Early clearing information
This course is available through clearing for home and international applicants
If you already have your exam results, meet the entry requirements, and are not holding an offer from a university or college, then you may be able to apply to this course.
Contact the admissions team
Bachelor of Science (BSc)
BSc Global Development
Duration: 3 years
Year of entry: 2025
UCAS course code: L905 / Institution code: M20
- Key features:
Scholarships available
- Typical A-level offer: AAB
- Typical contextual A-level offer: BBB
- Refugee/care-experienced offer: BBC
- Typical International Baccalaureate offer: 35 points overall with 6,6,5 at HL
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £29,000 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).
Scholarships/sponsorships
We are committed to attracting and supporting the very best students from all backgrounds to study this course.
You could be eligible for cash bursaries of up to £2,500 to support your studies.
Find out about our funding opportunities
Course unit details:
Intermediate Statistical Methods
| Unit code | MGDI20251 |
|---|---|
| Credit rating | 20 |
| Unit level | Level 2 |
| Teaching period(s) | Semester 1 |
| Available as a free choice unit? | Yes |
Overview
This is an intermediate course in quantitative research methods for analysing both economic and social data. It focuses on applied statistics/econometric methods: how methods are used and interpreted rather than their theoretical derivations, and it is designed for students with strong quantitative background. It covers concepts, relevant applications in social science research, and practical exercises using statistical software. Emphasis is placed on understanding concepts and applications, estimation, testing, model building, and practical application using real-word data to answer pertinent development questions. Thus, the unit has strong focus on concepts, developing practical experience, and confidence use of statistical software (Stata).
Aims
The unit aims to enable students, through development of conceptual insights and practical skills to become:
- Critical and competent users of statistics in applied development studies and research.
- Able and critical readers of academic and policy articles with an empirical content.
Syllabus
- Probability distributions
- Statistical inference (estimation & significance tests)
- Analysing association between categorical variables
- Linear Regression and Correlation
- Linear Multiple regression analysis
- Multiple regression model
Teaching and learning methods
The course unit will draw on a range of teaching and learning strategies; lectures, tutorials, computer based lab sessions (STATA) and independent learning by students using e-learning materials provided on the VLE and the recommended textbooks. During the 2-hour lecture sessions, student participation will be encouraged and welcomed through asking and answering questions. Students will be expected to have gone through teaching slides and e-learning materials provided in the VLE before lectures/tutorials/Stata lab sessions.
Knowledge and understanding
- Undertake statistical inference: estimation and significance tests.
- Explain the conceptual foundation of multiple regression analysis.
- Use modern causal-effect theory to specify, fit regression models, and undertake robust regression analysis.
Intellectual skills
- Apply concepts in statistics/econometrics and critique statistical results presented in published articles and journals.
- Employ concepts in statistics/econometrics to analyse real-word data.
Practical skills
- Produce empirical work, using alternative forms of regression analysis.
- Analyse and interpret regression results.
Transferable skills and personal qualities
- Use Stata software package for conducting multivariate regression analysis, undertake diagnostic tests, and interpret quantitative results.
- Examine published empirical work with statistical/econometric contents, and make analytical judgement.
Assessment methods
Assessment 1: Mid-term examination (1 Hour) — 30%
Assessment 2: End of semester examination (2 Hours) — 70%
Feedback methods
Feedback on the assessments via the VLE within SEED guidelines.
Recommended reading
Agresti A. (2024). Statistical Methods for the Social Sciences, 6th Edition. Pearson Education Ltd.
Soderbom M. & Teal F. (2015). Empirical Development Economics, Routledge.
Stock J.H. & Watson M.W. (2020). Introduction to Econometrics, Updated 4th ed. Pearson Education.
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 20 |
| Practical classes & workshops | 10 |
| Tutorials | 10 |
| Independent study hours | |
|---|---|
| Independent study | 160 |
Teaching staff
| Staff member | Role |
|---|---|
| Lawrence Ado-Kofie | Unit coordinator |