MY454      Half Unit
Applied Statistical Computing using R

This information is for the 2017/18 session.

Teacher responsible

Dr Benjamin Lauderdale COL.8.10

Availability

This course is available on the MSc in Social Research Methods. This course is available as an outside option to students on other programmes where regulations permit.

The course is also available to research students, as MY554.

Pre-requisites

Students must have taken Applied Regression Analysis (MY452) or an equivalent intermediate regression course.

Course content

This course will cover basic statistical programming for social science research as well as several associated data analysis methods. Programming topics include basic programming, data structures, optimisation, and simulation. Applied statistical topics include nonparametric density estimation and regression, additive models, cross-validation, the bootstrap, and permutation/randomisation 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.

Teaching

20 hours of lectures and 10 hours of computer workshops in the LT. 2 hours of lectures in the ST.

Formative coursework

Students will be expected to produce 5 problem sets in the LT.

Each problem set is associated with a computer classes, and may be submitted for marking and feedback.

Indicative reading

Keele, L. Semiparametric Regression for the Social Sciences

Matloff, N. The Art of R Programming

 

Assessment

Exam (50%, duration: 2 hours, reading time: 5 minutes) in the main exam period.
Coursework (50%) in the ST.

Key facts

Department: Methodology

Total students 2016/17: Unavailable

Average class size 2016/17: Unavailable

Controlled access 2016/17: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills