MY452W Half Unit
Applied Regression Analysis
This information is for the 2025/26 session.
Course Convenor
Johan Ahlbäck
Prof Jouni Kuha
Availability
This course is available on the Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MSc in Applied Social Data Science, MSc in Environmental Policy and Regulation, MSc in European and International Politics and Policy, MSc in European and International Politics and Policy (LSE and Bocconi), MSc in European and International Politics and Policy (LSE and Sciences Po), MSc in Gender (Research), MSc in Gender, Development and Globalisation, MSc in Human Geography and Urban Studies (Research), MSc in Innovation Policy, MSc in International Migration and Public Policy, MSc in International Migration and Public Policy (LSE and Sciences Po), MSc in International Political Economy (Research), MSc in International Relations (Research), MSc in International Social and Public Policy (Research), MSc in Local Economic Development, MSc in Political Science (Conflict Studies and Comparative Politics), MSc in Political Science (Political Science and Political Economy), MSc in Public Policy and Administration, MSc in Social Research Methods and MSc in Urban Policy (LSE and Sciences Po). This course is freely available as an outside option to students on other programmes where regulations permit. It does not require permission.
This course is not controlled access. If you register for a place and meet the prerequisites, if any, you are likely to be given a place.
Requisites
Mutually exclusive courses:
This course cannot be taken with MY452A at any time on the same degree programme.
Additional requisites:
The course assumes a good working knowledge of basic descriptive statistics and statistical inference, to the level covered on a standard introductory statistics course such as MY451 (Introduction to Quantitative Analysis). Some prior familiarity with linear regression modelling will also be useful.
Course content
The course provides an introduction to statistical regression modelling and different types of regression models that are commonly used in the social sciences. The main topics covered are linear regression models, binary logistics models for dichotomous outcomes, multinomial and ordinal logistic models for polytomous outcomes, and Poisson and negative binomial regression models for counts. Examples are drawn from different social sciences. The course includes computer classes, where the R software is used for computation. Prior knowledge of R is not required.
Teaching
10 hours of seminars and 20 hours of lectures in the Winter Term.
2 hours of lectures in the Spring Term.
This course has a reading week in Week 6 of Winter Term.
The course runs twice per year: in AT (MY452A) and again in WT (MY452W). The content of the course, and the method of assessment, is exactly the same in each term.
Formative assessment
Weekly multiple-choice quizzes on Moodle, with feedback on the answers.
Indicative reading
- A course pack will be available for download online.
- Gelman, A., Hill, J. & Vehtari, A. (2022). Regression and Other Stories. Cambridge University Press.
- Agresti, A. (2018). Statistical Methods for the Social Sciences. Pearson Education Limited.
- James, G., Witten, D., Hastie, T., and Tibshirani, R. (2021). An Introduction to Statistical Learning with Applications in R. Springer.
Assessment
Exam (100%), duration: 120 Minutes in the Spring exam period
Key facts
Department: Methodology
Course Study Period: Winter and Spring Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 44
Average class size 2024/25: 11
Controlled access 2024/25: NoCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.