Statistics Research Areas

Professor Ray Chambers

Sample Survey Design and Analysis; Robust Statistical Methods; Graphical Methods in Statistics; Computer Intensive Statistical Methods; Statistical Modelling and Inference; Longitudinal Data Analysis; Analysis of Computer-Linked Data

 

Dr Robert Clark

• Survey methodology, including design, estimation and analysis
• Household surveys
• Modelling the complex dependencies between observations that arise in many surveys, administrative datasets and observational studies

 

Prof Brian Cullis

• Mixed models;
• analysis of genomic data;
• spatial analysis;
• design of experiments;
• efficient estimation for the analysis of large data-sets

 

Dr Pam Davy

• Telecommunications traffic modelling
• Data mining
• Computational finance
• Spatial statistics

 

Professor David Griffiths

• Epidemiology and public health applications of statistics
• Statistics education
• Secondary interests covering quality management, inference, statistical graphics and the history of statistics.

 

Dr Chandra Gulati

• Statistical decision theory
• Time series / cointegration
• Statistical quality control

 

Associate Professor Yan-Xia Lin

• The theory of Inference on stochastic processes
• The quasi-likelihood method and its applications
• The theory of stochastic analysis and its applications in finance
• Time series analysis
• Long-memory processes
• Cointegration analysis and its applications
• GARCH models and GARCH-X models
• Mathematics Finance
• Bioinformatics
• Confidential data
• Survey methodology

 

Dr Anne Porter

• Statistical education. Areas researched include:
  • development of flexible teaching and learning strategies (e.g. use of online resource base, delivery via WebtCT.
    
  • development of curriculum and pedagogical practices
    
  • analysis of theoretical and methodological perspectives regarding the nature of teaching and learning in relation to Statistics (e.g. use of reflective practice, experiential learning techniques)
    
  • integration of generic skills into teaching and learning of statistics.
• Applied statistics. These projects emanate from consultancy work. To date these include studies in sport, education and health.
• Sample surveys in particular internet surveys (security, representativeness, modes of production etc).

 

Professor David Steel

• Analysis of aggregate data and ecological inference
• A general method for analyzing social data for modifiable geographical areas
• Estimation and inference for household surveys
  
• Combining aggregate data and unit record
  
• Innovations with area level
  
• Sample survey design, analysis and methodology.