MY559      Half Unit
Special Topics in Quantitative Analysis: Applied Statistical Computing

This information is for the 2013/14 session.

Teacher responsible

Dr Benjamin Lauderdale COL.8.10.


The course is available to all research students.


The course will assume knowledge of linear and logistic regression models, to the level covered in MY452.

Course content

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 2013/2014 session, this course will cover computer programming for social science research and some of the advanced data analysis methods that require significant computation. The main topics covered are data collection and management, 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.

Formative coursework

Exercises from the computer classes can be submitted for marking.

Indicative reading

Matloff, N. 'The Art of R Programming'

Shalizi, CR. 'Advanced Data Analysis from an Elementary Point of View'


Coursework (100%, 4000 words).

Key facts

Department: Methodology

Total students 2012/13: 3

Average class size 2012/13: Unavailable

Value: Half Unit

Guidelines for interpreting course guide information