MSc Psychological Research Methods with Data Science
We leave our digital footprint wherever we go, from the updates we knowingly share on social media, to the way we simply interact with information online. This trail of data, and the conclusions that can be drawn from it, is valuable to organisations for decision making and risk management, but it takes experts to turn these large behavioural datasets into meaningful insight.
Bringing together practical training in the latest research techniques with computational data analysis classes, the MSc Psychological Research Methods with Data Science course has been developed to enable psychology students to make the transition to becoming data scientists. Throughout your training you'll learn how to process and transform large scientific datasets in order to uncover hidden patterns that can be applied to real-world organisational and psychological problems. You'll develop skills in the programming languages Python and R, and learn how to use, when to use, and how to interpret the output from specialist SPSS software.
Alongside your training in data science, you'll learn the latest techniques that are applied in cutting-edge psychology research, ranging from neuroimaging and multivariate statistics, to clinical trial design and qualitative interview methods. You'll also receive professional skills training in research ethics and presenting to an academic audience, before completing an extended research project, incorporating data science techniques in your chosen specialism across clinical, cognitive, developmental or social psychology.
Develop the technical skills in data science that employers are looking for and tailor your studies to your research interests, ready to take the next step towards a PhD, clinical training or a career in psychological research or data science.
Make the transition to data science
Throughout your studies you'll receive training in a wide variety of psychological research methods, advanced statistical methods, and data science, giving you the expertise to analyse mass datasets with an understanding of the ethical implications of using data to predict and influence human behaviour.
Through your research project, you'll have the opportunity to explore diverse topics, from modelling attitude formation and processing health-risk information, to the application of electroencephalography to social development. No matter which specialist project you choose, you'll be putting your new advanced statistics and data analysis and visualization skills into practice.
Full-time or part-time study?
You can do this course as a full-time student in one year, or as a part-time student over two years.
Course Director: Dr Tom Stafford
If you would like to know anything else about this course, contact:
You can also visit us throughout the year:
|About the course||
This course is designed to train you in data handling and statistics, alongside the latest research methods that are applied in cutting-edge psychology research, ready for clinical training, a PhD or an exciting career in data science. Your training will be led by our experts. Dr Chris Stride is a professional statistician who will teach you the most commonly applied quantitative methods including multilevel modelling, factor analysis, and structural equation modelling, as well as the skills of when to apply such techniques and how to interpret the output. Dr Tom Stafford is a psychologist with extensive experience of handling large data sets to answer pressing problems in psychology who will lead your computational data analysis training and aid your transition to data science. Throughout your course, we'll teach you the skills you need and give you the opportunities to apply them to the area of psychology that you're interested in: from cognitive and developmental, to social and clinical psychology.
Alongside your data science training you'll learn a broad range of research techniques from neuroimaging (EEG, fMRI), behavioural genetics, through experimental methodologies and clinical trial design, to qualitative interview, diary study methodologies and specialist methods for working with infants, children and clinical populations. You'll also begin training in a range of skills that are important for data scientists in academia and professional roles: you'll understand ethical issues and the implications of using data to predict and influence human behaviour, and develop your presentation skills ready to take part in our annual student-led summer conference.
The Research Project in Psychology with Data Science and Systematic Literature Review course components, which include coverage of meta-analysis, give you the opportunity to focus on a chosen psychological research question in detail under the supervision of one of our world-class researchers. You can choose a supervisor from an area of psychology that matches your research interests and future career aspirations within cognitive, developmental, social or clinical psychology. These projects give you the opportunity to put your new data science and research methods knowledge into practice while addressing an issue at the cutting edge of psychological research. It's common for MSc research projects and literature reviews to form the basis of publications in peer-reviewed journals.
Example research projects include:
In addition to technical skills and specialist knowledge of psychological research methods and data science, throughout your course you’ll also develop transferable skills around problem solving and communication, sought after by employers around the globe. In order to build these skills, you’ll learn through small-group teaching in a mixture of seminars, workshops and one-to-one supervision. All assessment is coursework-based.
Read more about this course on the University of Sheffield's webpages for postgraduate students:
|After your degree||
For this course, we usually ask for a 2:1 BSc honours degree, or equivalent, in Psychology, or a closely related discipline.
Applicants with professional experience may also be considered following interview.
We can also accept qualifications from other countries. You can find out which qualifications we accept from your country on the University's webpages for international students.
English Language Requirements
If you have not already studied in a country where English is the majority language, it is likely that you will need to have an English language qualification. We usually ask for:
You can find out whether you need to have an english language qualification, and which other English language qualifications we accept, on the University's webpages for international students.
The English Language Teaching Centre offers English language courses for students who are preparing to study at the University of Sheffield.
|Funding and scholarships||
Funding is available, depending on your fee status, where you live and the course you plan to study. You could also qualify for a repayable postgraduate masters loan to help fund your studies.
Up-to-date fees can be found on the University of Sheffield's webpages for postgraduate students:
Departmental Taught Postgraduate Bursaries
Each year we offer two bursaries to students on this program. Students who are awarded a bursary get a £1,500 reduction in their tuition fees. These bursaries are awarded on a competitive basis, based on:
To be considered for a bursary in the year that you intend to start your course, submit your application to study with us by 31 May. All applications received before this deadline will automatically be considered for a bursary.
All students will study:
|Research Project in Psychology with Data Science (60 credits)||
Module leader: Dr Tom Stafford
Students conduct, analyse and write up a research project under the guidance of their academic supervisor. The topic and methods chosen will normally be closely related to the area of expertise of the supervisor. In conducting the research project under supervision, students gain first-hand practical experience of managing the research process, starting with the formulation of a specific research question on the basis of review of relevant literature and guidance from the supervisor, through to the design, execution and analysis of a study, and the writing-up of a report. Data analysis for the project will involve the use of data science methods. All projects must be submitted to, and receive approval from, the Psychology Department Ethics Committee before they can proceed. Projects are written up in the standard format for submission to an appropriate academic journal (e.g., British Journal of Social Psychology).
|Research Methods in Psychology (30 credits)||
Organiser: Dr Jilly Martin
Seminars on the methods currently being applied by psychologists are presented by experts in their application. Methods covered include behavioural genetics, eye-tracking, questionnaire design, experimental methods for working with infants and children, qualitative data collection and analysis, and neuroimaging (EEG, fMRI).
|Intermediate Multivariate Statistics for Psychology (15 Credits)||
Module leader: Dr Chris Stride
The course addresses a range of commonly applied quantitative methods including multiple regression (including testing for mediation and moderation), analysis of covariance, exploratory factor analysis and reliability analysis. The emphasis is on conceptual understanding of when to apply these techniques and how to interpret the output rather than on the underlying mathematics. Additionally a three day course in using SPSS software is offered in the Spring semester.
|Advanced Statistical Methods for Psychologists (15 Credits)||
Module leader: Dr Chris Stride
This module covers advanced statistical methods and software skills increasingly required by researchers and data analysts in psychology and other social science disciplines. Specific techniques covered include confirmatory factor analysis and structural equation modelling (using Mplus software), multilevel modelling for both cross-sectional and longitudinal data, and generalised linear models. Lectures will be used to teach the rationale behind and principles behind these techniques, with practical sessions offering the opportunity to apply and develop student's knowledge.
|Data Analysis and Visualization (15 credits)||
Module leader: Dr Tom Stafford
This module will train students in basic skills in computational data analysis. Students will learn how to import/export scientific data sets in different formats, how to process and transform them, and how to visualise results. Teaching will be hands-on and computer lab-based and will focus on the programming language Python and associated scientific software. No prior programming experience will be necessary.
|Systematically Reviewing Psychological Research (30 credits)||
Module leader: Professor Richard Rowe
Seminars address searching on-line databases such as Web of Knowledge and Google Scholar, the process of conducting systematic and narrative literature reviews and meta-analysis. The application of reference managing software to manage reference libraries is also addressed. You will complete your own literature review on a topic of your choice under supervision of an academic member of staff.
|Current Issues in Psychological Research (15 credits)||
Module leader: Dr Aarti Iyer
Seminars are presented by academics on contemporary controversies in their research areas. Particular attention is paid to the way different research methods are triangulated to advance the field.
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.
We timetable teaching across the whole of our campus, the details of which can be found on our campus map. Teaching may take place in a student’s home department, but may also be timetabled to take place within other departments or central teaching space.