Placement-based dissertation, in which you will produce a piece of research on behalf of one of our partner organisations.
We work with over 25 partners across Greater Manchester to provide students with placements across diverse sectors, including Barnardos, British Red Cross, Manchester United FC, HM Inspectorate of Probation, Greater Manchester Police, The Children’s Society, Manchester City FC, and Citizen’s Advice.
A range of quantitative techniques will be covered including multiple regression, multi-level modelling, questionnaire design and psychometric testing, quantitative evaluation, and data management. One unit, ‘Statistics in Practice’ explores knowledge exchange, mobilisation and achieving impact with research. There is a mixture of core units and specialist options. The course culminates in a placement based dissertation, in which students will produce a piece of research on behalf of one of our partner organisations.
The core units include:
The optional units include:
This unit will provide the opportunity to research and produce a sustained, in-depth, piece of scholarly work based on a specific topic of study using quantitative methods. For this you will work with a community organisation and the choice of topic will be negotiated in conjunction with that organisation. We have a substantial list of community organisation available for you to work with which include Her Majesties Inspectorate of Probation, British Red Cross, Manchester City and Manchester United Football Club, Trafford Citizen's Advice Bureau, Manchester Probation Service, the Children’s Society, The Boys and Girls Clubs of Greater Manchester. The final submitted dissertation is around 10,000 words in length.
Central to any quantitative analysis is data, and as such, data requires careful management. This unit will provide you with all the necessary knowledge and skills to competently manage data in a range of settings.
This unit provides an introduction to the key foundations of quantitative analysis. It examines key quantitative concepts (such as, sampling, validity, generalisability) and their relationship to research design and analysis. The presentation of data (including data visualisation) will be explored. The unit will review key stages of analysis, including univariate, bivariate analyses; statistical tests for significance; simple linear regression; recoding; hypothesis and construction.
Correlation and regression are regarded as the meat and potatoes of contemporary social science. This unit focuses on regression which is by far the most widely used and versatile technique in quantitative research. It will introduce you to the theory and practice of regression. The unit comprises taught and practical components in equal proportions. Emphasis will be given on illustrating multiple regression through social science examples. SPSS will be used for the practical sessions in lab. However, those with advanced skills on statistical software will be encouraged to use STATA.
This unit will provide an introduction to social science research methodology and design. It will explore the underpinning historical philosophies that have influenced social science inquiry generally and quantitative approaches specifically. Relatedly it will explore how such philosophical approaches have shaped research design and core methods concepts.
Questionnaire is one of the most commonly used tools for collecting quantitative data. Good quality data in quantitative surveys depends on the successful designing of a questionnaire. This unit has two parts which are linked with each other. The first part will provide you with the tools required to design questionnaires in an efficient and effective manner. The second part is about how to develop multi-item scales in questionnaire and test their reliability and validity. In both parts, a practical approach will be used allowing you to discuss your own research interests and design for your own questionnaire. Teaching and learning will take place through lectures, workshops and lab activities.
The overarching aim of this unit is to enable you to develop a critical awareness of the real world context of quantitative research. It will focus on the identification and development of your career-ready skills, specifically in relation to research impact, knowledge mobilisation,dissemination strategies and the presentation of research.
This module introduces you to evaluation with a focus on the use of quantitative methods. A range of evaluation frameworks (experimental and quasi-experimental) that tend to favour quantitative methods will be explored. You will assess the strengths and weaknesses of different evaluation frameworks and methods and also place these in the context of underlying epistemological debates. The potential for evaluation to influence policy and practice will be an important consideration during the module. We will look at the use of Systematic Review and meta-analysis, and discuss the potential for evidence-based policy. Much quantitative evaluation culminates in economic evaluation and we will look at widely used approaches to economic evaluation, including Cost Benefit Analysis.
This unit explores the foundations of mixed method research, the applied considerations in planning and designing a mixed method research study. It will also give practical opportunity to conduct a mixed method study, develop an acute awareness of mixed method analytic techniques and gain valuable experience in disseminating mixed method findings through a poster presentation and report writing.
Social and behavioural scientists aim to explain variability in human behaviour and attitudes. However, many of these data have a hierarchical or clustered structure because of shared membership of social contexts - the family, the school, the workplace and so on. One way in which social scientists further their understanding of social behaviour is by using statistical models to analyse quantitative data. A weakness of the way in which these models are often applied to social data is that they focus too much on the individual, and too little on the social and institutional contexts in which individuals are located. Multi-level modelling aims to redress the balance by emphasising both individuals and their social contexts.
This unit is designed to give you an introduction to the theory and application of multi-level models. The main aim of the unit is to provide you with the necessary conceptual understanding and practical skills to be able to undertake report and interpret a multi-level linear model analysis through ‘hands on’ practical sessions in labs, using SPSS/Stata/MLwiN statistical software package.
Each programme of study that we offer undergoes an annual review to ensure an up-to-date curriculum supported by the latest online learning technology. In addition, we undertake a major review of the programme, normally at 6-yearly intervals, but this can take place at a more frequent interval where required. Applicants should note that the programme currently provided may be subject to change as a result of the review process. We only make changes where we consider it necessary to do so or where we feel that certain changes are in the best interests of students and to enhance the quality of provision. Occasionally, we have to make changes for reasons outside our control. Where there are changes which may materially affect the current programme content and/or structure, offer holders will be informed.
You will be assessed through research reports, presentations, research proposals, lab tests and a self-directed, research-based dissertation.
Your studies are supported by a team of committed and enthusiastic teachers and researchers, experts in their chosen field. We also work with external professionals, many of whom are Manchester Met alumni, to enhance your learning and appreciation of the wider subject. Details of departmental staff can be found at: http://www2.mmu.ac.uk/sociology/staff/
Download our course application form. There are instructions on what to do next and who to send the form to in the Word document.
The programme will be a considerable asset to postgraduates wishing to pursue a career involving quantitative research skills within a diverse range of organisations within the public/ private/ voluntary sectors, businesses, academia, think tanks, research centres, and NGOs.
Quantitative Skills (QS) underpin evidence-based planning and practice in the public, private and other sectors. However, over two thirds of employers in the UK identify a shortage of QS among employees. Numerical and analytic skills are highly prized in a diverse range of careers. Quantitative skills are transferable between workplaces and sectors across the UK. There is a global shortage of quantitative skilled workers; it is estimated that by 2018 there will be a shortage of 15k-20k data scientists and up to 1.5m data savvy professionals in North America alone.
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This online prospectus provides an overview of our programmes of study and the University. We regularly update our online prospectus so that our published course information is accurate and up to date. Please note that our programmes are subject to review and development on an ongoing basis. Changes may sometimes be necessary. For example, to comply with the requirements of professional or accrediting bodies or as a result of student feedback or external examiners’ reports. We also need to ensure that our courses are dynamic and current and that the content and structure maintain academic standards and enhance the quality of the student experience.
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