By the end of the PhD, all NWSSDTP-funded students are expected to have undertaken training in quantitative methods. Assuming a basic level of statistical literacy, quantitative research training should develop skill levels by using methods appropriate to the student’s specific discipline.

Typically, those students specialising in quantitative methods would be expected to be able to:

• Collate, analyse and interpret complex numerical data that may be presented in tabular or graphical form or other data relevant presentation formats
• Understand and undertake inferential statistical tests for parametric and non-parametric data
• Understand statistical inference, from cross sectional and longitudinal sample surveys and inference from research using experimental designs
• Understand the application of specific statistical approaches to data analysis and links to research design specifics (e.g. ANOVA, correlation, linear/non-linear regression, multivariate modelling, fixed and random effect models, growth trajectory and multi-level modelling)
• Apply data reduction and grouping methods, such as factor and cluster analysis, multidimensional scaling and other such data reduction methods linked to research design and data format
• Utilise longitudinal analysis, event history analysis, agent-based modeling or similar as appropriate.

NWSSDTP Training Catalogue Under Development