical methods is more important than a strong background in the area. Basic experience of a statistical software, such as SPSS, Stata, R or Excel is useful but not essential. If English is not your first language, you must provide evidence of your proficiency - i.e., IELTS score of at least 6.5 (minimum of 6 in each skill) or TOEFL 5777(paper), 233(computer), 90(internet). INTO University of Stirling offers a Graduate Diploma for students who do not meet the criteria: summer enrolment on that programme can lead to transition on the MSc in September. Modes of study 1 Year (full-time) Students will take three modules in both the Autumn and Spring semesters, completing their dissertation over the summer. The course runs from September to August each year. 2 Year (part-time) The course can be taken over two years with students studying 1 or 2 modules per semester. Individual modules Students are welcome to register for single modules (£595). All modules count for 20 credits at SQCF level 11.It may be possible to use the academic credits towards later postgraduate qualifications. Teaching style Modules are generally a combination of lectures and workshops. Teaching largely takes place on Tuesdays, although some components might take place on other days. The contact hours are sympathetic to those working alongside their studies. Most teaching is performed in smaller classes, with group activities. Modules are usually assessed by an examination, software based assignments, and essays. Career options Social statistics are an important area within applied social research, offering employment opportunities within the private, public and voluntary sectors, as well as further study. Students will develop thorough knowledge of software and learn a range of sought- after technical skills, including accessing, preparing, analysing and summarising complex quantitative datasets. The course also provides the technical skillset required for further PhD study. Costs Fees for 2015/6 are £4,500 for UK/EU citizens or £11,900 for overseas students. Part-time students will pay half of the fees in each year (2016/7 fees may be higher). Details of any scholarships or fee reductions can be found at: ww.stir.ac.uk/scholarships ww.stir.ac.uk/scholarships How to apply For further information, please contact: Postgraduate Office Tel: +44 (0) 1786 467691 email: appliedsocialresearch@stir.ac.ukappliedsocialresearch@stir.ac.uk http://www.stir.ac.uk/social- science/courses/taught-postgraduate- courses/ Summarising patterns from an ‘Association model’ Describing measures from a large and complex comparative survey dataset

4. Quantitative expertise Dave Griffiths (Programme Director) is a Lecturer in Quantitative Methods. His research explores social connections and social advantage, with interests in network analysis, social stratification, social capital and large-scale secondary social surveys. http://rms.stir.ac.uk/converis-stirling/person/11497 Paul Lambert (Programme Deputy Director) is a Professor of Sociology. His work analyses secondary survey datasets, with specific interests in occupational information, the social structure of stratification, cross-national comparisons and e-social science. http://rms.stir.ac.uk/converis-stirling/person/10815 Alasdair Rutherford is a Lecturer in Quantitative Methods. He has experience of academia, the public and voluntary sectors and consultancy work. His research interests include charities and non-profits, the economics of volunteering, migration, and social care. http://rms.stir.ac.uk/converis-stirling/person/10779 Marina Shapira is a Lecturer in Quantitative Methods. Her research explores socio-economic stratification and inequality, ethnicity and immigration, education, sociology of youth and comparative international research, including advanced statistical analyses of social surveys. http://rms.stir.ac.uk/converis-stirling/person/10882 School of Applied Social Science The School of Applied Social Science is a large inter-disciplinary unit, combining teaching and research interests in Sociology, Social Policy, Criminology, Social Work, Dementia and Housing Studies and a number of specialist centres. It has sustained successful research record and in the 2014 Research Excellence Framework, 75% of our research was assessed as internationally excellent or world leading, with the top 24% of our work judged as world leading.. We were also given the highest possible ratings for Sociology and Social Work in the most recent teaching quality exercises. We are an ESRC recognised postgraduate research training centre, as part of the Scottish Graduate School. The School has a Social Surveys and Social Statistics research group, including four full-time lecturers with a focus on social statistics. The group has housed various research projects on themes relating to the course content and has many PhD students working in such area (funded by the Economic and Social Research Council, Scottish Government and Skills Development Scotland). Stirling has over 11,000 students, of which over 3,400 are on postgraduate courses. It is an international institution, in the top 2.5% of global higher education institutions and with over 80 nationalities represented on campus. Its 330-acre site is regarded as one of the most attractive university campuses in Europe, with its own loch and an 18 th -century castle, overlooked by the Ochil Hills and the Wallace Monument. It has outstanding sporting facilities, including an Olympic sized swimming pool, an all-weather athletics track, a large gym, a nine-hole golf course and the Scottish Tennis Centre. The city of Stirling has a population of 46,000 at the heart of Scotland, with easy transport links to both Edinburgh and Glasgow (roughly 1 hour away). Stirling, and its nearby towns, are viewed as one of the most attractive parts of the UK.