MY552M Half Unit
Applied Regression Analysis
This information is for the 2021/22 session.
Dr Daniele Fanelli
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.
Students are required to have completed MY451/MY551 Introduction to Quantitative Analysis or an equivalent level statistics course.
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.
This course is delivered through a combination of classes and lectures totalling a minimum of 20 hours per term. This year, some or all of this teaching will be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos.
The course runs twice per year: in MT (MY552M) and again in LT (MY552L). 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 MT.
Self-guided computer exercises to be completed before weekly classes for discussion.
A Agresti & B Finlay, Statistical Methods for the Social Sciences. A course pack will be available for download online. Additional reading will be recommended.
Exam (70%, duration: 2 hours) in the summer exam period.
Continuous assessment (30%) in the MT.
Homework and participation will constitute 30% of the final overall mark.
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Important information in response to COVID-19
Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Total students 2020/21: 1
Average class size 2020/21: 1
Value: Half Unit