skip to navigation skip to content
- Select training provider - (Cambridge Research Methods)

Cambridge Research Methods

Cambridge Research Methods course timetable

Show:

Thu 18 Jan – Thu 25 Jan

Now Today



Thursday 18 January

10:00
Introduction to Stata (LT) (1 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture(s) on Moodle

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.

14:00
Introduction to Stata (LT) (2 of 4) Finished 14:00 - 16:00 University Centre, Hicks Room

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.

16:00
Introduction to Empirical Research (LT) Finished 16:00 - 18:00 SSRMP Zoom

This module is for anyone considering studying on an SSRMP module but not sure which one/s to choose. It provides an overview of the research process and issues in research design. Through reflection on a broad overview of empirical research, the module aims to encourage students to consider where they may wish to develop their research skills and knowledge. The module will signpost the different modules, both quantitative and qualitative, offered by SSRMP and encourage students to consider what modules might be appropriate for their research and career development.

Please note: This module has pre-recorded lectures which need to be watched before the live workshop session.

Introduction to Content Analysis (Group 1) new (1 of 5) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

Introduction to Content Analysis (Group 2) new (1 of 5) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

Introduction to Content Analysis (Group 3) new (1 of 5) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

Friday 19 January

10:00
Introduction to Stata (LT) (3 of 4) Finished 10:00 - 12:00 SSRMP pre-recorded lecture(s) on Moodle

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.

14:00
Introduction to Stata (LT) (4 of 4) Finished 14:00 - 16:00 University Centre, Cormack Room

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.

Monday 22 January

10:00
Foundations in Applied Statistics (FiAS-5) (1 of 4) Finished 10:00 - 12:30 SSRMP pre-recorded lecture(s) on Moodle

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
Foundations in Applied Statistics (FiAS-6) (1 of 4) Finished 10:00 - 12:30 SSRMP pre-recorded lecture(s) on Moodle

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
14:00
Foundations in Applied Statistics (FiAS-5) (2 of 4) Finished 14:00 - 16:00 University Centre, Cormack Room

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
Public Policy Analysis (1 of 3) Finished 14:00 - 16:00 Lecture Theatre A (Arts School)

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.

16:00
Foundations in Applied Statistics (FiAS-6) (2 of 4) Finished 16:00 - 18:00 University Centre, Cormack Room

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
Introduction to Focus Group Research (LT) new (2 of 4) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

This module introduces focus group research as a qualitative research method. Attention is given to the key elements and methodological consideration of conducting focus group research. It also explores the process of conducting focus group research, where students are given the opportunity to design focus group questions, and to experience the role of researcher in the practical workshops.

Tuesday 23 January

10:00
Causal Inference Methods new (1 of 4) Finished 10:00 - 12:00 Titan Teaching Room 1, New Museums Site

The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences.

14:00
Causal Inference Methods new (2 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences.

16:00
Ethical Review for Social Science Research (LT) new (1 of 2) Finished 16:00 - 17:30 SSRMP Zoom

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.

17:30
Open Source Investigation for Academics (LT) new (1 of 8) Finished 17:30 - 18:30 SSRMP Zoom

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.

Wednesday 24 January

10:00
Foundations in Applied Statistics (FiAS-5) (3 of 4) Finished 10:00 - 12:30 SSRMP pre-recorded lecture(s) on Moodle

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
Foundations in Applied Statistics (FiAS-6) (3 of 4) Finished 10:00 - 12:30 SSRMP pre-recorded lecture(s) on Moodle

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
14:00
Foundations in Applied Statistics (FiAS-5) (4 of 4) Finished 14:00 - 16:00 University Centre, Cormack Room

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
16:00
Foundations in Applied Statistics (FiAS-6) (4 of 4) Finished 16:00 - 18:00 University Centre, Cormack Room

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
Introduction to Focus Group Research (LT) new (3 of 4) Finished 16:00 - 18:00 SSRMP Zoom

This module introduces focus group research as a qualitative research method. Attention is given to the key elements and methodological consideration of conducting focus group research. It also explores the process of conducting focus group research, where students are given the opportunity to design focus group questions, and to experience the role of researcher in the practical workshops.

Thursday 25 January

10:00
Causal Inference Methods new (3 of 4) Finished 10:00 - 12:00 Titan Teaching Room 1, New Museums Site

The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences.

14:00
Digital and Online Research Methods (1 of 2) Finished 14:00 - 16:00 SSRMP Zoom

Virtual Data Collection in the Time of COVID-19: Practical and Ethical Considerations

Doing data collection in the time of COVID-19 has required the adaptation of existing approaches. While face-to-face data collection is not feasible during the COVID-19 crisis, phone- and internet-based interviews offer an alternative means of collecting primary data. In this workshop, we discus key practical and ethical issues concerning virtual approaches to data collection. We provide practical examples drawing on two related research projects that took place in a lower-middle income context during the Covid-19 school closures.

Causal Inference Methods new (4 of 4) Finished 14:00 - 16:00 Titan Teaching Room 1, New Museums Site

The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences.

16:00
Introduction to Content Analysis (Group 1) new (2 of 5) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

Introduction to Content Analysis (Group 2) new (2 of 5) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

Introduction to Content Analysis (Group 3) new (2 of 5) Finished 16:00 - 18:00 Titan Teaching Room 1, New Museums Site

Content analysis has been widely used to study different sources of data, such as interviews, conversations, speeches, and other texts. This module adopts an interactive approach, where students are introduced to the key elements of content analysis, how to conduct content analysis, and a range of examples of the use of content analysis. This module offers two practical workshops, where students have a hands-on opportunity to practice performing content analysis, followed by guided reflection.

An Introduction to Embodied Inquiry new Finished 16:00 - 18:00 Syndics Room 17 Mill Lane

This short course introduces Embodied Inquiry as a research method interested in knowledge generated through the body, not just knowledge of the body. Embodied Inquiry has gained traction as a creative research method capable of challenging the mind-body split and exploring the possible role of the body in research, both for the researcher and for participants. The course will provide a broad overview of the theoretical grounding for embodied inquiry, what embodied inquiry can look like within the social sciences as well as the benefits and pitfalls of embodied inquiry as a method. In addition, the course will provide opportunities to consider how embodied inquiry might relate to individual’s research projects and identifying where to find out more about embodied inquiry.