Summer Schools


Quantitative Research Summer School

We are currently reviewing our 2021 delivery. To register your interest for Summer 2021, contact us here.


This is an introductory course to quantitative methods and statistics. The course starts with the very core elements of statistical analysis and covers descriptive statistics for categorical and continuous data, analysis of contingency tables, proportions, measures of central tendency and dispersion, before moving onto correlation and simple linear regression and working up to multiple linear regression. The course finishes with a brief overview of further regression techniques such as logistic regression and is designed to prepare students for further statistical courses in later years. It is designed to give a good grounding in the use of the statistical software SPSS.


Throughout the course the students will work in multi-disciplinary groups including both international and Kent undergraduates from across the social sciences. The program is based on a problem-based learning initiative framework. In this learning model the teachers (or instructor) give the tools, via lectures and seminars, to enable to students to conduct an investigation into a real-world problem that they get to define. The group project of 4 or 5 students is where they apply the knowledge they are learning to a problem that they define and of direct interest to them on the theme of Race and Ethnicity.

This module aims to develop key statistical skills in students. Learning will be oriented towards:

  • Assessing the strengths and limitations of using regression analysis for the establishment of causal inference; This includes:
    • Distinction between causality, correlation or association
    • Levels of measurement (e.g. nominal, ordinal, interval, ratio)
    • Methods of regression analysis (e.g. OLS and logistic regression) and related assumptions
  • Learning how to respond to research questions with the application of statistical methods of analysis, mainly regression methods, with the help of statistical software.
  • Learning how to interpret the outcome of regression models and contextualise the results within broader theories.

For additional reasons to join us, visit our Canterbury Summer Schools overview.

The Quantitative Methods Summer School is part of the University of Kent Summer School programme. It will allow you to make lasting connections with students from around the world, studying a range of subjects but sharing your own enthusiasm. International study will enable you to gain a deeper understanding of another culture, make lifelong friends from a wide variety of backgrounds and benefit from globally-renowned academic excellence.

Please note: if you are a current Kent Social Sciences student seeking to add Quantitative Methods to your undergraduate degree please visit

Providing School: School of Social Policy, Sociology and Social Research

Campus: Canterbury

Credit Transfer Option: 15 UK Credits (150 study hours; 7.5 ECTS; suggested 3.75 US credits*) for transfer purposes.

Price: TBC for 2021; for two weeks. Includes tuition, accommodation, teaching materials, welcome meal, organised trips and full library access

*Suggested 3.75 US credits based on 1/8th of a full academic year. Please check with your home institution for their UK to US credit conversion rules.

back to top

Learning outcomes

By the end of this International Summer School course, you will:

Intended specific learning outcomes

    1. Demonstrate knowledge of validity, reliability and transparency issues when carrying out statistical analyses;
    2. Understand the difference between descriptive statistics (i.e. central tendency and dispersion) and inferential statistics (i.e. correlation, regression);
    3. Demonstrate an ability to select the correct method of statistical analysis (description, correlation/association, statistical inference) based on the research question under study, the study design and data available;
    4. Demonstrate at least a basic ability to read, understand and report/represent (e.g. tables, graphs) the results of regression analyses;
    5. Demonstrate at least a basic ability to carry out multiple forms of regression analysis with the help of statistical software (e.g. SPSS, Excel).
    6. Demonstrate at least a basic understanding of which assumptions of regression (e.g. heterocedasticity) are most often violated, and to know where to find further information about the appropriate actions to take when assumptions are not met (e.g. remove outliers);
    7. Understand at least the basic underlying principles of causality and main limitations when assessing causal inference;
    8. Understand at least at a basic level the advantages and limitations of using regression for the study of causality;

Intended generic learning outcomes

    1. Demonstrate quantitative analytical skills that will enable them to examine complex societal processes;
    2. Understand the strengths and weaknesses of quantitative methods of analysis and apply sound judgement when selecting the statistical method of analysis;
    3. Demonstrate proficiency in the use of one or various statistical software packages (e.g. SPSS)

Learning and teaching methods

The teaching takes problem-based learning approach where students work in mixed-subject groups to define their own research question and complete the research over the two weeks. Lecturers will support the students with tuition on the adequate tools to be used for their research and guide them through the research process.

Total number of study hours will comprise 150 hours which will include elements of independent and private study as follows:

14 hours lectures, 9 hours seminars, 18 hours of research supervisor-supported group work, 109 hours independent study

Total: 150 hours


  • 55% for subsequent individual report where the analysis and an extra work from the feedback in the conference due 3 weeks after the end of the course and returned 10 days later.
  • 40% awarded for the group work exercise, assessed via a student led conference on the last day of the 2 week course where marks are awarded to all members of the group dependent on the overall quality of the research topic.
  • 5% for regular and punctual attendance to each of the 10 days (including 9 lectures, 9 seminars and the final day conference)

Indicative Timetable






AM Welcome and Registration

AM Group Work

AM Group Work

AM Group Work

AM Group Work

Introduction to the Course

Guest Lecture, The Measurement of Ethnicity

Lecture 2: Categorical and Continuous Data and Descriptive Statistics

Lecture 3: Contingency Tables and Chi Squared

Lecture 4: Inference for Proportions and Means

Lecture 5: Correlation

Next Steps

Next Steps

Next Steps

Next Steps

Lecture 1 - What is Data?

Group Work

Group Work

Group Work

Group Work

Group Work

Expert Lunch 1 - "Numbers at Work"

Group Work

PM Seminar 1 - Introduction to SPSS and the Data Archive



PM Seminar 2 - Variable Selection, creating and using descriptive statistics


PM Seminar 3 - Bivariate Analysis




PM Seminar 4 - Inference for Proportions and Means



PM Seminar 5 - Correlation and Outliers



To gain entry on to the Canterbury Quant Summer School you will need to be either:

  • studying at a university outside the UK or at a UK university and considering options for further study in the UK
  • a professional exploring options for undergraduate or postgraduate study in the UK. 

You will also need to:

  • demonstrate an interest in and an aptitude for the study of Quantitative Methods and Research, with a general confidence with Maths (minimum B in GCSE Maths or equivalent). This is an introductory course so those who have worked extensively with quantitative methods will not find this course useful.
  • interest in social issues and social policy
  • applicants will also need to be confident reading, writing and discussing in English to participate in the Summer School and will have at least IELTS 6.0 or equivalent with a minimum of 5.5 in each skill. Please note that an IELTS test is not required and that we can use English language iGCSE/GCSE, iB Standard Level English, TOEFL, PTE, TOEIC, FCE/CAE, CET-4 (China) among others.

Fees and Scholarship

A reminder that you can apply for more than one Summer School.


  Earlybird Price Standard Price

Without Accommodation

TBC for 2021

TBC for 2021

With Accommodation included

TBC for 2021

TBC for 2021

We also offer a 10% discount to students from our recognised Partner Universities.

Fees Include full tuition for the summer school, accommodation, teaching materials, a welcome meal, full access to the University library facilities. Also included are visits to Canterbury Cathedral, Margate, Whitstable and to London.

Scholarship Opportunities

We will have a number of £500 Internationalisation Scholarships available for the Canterbury Summer Schools available to students not currently studying at the University of Kent. If you are a current student at another institution you may also wish to enquire about any mobility scholarships within your home institution or Government.

Accommodation details

The accommodation for this summer school is based in Park Wood and is offered on a self-catered basis. Students will be placed in their own room and will share bathrooms and kitchen. Check-in is after 14h00 on the first Sunday and check-out is before 10h00 on the final Sunday. All students will be offered University accommodation (included in fee), although if you wish to make alternative arrangements you can pay tuition fees only, saving £250 per two-week course.

Additional details about our accommodation is available on our Accommodation webpage.

Getting here

You will find useful directions to the Canterbury Campus on our Directions page. Students who wish to arrange a taxi transfer from one of the London airports may wish to visit our Booking a Taxi in the UK page.


Every effort is made to ensure that the information contained in publicity materials is fair and accurate at the time of going to press. However, the courses, services and other matter covered by web pages and prospectuses are subject to change from time to time and changes may need to be made following publication and/or after candidates have been admitted to the University. Please see our institution wide Terms and Conditions / Disclaimer page for further information. Please note that modules shown are based on the current curriculum, but are subject to change.

University of Kent - © University of Kent

The University of Kent, Canterbury, Kent, CT2 7NZ, T: +44 (0)1227 764000

Last Updated: 14/10/2020