MY452M Half Unit
Applied Regression Analysis
This information is for the 2021/22 session.
Dr Daniele Fanelli
This course is available on the Global MSc in Management, Global MSc in Management (CEMS MiM), Global MSc in Management (MBA Exchange), MPhil/PhD in Demography/Population Studies, MSc in Applied Social Data Science, MSc in Comparative Politics, MSc in Conflict Studies, MSc in European and International Public Policy, MSc in European and International Public Policy (LSE and Bocconi), MSc in European and International Public Policy (LSE and Sciences Po), MSc in Gender (Research), MSc in Human Geography and Urban Studies (Research), MSc in International Migration and Public Policy, MSc in International Migration and Public Policy (LSE and Sciences Po), MSc in International Social and Public Policy (Research), MSc in Local Economic Development, MSc in Political Science and Political Economy, MSc in Public Administration and Government (LSE and Peking University), MSc in Public Policy and Administration, MSc in Social Research Methods and MSc in Urban Policy (LSE and Sciences Po). This course is available with permission as an outside option to students on other programmes where regulations permit.
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 or an equivalent level statistics course
MY452 is open to any and all post-grad students around the School who have already have a grounding in quantitative methods.
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 (MY452M) and again in LT (MY452L). 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: 81
Average class size 2020/21: 12
Controlled access 2020/21: No
Value: Half Unit