- UCAS course code
- LL23
- UCAS institution code
- M20
Bachelor of Arts (BASS)
BASS Politics and Sociology
Duration: 3 or 4 years
Year of entry: 2025
UCAS course code: LL23 / Institution code: M20
- Key features:
Study abroad
Industrial experience
- Typical A-level offer: ABB including specific subjects
- Typical contextual A-level offer: BBC including specific subjects
- Refugee/care-experienced offer: BBC including specific subjects
- Typical International Baccalaureate offer: 34 points overall with 6,5,5 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 £26,500 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
Scholarships and bursaries, including the Manchester Bursary , are available to eligible home/EU students.
Some undergraduate UK students will receive bursaries of up to £2,000 per year, in addition to the government package of maintenance grants.
You can get information and advice on student finance to help you manage your money.
Course unit details:
Applied Statistics for Social Scientists
| Unit code | SOST10142 |
|---|---|
| Credit rating | 20 |
| Unit level | Level 1 |
| Teaching period(s) | Semester 2 |
| Available as a free choice unit? | Yes |
Overview
The main topics to be covered are:
- Data exploration and visualization using R
- Descriptive statistics
- Modelling with Continuous Data
- Modelling with categorical Variables
Aims
The aims of this course are for each student to achieve:
- an introductory to data cleaning and exploration
- an understanding of basic statistics tests
- an understanding of multivariate statistical analysis
- an ability to use statistical software R
Learning outcomes
- be able to import and export data in R
- be able to prepare data in R
- be able to produce visualisations of data
- be able to understand and run descriptive statistics in R
- be able to understand and run a battery of test of hypothesis in R
- be able to understand and run a variety of statistical models in R
Teaching and learning methods
Lectures, practicals and coursework.
Please note the information in scheduled activity hours are for guidance only and may change.
Assessment methods
| Method | Weight |
|---|---|
| Written assignment (inc essay) | 75% |
| Set exercise | 25% |
Feedback methods
Feed-back on individual based essay
Recommended reading
Agresti, A. (2018). Statistical Methods for the Social Sciences (5th ed.). Pearson.
Fogarty, B. (2019). Quantitative Social Science Data with R.
Hothorn, T., & Everitt, B. (2014). A handbook of statistical analyses using R (Third edition). CRC Press, Taylor & Francis Group. Landers, R. N. (2019). A step-by-step introduction to statistics for business. SAGE.
Leon-Guerrero, A., & Frankfort-Nachmias, C. (2018). Essentials of social statistics for a diverse society (Third edition). SAGE.
Wickham, H., & Grolemund, G. (2017). R for Data Science: import, tidy, transform, visualize, and model data. O’Reilly UK Ltd.
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 20 |
| Practical classes & workshops | 8 |
| Independent study hours | |
|---|---|
| Independent study | 172 |
Teaching staff
| Staff member | Role |
|---|---|
| Todd Hartman | Unit coordinator |