The University is required to collect the following information by the Higher Education Statistical Agency.
The University of Essex is registered under the terms of the Data Protection Act to enable it to hold and process personal data about its participants. These data comprise details about admission, academic background, course registration and academic progress while at the University. They also include information collected by the University for the purposes of equal opportunities monitoring. The University will process these data for various administrative, academic and health and safety purposes. The data will be kept secure and accurate and will only be disclosed to people who have a need to know in accordance with the University’s registration under the Act.
Other White Background
Black or Black British- Carribbean
Black or Black British- African
Other Black Background
Asian or Asian British- Indian
Asian or Asian British- Pakistani
Asian or Asian British- Bangladeshi
Chinese or Other Ethnics Background- Chinese
Other Asian Background
Mixed- White and Black Carribbean
Mixed- White and Black African
Mixed- White and Black Asian
Other Mixed Background
Other Ethnic Background
Blind/ Partially Sighted
Deaf/ Hearing Impaired
Weelchair User/ Mobility Problems
Personal Care Support
Mental Health Difficulties
An Unseen Disability (E.G Asthma or Diabetes)
A Disability not mentioned above
Prefer not to say
Special Requirements / Medical Notes
Fees: Course fees are described here.
Schedule: The course schedules for each session can be found here.
Morning courses are 10:00-13:30 BST time. Afternoon 14:15-17:45 BST time. These times are final.
Sessions: Pre-sessional: Monday 4-Friday 8 July, Session 1: Monday 11-22 July, Session 2: Monday 25 July-Friday 5 August and Session 3: Monday 8-Friday 19 August 2022.
Courses are delivered in in person, online or hybrid mode.
In person courses will be held at our Colchester campus. Online study is not available for these courses.
Online courses will be taught via Zoom. In person study is not available for these courses.
Hybrid courses are available for study either in person or online. Hybrid delivery of courses will include synchronous live sessions during which on campus and online students will be taught simultaneously.
for each session you will attend. no more than one afternoon and one morning course
– Note that course 2Q is a full day course and
course that occurs simultaneously. cannot be taken in conjunction with an afternoon or morning
– Maths classes begin at 8:15 am every morning and is offered free of charge with any paid course. Participants are encouraged to attend these lectures if they feel they need supplementary instruction.
– Intro to R (6 hours) takes place the Sunday before each session and can be taken in conjunction with any course.
– If you have questions about your application, please
contact the ESS office by email before completing your application.
0A Introduction to R Programming in the Social Sciences (Online) – PM
1A Maths (Online only)
1X Introduction to R (Online only)
1B Introduction to Quantitative Text Analysis (Online only)
1C Introduction to Regression (Online only)
1D Introduction to Social Network Analysis (Hybrid)
1E Statistical Modeling for Multilevel and Complex data (In person only)
1H Qualitative Data Analysis: From Content to Discourse (In person only)
1I Qualitative Interviewing (In person only)
1J Beyond OLS: Categorical, Choice and Count Models (Online only)
1K Introduction to Applied Bayesian Statistics (Hybrid)
1L Web Scraping and Data Management for Social Scientists (Online only)
1N Methods for Fieldwork in Social Science (Hybrid)
1P Introduction to GIS, Geospatial Data and Spatial Analysis (17.5 hours, week one, online only)
1Q Doing Discourse Analysis: Populism, Neoliberalism and Radical Democratic Politics (Online only)
1F Introduction to Statistics for Survey Data Analysis (Hybrid)
1G Longitudinal Data Analysis (Online only)
1M Introduction to Quantitative Methods in R (Online only)
1S Quantitative Methods for Hard to Reach Populations (17.5 hours, week one only, Online only)
Full Day Course
Both 1P (Online) and 1S (Hybrid)
2A Maths (Online only)
2X Introduction to R (Online only)
2B Quantitative Data Analysis and Statistical Graphics with R (In person only)
2E Multilevel Models: Practical Applications (Online only)
2F Quantitative Text Analysis (In person only)
2G Panel Data Analysis for Comparative Research (In person only)
2H Mixed Methods Research (In person only)
2I Applying Discourse Theory – Politics, Ideology, Populism (Hybrid)
2L Spatial Econometrics (Hybrid)
2M Introduction to Probability Theory for MLE, Bayesian Inference and Machine Learning Using R (Hybrid)
2N Confirmatory Factor Analysis and Structural Equation Modelling (Online only)
2C Advanced Survey Data Analysis and Survey Experiments (Online only)
2D Case Study Methods (In person only)
2J Machine Learning for Social Scientists (In person only)
2K Causal Inference and Experiments in the Social Sciences (Hybrid)
2R Advanced Social Network Analysis (17.5 hours, week one only, Hybrid)
2S Introduction to Statistics for Social Science Research with SPSS (Online only)
2T Survival Analysis and Event History Modelling (17.5 hours, week two only, online only)
Full Day Course
2Q Ethnography and Ethnographic Methods (35 hours, week one only, in person only)
Both 2Q (in person) and 2T (online)
Both 2R (Hybrid) and 2T (Online only)
3A Maths (Online only)
3X Introduction to R (Online only)
3B Advanced Methods for Social Media & Textual Data (In person)
3D Computational Methods for Social Data Science: Exploring Society Through Visualisation and Modelling (Hybrid)
3F Bayesian Analysis for the Social and Behavioural Sciences (Hybrid)
3H Introduction to Programming in Python for Social Scientists (17.5 hours, week one only, Hybrid)
3G Quantitative Methods for Causal Inference and Policy Evaluation (Online only)
3K Time Series and Panel Models for Dynamic and Heterogeneous Processes (Hybrid)
3L Scaling Methods and Ideal Point Estimation for Surveys and Behaviour (Hybrid)
3M Advanced Methods for Text as Data: Natural Language Processing (Online only)
3N Advanced Machine Learning (Online only)
3P Agent-Based Models (17.5 hours, week one only, Hybrid)
Full Day Course
Both 3H (Hybrid) and 3P (Hybrid)
Policy Statement on Equality, Diversity and Inclusion
The University of Essex fosters good relations between people who share a relevant protected characteristic and those who do not, celebrates diversity, challenges inequality and is committed to nurturing an inclusive and diverse community that is open to all who have the potential to benefit from membership of it, and which ensures equality of opportunity for all its members. We expect all our campus communities, employees, workers, contractors, students, invitees and visitors to be treated, and to treat others, with dignity and respect. We have a zero-tolerance approach to discrimination, harassment and bullying. Zero tolerance means that (i) we will take action and (ii) the action will be proportionate to the circumstances of the case.
We are committed to meeting our obligations under the Equality Act 2010, which requires the University show no discrimination as required by law on account of age, disability, gender reassignment*, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, and sexual orientation. The University will always act lawfully and this may include taking action to support people with particular protected characteristics, including disability and sex. In addition to its obligations under the EA, the University shall adopt policies, practices, and procedures that define expected standards of behaviour and specify any additional characteristics, beyond those required by law, to which protection is provided, for example, in relation to political belief, social background and refugee status.
For the purposes of this Policy Statement the term ‘trans’ is an umbrella term to describe people whose gender is not the same as, or does not sit comfortably with, the sex they were assigned at birth. The term ‘non-binary’ is an umbrella term for people whose gender identity does not sit comfortably with ‘woman’ or ‘man’. Non-binary identities are varied and can include people who identify with some aspects of binary identities, while others reject them entirely.
*The University’s policies, practices and procedures specifically extend to all gender identities including trans, non-binary and gender non-conforming people.
I understand that it is a term of my contract with the University to agree to the following and that it is my responsibility to read the necessary regulations, policies and procedures before I agree.
I agree to comply with and meet any and all conditions set out in the
Regulations relating to Registration, the Code of Student Conduct, IT Acceptable Use Policyand Library Regulations from the date of my first period of registration as a student on the summer school to the date I complete the course or withdraw permanently, as recorded by the University. I understand that this period may include a series of individual registration periods. I understand that, I have to provide original documents to Registration to prove who I am, and show that I have the right to study in the UK for the course I am taking. The documents I need to give are shown in the
Acceptable Types of ID list on the University’s website.
I understand that each time I register I have to pay all of the fees. If I am getting funding for my fees from a sponsor (e.Government, Embassy, Employer) I understand that I have to pay all of the fees myself if my sponsor does not pay.
Cancellation and Refund Policies
Cancellations made prior to 1st June 2022: an administrative charge of £50.00 or a full refund less your £50.00 non-refundable deposit payment.
Cancellations made between 1st June and 1st July 2022: A fifty percent charge or refund of fifty percent.
Cancellations made after 1st July 2022: No refund to be made.
Registered participants on courses cancelled by the Summer School organisers will be entitled to claim a full refund.
Registered participants with unsuccessful visa attempts will be entitled to claim a full refund.
Extenuating circumstances will also be considered at the organiser’s discretion.
I understand that the information being collected on this form is necessary for my contract with the University. I understand that there is a fuller explanation of how the University uses my personal data, and of my rights in relation to my data, in the University’s
I accept that the University is not liable for any loss or damage suffered or incurred by me or other parties as a result of delays or in termination of its services or any aspect of its academic provision by reason of natural disaster or unavoidable events that are beyond the reasonable control of the University.
I will follow all the University’s health and safety regulations and guidance related to the COVID-19 pandemic.
I will read the University’s
webpage prior to coming onto campus and act accordingly if I am attending a summer school in-person.
I agree to abide by the above Registration declaration statements for the duration of my period of registration at the University