Dissertation prize

Did you know that the Q-Step programme offers a prize of £300 annually for the best Honours dissertation using quantitative methods?

Any student who would like to be considered for the prize should contact Alison.koslowski@ed.ac.uk

To be eligible for the prize, the student must be taking a degree programme with a significant component in the School of Social and Political Science, and the dissertation must use advanced statistical methods and ideas. Examples of these methods are below, but this list is not exhaustive. A student does not have to be taking a named quantitative degree programme for the dissertation to be eligible.

The best dissertation will be decided primarily on the basis of the mark awarded. The decision on which dissertation has won the prize will be taken after the meetings of the Honours examination boards in May-June, but before the graduation ceremony.

Examples of quantitative methods that would make a dissertation eligible to be considered for the prize

The dissertation would have to make significant use of methods or design or software or communication or epistemology from the following list. It is not necessary to use advanced methods under all of these headings.

Examples of advanced methods
  • Multiple regression (linear, logistic, multinomial).
  • Principal components analysis, cluster analysis, and other data reduction techniques.
  • Multilevel modelling.
  • Network analysis.
Examples of advanced design and data management
  • Complex survey design (eg clustering, stratification) and its consequences.
  • Design of experiments.
  • Use of digital social research (eg sampling via Twitter and Facebook).
Examples of advanced software
  • R.
  • The more advanced modules in Stata.
  • Specialised software (such as MLwiN).
  • Complex linking between software packages.
Examples of advanced public communication
  • Communicating statistical results of an advanced kind to non-specialist audiences: eg reporting the results of regression, principal components analysis, etc. for both specialist and non-specialist audiences.
Examples of advanced epistemology
  • Induction, laws of large numbers, central limit theorem, the statistical (or probabilistic) concept of an ‘event’.
  • The history of statistical reasoning.
  • Complex ethical principles (eg stopping rules in clinical trials).
Three students looking at laptops