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Short-term, flexible and focused training in quantitative research methods, data analysis, and statistics, for aspiring and developing researchers.


This course aims to provide behavioural and social science graduates with high-quality
training in quantitative research methods and statistics, which advances on their
undergraduate-level training and is tailored to their future doctoral research training needs. It also aims to provide academic staff and other professionals with a platform to undertake
certified training in a specialised skill-set, which is necessary to facilitate the testing of
specific research questions via the collection, sourcing and analysis of quantitative data, for
the production of high-quality, high-impact research outputs.

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About this course

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This new blended-learning PgCert in Quantitative Methods for the Behavioural and Social Sciences has been designed by experienced quantitative research staff in the School of Psychology, based within the Faculty of Life and Health Sciences, at Ulster University. Targeted primarily at prospective PhD applicants who seek focussed and condensed quantitative analysis and methodology skills training; academics who seek flexible and accessible training to become both research literate and active; and researchers who seek expert guidance and training to enhance their quantitative analytic and methodological knowledge and skill, the course is a timely addition to the postgraduate training portfolio of UU. The course offers certified training in a specialised skill-set necessary (i) to design and conduct research studies using quantitative methodologies, (ii) to manipulate and analyse primary and secondary sources of quantitative data appropriately, and (iii) to present resulting research findings in the form of high-quality research outputs. The blended-learning mode of delivery (Coleraine) will offer students the freedom and flexibility to study for a postgraduate award in their own time and at their own pace, whilst also offering expert face-to-face support and guidance to master aspects of methods and statistics training that are traditionally recognised to be challenging for the novice researcher/analyst.

Structure and Content

The course is a 60-credit PgCert in Quantitative Methods for the Behavioural and Social
Sciences. There are three compulsory modules and students elect to do one optional module from a choice of three:
PSY707: Foundations in data analysis using SPSS (10 credits)
PSY706: Survey methodology (15 credits) - solely online
PSY711: Principles of research design (15 credits) - solely online
Options (Students elect to complete one; all 20-credit)
PSY708: Introduction to the general linear model
PSY709: Introduction to latent variable modelling
PSY710: Analysing longitudinal data

Four computing and statistics modules (PSY707, 708, 709, and 710) are delivered
on-campus in condensed face-to-face teaching blocks in Semester 3 (late-August/early September). The face-to-face computing and statistics sessions provide students with an
opportunity to learn the practical elements of the module in an interactive
environment. Students choose one optional module that most closely aligns to their individual research interests and training needs. PSY708 covers a wide range of commonly used statistical techniques such as analysis of variance (ANOVA), bivariate and multiple regression, logistic and multinomial regression, as well as introducing exploratory and confirmatory factor analysis. PSY708 would be most applicable for students who have had limited experience in the analysis of quantitative data in their primary degree, or for those experienced academics who may have covered this material to some extent in their
primary degree years previously. PSY709 introduces students to the latent variable modelling framework, and would be most suitable for students who wish to test more complex research hypotheses using a robust statistical framework. PSY710 focuses on developing skills that are necessary for data that is longitudinal in nature (e.g. data collected on individuals or a group over time). This module would be most suitable for students who have a good general knowledge of latent variable modelling, and wish to apply this type of analysis to longitudinal data. Students will be guided to select the optional module that is most suitable and relevant to their training needs.

The two fully online modules, PSY706 and PSY711, are more theoretical/conceptual in nature, covering all aspects of survey methodology and the principles of research design. Both modules will teach students the main strategies and stages for designing research studies to collect high quality, robust quantitative data, while also teaching students the necessary skills to be able to critically evaluate findings from published research studies in their discipline. These two modules have been designed to help students understand the design and methodological processes that must be undertaken to collect quantitative data that is of a high quality and amendable to empirical investigation using appropriate
statistical modeling.


Students will be required to attend the Coleraine campus for a face-to-face teaching block in Semester 3 (late August/early September). The duration of time spent on campus during the teaching block will vary depending on the optional modules taken, but students can expect to be on campus for between 2-5 days (9am-5pm each day). The remainder of the course is delivered online via Ulster's virtual learning environment (Blackboard). Students are expected to go into the online environment on a regular basis and engage with the learning material. Students are expected to contribute to online weekly activities within the modules and complete these within the weekly deadlines set. Attendance is monitored.

Part-time students must take modules PSY707 and PSY708/PSY709/PSY710 in Semester 3&1, but take modules PSY706 and PSY711 in Semester 2.

Start dates

  • September 2018
How to apply


Here is a guide to the subjects studied on this course.

Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand. Please contact the course team for the most up to date module list.

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Year one

Survey methodology

Year: 1

This module introduces students to the cornerstones of survey methodology. It provides students with the skills necessary to conduct a comprehensive and robust survey for the collection of primary quantitative data. It also teaches students how to identify and source rich, high-quality secondary data resources from reputable data repositories for research purposes. Students will also be knowledgeable of important professional, legal, and ethical issues in relation to data management and storage.

Foundations in data analysis using SPSS

Year: 1

This module establishes a foundation of basic research skills by introducing key concepts of: the scientific method; research designs used in the behavioural and social sciences; a range of graphical and descriptive statistical techniques; statistical inference; hypothesis testing; and, the application of SPSS in data analysis.

Principles of research design

Year: 1

Researchers in the social sciences must have a good understanding of and grounding in both the practice and philosophies of social science research. This module facilitates students to become informed consumers and producers of research. Students will explore different approaches to knowledge construction and examine various research paradigms, their approaches to enquiry and their underlying assumptions. Students will evaluate a range of research designs and methodological processes and will have opportunities to consider the principles which underpin and guide research.

Introduction to the general linear model

Year: 1

This module is optional

This module presents methods relating to statistical data analysis of data collected from both survey and experimental research. Issues relating to data quality, experimental and non-experimental design, and multivariate statistical analysis will be addressed during lectures and additional experience in the use of multivariate statistical techniques is gained through practical computer based sessions.

Introduction to latent variable modelling

Year: 1

This module is optional

This module introduces students to the principles of latent variable modelling (LVM) and how such statistical models can be specified and tested. LVM is now the preferred method of statistical analyses in all social sciences due to its power and flexibility. This module will cover the theoretical and statistical basis of LVM, and provide the students with the skills to specify, estimate and interpret such models. The module will be delivered by means of lectures and practical session. There will be extensive use of secondary data resources.

Analysing longitudinal data

Year: 1

This module is optional

The module seeks to develop students? knowledge and understanding of methods for analysing longitudinal data within a latent variable framework. Latent growth models, mixture models and models involving mediation and moderation will be described, together with combinations thereof. Students will be introduced to the concepts, terms and approaches underlying these models and will gain experience implementing and estimating the models using appropriate statistical software.

Entry conditions

We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements.

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Entry Requirements

Applicants must hold a degree in the behavioural or social sciences (e.g. psychology,
geography, political science, health economics, sociology, or equivalent) or demonstrate
their ability to undertake the course through the accreditation of prior experiential learning.

English Language Requirements

English language requirements for international applicants
The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement.

Ulster recognises a number of other English language tests and comparable IELTS equivalent scores.

Teaching and learning assessment

Teaching will involve a combination of on-campus teaching blocks (comprising lectures and practical computing and statistics workshops), as well as online lectures, seminars/interactive sessions and practicalexercises. Students will be expected to engage with the material presented, contribute to discussion boards, and will be encouraged to consolidate their skills as independent learners.

Exemptions and transferability

Students may apply for Accreditation of Prior Learning (APL) for Module PSY707 (Foundations in data analysis using SPSS -10 credits) if evidence can be provided to indicate that the learning outcomes for this module have been already been obtained. Applicants can enquire about APL at the time of applying.

Careers & opportunities

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Career options

The demands for quantitative skills in the workplace has risen sharply in the past two decades. Upon successful completion of this course, graduates will be ideally positioned to
apply for early-career posts (e.g. research assistant; project manager posts) in a
wide variety of academic and non-academic settings. It is expected that many
graduates will use this course as a stepping-stone to doctoral-level research study.
Professionals undertaking this course as continuing professional development may
be able to diversify into other roles within their current/future employment (e.g.
assume more research-related tasks in teaching, supervision, and enhance their
own personal programme of research).

Academic profile

This course has been designed by experienced quantitative research staff in the School of Psychology. The School of Psychology at Ulster has a long and strong tradition of employing academic and research staff with expertise in quantitative research methods. Staff interests and expertise have ensured that a strong emphasis is always placed on helping students to acquire the necessary skills to conduct high-quality research using a range of methodologies. Staff also have substantive research interests in applied psychology, with a specific focus on mental health and wellbeing (as evidenced by extensive research funding and multiple peer-reviewed research publications in high-quality international peer-reviewed journals). Much of this internationally recognised research is conducted using national, epidemiological, cross-sectional and longitudinal data resources from around the world under the theme of ‘Population and Mental Health Sciences and Health Services Research’, within the Psychology Research Institute. Since 2005, senior staff have also successfully secured substantial grant income from the Economic and Social Research Council (ESRC) to provide training in advanced statistical modelling to research staff and students at institutions in Northern Ireland and across the UK. They are also one of the leading recipients of ESRC Secondary Data Analysis Initiative (SDAI) funding for administrative data analysis in the UK. The majority of the teaching team are Fellows of the Higher Education Academy, some of whom have received recognition for their teaching.


How to apply Request a prospectus

Applications to our postgraduate courses are made through the University’s online application system. The closing date for applications is 31st May 2018.

Start dates

  • September 2018

Fees and funding

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Additional mandatory costs

Tuition fees and costs associated with accommodation, travel (including car parking charges), and normal living are a part of university life.

Where a course has additional mandatory expenses we make every effort to highlight them. These may include residential visits, field trips, materials (e.g. art, design, engineering) inoculations, security checks, computer equipment, uniforms, professional memberships etc.

We aim to provide students with the learning materials needed to support their studies. Our libraries are a valuable resource with an extensive collection of books and journals as well as first-class facilities and IT equipment. Computer suites and free wifi is also available on each of the campuses.

There will be some additional costs to being a student which cannot be itemised and these will be different for each student. You may choose to purchase your own textbooks and course materials or prefer your own computer and software. Printing and binding may also be required. There are additional fees for graduation ceremonies, examination resits and library fines. Additional costs vary from course to course.

Students choosing a period of paid work placement or study abroad as part of their course should be aware that there may be additional travel and living costs as well as tuition fees.

Please contact the course team for more information.


Course Director: Dr Orla McBride

T: +44 (0)28 7167 5341


Admission enquiries

T: +44 (0)28 7012 4159