杏吧论坛

Dr Michael Schultz

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 Environmental Policy and Regulation, MSc in European and International Politics and Policy, MSc in European and International Politics and Policy (杏吧论坛 and Bocconi), MSc in European and International Politics and Policy (杏吧论坛 and Sciences Po), MSc in Gender (Research), MSc in Inequalities and Social Science, MSc in International Migration and Public Policy, MSc in International Migration and Public Policy (杏吧论坛 and Sciences Po), MSc in International Political Economy (Research), MSc in International Relations (Research), MSc in International Social and Public Policy (Research), MSc in Political Science (Conflict Studies and Comparative Politics), MSc in Public Administration and Government (杏吧论坛 and Peking University) and MSc in Public Policy and Administration. This course is available with permission as an outside option to students on other programmes where regulations permit.

The course is also available to research students as MY551.

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.

An intensive introduction to quantitative data analysis in the social sciences. The course is intended for students with no previous experience of quantitative methods or statistics. It covers the foundations of descriptive statistics and statistical estimation and inference. At the end of the course students should be able to carry out and interpret a range of data analysis techniques, from univariate and bivariate descriptives to multiple linear regression and binary logistic regression at an introductory level. The seminars and computer exercises give 'hands-on' training in the application of statistical techniques to real social science research problems using the R computer package (no prior knowledge of R is necessary).

This course is delivered through a combination of lectures and seminars totalling a minimum of 30 hours across Winter Term.

The course runs twice per year: in AT (MY451A) and again in WT (MY451W). 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 WT.

Self-guided computer exercises to be completed before weekly classes for discussion and a weekly online quiz.

A course pack will be available for download online. Additional reading: many introductory statistics books are available. But we particularly recommend Alan Agresti and Christine Franklin (2009) Statistics: The Art and Science of Learning from Data. Pearson Education. Or Alan Agresti and Barbara Finlay (2009, 4th edition) Statistical Methods for the Social Sciences. Pearson Education (note that the second book is more advanced and is particularly useful if you are planning to take MY451 and MY452).

Exam (100%, duration: 2 hours) in the spring exam period.