MY552A Half Unit
Applied Regression Analysis
This information is for the 2023/24 session.
Teacher responsible
Professor Jouni Kuha
Availability
This course is available on the MPhil/PhD in Cities Programme, MPhil/PhD in Data, Networks and Society, MPhil/PhD in European Studies, MPhil/PhD in Health Policy and Health Economics, MPhil/PhD in International Relations, MPhil/PhD in Media and Communications, MPhil/PhD in Social Policy, MPhil/PhD in Social Research Methods, MPhil/PhD in Sociology, MRes/PhD in Management (Employment Relations and Human Resources), MRes/PhD in Management (Marketing), MRes/PhD in Management (Organisational Behaviour) and MRes/PhD in Political Science. This course is available as an outside option to students on other programmes where regulations permit.
Research students where programme regulations allow. 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.
Pre-requisites
Students are required to have completed MY451/MY551 Introduction to Quantitative Analysis or an equivalent level statistics course.
Course content
The course is designed for students with a good working knowledge of elementary descriptive statistics; sampling distributions; one and two sample tests for means and proportions; correlation and the linear regression model with one or more predictor variables. The course is concerned with deepening the understanding of the generalized linear model and its application to social science data. The main topics covered are linear regression modelling and binary, multinomial and ordinal logistic regression.
Teaching
This course is delivered through a combination of classes and lectures totalling a minimum of 20 hours across Autumn Term.
The course runs twice per year: in AT (MY552A) and again in WT (MY552W). The content of the course, and the method of assessment, is exactly the same in each term.
This course has a Reading Week in Week 6 of AT.
Formative coursework
Self-guided computer exercises to be completed before weekly classes for discussion.
Indicative reading
A Agresti & B Finlay, Statistical Methods for the Social Sciences. A course pack will be available for download online. Additional reading will be recommended.
Assessment
Exam (100%, duration: 2 hours) in the spring exam period.
Key facts
Department: Methodology
Total students 2022/23: Unavailable
Average class size 2022/23: Unavailable
Value: Half Unit
Course selection videos
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