Component

MA Public Opinion and Political Behaviour
MRes Political Economy options

Year 1, Component 06

Summer school option 1
EH110-7-SU
Introduction to Regression
(30 CREDITS)
EH125-7-SU
Introduction to Social Network Analysis
(30 CREDITS)
EH130-7-SU
Introduction to Quantitative Text Analysis
(30 CREDITS)
EH137-7-SU
Statistical Modelling for Multilevel and Complex Data
(30 CREDITS)
EH142-7-SU
Introduction to Statistics for Survey Data Analysis
(30 CREDITS)
EH143-7-SU
Introduction to Quantitative Methods in R
(30 CREDITS)
EH144-7-SU
Introduction to Applied Bayesian Statistics
(30 CREDITS)
EH145-7-SU
Causal Inference and Experiments in the Social Sciences
(30 CREDITS)
EH158-7-SU
Longitudinal Data Analysis
(30 CREDITS)
EH165-7-SU
Beyond OLS: Categorical, Choice, and Count Models
(30 CREDITS)
EH172-7-SU
Machine Learning for Social Scientists
(30 CREDITS)
EH173-7-SU
Introduction to Statistics for Social Science Research with SPSS
(30 CREDITS)
EH184-7-SU
Game Theory
(30 CREDITS)
EH193-7-SU
Quantitative Data Analysis and Statistical Graphics with R
(30 CREDITS)
EH203-7-SU
Advanced Survey Data Analysis and Survey Experiments
(30 CREDITS)
EH216-7-SU
Multilevel Models: Practical Applications
(30 CREDITS)
EH217-7-SU
Bayesian Analysis for the Social and Behavioural Sciences
(30 CREDITS)
EH222-7-SU
Advanced Methods for Social Media and Textual Data
(30 CREDITS)
EH233-7-SU
Web Scraping and Data Management for Social Scientists
(30 CREDITS)
EH239-7-SU
Longitudinal and Panel Data Analysis
(30 CREDITS)
EH246-7-SU
Mixed Methods Research
(30 CREDITS)
EH295-7-SU
Quantitative Text Analysis
(30 CREDITS)
EH302-7-SU
Heterogeneity and Dynamics: Time Series and Panel Data
(30 CREDITS)
EH315-7-SU
Advanced Machine Learning: Deep Learning Models
(30 CREDITS)
EH325-7-SU
Doing Discourse Analysis: Populism, Neoliberalism and Radical Democratic Politics
(30 CREDITS)
EH326-7-SU
Computational Methods for Social Data Science: Exploring Society Through Visualisation and Modelling
(30 CREDITS)

In modern data analysis, graphics and computational statistics are increasingly used together to explore and identify complex patterns in data and to make and communicate claims under uncertainty. This course will go beyond traditional ideas of charts, graphs, maps (and also statistics!) to equip you with the critical analysis, design and technical skills to analyse and communicate with social science datasets. The course emphasises real-world applications. You will work with both new, large-scale behavioural datasets, as well as more traditional, administrative datasets located within various social science domains: Political Science, Crime Science, Urban and Transport Planning. As well as learning how to use graphics and statistics to explore patterns in these data, implementing recent ideas from data journalism you will learn how to communicate research findings – how to tell stories with data.

EH337-7-SU
Quantitative Methods for Causal Inference and Policy Evaluation
(30 CREDITS)
EH348-7-SU
Spatial Econometrics
(30 CREDITS)
EH351-7-SU
Confirmatory Factor Analysis and Structural Equation Modelling
(30 CREDITS)
EH352-7-SU
Advanced Methods for Text As Data: Natural Language Processing
(30 CREDITS)
EH354-7-SU
Introduction to Probability Theory for MLE, Bayesian Inference and Machine Learning Using R
(30 CREDITS)
EH382-7-SU
Scaling Methods and Ideal Point Estimation for Surveys and Behaviour
(30 CREDITS)

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The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications. The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.

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