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Social Sciences Research Methods Programme course timetable

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Fri 22 Jan – Tue 9 Feb

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Monday 25 January

10:00
Basic Quantitative Analysis (BQA-5) (1 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture online

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

Basic Quantitative Analysis (BQA-6) (1 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture online

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

14:00
Basic Quantitative Analysis (BQA-5) (2 of 4) Finished 14:00 - 16:00 SSRMP Zoom

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

16:00
Basic Quantitative Analysis (BQA-6) (2 of 4) Finished 16:00 - 18:00 SSRMP Zoom

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

Tuesday 26 January

14:00
Introduction to Stata (1 of 2) Finished 14:00 - 18:00 SSRMP Zoom

The course will provide students with an introduction to the popular and powerful statistics package Stata. Stata is commonly used by analysts in both the social and natural sciences, and is the statistics package used most widely by the SSRMC. You will learn:

  • How to open and manage a dataset in Stata
  • How to recode variables
  • How to select a sample for analysis
  • The commands needed to perform simple statistical analyses in Stata
  • Where to find additional resources to help you as you progress with Stata

The course is intended for students who already have a working knowledge of statistics - it's designed primarily as a ""second language"" course for students who are already familiar with another package, perhaps R or SPSS. Students who don't already have a working knowledge of applied statistics should look at courses in our Basic Statistics Stream.

15:00
Research Ethics in the Social Sciences (2 of 2) Finished 15:00 - 17:00 Taught Online

Ethics is becoming an increasingly important issue for all researchers, particularly in the covid-19 era. The aim of this session is twofold: (I) to demonstrate the practical value of thinking seriously and systematically about what constitutes ethical conduct in social science research; (II) to discuss the new valences of research in the pandemic era and develop new practices to tackle the insecurity it has created.

This three-hour session will be delivered via Zoom, and involve mini-lectures, small group work, and group discussions.

Wednesday 27 January

10:00
Basic Quantitative Analysis (BQA-5) (3 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture online

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

Basic Quantitative Analysis (BQA-6) (3 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture online

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

14:00
Basic Quantitative Analysis (BQA-5) (4 of 4) Finished 14:00 - 16:00 SSRMP Zoom

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

16:00
Basic Quantitative Analysis (BQA-6) (4 of 4) Finished 16:00 - 18:00 SSRMP Zoom

This module follows on from Foundations in Applied statistics, and will teach you the basics of common bivariate techniques (that is, techniques that examine the associations between two variables). The module is divided between lectures, in which you'll learn the relevant theory, and hands-on practical sessions, in which you will learn how to apply these techniques to the analysis of real data.

Techniques to be covered include:

  • Cross-tabulations
  • Scatterplots
  • Covariance and correlation
  • Nonparametric methods
  • Two-sample t-tests
  • ANOVA
  • Ordinary Least Squares (OLS)

For best results, students should expect to do a few hours of private study and spend a little extra time in the computer labs, in addition to coming to class.

Friday 29 January

10:00
Doing Multivariate Analysis (DMA 4) (1 of 4) Finished 10:00 - 12:00 SSRMP Zoom

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

14:00
Doing Multivariate Analysis (DMA 4) (2 of 4) Finished 14:00 - 16:00 SSRMP Zoom

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

Monday 1 February

14:00
Public Policy Analysis (1 of 3) Finished 14:00 - 16:00 SSRMP Zoom

The analysis of policy depends on many disciplines and techniques and so is difficult for many researchers to access. This module provides a mixed perspective on policy analysis, taking both an academic and a practitioner perspective. This is because the same tools and techniques can be used in academic research on policy options and change as those used in practice in a policy environment. This course is provided as three 2 hour sessions delivered as a mix of lectures and seminars. No direct analysis work will be done in the sessions themselves, but some sample data and questions will be provided for students who wish to take the material into practice.

Feminist Research Practice new (1 of 4) POSTPONED 14:00 - 15:15 SSRMP Zoom

This series of workshops are aimed at students interested in interdisciplinary and feminist research practice. The course revolves around a simple query: what makes research feminist? It is the starting point to engage with classic and more contemporary writings on feminist knowledge production to answer some of the following questions: what are the ‘proper’ objects of feminist research? Who can do feminist research? Why do we do feminist research, and what is its relevance? Who do we cite in our research? We will have in-class discussions and hands-on assignments that will allow students to practice some of the main debates we will read about.

Tuesday 2 February

14:00
Introduction to Stata (2 of 2) Finished 14:00 - 18:00 SSRMP Zoom

The course will provide students with an introduction to the popular and powerful statistics package Stata. Stata is commonly used by analysts in both the social and natural sciences, and is the statistics package used most widely by the SSRMC. You will learn:

  • How to open and manage a dataset in Stata
  • How to recode variables
  • How to select a sample for analysis
  • The commands needed to perform simple statistical analyses in Stata
  • Where to find additional resources to help you as you progress with Stata

The course is intended for students who already have a working knowledge of statistics - it's designed primarily as a ""second language"" course for students who are already familiar with another package, perhaps R or SPSS. Students who don't already have a working knowledge of applied statistics should look at courses in our Basic Statistics Stream.

Wednesday 3 February

14:00
Issues in Measurement: Validity and Reliability Finished 14:00 - 16:00 SSRMP Zoom

This short two-hour course will provide an introduction to measurement issues in the social sciences. We design questions (or "survey instruments") to gain information on the concepts we are researching. Two prime considerations in whether an instrument is effective are validity (does our instrument actually measure what we want it to measure?) and reliability (does our instrument give consistent results across a range of different situations?) Considerations of validity and reliability are important across many areas of social science, including the measurement of personality and mental health; attitudes; ability tests; substance use disorders; and cultural differences and similarities between various groups. The course will discuss the importance, concepts, and types of validity and reliability. We will also briefly look at some statistical techniques for validity and reliability checks: Cronbach’s Alpha, Kappa coefficient, and Factor Analysis.

15:00
Atlas.ti (1 of 3) Finished 15:00 - 17:00 SSRMP Zoom

This course provides an introduction to the management and analysis of qualitative data using Atlas.ti. It is divided between pre-recorded lectures, in which you’ll learn the relevant strategies and techniques, and hands-on live practical sessions in Zoom, in which you will learn how to analyse qualitative data using the software.

The sessions will introduce participants to the following:

  • consideration of the advantages and limitations of using qualitative analysis software
  • setting-up a research project in Atlas.ti
  • use of Atlas.ti's menus and tool bars
  • importing and organising data
  • starting data analysis using Atlas.ti’s coding tools
  • exploring data using query and visualization tools

Please note: Atlas.ti for Mac will not be covered.

Thursday 4 February

11:30
Reading and Understanding Statistics (1 of 4) Finished 11:30 - 13:30 Taught Online

This module is for students who don’t plan to use quantitative methods in their own research, but who need to be able to read and understand published research using quantitative methods. You will learn how to interpret graphs, frequency tables and multivariate regression results, and to ask intelligent questions about sampling, methods and statistical inference. The module is aimed at complete beginners, with no prior knowledge of statistics or quantitative methods.

15:30
Ethnographic Methods (1 of 4) Finished 15:30 - 17:00 Taught Online

This module is an introduction to ethnographic fieldwork and analysis and is intended for students in fields other than anthropology. It provides an introduction to contemporary debates in ethnography, and an outline of how selected methods may be used in ethnographic study.

The ethnographic method was originally developed in the field of social anthropology, but has grown in popularity across several disciplines, including sociology, geography, criminology, education and organization studies.

Ethnographic research is a largely qualitative method, based upon participant observation among small samples of people for extended periods. A community of research participants might be defined on the basis of ethnicity, geography, language, social class, or on the basis of membership of a group or organization. An ethnographer aims to engage closely with the culture and experiences of their research participants, to produce a holistic analysis of their fieldsite.

Session 1: The Ethnographic Method What is ethnography? Can ethnographic research and writing be objective? How does one conduct ethnographic research responsibly and ethically?

Session 2: Ethnography and/as Audio Shortly after the phonograph was invented, ethnographers began using audio recording to document the cultural practices they were researching. For some, it has served as a kind of scientific tool to gather evidence and generate archives of linguistic, musical, and other sonic practices; for many others, it has served as an essential tool for interviewing about any topic; and for other still, audio recording and re-composition offer new possibilities of what ‘writing culture’ means. What are the consequences of using audio recording in fieldwork? And what are the technical, ethical, and aesthetic dimensions of doing so?

Session 3: Visual Anthropology This session outlines the relation of ethnographic film to anthropology and ethnographic knowledge generally, looks at some examples of contemporary ethnographic film practice, and inquires into the possible utility of photography and video recording in the research process of ethnographic fieldwork in general. We continue the prior session’s consideration of some of the epistemological, theoretical, social, and ethical considerations that tend to arise around use of these audiovisual recording technologies in anthropological fieldwork and analysis.

Session 4: Relationships in the Field Ethnographic methodology and participant observation often involve researchers’ positioning in existing networks of social relations. This session is meant to help attendees manage interpersonal relationships with research participants from academic, political, and ethical perspectives. We will discuss when and why relationships in ethnographic fieldwork can be a reason for concern. We will reflect on the social distinctions that emerge when doing fieldwork with other people and their effects on researchers’ decision-making process. Finally, we will think through different fieldwork strategies when working with others, and how they impact the production of ethnographic knowledge.

Friday 5 February

10:00
Doing Multivariate Analysis (DMA 4) (3 of 4) Finished 10:00 - 12:00 SSRMP Zoom

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

14:00
Doing Multivariate Analysis (DMA 4) (4 of 4) Finished 14:00 - 16:00 SSRMP Zoom

This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently.

Half of the module is based in the lecture theatre, and covers the theory behind multivariate regression; the other half is lab-based, in which students will work through practical exercises using statistical software.

To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models.

Monday 8 February

09:00
Diary Methodology (1 of 3) Finished 09:00 - 13:00 SSRMP pre-recorded lecture online

This SSRMP module introduces solicited diaries as a qualitative data collection method. Diary methodology is a flexible and versatile tool which has been used across a variety of disciplines (e.g. public health, nursing, psychology, media studies, education, sociology).

Solicited diaries are particularly powerful in combination with qualitative interviews, enabling the remote collection of rich data on intimate or unobservable topic areas over a longer period of time. This multi-method approach, also known as the ‘diary-interview method’ (DIM), has been originally developed as an alternative to participant observation (see: Zimmerman, D. H., & Wieder, D. L. (1977). The Diary: Diary-Interview Method. Urban Life, 5(4), 479–498.), which makes it an especially attractive qualitative data collection method in Covid-19 times.

In addition to the engagement with pre-recorded videos on Moodle (covering diary methodology basics), you will get hands-on experience with designing your own qualitative diary (3 hours live workshop via Zoom) and trying out the role of a researcher as well as research participant over a 5-day period (teaming up with a module colleague and filling out each other’s diaries). We will reflect on these experiences and answer remaining questions in a final 1-hour live session via Zoom.

The module is suitable for anybody interested in learning more about the method and/or using solicited qualitative diaries in their own research projects.

14:00
Public Policy Analysis (2 of 3) Finished 14:00 - 16:00 SSRMP Zoom

The analysis of policy depends on many disciplines and techniques and so is difficult for many researchers to access. This module provides a mixed perspective on policy analysis, taking both an academic and a practitioner perspective. This is because the same tools and techniques can be used in academic research on policy options and change as those used in practice in a policy environment. This course is provided as three 2 hour sessions delivered as a mix of lectures and seminars. No direct analysis work will be done in the sessions themselves, but some sample data and questions will be provided for students who wish to take the material into practice.

Feminist Research Practice new (2 of 4) POSTPONED 14:00 - 15:15 SSRMP Zoom

This series of workshops are aimed at students interested in interdisciplinary and feminist research practice. The course revolves around a simple query: what makes research feminist? It is the starting point to engage with classic and more contemporary writings on feminist knowledge production to answer some of the following questions: what are the ‘proper’ objects of feminist research? Who can do feminist research? Why do we do feminist research, and what is its relevance? Who do we cite in our research? We will have in-class discussions and hands-on assignments that will allow students to practice some of the main debates we will read about.

Tuesday 9 February

12:30
Qualitative Research Rigour new Finished 12:30 - 13:30 SSRMP Zoom

Historically, qualitative research has been criticised for being less rigorous than quantitative research through not fulfilling quality standards such as objectivity, validity, and reliability. This leads to questions whether qualitative research can fulfil these specific markers of rigour, how it can come as close as possible to fulfilling them, and whether qualitative research should at all attempt to live up to these understandings of research quality. Responding to this debate, many methodologists have argued for the need of translating objectivity, validity, and reliability within qualitative research designs.

The discussion of rigour is a loaded one, among methodologists of all three research approaches (qualitative, quantitative, mixed-methods) as well as mong qualitative researchers themselves. This course introduces different quality strategies for qualitative research to help students make informed decisions for improving their own empirical work and to better judge the rigour of empirical qualitative research done by others.

14:00
Further Topics in Multivariate Analysis (FTMA) 1 (1 of 4) Finished 14:00 - 16:00 SSRMP pre-recorded lecture online

This module is an extension of the three previous modules in the Basic Statistics stream, and introduces more complex and nuanced aspects of the theory and practice of mutivariate analysis. Students will learn the theory behind the methods covered, how to implement them in practice, how to interpret their results, and how to write intelligently about their findings. Half of the module is based in the lecture theatre; the other half is lab-based, in which students will work through practical exercises using the statistical software Stata.

Topics covered include:

  • Interaction effects in regression models: how to estimate these and how to interpret them
  • Marginal effects from interacted models
  • Ordered and categorical discrete dependent variable models (ordered and multinomial logit and probit)

To get the most out of the course, you should also expect to spend some time between sessions building your own statistical models.

Qualitative Interviews with Vulnerable Groups (1 of 3) Finished 14:00 - 16:00 SSRMP Zoom

Qualitative interviews are often used in the social sciences to learn more about the world and can be particularly appropriate for people we might class as vulnerable. The course will try to achieve two things. First, it will have a strong practical arc, guiding students through the complete process of designing and delivering interviews and what to do with the data when you have it. It is particularly important, therefore, that students come to the course prepared with a research question in mind (it does not have to be your actual dissertation topic). Second, we will repeatedly think carefully about the challenges of interviewing with populations that are deemed vulnerable (especially prisoners, women in the criminal justice system, and people living with trauma). We will explore how, in all stages of the research cycle, questions of ethics and the importance of understanding ‘whole people’ remain pertinent.

In the first session we will think about how to frame a study and research question, and how to design an interview schedule that allows you to access your question sensibly and creatively! We will also think about the challenges of interviewing those with trauma, in particular, as a case study.

In the second session we will think through the challenges of actually undertaking interviews in the field. Many hints and tip will be shared, and students will be encouraged to undertake a short mock interview.

In the third session we explore various ways in which to approach a mass of interview data and different approaches towards analysis.

In the final session, we burrow down into analysis and talk about how to write up your research.

In both of the final sessions students will be asked to engage with real interview transcripts that have been anonymised.

Further Topics in Multivariate Analysis (FTMA) 2 (1 of 3) Finished 14:00 - 16:00 SSRMP pre-recorded lecture online

This module is an extension of the three previous modules in the Basic Statistics stream, and introduces more complex and nuanced aspects of the theory and practice of mutivariate analysis. Students will learn the theory behind the methods covered, how to implement them in practice, how to interpret their results, and how to write intelligently about their findings. Half of the module is based in the lecture theatre; the other half is lab-based, in which students will work through practical exercises using the statistical software Stata.

Topics covered include:

  • Interaction effects in regression models: how to estimate these and how to interpret them
  • Marginal effects from interacted models
  • Ordered and categorical discrete dependent variable models (ordered and multinomial logit and probit)

To get the most out of the course, you should also expect to spend some time between sessions building your own statistical models.

16:00
Further Topics in Multivariate Analysis (FTMA) 1 (2 of 4) Finished 16:00 - 18:00 SSRMP Zoom

This module is an extension of the three previous modules in the Basic Statistics stream, and introduces more complex and nuanced aspects of the theory and practice of mutivariate analysis. Students will learn the theory behind the methods covered, how to implement them in practice, how to interpret their results, and how to write intelligently about their findings. Half of the module is based in the lecture theatre; the other half is lab-based, in which students will work through practical exercises using the statistical software Stata.

Topics covered include:

  • Interaction effects in regression models: how to estimate these and how to interpret them
  • Marginal effects from interacted models
  • Ordered and categorical discrete dependent variable models (ordered and multinomial logit and probit)

To get the most out of the course, you should also expect to spend some time between sessions building your own statistical models.