Overview

This three-day course will focus on familiarising participants with the fundamentals of survey design and analysis, combined with practical applications using the statistical programme R. 

Please note this course is taught in person at our Bloomsbury campus.

Specifically, we will cover:

• Sampling and weighting methods and how these relate to questions of representativeness.
• Survey question and response scale design and to what extent a given question and its associated scale may (or may not) be measuring what was intended.
• Different types of response bias, such as social desirability or non-response; effective ways to describe survey data and simple multivariate analysis.
• A quick tour of the increasingly popular field of survey experiments. 

On each day, the sessions will conclude with some time to implement the concepts discussed in the lecture. Specifically, participants will do a series of practical exercises, whose solutions will be discussed step-by-step together as a class. Participants will be encouraged to work together and feel free to ask any questions to allow them to learn in a collaborative environment. In the last session of the third day, there will be an opportunity for participants to present their own survey idea and receive constructive feedback from the course instructor and other participants.

At the end of the three days, participants will have reached a good level of survey literacy, be able to identify well (or ill) designed surveys and gained confidence in their capacity to interpret survey results. The guiding theme of the course will be to learn how to think critically about what information can (and cannot) be learnt from any specific survey data.

This course is subject to minimum enrolment numbers. Should the course not proceed, participants will be informed no later than two weeks prior to the start date and will receive a full refund of any fees paid.

Who this course is for

The course is aimed at anyone who wants to use surveys or survey analysis in their professional life, including for research. 

Students should have some basic knowledge of statistics. For instance, you should know what a mean and standard deviation are and how these are calculated. Otherwise no specific background or qualifications are necessary. 

Course content

The course will be structured as follows:

• Day 1: Sampling, weighing and representativeness
• Day 2: Survey question wording and scaling methods
• Day 3: Survey experiments and causality

Teaching and structure

The course will include lectures, live coding demos and seminar exercises where students apply their knowledge using the programming language R.

It would be helpful to review the basics of descriptive statistics before the course. Students will also be sent instructions before the course on how to download the free statistical software, R, that we will use. 

Certificates

Participants will be issued with a certificate of participation upon completion of the course.

Learning outcomes 

By the end of this course you will be able to:

• Explain the main considerations involved in sampling such as weighting and representativeness.
• Critically evaluate opinion survey questions as well as successfully write their own surveys.
• Apply the main methods for analysing and extracting information from opinion surveys. 

Cost

The standard course fee is £375.

Course team

Dr. Julia de Romemont

Julia is a Lecturer in Quantitative Methods and Political Science in the UCL Department of Political Science.

She teaches a range of courses at UCL on data science and quantitative methods, including a popular module on quantitative measurement which has helped inform this course. She also applies a wide range of these methods in her research, which uses surveys and survey experiments to study public opinion on the welfare state and immigration. 

Course information last modified: 10 Apr 2026, 16:19