Social Sciences Research Methods Programme course timetable

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

Module 4 introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research.

Students are introduced to multilevel modelling techniques (a.k.a. hierarchical linear modelling). MLM allows one to analyse how contexts influence outcomes ie do schools/neighbourhoods influence behaviour.

STATA will be used during this module - there will be no overlap with other SPSS modules. No prior knowledge of STATA will be assumed.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research.

The module provides an overview of interviewing as a social research method - guidance on planning interviews, pre-interview and post-interview tasks, positionality and ethics. It also provides an introduction to module structure, based on a specific interview topic. It concentrates on the processes of organising information after interviews, including interpretation through coding and close reading. Case Studies will look at PhD research on perceptions of forest use in Madagascar; in particualar the process of gathering qualitative interviews - planning through transcription to analysis. Looking at issues of gaining access and introducing sensitive research to interviewees, creating a good interview environment; the ethics of researching controversial/illegal topics.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

The module introduces time series techniques relevant to forecasting in social science research and computer implementation of methods; covering time series regression; moving average; exponential smoothing, and decomposition. The study of applied work is emphasised in this non-specialist module.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

Module 4 introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

Module 4 introduces students to one of the most fundamental statistical techniques, namely regression analysis. Students learn about assumptions underlying regression models, how to run regression analysis using SPSS and how to access and solve possible problems with a regression model.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research.

Students are introduced to multilevel modelling techniques (a.k.a. hierarchical linear modelling). MLM allows one to analyse how contexts influence outcomes ie do schools/neighbourhoods influence behaviour.

STATA will be used during this module - there will be no overlap with other SPSS modules. No prior knowledge of STATA will be assumed.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This course is intended for students with no prior statistical training who wish to improve their comprehension and critical analysis of statistics as presented in academic publications. This is a distinct skill which is often overlooked when studying the application of statistics and one, as with any other skill, which requires training.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for eligible graduate students who have no prior training in statistics.

It introduces students to the basic general concepts that underlie descriptive and inferential statistics. Topics covered include the notion of variables and how they are measured; ways of describing the central tendency and dispersion of a variable; basic idea of sampling and statistical inference; and principles of hypothesis testing and statistical significance.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This module aims to provide students with an overview of survey methods, uses and limitations; to introduce students to the practicalities of design and use of surveys; to examine complexities of question and answer process; to examine practicalities of survey sampling and response.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research.

Introducing students to the general philosophical debates concerning scientific methodology; assessing their ramifications for the conduct of qualitative social research. To critically evaluate major programmes in the philosophy of sciences, considering whether there are important analytic differences between the social and natural sciences; and whether qualitative methods themselves comprise a unified approach to the study of social reality.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research.

An introduction to comparative historical research methods, emphasising their qualitative dimensions.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for eligible graduate students who have no prior training in statistics.

It introduces students to the basic general concepts that underlie descriptive and inferential statistics. Topics covered include the notion of variables and how they are measured; ways of describing the central tendency and dispersion of a variable; basic idea of sampling and statistical inference; and principles of hypothesis testing and statistical significance.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This course is intended for students with no prior statistical training who wish to improve their comprehension and critical analysis of statistics as presented in academic publications. This is a distinct skill which is often overlooked when studying the application of statistics and one, as with any other skill, which requires training.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This foundational course is for eligible graduate students who have no prior training in statistics.

It introduces students to the basic general concepts that underlie descriptive and inferential statistics. Topics covered include the notion of variables and how they are measured; ways of describing the central tendency and dispersion of a variable; basic idea of sampling and statistical inference; and principles of hypothesis testing and statistical significance.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.

This module aims to provide students with an overview of survey methods, uses and limitations; to introduce students to the practicalities of design and use of surveys; to examine complexities of question and answer process; to examine practicalities of survey sampling and response.

This module is part of the Social Science Research Methods Course programme which is a shared platform for providing research students with a broad range of quantitative and qualitative research.

Introducing students to the general philosophical debates concerning scientific methodology; assessing their ramifications for the conduct of qualitative social research. To critically evaluate major programmes in the philosophy of sciences, considering whether there are important analytic differences between the social and natural sciences; and whether qualitative methods themselves comprise a unified approach to the study of social reality.