NCRM is a Hub-Node network of research groups, each conducting research and training in an area of social science research methods, coordinated by the Hub at the University of Southampton. https://www.ncrm.ac.uk/training/ Sun, 16 Aug 2026 19:37:49 +0100 en-uk https://www.ncrm.ac.uk/incoming/furniture/images/sitewide/NCRM_new_Logo.gif https://www.ncrm.ac.uk/training/ NCRM is a Hub-Node network of research groups, each conducting research and training in an area of social science research methods, coordinated by the Hub at the University of Southampton. https://www.ncrm.ac.uk/training/show.php?article=14934 Ethnographic methods are increasingly popular with researchers across the social sciences, but the full potential and possible pitfalls of this complex practice are often overlooked in favour of catch-phrase definitions. This course moves beyond standard understandings of ethnography that depict it as a generic qualitative method founded on ‘participant observation’ to provide learners with a sophisticated, state-of-the-art approach based on cutting-edge academic research. The course will blend theorical and practical considerations. On the one hand, the course examines the theoretical scaffolding of ethnography, recognising that a thorough understanding of the epistemological foundations of the methods we use is essential to conducting rigorous and ethical research. On the other, the spirit of the course is inherently practical and pragmatic, as it aims at preparing researchers to design and conduct ethnographic fieldwork, as well as writing it up for academic and non-academic audiences.The course covers:Epistemology, method, and research design: ethnography beyond participant observationPreparing for fieldwork: a pragmatic approach to designing research projectsEthics and power: access, collaboration, co-production, and the possibility of decolonising researchWriting ethnography: from the practical to the politicalBy the end of the course participants will:Grasp the practice of ethnographic research beyond participant observationUnderstand the potential of ethnography beyond the traditional ‘study of culture’Have a sophisticated understanding of ethnographic research, from the design stage to its execution and writing up, including an overview of sensorial considerations and visual methodsBe able to appreciate the ethical and power dimensions of ethnographic researchUnderstand the ethics and politics of writing, publishing, and representing ethnographicallyThis advanced course is suitable for any researchers equipped with some prior knowledge/experience using both standard qualitative methods (interviews, focus groups, life histories, etc.) as well as ethnographic methods but is interested in advancing their understanding of ethnographic research to a professional level. Researchers working within and outside academia (private sector, government, charitable institutions, etc.) are equally welcome to apply. The course is likewise suitable for postgraduate students in any social science (human geography, sociology, business school, political sciences, area studies, education, etc.), particularly if enrolled or intending to enrol in a research degree (e.g., PhD, Masters by Research, Masters in Research Methods). Please note that this course is also suitable for postgraduate researchers with an UG background in anthropology, as the course if pitched to an advanced level.Pre-requisitesExperience using ethnographic research methods and qualitative research methods.Preparatory ReadingDemetriou, O. (2023), ‘Reconsidering the vignette as method. Art, ethnography, and refugee studies’, American Ethnologist, 50(2): 208-222.Hage, G. (2005), ‘A not so multi-sited ethnography of a not so imagined community’, Anthropological Theory 5, no.4: 463-475.Ingold, T. (2014), ‘That’s enough about ethnography!’, HAU Journal of Ethnographic Theory 4, no 1: 383–395Stefanelli, A. (forthcoming 2024) ‘Reading ethnography in the classroom: complementary strategies to develop students’ ethnographic imagination.’ Learning and Teaching in the Social Sciences.This online course will run from 09:30 to 15:15 both days. jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 06 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14934 https://www.ncrm.ac.uk/training/show.php?article=14922 In this one day online course (taught over 2 mornings) we will explore how to use R to import, manage and process spatial data. We will also cover the process of making choropleth maps, as well as some basic spatial analysis. Finally, we will cover the use of loops to make multiple maps quickly and easily, one of the major benefits of using a scripting language to make maps, rather than traditional graphic point-and-click interface.The course covers: Using R to import, manage and process spatial dataDesign and creation of choropleth mapsBasic spatial analysisWorking with loops in R to create multiple mapsBy the end of the course participants will:Use R to read in CSV data & spatial dataKnow how to plot spatial data using RJoin spatial data to attribute dataCustomize colour and classification methodsUnderstand how to use loops to make multiple mapsKnow how to reproject spatial dataBe able to perform point in polygon operationsKnow how to write shapefiles This course is ideal for anyone who wishes to use spatial data in their role. This includes government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map. This course is also suitable for those who wish to have an overview of what spatial data can be used for. No previous experience of spatial data is required.No previous experience of coding is required, although participants would benefit from some experience of using spatial data (e.g. Google Maps).THIS COURSE IS BEING TAUGHT OVER TWO MORNINGS AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES. jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 30 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14922 https://www.ncrm.ac.uk/training/show.php?article=14921 In this online one day course (taught over two mornings) you will learn what GIS is, how it works and how you can use it to create maps. We assume no prior knowledge of GIS and you will learn how to get data into the GIS, how to produce maps using your own data and what you can and cannot do with spatial data. You will gain practical experience in data importation, map creation, and analysis techniques, empowering them to enhance their research insights with compelling spatial visualisations.The course covers: What is GIS and spatial data?How to classify data for a choropleth mapHow to create a publication ready mapHow to work with different data sources including XY coordinate and postcode dataBy the end of the course participants will:Be able to set up QGIS and add dataUnderstand how to add data with latitude & longitude coordinatesKnow how to classify data for a choropleth mapBe able to join tabular data to spatial dataDesigning and producing a publication ready map in QGISUnderstand how to import a range of data types into QGISThis course is ideal for anyone who wishes to use spatial data in their role. This includes students, academic, government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map. This course is also suitable for those who wish to have an overview of what GIS and spatial data can be used for, and how you can better represent your data with maps. No previous experience of spatial data is required.THIS COURSE IS RUN OVER TWO MORNINGS (10:00-13:00) AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES. jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 30 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14921 https://www.ncrm.ac.uk/training/show.php?article=14913 Ethical research is better quality research. This course is designed to raise your awareness of why and how you need to think and act ethically in practice throughout your research work. The current system of ethical review by committee can lead to the misleading sense of having ‘done ethics’. This course shows you how to conduct research which is truly ethical. It also provides the opportunity for discussion of your own ethical dilemmas, if you wish.The course covers: Research ethics in context – ethical breaches past and present, ethics activism, trauma-informed research, debiasingPotential ethical pitfalls at each stage of the research process, from question setting to aftercareHow to think and act ethically throughout researchBy the end of the course participants will:Recognise the importance of context for ethical decision-makingUnderstand why they need to think and act ethically throughout research workBe clearer about potential ethical pitfalls at different stages of the research processKnow how to approach ethical thought and action at any point in their research This course is aimed at Doctoral students, early career researchers (any discipline), practice-based/applied researchers and possibly government researchers and independent researchers.THIS COURSE IS TAUGHT OVER TWO MORNINGS AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.Programme:Day One09:30    Welcome and introductions09:40    Research ethics in context: presentation10:00    Discussion, Q&A10.15    When do we need research ethics?10:20    Video and discussion10:40    Trauma-informed research: presentation10:50    Debiasing techniques: presentation11.00    Discussion, Q&A11.10    Break time11.25    Ethical research design: discussion11.35    Ethical context-setting: discussion         11:45    Ethical data gathering: discussion11:55    Ethical data analysis: discussion12:05    Video and discussion12:20    Q&A12:30    CloseDay Two09:30    Welcome, questions arising from Day 109:40    Ethical research reporting: discussion09:50    Ethical research presenting: discussion10.00    Ethical research dissemination: discussion10.10    Ethical aftercare: discussion10.20    Researcher wellbeing10.30    Unethical research today – presentation10.45    Video and discussion11.10    Break time11.25    Real-life ethical dilemmas from research #111:40    Real-life ethical dilemmas from research #211:55    Real-life ethical dilemmas from research #312.10    Discussion, Q&A, evaluation12.30    Close jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 30 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14913 https://www.ncrm.ac.uk/training/show.php?article=14912 This online course will explain when and why to use documents as data for research, show you how to gather documentary data, and consider some ways to analyse that data.The course covers: When and why to use documents as dataHow to find personal and official documents, historical documents, mainstream print media documents, virtual documents, and self-published documentsHow to assess the quality and usefulness of documents for research purposesSome methods of analysing documentary dataBy the end of the course participants will:Know how to find the documents they need for their researchKnow how to assess the quality and usefulness of documentsUnderstand how to approach the analysis of documentary dataHave an action plan for using documents in their own researchThis is an intermediate level course assuming a good basic knowledge of research methods. It would suit postgraduate students, early career researchers in academia, practice-based and independent researchers.Please note the course will run from 09:30 - 12:30 on the 9th and 10th March and equates to one full teaching day for payment purposes. jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 30 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14912 https://www.ncrm.ac.uk/training/show.php?article=14911 The aim of this two-day online training course is to introduce participants to the practice and ethics of ethnographic research. Through a mix of plenary sessions, group and independent work, participants will learn the basic principles of participant observation and research design, as well as the foundations of ethical ethnographic research. The course will also examine the ways in which other qualitative and creative methods of data collection may be productively integrated in ethnographic research.The course covers:Research designQualitative methods in ethnographic researchAccess and powerResearch ethics in participant observationBy the end of the course participants will:Understand the epistemological foundations of ethnographic researchHave a solid understanding of ethnographic research in actionBe able to design and conduct research integrating qualitative and ethnographic research methodsBe able to conduct ethical ethnographic researchThe course is suitable for any professional researchers interested in learning more about using ethnographic methods – whether within or outside academia (private sector, government researchers, etc.).The course is likewise suitable for postgraduate students in any social science (human geography, sociology, business school, political sciences, area studies, education, etc.) with prior knowledge of any qualitative research methods, but not necessarily of ethnography.Some prior training in qualitative research methods, broadly defined – regardless of whether that includes ethnographic methods specifically.Day 1Morning session:•          09:30-09:45     Introduction to the course•          09:45-10:45     Plenary – The Practice of Ethnography•          10:45-11:00      Break•          11:00-12:00      Group work followed by class discussionAfternoon session:•           12:45-13:45      Plenary - Qualitative methods in ethnographic practice•           13:45-14:00      Break•           14:00-15:15      Practical exercise followed by class discussionDay 2Morning session:•           09:30-10:45     Plenary - Research ethics in ethnography•           10:45-11:00      Break•           11:00-12:00      Group work followed by class discussionAfternoon session:•           12:45-1:345       Plenary – Writing ethnography•           13:45-14:00       Break•           14:00-15:00       Practical exercise, followed by class discussion         •           15:00-15:15       Conclusions and Evaluations jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 30 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14911 https://www.ncrm.ac.uk/training/show.php?article=14399 Level: Professional (P)This online training course will be delivered over 4 afternoon sessions, running from 1:00pm to 5:00pm on each day. This course will cover R object-oriented programming techniques. It will discuss what OOP is and the different varieties within R. Beginning with the popular S3 and S4 OOP frameworks, we’ll finish with the new {R6} package that is used extensively in Shiny applications. The course will then introduce the {rlang} package as a way of parsing variables from a data set into a function. Furthermore, it cover environments and function-evaluation in R, to help you understand how the tools in {rlang} work under the hood. This course will be delivered over 4 sessions. Course Outline This course will cover the following topics:Advanced Functions: Scoping rules (including lexical scope), The … argument, Argument matchingS3 classes: Introduction to object-oriented programming, Constructing S3 objects, DrawbacksS4 classes: Creating and using S4 classes, Differences between S3 and S4 classesR6 classes: Differences between {R6} and S3/S4, Mutable states, Creating methods, Shallow and deep copiesModifying user argument in functions callsQuoting code with quosuresUsing quasi quotation Learning outcomesBy the end of this course, delegates will be able to :Select the most appropriate form of OOP for their taskLeverage encapsulation, polymorphism and inheritance to provide a nice user interface to their codeWrite functions with rich results, user-friendly display and programmer-friendly internalsExtend the functionality of functions for new object typesWrite code that is extensible by othersUse the {rlang} operators {{}}, !!, !!! and := to pass variablesModify user functions using enquo()Parse and deparse expressions Target AudienceThis course assumes that participants are comfortable with the fundamentals of R programming. As such the course will be of interest to anyone who uses R, in particular those who want to develop their computer skills to cover more advanced topics. Delegate Feedback ““Extremely good teacher, great explanations, funny examples and very flexible in terms of content and time. I got to know a lot of things, that I did not think were possible.” “Material well presented and delivered” ”I am not scared of R anymore. It was actually fun!”“Really great course! Useful content that will greatly benefit me in my future R projects.” training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14399 https://www.ncrm.ac.uk/training/show.php?article=14397 Level: Professional (P)This online training course will be delivered over 4 afternoon sessions, running from 1:00pm to 5:00pm on each day. This course will cover R object-oriented programming techniques. It will discuss what OOP is and the different varieties within R. Beginning with the popular S3 and S4 OOP frameworks, we’ll finish with the new {R6} package that is used extensively in Shiny applications. The course will then introduce the {rlang} package as a way of parsing variables from a data set into a function. Furthermore, it cover environments and function-evaluation in R, to help you understand how the tools in {rlang} work under the hood. This course will be delivered over 4 sessions. Course Outline This course will cover the following topics:Advanced Functions: Scoping rules (including lexical scope), The … argument, Argument matchingS3 classes: Introduction to object-oriented programming, Constructing S3 objects, DrawbacksS4 classes: Creating and using S4 classes, Differences between S3 and S4 classesR6 classes: Differences between {R6} and S3/S4, Mutable states, Creating methods, Shallow and deep copiesModifying user argument in functions callsQuoting code with quosuresUsing quasi quotation Learning outcomesBy the end of this course, delegates will be able to :Select the most appropriate form of OOP for their taskLeverage encapsulation, polymorphism and inheritance to provide a nice user interface to their codeWrite functions with rich results, user-friendly display and programmer-friendly internalsExtend the functionality of functions for new object typesWrite code that is extensible by othersUse the {rlang} operators {{}}, !!, !!! and := to pass variablesModify user functions using enquo()Parse and deparse expressions Target AudienceThis course assumes that participants are comfortable with the fundamentals of R programming. As such the course will be of interest to anyone who uses R, in particular those who want to develop their computer skills to cover more advanced topics. Delegate Feedback ““Extremely good teacher, great explanations, funny examples and very flexible in terms of content and time. I got to know a lot of things, that I did not think were possible.” “Material well presented and delivered” ”I am not scared of R anymore. It was actually fun!”“Really great course! Useful content that will greatly benefit me in my future R projects.” training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14397 https://www.ncrm.ac.uk/training/show.php?article=14899 In this one-day online training workshop you will be introduced to four qualitative research methods to better understand diverse lives - Photo Go-Alongs, Collage, Life History Interviews and Participant Packs. When researching social groups, researchers may focus on categories such as age, gender, sexuality and so on. These categories can turn catch-all terms into catch-all agendas. Treating groups of people with one shared characteristic as homogenous risks a cookie-cutter approach which overlooks diverse lives and needs. Given the complexity of what it means to be a person, a one-size fits all approach to engagement cannot suffice. The methods introduced in this training workshop are beneficial in exploring diverse lives and can be used when researching with any group. The session is aimed at PhD students and academics of all career stages across the UK who want to better understand: The specific place-based needs of people The everyday practices of peopleThe world from participants’ perspectivesHow to work with people in an inclusive and accessible wayThis online training workshop will be structured as follows:  IntroductionsOrigins and Approach Methods deep dive: * Photo Go-Alongs* Participant packs* Collage * Life Histories Workshops Learnings and close By the end of the course participants will:Be able to think critically about how creative, participatory methods might be incorporated into their research and/ or teaching. Have broadened their understanding of research methods from tools of data collection to techniques for capacity building.Have workshopped four qualitative methods for creatively engaging with people (Photo Go-Alongs, Collage, Life Histories and Participant packs).This online course will take place on Wednesday 9 December from 10:00 - 16:00, with 1 hour for lunch from 12:30 - 13:30.  jmh6@soton.ac.uk (NCRM, University of Southampton) Thu, 09 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14899 https://www.ncrm.ac.uk/training/show.php?article=14392 Level: Intermediate (I)Multiple linear regression is one of the most commonly used techniques in statistics and allows for the impact of multiple variables to be assessed simultaneously. The analysis of variance (ANOVA) is a related technique which allows the mean values of several groups to be compared. This course will utilize Jamovi's free software, to equip participants with the skills necessary to undertake both types of analysis, understand and interpret the output, check the assumptions that underpin each type of model, and present the results coherently. This course will be delivered over two morning sessions, running from 9:30am to 1:00pm on both days.Learning OutcomesBy the end of this course the attendees will:       Understand what is meant by the term Analysis of Variance (ANOVA) and the different ANOVA models availableAssess when it is appropriate to fit an analysis of varianceInterpret the result s of an analysis of varianceAssess model fitPresent the results of an analysis of varianceUnderstand what is meant by the term multiple linear regressionAssess when it is appropriate to fit a multiple linear regression modelCarry out a regression analysis using free softwareInterpret the results of a multiple linear regression analysisAssess model fitPresent the results of a multiple linear regression analysis      Topics CoveredThe first day will start with a brief recap on the concepts of hypothesis testing and choosing the right test. This will include the basic use of Jamovi software to carry out and interpret an independent t-test before progressing to the related technique ANOVA.  Assumption checking, two-way ANOVA’s and interactions will conclude the morning. The second day starts with correlation and simple linear regression to assess the relationship between two continuous variables before concentrating on multiple regression which allows multiple variables to be tested simultaneously. Both sessions will concentrate on producing and understanding outputs rather than mathematical content with regular exercises to reinforce learning. Target AudienceThis course is aimed at individuals who have some basic statistical knowledge and who wish to undertake analyses of quantitative data and who therefore wish to gain some insight into how to undertake these. Knowledge AssumedBasic statistical knowledge as the course is designed as a follow-on from our Basic Statistics course.Delegates will need to download the latest version of Jamovi onto their laptop as this will be used during the workshop: https://www.jamovi.org/download.html training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14392 https://www.ncrm.ac.uk/training/show.php?article=14838 Learn the essential principles of research project management at your own pace.This practical online self-study course will equip you to better manage any type of research – at whatever stage of your career – so you can:Identify the key skills every research project/programme manager needsUnderstand which skills are most in demand – inside and outside of academiaExplore the four core research project management stages necessary for delivering research objectives on time and on budgetFind out how to get up to speed on any project – at whatever stage you join itDiscover the Top 10 challenges research project managers face and tried and tested solutions for handling themShow funders that your project will complete within timeframe and resource limitations.Take away simple tools, templates and checklists to help you:Identify project stakeholders and prioritize their needsAssess the impact of potential risks to your research and discover tried and tested strategies for overcoming the most common threatsIdentify what skills and resources your project needs to achieve its objectivesBreak your project into manageable tasksWork out how long it should take to complete any given projectIdentify the critical activities you’ll need to monitor closely to make sure you complete your research as plannedTrack any project through to completion...…and much more!Additional benefits:Eight modules, fully recorded over 27 video lectures (no live component)Take away simple tools, templates and checklists you can use to manage any research projectSix months access to all video lectures and course materials. contact@evaluationworks.co.uk (Evaluation Works) Wed, 06 May 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14838 https://www.ncrm.ac.uk/training/show.php?article=14941 The aim of this interactive workshop is to explore creativity within research, to identify opportunities to use creative methods within the research process and to explore the foundations and theoretical underpinning related to these methods in qualitative research.We discuss what creativity is, why we should be creative in research and how we can introduce creativity and creative methods in our existing paradigms and methods. Subsequently, delegates actively experiment with "pick a card" and "diamond 9" activities, photo elicitation, and the process of creating representations of experiences. Delegates also have opportunities to consider creativity within diary methods and observations as data collection. Creative research methods have been found particularly helpful in yielding rich qualitative data and thus provide a deeper insight into research participants' experiences. All tasks are explored in view of 4 guiding questions allowing delegates to focus on practical, methodological and ethical considerations regarding the approaches presented.In line with the pedagogical principles of social constructivism the course is delivered as a mixture of interactive group tasks, discussions and lectures to enable active and experiential learning. This workshop can be taken on its own or in conjunction with the workshop "Creative Data Analysis".Looking to book for six or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses. training@the-sra.org.uk (Social Research Association) Tue, 11 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14941 https://www.ncrm.ac.uk/training/show.php?article=14907 New to the CLS cohort studies? This webinar will give you an overview of four internationally renowned national cohort studies and the wide range of opportunities they offer to researchers.About the eventThis flagship CLS webinar will give first-time users an insight into four world-leading cohort studies. These studies follow generations born between 1958 and 2002 and are a powerful resource for addressing a wide range of scientific questions in various social, economic, health, political and geographical sciences. The data are free to download from the UK Data Service. What’s covered?You will learn about the data collected in each study, possible research topics, how to access and get started with the data and examples of the types of analyses that can be undertaken using the following studies: 1958 National Child Development Study 1970 British Cohort Study Next Steps Millennium Cohort Study. Why attend?Gain an overview of the type of research topics that the data could offer.Find out about the types of analyses that can be performed with the data.Learn how the cohort studies could be used in coursework or dissertations.Discover how to access and get started handling the data.Get answers to specific questions about the cohort studies and how to use them.Who should attend?This webinar is suitable for a wide range of researchers including: postgraduate students (Masters and PhD) interested in using the cohorts for a dissertation or thesisundergraduate students looking for data resources for their final year dissertationresearchers in academia (particularly early career researchers)researchers in the public or the third sector new to the cohort studies.  radhika.jhamaria.23@ucl.ac.uk (UCL Centre for Longitudinal Studies) Wed, 22 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14907 https://www.ncrm.ac.uk/training/show.php?article=14940 Focus groups are a popular qualitative research method which allow us to explore a variety of views and experiences from participants. They produce a particular type of qualitative data via the interaction which participations have with each other and the activities they engage in. As a qualitative method, focus groups also rely on effective moderation and facilitation skills. This online interactive course helps participants to improve the quality of their focus groups and moderation skills, and provides strategies to help them generate a participative and effective focus group discussion.The course aims to give participants a clear understanding of when and how to use focus groups as a qualitative method and to provide first-hand experience of one of the key roles: moderator and group member. We also consider research ethics, how to modify the style and approach depending on the sensitivity of the topic, and the nature of the participants. Although the focus is primarily on in person focus groups, participants will consider strategies for conducting focus groups in both in-person and online settings, and the different challenges these focus group styles present for moderators. Through practical hands-on activities on designing focus group schedules and moderation, participants will gain skills in focus group design, questioning, moderation, and facilitation.By the end of the course, participants will have knowledge of focus groups as a qualitative method and the type of data they generate. They will have knowledge of the role of the moderator and how to effectively design, plan and conduct a focus group. They will also have an awareness of the different ways in which focus groups can be facilitated (i.e. in-person, online, text) although the focus of this course will be on designing and facilitating in-person focus groups.Looking to book for four or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses. training@the-sra.org.uk (Social Research Association) Tue, 11 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14940 https://www.ncrm.ac.uk/training/show.php?article=14894 OverviewLearn how to review literature and analyse documents efficiently and systematically with NVivo Learning objectivesBy the end of the course, participants will be able to:Differentiate types of literature review and document analysisMake an informed decision as to an appropriate methodology for their needsDevelop a framework for undertaking a literature review and/or document analysis systematicallyNavigate digital tools designed to facilitate literature reviewing and/or document analysisKnow where to go for more resources and advice in undertaking a literature review and/or document analysis Who is this course for?This course is designed for postgraduate students and early career researchers in any discipline working on or planning for a literature review or documentary analysis. No prior knowledge of NVivo is required. Course overview and aimsNVivo can be harnessed to organise a range of types of materials and our ideas about them. This includes electronic copies of journal articles, and documents such as reports, public records and policy statements, amongst other materials. Framed by reviewing and documentary analysis methodologies, this course provides an introduction to NVivo’s powerful tools that facilitate in-depth analysis of individual items, as well as cross-item comparison; all with a view to enabling structured, efficient writing of findings. TopicsTypes of literature review & document analysis – differentiating review methodologies and understanding their purposesReview and analysis questions – developing focused questions to guide reading and appraising literature and documentsPlanning a literature review or document analysis – considerations in ensuring reviews and analyses are efficient and systematicTasks involved in reviewing literature and analysing documents - working directly and indirectly with literature and documentsDigital tools for reviewing and analysing literature and documents – understanding the different role of bibliographic software and the tools available in NVivoStructuring notes and writing up – tying report-writing with review objectives and sharing with different audiences Format and documentationAll our workshops are hands-on, delivered through a blend of demonstration, discussion and practical exercises, rather than providing simplistic, mechanical instruction.To deliver as tailored an experience as possible, we contact you on enrolment in order to understand your research goals and analytical strategies. Additionally, our participant numbers are capped to a small group size and we run our courses with two facilitators, allowing us to cover the core topics, as well as specialist needs arising out of individual projects.Participants are provided with slide decks, reading lists and a range of resources to accompany the course and to support consolidation of the topics covered.Participants must have access to NVivo on either a Windows or Mac machine. The course will be taught on NVivo v15, however, participants running NVivo 12 or later are also able to follow the course.A two-week trial version of the software is available free of charge from the NVivo website. Feedback from previous attendees"The trainers are knowledgeable, passionate and witty . They were able to carry the group and have our full attention during the entire session. Highly recommend to anyone who is doing or planning to do a literature review""Working hands-on in the software in tandem with the course leaders, cementing the learning. This makes me confident that I will be able to use the information going forward in my own work.""All of it was really useful thank you so much! Really practical and meaningful." FacilitatorsChristina Silver, PhD is the director of Qualitative Data Analysis Services and manager of the CAQDAS Networking Project at the University of Surrey, UK. Christina’s interests relate to the relationship between technology and methodology and the effective teaching of qualitative methods and digital tools. She is co-author of Using Software in Qualitative Research: A Step-by-Step Guide (Sage publications, 2007, 2014) and Qualitative Analysis using ATLAS.ti/MAXQDA/NVivo: The Five-Level QDA® Method (Routledge 2018). Christina has trained more than 11,000 researchers around the world in qualitative methods and the use of digital tools for analysis, since 1998, and is a Fellow of the UK Academy of Social Sciences.Sarah L Bulloch, PhD is a senior associate of Qualitative Data Analysis Services and teaching fellow at the CAQDAS Networking Project at the University of Surrey, UK. Sarah has expertise in both qualitative and quantitative analysis techniques and has applied them in academic, public sector, private and third sector contexts. Her current work and research centres around enabling others to apply research methods, and the digital tools to support them, in a meaningful, robust and flexible way. Sarah first used CAQDAS packages in 2006 and started teaching them in 2010. About QDAS | Qualitative Data Analysis ServicesQDAS provide tailored and flexible training, consultancy, coaching and analysis for qualitative and mixed-methods researchers. We specialise in facilitating high-quality analysis through the powerful use of digital tools. Our website provides information about our work, including our pedagogy - the Five-Level QDA method, which underpins the way we think about, undertake and teach methods and tools. info@qdas.co.uk (QDAS | Qualitative Data Analysis Services) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14894 https://www.ncrm.ac.uk/training/show.php?article=14939 Qualitative interviewing is a popular method in social research and it is often described as a conversation between interviewer and interviewee. It allows us to collect detailed and rich information about individuals’ lives, their experiences, behaviours, and how they understand and make sense of the world. The rich insight it provides into people’s lives is one of the benefits which the method offers over standardised surveys or questionnaires.This introductory level course introduces participants to the method of qualitative interviewing. This includes its benefits, examples of effective interviewing, and the key ethical and practical issues to be considered. We look at types of qualitative interview which include structured, unstructured and semi-structured interviews. In particular, we explore the benefits of semi-structured interviewing which involves a combination of pre-set open ended questions with room for the exploration of other (sometimes unanticipated) topics. Participants gain experience of designing their own interview schedule and of conducting a semi-structured interview.By the end of the workshop, participants will have knowledge of various forms of qualitative interview and theories of interviewing. They will be able to distinguish between various types of interviews and questioning. They will be aware of practical and ethical issues which must be considered prior to interviews. They will also be able to design their own semi-structured interview schedule and conduct a semi-structured interview.Looking to book for six or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses. training@the-sra.org.uk (Social Research Association) Tue, 11 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14939 https://www.ncrm.ac.uk/training/show.php?article=14384 Level: Foundation (F)The course will be delivered over 5 morning sessions, running fro 9:00am to 1:00pm each day. The purpose of this course is to help participants understand some basic statistical concepts and develop a strategy for approaching simple data analysis. The course will introduce basic concepts such as hypothesis testing and confidence interval estimation. It will provide the tools to undertake simple analysis of a dataset and will include some helpful hints and tips for reading and understanding reported statistics.Learning OutcomesBy the end of this course, participants will understand basic approaches to statistical inference, including hypothesis testing and confidence interval estimation. They will be equipped with the skills necessary to undertake simple analysis and to understand some of the basic terms often used to report statistical results. The course will include some calculations by hand to aid understanding. Topics CoveredData Summary; The normal distribution; Confidence intervals; Introduction to hypothesis tests; Analysis of contingency tables – chi-squared test;  T-tests; Non-parametric tests, (Wilcoxon signed rank test, Mann-Whitney U test); Introduction to correlation and regression; Basic presentation of data and results. Target AudienceThis course is aimed at those who have either never undertaken a formal statistics course, or who have studied some statistics in the past but wish to undertake a refresher. It is ideal for statistical novices who have never had any formal training but are starting to encounter statistics in their work and wish to gain some insight.Delegate Feedback"Ellen and Jenny were extremely knowledgeable. They were also approachable and happy to give further explanations when necessary""Excellent course. Hard to fault. I can see why it's popular""This was a fantastic course, the presenters had a very high knowledge but were able to 'dumb it down' for me as I am new to this"  training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14384 https://www.ncrm.ac.uk/training/show.php?article=14938 One of the most popular software tools for data management and analysis is the open source package R, which is often used with the Rstudio interface. These are extremely powerful and are able to handle most types of data and analyses used in social research.In this course you will learn the basics of R and Rstudio. We will cover the main types of objects in R and how to select cases and variables. We will also discuss how to import and export data and how to describe the data using tables and summary analyses. Through the practical exercises you will get accustomed to running functions in R and using the syntax.IMPORTANT: participants will need to have a working knowledge of quantitative data.Looking to book for six or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house training. training@the-sra.org.uk (Social Research Association) Tue, 11 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14938 https://www.ncrm.ac.uk/training/show.php?article=14920 Anyone asked to conduct a research or evaluation project or study - small or large - faces the challenge of how best to manage this. University and professional training in research (and evaluation) principles and methods have long neglected this vital aspect of successfully delivering projects. More recently, shrinking budgets and timetables (but not expectations) have added to the challenges for principal investigators and others leading the design and delivery of projects and intensified the need for more structured approaches to project management. Using a mixture of shared slides, interactive sessions and exercises in small groups, this practical course provides an intensive introduction to how to rise to these challenges using tried and tested methods. It is aimed at participants from all sectors, those new to project management in research and evaluation, and those who may have some experience but are looking to widen their knowledge of structured approaches.NB. A parallel course, Management for Commissioned Research and Evaluation, focuses on the different project management challenges and skills needed for those specifying and commissioning externally contracted projects. The two separate courses can be taken separately over one day or together over two consecutive days.Looking to book for six or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house training. training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14920 https://www.ncrm.ac.uk/training/show.php?article=14919 Project leaders, analysts, contract managers and others involved in commissioning or funding ‘external’ research, or evaluation studies face special challenges in managing for their effective delivery. They typically need to successfully navigate the appropriate scoping and specification of the project, the commissioning process and selection of well-placed contractors as well as subsequent contract scrutiny and management to provide for responsive delivery and where pressures on budgets and often intensive timetables add to the challenges of doing this well. This course provides an intensive introduction to practical processes for managing externally contracted projects, working relationships and minimising delivery risks and challenges. It is aimed at participants from governmental and other public bodies, research councils, larger charities and other organisations commissioned research and evaluation studies.NB. A parallel course, Research and Evaluation Project Management for Project Leaders, focuses on the different project management challenges and skills needed for those designing and delivering commissioned or funded projects. The two separate courses can be taken separately over one day or together over two consecutive days.Looking to book for four or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses. training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14919 https://www.ncrm.ac.uk/training/show.php?article=14667 Overview of 2-day courseMixed models have become increasingly popular, as they have many practical applications. However, the traditional linear mixed model with normally distributed errors is not appropriate for modelling discrete responses such as binary data and counts. Such responses are typically analysed using generalised linear models such as logistic regression and Poisson regression.Commonly-used generalised linear models will be extended to deal with multiple error structures, using a variety of scientific examples, mainly medical and health related applications, such as investigating the presence of adverse events in a clinical trial.The emphasis will be on practical understanding, although an outline of the theory will be presented. Practical examples will be used to illustrate the methods and participants will have the opportunity to fit and interpret models themselves in hands-on computer practicals.Practical work will be based on the R software; see https://www.r-project.org/.  Model fitting will mainly be done using the CRAN package GLMMadaptivePresentersSandro Leidi and James Gallagher Cost£582 (inclusive of 20% VAT)Delivery ModeAll training is online and will be delivered live each day between 09:00 and 17:30 (GMT). Delivery platform: Zoom, which may be freely accessed.  Questions may be asked using Zoom's chat box.  Note our online courses are delivered by a team of two presenters, meaning at least one presenter is always available to provide additional support.  During presentations, the team member who is not speaking can take questions in addition to the presenter. We also use Zoom meetings rather than webinars to encourage further interaction during an online course.​Who Should Attend?Data analysts and statisticians working in medicine, health and related areas, who wish to have a practical introduction to Generalised Linear Mixed Models. It is assumed that participants are R users and familiar with the practical use of both generalised linear models and linear mixed models. How You Will BenefitYou will learn to formulate generalised linear models with both fixed and random effects for a range of situations, how to fit them and how to interpret their output.What Do We Cover?Review of generalised linear models and linear mixed modelsBinary and binomial outcomes: logistic regression with mixed effectsCount outcomes: Poisson and negative binomial regression with mixed effectsOrdered outcomes: proportional odds regression with mixed effectsAdaptive Gauss-Hermite Quadrature fitting method; inferential proceduresConvergence issues and solutionsInterpretation of effects in a generalised linear mixed model and predictionGLMMadaptive CRAN package for fitting generalised linear mixed models; ordinal CRAN package for fitting the proportional odds model with random effects.Notes on course content:The GLMMadaptive package can currently only fit models where the random effects part is defined by a single grouping factorThe course does not cover marginal or GEE type models for repeated measurements.SoftwarePractical work will be done in R.Note: For practical work, participants must download and install a number of CRAN packages in R.  This must be done prior to the start of the course. jamesgallagher1929@gmail.com (Statistical Services Centre Ltd) Mon, 12 Jan 2026 00:00:00 +0000 https://www.ncrm.ac.uk/training/show.php?article=14667 https://www.ncrm.ac.uk/training/show.php?article=14918 Over the years the discipline of evaluation has evolved and developed and is applied to many policies and practices. It forms the core of policy, accountability and strategic planning processes of many different types of organisations, and informs evidence-based decision making about public and grant funded programmes and initiatives. Much is expected of evaluation in the public, private and voluntary sectors and people responsible for commissioning, conducting and using evaluation are increasingly required to have a broad understanding of the evaluation types, skills and competencies. The course provides an introduction to this wide field and will be suitable for those new to evaluation and others who may have some experience but are looking to widen their knowledge of evaluation options and practice.*For those with more experience or needing more specialist methods, SRA also offers courses in Impact Evaluation (Advanced), Theory-based Evaluation (Advanced) and Research and Evaluation Project Management (Introductory).Looking to book for six or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house training. training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14918 https://www.ncrm.ac.uk/training/show.php?article=14809 JBI Scoping Review Workshop (Online Short Course) This JBI-accredited course covers the key principles, steps and reporting guidelines for undertaking a Scoping Review and explores how Scoping Reviews are different from Systematic Reviews. The course is delivered by experts from the University of Nottingham Centre for Evidence Based Healthcare and will run online over two days (November 19th & 20th 2026, 09:30-13:30 on each day).  catrin.evans@nottingham.ac.uk (University of Nottingham) Wed, 15 Apr 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14809 https://www.ncrm.ac.uk/training/show.php?article=14933 Course OverviewNavigating Qualitative AI: Ethical, Methodological and Practical ConsiderationsThe Navigating Qualitative AI course provides an introduction into developments, debates and practicalities in the role and use of Generative AI in Qualitative Research. The course is split into three modules combining synchronous and asynchronous learning to provide a comprehensive introduction to the principles, practices and ethics of using AI tools to facilitate the analysis of qualitative materials. Module 1: Mindsets for considering the use of AI for Qualitative ResearchModule 2: Harnessing Generative-AI tools for qualitative analysisModule 3. Integrating Generative-AI tools into qualitative analysis processesChoose from three pathways through the course according to your interests and needs (note, to take Module 2 or 3 it is a pre-requisite to have first completed Module 1):Pathway 1 – Module 1 onlyPathway 2 – Module 1 and 2Pathway 3 – Module 1 and 3Module 3. Integrating Generative-AI tools into qualitative analysis processes(Synchronous Delivery = hands-on guided exercises using selected tools, and discussion)This module comprises demonstrations and hands-on exercises focused on integrating the use of GenAI capabilities into existing qualitative analysis workflows, using selected qualitative analysis programs. The sessions combine demonstrations, hands-on exercises, and discussion about how integrating GenAI may impact practice. Using sample data, we consider a series of analytic tasks and methodological implications of use in different contexts, with different types of data and at different stages in the analytic process. The tools-focus in this module is on existing qualitative software programs, using NVivo and MAXQDA as core examples. The course covers:Principles of integrating AI tools into qualitative analysis processes - 16 November 2026 (13:30-16:45)Overview of the capabilities of established qualitative software programs (AI and non-AI tools)Ensuring analytic methods drive the use of AI tools Hands-on exercises using NVivoExploring MAXQDA’s AI tools for qualitative analysis - 18 November 2026 (13:30-16:45)Overview of MAXQDA’s tools Hands-on exercises integrating AI tools into a qualitative analysis process (using literature, transcripts and open-ended survey responses),By the end of the course participants will:Understand opportunities for the use of AI tools at different stages of the qualitative analysis workflowUnderstand the methodological consequences of using AI tools (potentials and risks)Identify skills in harnessing AI tools in ways that enable human-centred approachesThis course is aimed at students and researchers interested in qualitative analysis, within any sector or discipline. Participants must have attended Module 1 in order to attend this module.The course takes place over two afternoons (16 and 18 November) and equates to one teaching day for payment purposes. This page is for Module 3: Integrating Generative-AI tools into qualitative analysis processesIf you wish to register for Modules 1 or 2, please do so here:Module 1 - Mindsets for considering the use of AI for Qualitative Research - 30 Sept and 1 OctModule 1 - Mindsets for considering the use of AL for Qualitative Research - 2 and 4 NovModule 2 - Harnessing Generative-AI tools for qualitative analysis - 12 and 13 Oct jmh6@soton.ac.uk (NCRM, University of Southampton) Wed, 05 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14933 https://www.ncrm.ac.uk/training/show.php?article=14917 This introductory course provides an overview of the key principles and procedures in mixed methods research. Mixed methods research can be a valuable approach when conducting research on complex topics that cannot be fully understood by quantitative or qualitative research alone. The course covers the theories behind mixed methods research, why to use mixed methods research and how to integrate the quantitative and qualitative elements of your research. We will focus on how to design and conduct mixed methods research and how to present and report mixed methods findings.Attendees are provided with guidance and will have the opportunity to discuss their projects and how they can use mixed methods research in their work. This course will benefit those involved in research in a variety of sectors and disciplines, and only a basic understanding of quantitative and qualitative research methods is required.Looking to book for six or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14917 https://www.ncrm.ac.uk/training/show.php?article=14893 OverviewGetting started with NVivo: a comprehensive introduction to qualitative data analysis. Learning objectivesBy the end of the course, participants will be able to:Strategies and tactics in qualitative research – the importance of methodology and how research objectives drive the use of software toolsData formatting – transcription protocols that maximise functionality in NVivoSetting up a project – structuring the NVivo workspace in line with your objectivesExploring data – in-depth annotation and initial high-level explorationsConceptualising data – interpretive and inductive coding compared with automated coding optionsOrganising data – attaching socio-demographics or other meta-data to the units in your analysisInterrogating and visualising data – uncovering relationships and mapping ideas Who is this course for?This course is designed for postgraduate students and early career researchers in any discipline working on or planning to work with interview or focus group data.No prior knowledge of NVivo is required. Course overview and aimsNVivo can be harnessed to manage, analyse and interpret any qualitative materials. This course focuses on harnessing NVivo when working with primary data generated from conversations with participants through interviews and focus-group discussions. It is framed by the Five-Level QDA® method, which provides an adaptable framework for ensuring the tools you use in NVivo are driven by the methodological needs of your project.The course provides a comprehensive overview of NVivo by introducing its core components using sample transcripts and course participants are facilitated in using the software in guided hands-on sessions. We discuss common approaches to analysing interview and focus-group transcripts, open-up thinking about how to appropriately choose between them and provide a framework for planning and documenting your analysis. TopicsStrategies and tactics in qualitative research – the importance of methodology and how research objectives drive the use of software toolsApproaches to analysing interview and focus-group transcripts – commonly used analytic approaches for interview and focus-group data and their appropriateness to your objectivesPlanning an analysis – the purpose and use of Analytic Planning WorksheetsData formatting – transcription protocols that maximise functionality in NVivoSetting up a project – structuring the NVivo workspace in line with your objectivesExploring data – in-depth annotation and initial high-level explorationsConceptualising data – interpretive and inductive coding compared with automated coding optionsOrganising data – attaching socio-demographics or other meta-data to the units in your analysisInterrogating and visualising data – uncovering relationships and mapping ideas Format and documentationAll our workshops are hands-on, delivered through a blend of demonstration, discussion and practical exercises, rather than providing simplistic, mechanical instruction.To deliver as tailored an experience as possible, we contact you on enrolment in order to understand your research goals and analytical strategies. Additionally, our participant numbers are capped to a small group size and we run our courses with two facilitators, allowing us to cover the core topics, as well as specialist needs arising out of individual projects.Participants are provided with slide decks, reading lists and a range of resources to accompany the course and to support consolidation of the topics covered.Participants must have access to NVivo on either a Windows or Mac machine. The course will be taught on NVivo v15, however, participants running NVivo 12 or later are also able to follow the course. A two week trial version of the software is available free of charge from the NVivo website Feedback from attendees"Really helpful (and impressive!) that both hosts were very knowledgeable about how to use NVivo on both Mac and Windows.""Sarah and Christina’s style of teaching is spot on! Super clear, straightforward and to the point. What a great learning experience. Thank you.""Christina and Sarah are extremely positive and engaging and very supportive when queries are raised. They have so much knowledge and experience and explain very clearly in plain English""As a standalone course - it is very useful and helpful and they are probably the best, or at least, one of the best presenters for online learning courses that I have done. ""The training materials were effective, particularly due to the helpfulness of the instructors. The hands-on training approach made the one-day online session engaging and interactive, ensuring that it never felt boring. Time truly flew by during the training! I especially appreciated the detailed explanations about NVivo, which have significantly boosted my confidence in how to approach my research. Overall, I found the training to be extremely useful, providing me with valuable skills and insights that I can directly apply to my work. Thank you for the excellent training experience!" FacilitatorsChristina Silver, PhD is the director of Qualitative Data Analysis Services and manager of the CAQDAS Networking Project at the University of Surrey, UK. Christina’s interests relate to the relationship between technology and methodology and the effective teaching of qualitative methods and digital tools. She is co-author of Using Software in Qualitative Research: A Step-by-Step Guide (Sage publications, 2007, 2014) and Qualitative Analysis using ATLAS.ti/MAXQDA/NVivo: The Five-Level QDA® Method (Routledge 2018). Christina has trained more than 11,000 researchers around the world in qualitative methods and the use of digital tools for analysis, since 1998, and is a Fellow of the UK Academy of Social Sciences.Sarah L Bulloch, PhD is a senior associate of Qualitative Data Analysis Services and teaching fellow at the CAQDAS Networking Project at the University of Surrey, UK. Sarah has expertise in both qualitative and quantitative analysis techniques and has applied them in academic, public sector, private and third sector contexts. Her current work and research centres around enabling others to apply research methods, and the digital tools to support them, in a meaningful, robust and flexible way. Sarah first used CAQDAS packages in 2006 and started teaching them in 2010. About Qualitative Data Analysis ServicesQDA Services provide tailored and flexible training, consultancy, coaching and analysis for qualitative and mixed-methods researchers. We specialise in facilitating high-quality analysis through the powerful use of digital tools. Our website provides information about our work, including our pedagogy - the Five-Level QDA method, which underpins the way we think about, undertake and teach methods and tools. info@qdas.co.uk (QDAS | Qualitative Data Analysis Services) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14893 https://www.ncrm.ac.uk/training/show.php?article=14876 Overview of 1-day courseAre you working in Learning Analytics or Student Analytics?Ever been asked for the margin of error on a percentage?Or if the difference between your percentage and a benchmark is statistically significant?Or if the change in student retention rate from last year is statistically significant?This one-day course provides participants with hands-on experience of analysing their own type of records for data-driven planning and confidently interpreting numerical results for reports to policy makers and committees, or for returns to the Higher Education Statistics Agency.Presentations, demonstrations and hands-on computer practicals will make use of the free statistical software R; see https://www.r-project.org/.  Note the course does not focus on teaching R, but on the use of supplied R functions to perform statistical analyses of interest.  Formulae are kept to a minimum; instead, we concentrate on results, their interpretation and reporting in plain language.​PresentersSandro Leidi and James GallagherCost£282 (inclusive of 20% VAT)Delivery ModeAll training is online and will be delivered live between 09:00 and 17:30 (GMT).  The delivery platform is Zoom, which may be freely accessed.  Questions may be asked verbally or using Zoom's chat box.  Note our online courses are delivered by a team of two presenters, meaning at least one presenter is always available to provide additional support.  During presentations the team member who is not speaking can take questions in addition to the presenter. We also use Zoom meetings rather than webinars to encourage further interaction during an online course.​Who Should Attend?Administrators in educational establishments working in Policy, Planning and Strategy units; Data and Insight units; Business Intelligence units; those involved in learning analytics or extracting actionable insights from student records and in reporting to policy makers or committees; those involved in producing returns to the HESA.  Anyone in these positions will benefit greatly from this course.No previous experience of the R software is required.How You Will BenefitBy the end of the course you will be familiar with basic statistical methods for making sound assessments, and extracting actionable insights.  What Do We Cover?Estimation: standard errors and confidence intervals for percentagesComparing a percentage to a benchmark: one-sample z-testComparing two percentages: two-sample z-testComparing more than two percentages: chi-square test.The course will make use of our R functions which will be made freely available. Note the course does not focus on teaching R, but on the use of the supplied R functions to perform statistical analyses covering the above syllabus.SoftwarePractical work will be done in R.Note:For practical work, participants must download and install the R software.  This must be done prior to the start of the coursePractical work is based on the Windows operating system.Extra InformationThe content of this course is identical to that of Statistics for University Administrators. The only difference is the R statistical software is used instead of Excel.  R has two advantages:It is a free dedicated statistics package and can be used for other analysesIt is a widely used software which will be maintained by the R Foundation for many years to come. jamesgallagher1929@gmail.com (Statistical Services Centre Ltd) Tue, 16 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14876 https://www.ncrm.ac.uk/training/show.php?article=14404 Level: Intermediate (I)This course will be delivering over 4 afternoon sessions, running from 1:00pm to 5:00pm each day.This course covers the fundamentals of machine learning and the methodology for applying these to real-world analytics problems. The course outlines the stages involved in a machine learning analysis, and walks through how to perform them using the R programming language and the tidymodels suite of packages. Participants will be provided with exercises to complete through the course in order to gain hands-on experience in using the methods presented.The individual stages of: problem formulation, data preparation, feature engineering, model selection and model refinement will be walked through in detail giving participants a solid process to follow for any machine-learning analysis. This includes methods for evaluating machine-learning models in terms of a performance metric as well as assessing bias and variance.  Learning OutcomesFollowing this course the attendees will:Be familiar with the overall process of how to apply machine-learning methods in an analysis projectUnderstand the differences and similarities between statistical modelling and machine-learning theoriesHave gained hands-on experience in working with the tidymodels suite of packages in RGain an intuitive understanding of how several specific machine-learning methods solve the problems of prediction and classification Topics CoveredIntroduction to machine-learning: parsnip package; basic train and testStages of machine-learning: problem formulation; data preparation; feature engineering; model selectionHighlighted Models: Decision trees and random forests; K-nearest neighbours, linear regression and logistic regression. Target AudienceMachine Learning can be applied to data in a whole range of fields from Finance to Pharmaceutical, Retail to Marketing, Sports to Travel and many, many more! This course is aimed at anyone interested in applying machine learning methods to their data in order to: gain deeper insight, make better decisions or build data products Assumed KnowledgeThis course assumes participants are comfortable with the basic syntax and data structures in the R languageFor this online course, participants are not required to have R installed on their own laptops. A virtual environment, which can be accessed through a web browser, will be used to run R and view course materials. training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14404 https://www.ncrm.ac.uk/training/show.php?article=14916 Research design always has to spell out how to gather data in a way that helps researcher(s) tackle the main aims and questions of a project. When those aims and questions are already fixed, as they usually are when responding to a tender, the focus shifts to creating a design that is realistic, convincing, and gives the researcher(s) what they need to deliver the project.This course will give participants a live experience of qualitative research design. We will work collectively and in small groups using a sample tender to scope out the multiple ways in which it would be possible to approach the research. We will draw on established and novel research methods and different combinations of both, to show the variety of options available to participants when they undertake qualitative research. We will consider the relationships between research questions, data and analysis; and the key issues of sampling, access, engagement, timing and ethics.By the end of the course, participants will have gained new knowledge and experience of qualitative research design. They will have a good understanding of relevant practical and ethical issues, and be in a position to propose robust designs that meet the needs of relevant calls for tender.Looking to book for four or more people from your organisation? Please let us know before booking by emailing: training@the-sra.org.uk training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14916 https://www.ncrm.ac.uk/training/show.php?article=14915 Artificial intelligence and large language models (LLMs) are becoming part of everyday social research, being used in everything from literature reviews to survey question development, analysis and reporting. This course will equip participants with the tools to understand the current capabilities of these models and how to use them effectively in the quantitative research workflow.The course starts by introducing key concepts such as AI, machine learning, and Large Language Models (LLMs) in non-technical language. It then discusses the stages of quantitative research and how LLMs can be used effectively at each stage. Participants will learn how to choose between different types of tools, such as chatbots, in-editor assistants, and coding agents, and why instructions, context, tools, and human review shape what LLM systems can do.The course is a mix of lectures covering key concepts in non-technical terms, workflows, and examples, as well as hands-on practicals where researchers can apply key concepts to real-world problems to better understand the strengths and limitations of these tools.Looking to book for four or more people from your organisation? Please let us know before booking by emailing: training@the-sra.org.uk training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14915 https://www.ncrm.ac.uk/training/show.php?article=14914 A well designed theory-based evaluation (TBE) helps unpick the often unclear expectations and assumptions which underlie new policy, programmes and initiatives. It can go well beyond measuring what comes out of an intervention to better understand what works (and what doesn’t), and why, and what may be holding it back from working better. Although not a new approach, its use has been held back by confusion about the different approaches to TBE, and a lack of practitioner knowledge about how to apply these promising methods. The course will provide a practical introduction to TBE principles, setting out different ‘layered’ options and approaches and practical examples of how it can be used in often complex social and community development contexts. This online course provides a more flexible opportunity for an introduction to TBE. It shares much of the same content as the ‘face to face’ SRA course and is led by the same tutor.Looking to book for six or more people from your organisation? Contact us to find our more about our in-house training: training@the-sra.org.uk training@the-sra.org.uk (Social Research Association) Wed, 29 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14914 https://www.ncrm.ac.uk/training/show.php?article=14906 About the eventThis webinar highlights the value of using lifecourse data to support physical health research using relevant measures available in four British cohort studies:1958 National Child Development Study (NCDS)1970 British Cohort Study (BCS70)Next StepsMillennium Cohort Study (MCS).Why attend?Learn about the types of physical health information collected, and examples of what we’ve already learned about physical health from the cohorts to help shape your own research questions.The session will include:an outline of physical health data and measures available in the CLS cohorts, including objective and self-reported anthropometrics, biomarkers, health behaviours and linked administrative dataan explanation of the process for accessing the data and resourcesa showcase of research using physical health measures in the cohortsan overview of research opportunities that the data can offera Q&A with our expert panel.Who should attend?This webinar will be beneficial for students, academics, third sector and policy individuals from across disciplines, and all career stages, who are interested in using physical health measures from the cohorts in their research. No prior experience of the data is required.It will also be of interest to those wishing to conduct cross-cohort analyses. radhika.jhamaria.23@ucl.ac.uk (UCL Centre for Longitudinal Studies) Wed, 22 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14906 https://www.ncrm.ac.uk/training/show.php?article=14891 Capturing the views and experiences of children and young people directly, rather than by proxy (e.g. through parents or professionals), is increasingly recognised as essential for sound research and policy development. Drawing on the tutors' extensive experience and expertise in this field, this long-running, practical, and highly interactive training provides an opportunity for participants to explore the ethical, methodological and real-world considerations of doing research and evaluation with children and young people, both face-to face and remotely.This online course runs over two half days which helps participants reflect on and consolidate the learning and how to apply it to their own work. We also run it in person, as a one-day course, usually about once per year.This course is very popular, and often run in-house as well. For more information about our in-house courses, contact training@the-sra.org.uk. training@the-sra.org.uk (Social Research Association) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14891 https://www.ncrm.ac.uk/training/show.php?article=14931 Course OverviewNavigating Qualitative AI: Ethical, Methodological and Practical ConsiderationsThe Navigating Qualitative AI course provides an introduction into developments, debates and practicalities in the role and use of Generative AI in Qualitative Research. The course is split into three modules combining synchronous and asynchronous learning to provide a comprehensive introduction to the principles, practices and ethics of using AI tools to facilitate the analysis of qualitative materials. Module 1: Mindsets for considering the use of AI for Qualitative ResearchModule 2: Harnessing Generative-AI tools for qualitative analysisModule 3. Integrating Generative-AI tools into qualitative analysis processesChoose from three pathways through the course according to your interests and needs (note, to take Module 2 or 3 it is a pre-requisite to have first completed Module 1):Pathway 1 – Module 1 onlyPathway 2 – Module 1 and 2Pathway 3 – Module 1 and 3Module 1. Mindsets for considering the use of AI for Qualitative Research (Synchronous Delivery = lectures, illustration, and discussion)This module provides essential context to considering the potential use of AI in qualitative projects, focusing on the current landscape of AI tools and their impact on qualitative research practice. Practical, ethical and methodological implications are discussed in relation to the contexts in which research and evaluation happen. The course covers:The landscape of Qualitative AI - 2 November 2026 (13:30-16:45)development of AI tools in qualitative research spacesethical considerations and how to navigate themmethodological consequences when using AI for qualitative analysisCritically engaging with the Qualitative AI space - 4 November 2026 (13:30-16:45)potential uses of AI throughout the qualitative workflowgenres of AI tools for qualitative data analysiswhen the use of AI is - and is not - methodologically appropriate By the end of the course participants will:Understand historical contexts of current developments in AI within in the Qualitative Research fieldUnderstand the range of ethical issues involved in using AI for Qualitative Research and how to navigate use in appropriate waysPossess critical thinking skills around the role of AI in different Qualitative Research contextsThis course is aimed at students and researchers interested in qualitative analysis, within any sector or discipline.The course takes places over two afternoons (2 and 4 November) and equates to one teaching day for payment purposes. This page is for Module 1: Mindsets for considering the use of AI for Qualitative Research. If you wish to register for Modules 2 or 3, please do so here:Module 2 - Harnessing Generative-AI tools for qualitative analysis - 12 and 13 OctModule 3 - Integrating Generative-AI tools into qualitative analysis processes - 16 and 18 Nov jmh6@soton.ac.uk (NCRM, University of Southampton) Wed, 05 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14931 https://www.ncrm.ac.uk/training/show.php?article=14797 Course detailsDate: Monday 2nd & Monday the 9th November 2026Time: 09:00 – 13:00Location: This is an online course conducted via ZoomDuration: 8 learning hoursWho this course is forThis course is ideal for people who have an awareness of evidence-based health. It's also useful for people who are in the process of or about to undertake a systematic review. Previous delegates have been:ResearchersHealthcare professionalsAcademic cliniciansEducation and policy commissionersMedical studentsPhD or MSc studentsLearning outcomesAfter completing this course, you will understand:What a systematic review isScoping the research question and writing a protocolLiterature searchingInclusion/exclusion screeningData extraction and critical appraisalData synthesisPlease note this course will NOT cover realist synthesis or qualitative analysis.This course is delivered by Southampton Health Technology Assessments Centre (SHTAC)Course Leaders:Jonathan ShepherdCourse TutorsGeoff FramptonEmma MaundKaren PickettJonathan ShepherdLois Woods  A.Vincent@soton.ac.uk (University of Southampton) Wed, 27 May 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14797 https://www.ncrm.ac.uk/training/show.php?article=14407 Level: Intermediate (I)This tutor-lead virtual course will introduce how the tidyverse and ggplot2 can be used to reproducibly create publication quality charts from R. Learning OutcomesReproducibly import and wrangle data with the tidyverse in preparation for charting with ggplot2. Confidently choose the appropriate geoms for visualising data with ggplot2. Understand how to use factors using the forcats package to control the display (or order) of chart elements. Effectively control the use of colours and themes in ggplot2 charts. Understand how to augment GIS data using sf and the tidyverse to be visualised with ggplot2. Reproducibly export publication quality charts for papers, posters and other printed media.Delegates are expected to have a laptop with the R software installed. Topics CoveredR, Data Visualisation, ggplot2, Data Presentation, Exploratory Data Analysis. Target AudienceThis course is designed for both novice and experienced R users who want to create publication quality printed charts with ggplot2. training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14407 https://www.ncrm.ac.uk/training/show.php?article=14390 Level: Intermediate (I)If you’re looking to improve the way you plan your work and improve efficiency by introducing statistical forecasting, then this course is ideal. By the end of the session you will have a firm grasp of how to summarise and measure trends, as well as how to extrapolate trends into a forecast. You will also have a good understanding of how to perform relevant calculations in Excel. This course is being delivered over two morning sessions, which will run from 9:00am to 1:00pm on both days.This course looks at one of the big questions in businesses -- finding out what is going to happen next. It would be so much easier to plan sales, purchases, production, staff and logistics if we knew the answer to this question! Many businesses know how important it is to forecast for the future, yet many fail to apply the fundamental concepts of statistical forecasting. Those that don’t use statistical forecasting face higher costs and uncertainty when reality diverges from their plans. Those that do use statistical forecasting are able plan for the future much more effectively and efficiently. Learning OutcomesUnderstand the distinction between sober & drunk time series (seriously!)Learn how to use hypothesis testing to confirm that a trend is a genuine trend.Learn how to use moving averages correctly to identify potential turning points.Discover the simplest method of identifying seasonality in your time series and to confirm it with hypothesis test.Uncover the basic principles of statistical process control and how you can use it to confirm deviations from an expected trend.Learn 4 different ways of extrapolating an existing trend to produce forecast. Topics CoveredTime series analysis, forecasting, trend identification, seasonality, moving averages, trend extrapolation, statistical process control, forecasting using extrapolations. Target AudienceAnyone involved in business planning, performance analysis and other similar roles that require analyses of historical trends and extrapolation of those trends to create forecasts. Course PrerequisitesThis course would be suitable for anyone who has completed our two day "Basic Statistics" course.Other participants should ideally have an understanding of the following:Basic statistical concepts including expectation, variance, distribution and correlation.Probability and risk including knowing what false positives and false negatives areKnow how to calculate of confidence intervals for the mean of 1 sample and the difference in means between 2 samples.Know how to calculate the slope and intercept of a simple regression models with 1 variableUse of Microsoft Excel including the use of formulae such as IF, VLOOKUP, OFFSET, etc.Produce and interpret line charts, column charts and scatter plots in Excel. training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14390 https://www.ncrm.ac.uk/training/show.php?article=14889 This one-day foundation course provides participants with an introduction to the key principles and benefits of qualitative research. This includes the main methods and techniques employed in qualitative studies such as interviews, focus groups and observations. It outlines how to design an effective qualitative research question, how to design research instruments, how to sample and recruit participants, data analysis, and related ethical considerations. It also considers how to assess a qualitative research project’s quality and rigour.Qualitative research seeks to understand people’s lived experiences and to answer questions about meaning and perspective, including from the standpoint of the participants themselves. It is particularly effective in obtaining culturally specific information about the values, views, behaviours, and contexts of particular groups. This foundational course provides an introduction to qualitative research tools and techniques which help us to answer these questions. It will equip participants with the knowledge, skills and confidence required to begin their own qualitative investigations.The course is delivered online via Zoom. It includes a combination of presentations, discussions and practical activities. It is designed to equip participants to confidently implement their own qualitative design in research projects in a range of contexts.Looking to book for four or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses. training@the-sra.org.uk (Social Research Association) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14889 https://www.ncrm.ac.uk/training/show.php?article=14887 The aim of this training session is to explore positionality, the role of the researcher and more specifically, the researcher's emotions within the process of qualitative research. Although emotions are a fundamental part of how the world is experienced, the researcher's emotional and bodily responses throughout the research process are often ignored.Drawing on embodied and creative techniques we explore practical strategies and undertake exercises to attend to and to become more aware of our physical being and thoughts. By practising conscious noticing, we discuss our being, assumptions and beliefs and how they impact research. Delegates learn about different approaches to when and how to tend to reflexivity considerations. Finally, we consider how to translate records of personal experiences into public reflexivity statements within research reports.The course is delivered as a mixture of interactive group tasks, discussions and lectures to enable active and experiential learning.Looking to book for four or more people from your organisation? Please let us know before booking by emailing: training@the-sra.org.uk training@the-sra.org.uk (Social Research Association) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14887 https://www.ncrm.ac.uk/training/show.php?article=14692 Want to learn more about mixed methods research? Need support or advice with your mixed methods research? Our online course could help you!The ‘Introduction to Mixed Methods Research’ course from (Methodical) will be delivered by experienced mixed methods researchers Dr Sarah Jasim, a senior research fellow at University College London and London School of Economics and Dr Ruth Plackett, a senior research fellow at King’s College London.The course will cover:Key principles and procedures in mixed methods researchWhat is mixed methods research and why do we use it?How to plan a mixed methods research project.Understanding models of sequence and priority used in mixed methods research.How to analyse data and combine results.There will be opportunity to discuss your own research questions, methods, and desired outcomes.Relevant for PhD students, post-docs and researchers across disciplines and industries.The course will also be available on Monday Mar 2nd or Monday October 19th, 2025, 10-4pm online.   ruth.l.plackett@kcl.ac.uk (KCL) Thu, 22 Jan 2026 00:00:00 +0000 https://www.ncrm.ac.uk/training/show.php?article=14692 https://www.ncrm.ac.uk/training/show.php?article=14888 Working with quantitative data entails being proficient with data management and exploration in order to do analysis and get insights. And while there are multiple ways of doing this, R has emerged as one of the most popular tools for these tasks. R is a free and open source software for statistics and data science that is increasingly used with social survey data.Important: you will need some familiarity with quantitative data, and an understanding of variables, datasets, and re-coding. A basic knowledge of R is also a highly recommended.In this course you will be introduced to the use of R and will learn how to prepare and visualize data. We will focus on the use of the ‘Tidyverse’ package. Inspired by the concept of “tidy data” this package enables users to import, merge, recode, restructure and visualize data very efficiently.Half of the course will focus on how to efficiently transform variables and prepare them for analysis while the other half will focus on visualization. The course will combine presentations of the key concepts, hands on practical sessions and discussions of the solutions. In the practical part we will be using real world data to prepare the participants for working with their own data.Looking to book for four or more people from your organisation? Contact training@the-sra.org.uk to ask about our in-house courses. training@the-sra.org.uk (Social Research Association) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14888 https://www.ncrm.ac.uk/training/show.php?article=14767 This online session invites participants to think critically about what generative AI means for highereducation and academic research in particular at this moment of rapid change. We’ll look athow AI is already reshaping academic work and consider what this means for research, andscholarship. Rather than offering fixed answers, the session creates space to explore theopportunities and risks together. The focus is on developing a clearer understanding of whatAI means for researchers.Date: 15 October - afternoon (1.5 hours)PresenterDr Mark Carrigan FRSA FHEA is a Senior Lecturer in Education at the University of Manchester, where he co-leads the Digital Education Manchester group and serves as an AI Fellow at the Institute for Teaching and Learning. His work centers on three interconnected commitments: developing ontological and epistemological frameworks for understanding Large Language Models (LLMs) beyond current inadequate conceptualisations; examining higher education as a critical site where the social and cultural dynamics of LLMs unfold through practical challenges; and advancing Margaret Archer’s morphogenetic approach as a route to addressing these urgent questions.He is the author of Platform and Agency: Becoming Who We Are (Routledge, 2025), which develops a framework for understanding personal transformation in the digital age. His recent work includes Generative AI for Academics (Sage, 2024) and Social Media for Academics (Sage, 2nd edition), alongside eight other books. He co-edited Building the Post-Pandemic University (Edward Elgar, 2023), examining how universities are transforming in response to technological and social disruption.  jmh6@soton.ac.uk (NCRM, University of Southampton) Mon, 13 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14767 https://www.ncrm.ac.uk/training/show.php?article=14668 Overview of 2-day courseAre you working in Learning Analytics or Student Analytics?Ever been asked if the average mark is changing significantly over academic years, or if the difference between the rate of change for females and males is statistically significant? Or which factors are associated with non-continuation?Or which factors are associated with accepting an offer?Or if the chance of achieving a first class honours degree is associated with tariff points on entry? This two-day course provides participants with hands-on experience of analysing their own type of records for data-driven planning and confidently interpreting numerical results for reports to policy makers and committees. The focus of the course is on the use of two statistical modelling techniques:Linear regressionLogistic regressionLinear regression is used to examine how the mean of a numerical outcome, like final year mark, might be associated with different characteristics. If the outcome is binary, such as drop-out, logistic regression is used to investigate how the chance of failing to continue to the second year is associated with different characteristics.  Logistic regression is a popular modelling technique, for example it is advocated by the Office for Students in their Financial support evaluation toolkit.The course also illustrates how these modelling techniques may be used for one-step-ahead forecasting into next year.Presentations, demonstrations and hands-on computer practicals are based around the free statistical software R; see https://www.r-project.org/. Formulae are kept to a minimum; instead, we concentrate on results, their interpretation and reporting in plain language.PresentersSandro Leidi and James Gallagher Cost£516 (inclusive of 20% VAT)Delivery ModeAll training is online and will be delivered live each day between 10:00 and 16:30 (GMT+1). Delivery platform: Zoom, which may be freely accessed.  Questions may be asked using Zoom's chat box.  Note our online courses are delivered by a team of two presenters, meaning at least one presenter is always available to provide additional support.  During presentations, the team member who is not speaking can take questions in addition to the presenter. We also use Zoom meetings rather than webinars to encourage further interaction during an online course.​Who Should Attend?Administrators in educational establishments working in Policy, Planning and Strategy units; Data and Insight units; Business Intelligence units; those involved in learning analytics or extracting actionable insights from student records and in reporting to policy makers or committees. Anyone in these positions needing to answer questions around how student outcomes may be associated with different factors will benefit greatly from this course.It is assumed that participants will, prior to the course, have:An understanding of mathematical functions and equations. In particular, the natural logarithmic and exponential functions (loge() and exp() respectively), the equation of a straight line and its geometrical representationAttended the one-day course Statistics for University Administrators, or Statistics for University Administrators using R, or have equivalent knowledge.No previous experience of the R software is required; a brief introduction for the purpose of the course will be given.How You Will BenefitBy the end of the course you will be familiar with two common statistical modelling methods for investigating associations and extracting actionable insights, be able to report the results in plain language, and be able to perform analyses using free statistical software. You will also be able to follow official guidance on the use of such models, e.g. the Office for Students’ guidance on the use of binary logistic regression for investigating the effectiveness of financial support with respect to student outcomes.What Do We Cover?Introduction to the R software·Simple linear regression for relating a numerical outcome to a numerical explanatory variableExtending the linear regression model to incorporate categorical explanatory variables and interactions to allow for effect modificationUsing binary logistic regression in place of linear regression when modelling binary outcomesOne-step-ahead forecasting.SoftwarePractical work will be done in R.Note:For practical work, participants must download and install the R software prior to the start of the coursePractical work is based on the Windows operating system.Extra InformationThe R software is used on the course for two reasons:It is a free dedicated statistics package and can be used for other analysesIt is a widely used software which will be maintained by the R Foundation for many years to come. jamesgallagher1929@gmail.com (Statistical Services Centre Ltd) Mon, 12 Jan 2026 00:00:00 +0000 https://www.ncrm.ac.uk/training/show.php?article=14668 https://www.ncrm.ac.uk/training/show.php?article=14791 Overview of 1-day courseIn survival analysis in medical research, the proportional hazards assumption and the hazard ratio effect measure have been popular for decades, fuelled by extensive application of the log-rank test and the Cox regression model.  However, the hazard ratio can be clinically awkward to interpret, or the proportional hazards assumption may not hold, rendering the use of a hazard ratio effect measure questionable at best.In this course we introduce the restricted mean survival time (RMST), which is a well established, but under-used summary of the survival experience.  In recent years there has been a surge of interest in the RMST, particularly in oncology, but also in many other areas. We begin with a review of the definitions of the RMST, approaches to estimation and different RMST-based effect measures which are clinically meaningful alternatives to the hazard ratio and are not based on a proportional hazards assumption.For the practical analysis of survival data, which includes right-censoring, the course focuses on a non-parametric analysis for comparing treatments and a generalised linear model (GLM) -type modelling approach based on the use of pseudo-values.  The latter provides a flexible method for directly modelling the RMST in a regression framework, where a treatment effect may be adjusted for covariates.  Model checking is also considered. The course concludes with a brief consideration of an extension to the RMST known as the window mean survival time (WMST) or the long-term RMST (LT-RMST).The course is a practical introduction to analysing survival data using a RMST-based effect measure.  Only essential theoretical aspects of the methodology will be summarised.  Examples used will be drawn from applications in medicine and health, particularly clinical trials.Practical work will be based around the statistical software R; see https://www.r-project.org/.PresentersSandro Leidi and James GallagherCost£312 (inclusive of 20% VAT)Delivery ModeAll training is online and will be delivered live between 09:00 and 17:30 (GMT). Delivery platform: Zoom, which may be freely accessed.  Questions may be asked verbally or using Zoom's chat box.  Note our online courses are delivered by a team of two presenters, meaning at least one presenter is always available to provide additional support.  During presentations, the team member who is not speaking can take questions in addition to the presenter.​  We also use Zoom meetings rather than webinars to encourage further interaction during an online course.Who Should Attend?Statisticians and data analysts working with survival data in medical research. Participants will be assumed to have a working knowledge of:Survival analysis techniques applicable to right censoringRegression modellingThe R statistics software.How You Will BenefitYou will acquire practical experience in the use of RMST-based effect measures as an alternative to the hazard ratio.  You will also be able carry out adjusted as well as unadjusted analyses.What Do We Cover?Problems with proportional hazards and hazard ratio effect measure.  Introduction to the RMST: definition, approaches to estimation, RMST-based effect measures as an alternative to the hazard ratio.  The restricted mean time lost (RMTL)Non-parametric analysis for comparing two groups. Statistical inference: estimation, confidence intervals and hypothesis testing for different effect measures. Advantage of RMST-based effect measures over the hazard ratioAdjusting a treatment effect for covariates. Modelling the RMST using a GLM-type model based on pseudo-values; choice of link functions and effect measures; model fitting and comparison of modelsModel checking and the use of pseudo-residualsExtending the RMST: window mean survival time (WMST)CRAN packages, including geepack for modelling, emmeans for post-processing and survRM2 for non-parametric analysis.The course does not cover time dependent covariates.SoftwarePractical work will be done in R.Note: For practical work, participants must download and install a number of CRAN packages in R.  This must be done prior to the start of the course. jamesgallagher1929@gmail.com (Statistical Services Centre Ltd) Mon, 30 Mar 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14791 https://www.ncrm.ac.uk/training/show.php?article=14410 Level: Intermediate (I)This course will be delivered over 4 afternoon sessions, running from 1:00pm to 5:00pm each day.The intensive course on programming principles in R. This course covers the fundamental techniques such as functions, for loops and conditional expressions. It also covers the {tidyverse} package, {purrr}. {purrr} is a very powerful package that gives great flexibility to analysts, by enhancing R’s functional programming toolkit. By the end of this course, you will understand what these techniques are and when to use them. The course will also demonstrate how to use functions such as map(), map2() and pmap(), to iteratively map functions over multi-element objects like vectors and lists. Emphasis will also be placed on how to manipulate list outputs and how this can be applied to data..Learning OutcomesBy the end of the course, delegates will: Understand basic functions, multiple arguments and variable scopes.Have a thorough understanding for loops.Be able to apply basic functions.Have a thorough understanding of conditionals such as if, else and else if statements.Be familiar with possible R workflows such as directory structure and working with directories.Understand how the aforementioned techniques can be applied to their own data.Understand how these techniques will improve efficiency and results.Understand where to find help in R using resources and the help() function.Understand lists in R and know how to use {purrr} to map functions.Know what nested loops are and use {magrittr} to extract elements from them.Be able to create list columns and know how to access the data in them.Iteratively loop two or more objects to a function of choice using functions such as map2(), pmap() and imap().Recognize the advantages of using {purrr}.Understand how to extract elements from nested lists to achieve a desired output object class.Be able to effectively debug their code using multiple {purrr} functions for the debugging process.Save precious debugging time using e.g. safely() Topics CoveredConditionals: using if and else statements in RFunctions: what a function is, how are they used, and how can we construct our own functions.Looping in R: an introduction to the concept of looping in R. In particular for and while loops.Help: The help system in R can at first glance appear daunting, however, after the initial shock, R’s documentation is second to none.Project structure: Practical tips on how to structure a project.Data manipulation and aggregation using dplyrIntroduction to {purrr} and Lists: Introduction to lists in R and using {purrr} to map a function across a list.List-Columns and Nesting: Exploring nested data in list columns and using the mapping functions to manipulate them.Parallel Mapping: Using {purrr} functions to map over multiple lists in parallel.Manipulating {purrr} Output: Using {purrr} to efficiently extract elements from lists into vector and dataframe format, and change the hierarchy within nested lists.Best Practices in {purrr}: Showcase of functions from {purrr} which aid in the debugging process.  Target AudienceThis course is idea for anyone who would like to extend their basic familiarity with using R, and using R to write their own bespoke functions or optimizing their code. Assumed KnowledgeBasic prior experience with the R programming language is assumed. Namely that participants have some experience of R data structures, such as vectors, data frames, and experience in using pre-made functions from R packages.The course is aimed as a follow up the 'Introduction to R and Regression Modelling in R' training course.Whilst no statistical knowledge will be assumed, some of the examples will be statistical in nature.For this online course, participants are not required to have R installed on their own laptops. A virtual environment, which can be accessed through a web browser, will be used to run R and view course materials. training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14410 https://www.ncrm.ac.uk/training/show.php?article=14396 Level: Professional (P)This course introduces the Bayesian approach to meta-analysis. Attendees will learn practical ways in which they can combine multiple sources of published evidence while accounting for uncertainties such as response bias, publication bias, confounding, and missing information, using either BUGS, JAGS or Stan as software. With Bayesian models, this can be transparent and reproducible.This two-day course begins by reviewing classic meta-analysis methods and expressing them as statistical models. Once attendees understand meta-analysis in this larger context, they are able to extend the model flexibly to account for common problems such as papers that report only change from baseline. A series of problems will be tackled in this course, and attendees will leave with model code that they can immediately start using with their own projects. Learning OutcomesAfter attending, participants will be able to:Write out standard meta-analyses as statistical modelsUse BUGS, JAGS or Stan to fit such models to dataRecognise several common problems in meta-analysisExtend these models to account for these problemsUnderstand and communicate their findings Topics CoveredDay 1:A review of statistical models of meta-analysis​Introduction to Bayesian analysis problems in meta-analysis, and sources of uncertaintyModels for basic DerSimonian-Laird and Biggerstaff-Tweedie meta-analysesIntroduction to Bayesian software options: BUGS, JAGS and StanDay 2:Models for network meta-analysisModels for missing statisticsModels for reporting biasModels for publication biasModels for a mixture of statisticsModels for a mixture of study typesReporting Bayesian meta-analyses Target AudienceThis course will be of interest to evidence-based healthcare researchers, including those writing guidelines and evaluating policies. Attendees should be comfortable conducting simple meta-analyses in some software but do not have to have experience of Bayesian methods. Assumed KnowledgeThis course assumes that all participants have a basic grounding in Bayesian statistics, to the level covered by the RSS courses "Introduction to Bayesian Statistics" or "Introduction to Bayesian Analysis using Stan". There is no specific software expertise required, but examples will be written in BUGS and Stan, using R as an interface. We also assume that participants are familiar with the principles of systematic reviews, for example from reading relevant parts of the Cochrane Collaboration Handbook online. training@rss.org.uk (The Royal Statistical Society) Mon, 18 Aug 2025 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14396 https://www.ncrm.ac.uk/training/show.php?article=14932 Course OverviewNavigating Qualitative AI: Ethical, Methodological and Practical ConsiderationsThe Navigating Qualitative AI course provides an introduction into developments, debates and practicalities in the role and use of Generative AI in Qualitative Research. The course is split into three modules combining synchronous and asynchronous learning to provide a comprehensive introduction to the principles, practices and ethics of using AI tools to facilitate the analysis of qualitative materials. Module 1: Mindsets for considering the use of AI for Qualitative ResearchModule 2: Harnessing Generative-AI tools for qualitative analysisModule 3. Integrating Generative-AI tools into qualitative analysis processesChoose from three pathways through the course according to your interests and needs (note, to take Module 2 or 3 it is a pre-requisite to have first completed Module 1):Pathway 1 – Module 1 onlyPathway 2 – Module 1 and 2Pathway 3 – Module 1 and 3Module 2. Harnessing Generative-AI tools for qualitative analysis(Synchronous Delivery = hands-on guided exercises using selected tools, and discussion)This module comprises demonstrations and hands-on exercises using selected AI tools for Qualitative Data Analysis, and discussion about their potential for research and evaluation. Using sample data, we consider a series of analytic tasks and methodological implications of use in different contexts, with different types of data and at different stages in the analytic process. The tools-focus in this module is on general-purpose Generative-AI tools and new online Apps designed for GenAI-driven qualitative analysis. The course covers:Using general-purpose Generative-AI tools - 12 October 2026 (13:30-16:45)Overview of the capabilities of general-purpose Generative-AI toolsHands-on exercises following process of Query-Based Analysis (Morgan 2025)Chatbots – e.g. ChatGPT, Claude, Gemini etc.AI Research Assistant platforms – e.g. Notebook LMGenerative-AI driven analysis with bespoke online Apps - 13 October 2026 (13:30-16:45)Overview of the capabilities of bespoke online Apps for qualitative analysisHands-on exercises using Reveal platform (analysis of transcripts)Hands-on exercises using Blix platform (analysis of open-ended survey responses)By the end of the course participants will:Understand the potential uses of AI tools at different stages of the qualitative analysis workflowUnderstand the methodological consequences of using AI tools (potentials and risks)Identify skills in harnessing AI tools in ways that enable human-centred approachesThis course is aimed at students and researchers interested in qualitative analysis, within any sector or discipline. Participants must have attended Module 1 in order to attend this module.The course takes place over two afternoons and equates to one teaching day for payment purposes. This page is for Module 2: Harnessing Generative-AI tools for qualitative analysis.If you wish to register for Modules 1 or 3 please do so here:Module 1 - Mindsets for considering the use of AI for Qualitative Research - 30 Sept and 1 OctModule 1 - Mindsets for considering the use of AI for Qualitative Research - 2 and 4 NovModule 3 - Integrating Generative-AI tools into qualitative analysis processes - 16 and 18 Nov jmh6@soton.ac.uk (NCRM, University of Southampton) Wed, 05 Aug 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14932 https://www.ncrm.ac.uk/training/show.php?article=14875 Overview of 0.5-day courseThe statistical package R (www.r-project.org) is a freely available statistical software. R is part of an international collaboration and has become very popular; it is used for data analysis in many application areas and is used extensively in research and academia. In particular, it has flexible facilities for advanced modern statistical modelling and is equally well suited to more elementary statistics and graphics. In this hands-on tutorial we access R via RStudio which provides a user-friendly interface to R in an integrated development environment and is very popular among R users.  Participants will be supplied with a R script file containing R code which will be used for the entirety of the tutorial to demonstrate and illustrate the use of R.The tutorial begins with a general overview of RStudio and the concepts involved in using R, such as object orientation.  It then moves onto importing data from Excel, utilising the extension of R’s capabilities through the installation of third party CRAN packages.  Next the calculation of summary statistics for numerical data are illustrated using functions in the base installation of R, along with the production of some common graphics. The tutorial will finish with a discussion of some common sources of errors when using R.The majority of the tutorial will make use of a small educational dataset and a larger health study example. The tutorial will use the freely available RStudio Desktop version on a Windows operating system. Note the R language is not based on using point-and-click mode, but a written command syntax.PresentersSandro Leidi and James GallagherCost£126 (inclusive of 20% VAT)Delivery ModeAll training is online and will be delivered live between 09:00 and 12:30 (GMT).  The delivery platform is Zoom, which may be freely accessed.  Questions may be asked verbally or using Zoom's chat box.  Note our online courses are delivered by a team of two presenters, meaning at least one presenter is always available to provide additional support.  During presentations the team member who is not speaking can take questions in addition to the presenter.  We also use Zoom meetings rather than webinars to encourage further interaction during an online course.​Who Should Attend?Anyone involved in the analysis of data, either on a regular or irregular basis, who wants a practical introduction to R. No previous experience of the R software or RStudio is required.The tutorial is also suitable for anyone wanting brief refresher training.How You Will BenefitYou will be able to describe the essential concepts related to using R via RStudio and use R to import data and for basic statistical analysis including graphics.  In particular, you will also be able to:Write a script to (a) efficiently reproduce output and (b) have an auditable record of your analysis in your workflowInstall CRAN packages for specific analysesMake effective use of the many resources which are freely available to prepare for a deep dive into the R software applied to your particular area of interest. What Do We Cover?Introductory concepts of R and the RStudio interface: windows/panes, objects, data frames, working directory, attributes of an object in particular class, functions, R as a calculator, scripts, workspaces and CRAN packages; help systemImporting data from other applications: CSV, Excel into a data frame; the class of a data column and its importance; factors and their labelling. Missing valuesExploratory data analysis: summary statistics, statistical graphics for numerical data. Labelling of graphicsCommon errors and remedies.SoftwareThe tutorial will be conducted using the free version of RStudio Desktop on a Window operating system.Participants must download and install the R Gui and RStudio Desktop applications and install a number of CRAN packages prior to the start of the tutorial.​Course teaching materialsThere are no formal slides for this tutorial. Presentations will be based around a pre-supplied R script file, containing code to be executed live by both the presenters and participants in parallelA pdf file containing the output generated during the course of the tutorial will be supplied for future use along with a small number of ad hoc files such as a reference list. jamesgallagher1929@gmail.com (Statistical Services Centre Ltd) Tue, 16 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14875 https://www.ncrm.ac.uk/training/show.php?article=14892 OverviewEmbarking on qualitative data analysis: a beginner’s guide to critical considerations for your qualitative research Learning objectivesBy the end of the course, participants will be able to:Develop appropriate research questions;Focus a literature review to ensure it is efficient and effective;Understand the range of qualitative methodologies and their underlying assumptions;Make appropriate choices between methodologies, data collection strategies and analytic methodsIdentify the audiences of their work and frame their dissemination accordingly. Who is this course for?This course is designed for postgraduate students and early career researchers in any discipline who are new to working with qualitative data (e.g. literature and documents, transcripts of interviews and focus groups, visual materials, social media and online content, open-ended survey responses etc.) Course overview and aimsThis course provides a thorough overview of the principles and practices of undertaking qualitative data analysis. Framed around the research cycle, we discuss and illustrate the interrelated activities undertaken as analysis progresses – from the paradigms and assumptions that underlie qualitative projects, through the practicalities of planning and implementing an analysis, to writing up, visualising and sharing findings. The aim of this course is to open up thinking about the range and flexibility of qualitative data analysis approaches and to equip participants with the necessary mindsets and frameworks to plan and undertake their own projects. The course is led by two facilitators and the number of participants is limited to ensure everyone has the opportunity to discuss their work-in-progress. TopicsThe qualitative research cycle – planning and managing the iterative and cyclical nature of qualitative researchResearch in the wider landscape – research topics and objectives, reviewing the state of the art, developing research questionsThe role of methodology – underlying paradigms and assumptions, differences between methodologies and methodsThe ethics of working qualitatively – considerations for involving participants and representing their contributionsFrom methodology to data collection – types of qualitative data, ways of collecting qualitative data, integrating different types of data in an analysisAnalytic activities – integrate, organise, explore, reflect, interrogateQualitative analytic strategies – qualitative approaches, mixed-methods analysis and quantifying qualitative data, focusing on the examples of Grounded theory, Content Analysis, Thematic Analysis, Discourse Analysis, Action ResearchAnalysis exercise – small groups collaboratively analyse sample qualitative data using different strategies and compare and discuss their findingsCollating insights and presenting a narrative – sharing findings with different audiences Format and documentationAll our workshops are hands-on, delivered through a blend of demonstration, discussion and practical exercises, rather than providing simplistic, mechanical instruction.To deliver as tailored an experience as possible, we contact you on enrolment in order to understand your research goals and analytical strategies. Additionally, our participant numbers are capped to a small group size and we run our courses with two facilitators, allowing us to cover the core topics, as well as specialist needs arising out of individual projects.Participants are provided with slide decks, reading lists and a range of resources to accompany the course and to support consolidation of the topics covered. Feedback from previous attendees"Since beginning my doctoral journey this training is what I have been searching for! The trainers are exceptional and have a way of delivering complicated theory and methods in an accessible and engaging manner. This has been the very best experience - thank you! ""I've only just come out of the session, and it was a HUGE amount of information, delivered extremely clearly. I have studied qual methodologies for my masters, and this was a far clearer guide than anything else I have experienced.""A fantastic session that helped a lot of learning click into place. I feel a lot more confident about embarking on my PhD and have further areas of inquiry to focus on my direction." FacilitatorsChristina Silver, PhD is the director of Qualitative Data Analysis Services and manager of the CAQDAS Networking Project at the University of Surrey, UK. Christina’s interests relate to the relationship between technology and methodology and the effective teaching of qualitative methods and digital tools. She is co-author of Using Software in Qualitative Research: A Step-by-Step Guide (Sage publications, 2007, 2014) and Qualitative Analysis using ATLAS.ti/MAXQDA/NVivo: The Five-Level QDA® Method (Routledge 2018). Christina has trained more than 11,000 researchers around the world in qualitative methods and the use of digital tools for analysis, since 1998, and is a Fellow of the UK Academy of Social Sciences.Sarah L Bulloch, PhD is a senior associate of Qualitative Data Analysis Services and teaching fellow at the CAQDAS Networking Project at the University of Surrey, UK. Sarah has expertise in both qualitative and quantitative analysis techniques and has applied them in academic, public sector, private and third sector contexts. Her current work and research centres around enabling others to apply research methods, and the digital tools to support them, in a meaningful, robust and flexible way. Sarah first used CAQDAS packages in 2006 and started teaching them in 2010. About Qualitative Data Analysis ServicesQDA Services provide tailored and flexible training, consultancy, coaching and analysis for qualitative and mixed-methods researchers.We specialise in facilitating high-quality analysis through the powerful use of digital tools.Our website provides information about our work, including our pedagogy - the Five-Level QDA method, which underpins the way we think about, undertake and teach methods and tools. info@qdas.co.uk (QDAS | Qualitative Data Analysis Services) Tue, 23 Jun 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14892 https://www.ncrm.ac.uk/training/show.php?article=14905 This webinar will introduce key approaches to causal inference when using longitudinal data and explain how to apply these methods within CLS cohort data.About the eventJoin our experts for an overview of the challenges – and opportunities – involved in making causal inferences using data from four national cohort studies based at CLS: 1958 National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Next Steps and Millennium Cohort Study (MCS). The session will cover:The importance of formulating a clear causal research question as the first step of a research project.The three main sources of bias that arise when using causal inference methods: confounding, selection, and measurement. Use of causal Directed Acyclic Graphs (DAGs) to understand these biases and the assumptions they require.Understanding how DAGs can inform subsequent analyses, focusing on the ‘Elaborate Theories’ approach that can be easily applied to CLS cohort data.The statistical method of Quantitative Bias Analysis (QBA), which allows researchers to assess whether observed associations reflect bias or true causal effects. Who should attend?This webinar is aimed at researchers who want to use CLS cohort data to answer causal research questions. Researchers at all levels and across disciplines will benefit from this webinar. No prior experience of working with the data is required.  radhika.jhamaria.23@ucl.ac.uk (UCL Centre for Longitudinal Studies) Wed, 22 Jul 2026 00:00:00 +0100 https://www.ncrm.ac.uk/training/show.php?article=14905