Cambridge Research Methods (CaRM) course timetable

Open Source Investigation for Academics is methodology course run by Cambridge’s Digital Verification Corps, in partnership with Cambridge’s Centre of Governance and Human Rights, Social Sciences Research Methods Programme and Cambridge Digital Humanities, as well as with the Citizen Evidence Lab at Amnesty International.

NB. Places on this module are extremely limited, so please only make a booking if you are able to attend all of the sessions.

With such a large variety of qualitative research methods to choose from, creating a research design can be confusing and difficult without a sufficiently informed overview. This module aims to provide an overview by introducing qualitative data collection and analysis methods commonly used in social science research. The module provides a foundation for other SSRMP qualitative methods modules such as ethnography, discourse analysis, interviews, or diary research. Knowing what is ‘out there’ will help a researcher purposefully select further modules to study on, provide readings to deepen knowledge on specific methods, and will facilitate a more informed research design that contributes to successful empirical research.

NB. This module has video content that needs watching prior to the advertised start date, which can be found on the Moodle page.

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 (4 hours live workshop) and trying out the role of a researcher as well as research participant (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.

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

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.

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 SSRMP. 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.

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 SSRMP. 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.

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 SSRMP. 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.

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 SSRMP. 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.

This module is shared with Psychology. Students from the Department of Psychology MUST book places on this course via the Department; any bookings made by Psychology students via the SSRMP portal will be cancelled.

The course focuses on practical hands-on variable handling and programming implementation using rather than on theory. This course is intended for those who have never programmed before, including those who only call/run Matlab scripts but are not familiar with how code works and how matrices are handled in Matlab. (Note that calling a couple of scripts is not 'real' programming.)

MATLAB (C) is a powerful scientific programming environment optimal for data analysis and engineering solutions. More information on the programme and its uses can be found here

More information on the course can be found here

This module is shared with Psychology. Students from the Department of Psychology MUST book places on this course via the Department; any bookings made by Psychology students via the SSRMP portal will be cancelled.

The course focuses on practical hands-on variable handling and programming implementation using rather than on theory. This course is intended for those who have never programmed before, including those who only call/run Matlab scripts but are not familiar with how code works and how matrices are handled in Matlab. (Note that calling a couple of scripts is not 'real' programming.)

MATLAB (C) is a powerful scientific programming environment optimal for data analysis and engineering solutions. More information on the programme and its uses can be found here

More information on the course can be found here

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.

With such a large variety of qualitative research methods to choose from, creating a research design can be confusing and difficult without a sufficiently informed overview. This module aims to provide an overview by introducing qualitative data collection and analysis methods commonly used in social science research. The module provides a foundation for other SSRMP qualitative methods modules such as ethnography, discourse analysis, interviews, or diary research. Knowing what is ‘out there’ will help a researcher purposefully select further modules to study on, provide readings to deepen knowledge on specific methods, and will facilitate a more informed research design that contributes to successful empirical research.

NB. This module has video content that needs watching prior to the advertised start date, which can be found on the Moodle page.

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 (4 hours live workshop) and trying out the role of a researcher as well as research participant (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.

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

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.

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.

Ethics and the associated process of approval / review are an important component of any research project, not only practically enabling research to take place but also enabling researchers to consider the values underpinning their research. The aim of this course is to take both a practical and reflective approach to ethics. On a practical level, the course will focus on identifying the steps involved in seeking ethical approval or undertaking an ethical review. On a reflective level, the course will explore the values informing key ethical principles and concepts and how these may relate to individual’s research.

With such a large variety of qualitative research methods to choose from, creating a research design can be confusing and difficult without a sufficiently informed overview. This module aims to provide an overview by introducing qualitative data collection and analysis methods commonly used in social science research. The module provides a foundation for other SSRMP qualitative methods modules such as ethnography, discourse analysis, interviews, or diary research. Knowing what is ‘out there’ will help a researcher purposefully select further modules to study on, provide readings to deepen knowledge on specific methods, and will facilitate a more informed research design that contributes to successful empirical research.

NB. This module has video content that needs watching prior to the advertised start date, which can be found on the Moodle page.

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 (4 hours live workshop) and trying out the role of a researcher as well as research participant (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.

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

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.

This is an introductory course for students who have little or no prior training in statistics.

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to analyse real data using the statistical package, Stata.

You will learn:

• The key features of quantitative analysis, and how it differs from other types of empirical analysis
• The basics of formal hypothesis testing
• Basic concepts: what is a variable? what is the distribution of a variable? and how can we best represent a distribution graphically?
• Features of statistical distributions: measures of central tendency and dispersion
• The normal distribution
• Why statistical testing works
• Statistical methods used to test simple hypotheses
• How to use Stata

This is an introductory course for students who have little or no prior training in statistics.

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to analyse real data using the statistical package, Stata.

You will learn:

• The key features of quantitative analysis, and how it differs from other types of empirical analysis
• The basics of formal hypothesis testing
• Basic concepts: what is a variable? what is the distribution of a variable? and how can we best represent a distribution graphically?
• Features of statistical distributions: measures of central tendency and dispersion
• The normal distribution
• Why statistical testing works
• Statistical methods used to test simple hypotheses
• How to use Stata

This is an introductory course for students who have little or no prior training in statistics.

The module is divided between pre-recorded mini-lectures, in which you'll learn the relevant theory, and hands-on live practical sessions in Zoom, in which you will learn how to analyse real data using the statistical package, Stata.

You will learn:

• The key features of quantitative analysis, and how it differs from other types of empirical analysis
• The basics of formal hypothesis testing
• Basic concepts: what is a variable? what is the distribution of a variable? and how can we best represent a distribution graphically?
• Features of statistical distributions: measures of central tendency and dispersion
• The normal distribution
• Why statistical testing works
• Statistical methods used to test simple hypotheses
• How to use Stata