Dr Benjamin Lauderdale COL8.10

This course is available on the MSc in Political Science and Political Economy, MSc in Social Research Methods, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). 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 MY559.

Students must have completed Applied Regression Analysis (MY452).

The aim of the course is to introduce students to advanced analytic methods frequently used in leading-edge social research. The content of the course will change from year to year. In the 2014/2015 session, this course will cover computer programming for social science research and some advanced data analysis methods that require significant computation. The main topics covered are basic programming and data structures, web scraping and regular expressions, nonparametric density estimation and regression, additive models, the lasso, cross-validation, the bootstrap, and permutation/randomization inference. Lectures, class exercises and homework will be based on the use of the R statistical software package but will assume no background knowledge of that language.

20 hours of lectures and 10 hours of computer workshops in the LT.

Exercises from the computer classes can be submitted for marking.

Matloff, N. The Art of R Programming; Shalizi, CR. Advanced Data Analysis from an Elementary Point of View.

Exam (50%, duration: 2 hours) in the main exam period.
Coursework (50%, 2500 words) in the ST.