Course overview
This course offers training in the foundations of psychology, decision-making, behavioural economics and behaviour change. It will also develop your understanding of state-of-the-art methods in data science and data analytics, focusing on statistical methods, machine learning, and data visualisation.
You will gain an understanding of large-scale patterns in data, with an eye to comprehending the underlying factors driving human behaviour. This can be used to understand consumer behaviour, economics, politics, history, wellbeing, and many other large-scale patterns at national and international levels. Previous experience in behavioural science is not necessary, but you should have programming skills in at least one programming language (e.g., R, Python, Matlab, or others).
Skills from this degree
Graduates will be able to:
- Use data to understand how and why people make the choices they do, and understanding the consequences of their choices in relation to public policy (e.g. encouraging people to save for pensions or change to low-carbon behaviours), industry (e.g. understanding how to place a new product in the market), and individual behaviour (e.g. understanding why people drink and eat too much)
- Access and analyse large-scale datasets
- Utilise state-of-the-art techniques in data analysis and visualisation
- Design and conduct studies using data analysis to understand behaviour
Teaching
You will have a combination of lectures, seminars and practical classes or workshops. Lectures introduce you to a particular topic, seminars build on that knowledge and workshops and practical classes allow you to put what you are learning into practice. Seminars, practical classes and workshops are smaller groups than lectures giving access to tutors to help you put into practice what you are learning.
Class sizes
Class sizes will naturally vary, however our Psychology courses comprise of around 25-30 students.
Typical contact hours
Teaching occurs throughout the week, with an average of 8-12 hours of lectures and 5-7 hours of practical classes or seminars per week. You will also have meeting with your personal tutor at intervals throughout your course.
Assessment
We typically assess modules through a mix of assessment types, which include worksheets, essays, research reports, modelling and data analysis, class tests, exams, and presentations.
Reading lists
Most departments have reading lists available through Warwick Library. If you would like to view reading lists for the current cohort of students you can visit our Warwick Library web pageLink opens in a new window.
Your timetable
Your personalised timetable will be complete when you are registered for all modules, compulsory and optional, and you have been allocated to your lectures, seminars and other small group classes. Your compulsory modules will be registered for you and you will be able to choose your optional modules when you join us.