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Advanced Quantitative Methods

Course Code: PUBLG088

Course Tutor: Dr Slava Mikhaylov (Department of Political Science)

Assessment: One 3,000 word research design paper

Credit Value: 15 credits

About this course

The course builds on the introductory level of statistics and probability theory and introduces students to concepts and techniques essential to the analysis of modern social science data. The goal of the course is to teach students to understand and confidently apply various statistical methods and research designs that are essential for modern day data analysis. Students will also learn data analytic skills using the statistical software package R. This combination provides students with the skillset that is increasingly required by employers in today's highly competitive job market.

This is an advanced course intended for students who have already had some training in quantitative methods for data analysis. An introduction to statistics or econometrics at undergraduate level would serve as a very useful foundation for this course, although no formal prerequisites are required. Familiarity with computer programming or database structures is a benefit, but not formally required. If you are unsure whether your prior statistical training is sufficient to take this module, please contact the module tutor for confirmation.

If you do not have the required prerequisites but still wish to take the module, you should work through any good textbook for introductory level statistics with R. For example, Gelman, Andrew, and Jennifer Hill (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press. 

*Please note that this module is only available to SPP students. Students taking this course are not permitted to take PUBLG100A/B Introduction to Quantitative Methods.

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School of Public Policy,
The Rubin Building,
29/31 Tavistock Square,
London, WC1H 9QU.
Tel: +44 (0)20 7679 4999,
Fax: +44 (0)20 7679 4978,

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Tel: +44 (0)20 7679 4982/4950

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Page last modified on 09 aug 16 10:45

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