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The University of Kent, Canterbury, Kent, CT2 7NZ, T +44 (0)1227 764000
Statistics MSc, MPhil, PhD
This is a research programme within the Statistics subject area.
Outline
Staff research interests are diverse, and include: Bayesian statistics; bioinformatics; biometry; ecological statistics; epidemic modelling; medical statistics; nonparametric statistics and semi- parametric modelling; risk and queueing theory; shape statistics.
Statistics has strong connections with a number of prestigious research universities such as Texas A&M University, the University of Texas, the University of Otago, the University of Sydney and other research institutions at home and abroad.
The research interests of the group are in line with the mainstream of statistics, with emphasis on both theoretical and applied subjects.
The group regularly receives research grants. The EPSRC has awarded two major grants, which support the National Centre for Statistical Ecology (NCSE), a joint venture between several institutions. A BBSRC grant supports stochastic modelling in bioscience.
Key facts
- Subject area: Statistics
- Location: Canterbury
- School: School of Mathematics, Statistics and Actuarial Science
- Duration: MSc one year full-time or two years part-time, MPhil two years full-time or three years part-time, PhD registration three to four years full-time or five to six years part-time.
- Start: At any time but preferably in September.
- Fees and funding: More info
- Entry requirements: A first or 2.1 in a relevant subject. Please also check our general entry requirements (including English language requirements).
Research areas
Biometry and ecological statistics
Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.
Bayesian statistics
Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.
Bioinformatics, statistical genetics and medical statistics
Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.
Nonparametric statistics
Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.
Show all
|Key facts
- Subject area: Statistics
- Location: Canterbury
- School: School of Mathematics, Statistics and Actuarial Science
- Duration: MSc one year full-time or two years part-time, MPhil two years full-time or three years part-time, PhD registration three to four years full-time or five to six years part-time.
- Start: At any time but preferably in September.
- Fees and funding: More info
- Entry requirements: A first or 2.1 in a relevant subject. Please also check our general entry requirements (including English language requirements).
Staff research
Full details of staff research interests can be found on our website.
Dr Eryl Bassett: Honorary Senior Lecturer in Statistics
Theory of inference; life testing; applied statistics; statistical computing.
Dr Lothar Breuer: Reader in Statistics
Stochastic processes; queueing theory; risk theory; Markov-additive processes. Recent publications include: An Introduction to Queueing Theory: and Matrix-Analytic Methods (co-author, 2010).
Professor Philip Brown: Professor of Statistics
Multivariate analysis; medical statistics; Bayesian methods; chemometrics; electoral prediction and polling.
Professor James Griffin: Professor of Statistics
Bayesian nonparametric modelling; high frequency financial data analysis; regression with many explanatory variables; MCMC.
Dr Efang Kong: Lecturer in Statistics
Semi and non-parametric modelling and related subset selection; robust regression and Bahadur representation; empirical likelihood.
Dr Alfred Kume: Lecturer in Statistics
Shape analysis; directional statistics; image analysis.
Dr Alexa Laurence: Lecturer in Statistics
Medical statistics and applied statistics.
Dr Owen Lyne: Lecturer in Statistics
Stochastic epidemic models; applied probability; simulation; statistical inference; goodness of fit; branching processes; martingales; medical education.
Professor Byron Morgan: Professor of Applied Statistics
Biometry; cluster analysis; stochastic population processes; psychological applications of statistics; multivariate analysis; simulation; analysis of quantal assay data; medical statistics; ecological statistics; overdispersion; estimation using transforms. Recent publications include: Applied Scholastic Modelling (2008); Bayesian Analysis for Population Ecology (co-author, 2009).
Professor Martin Ridout: Professor of Applied Statistics
Analysis of discrete data in biology; generalised linear models; overdispersion; stochastic models; transform methods.
Professor Stephen Walker: Professor of Statistics
Bayesian inference; Bayesian nonparametric methods; time series; survival analysis; MCMC; matrix algebra. Recent publications include: Bayesian Nonparametrics (co-ed, 2010).
Dr Xue Wang: Lecturer in Statistics
Nonparametric regression; multiscale methods.
Professor Jian Zhang: Professor of Statistics
Semi and non-parametric statistical modelling; statistical genetics with medical applications; Bayesian modelling; Mixture Models; neuroimaging.
Further information:
Key facts
- Subject area: Statistics
- Location: Canterbury
- School: School of Mathematics, Statistics and Actuarial Science
- Duration: MSc one year full-time or two years part-time, MPhil two years full-time or three years part-time, PhD registration three to four years full-time or five to six years part-time.
- Start: At any time but preferably in September.
- Fees and funding: More info
- Entry requirements: A first or 2.1 in a relevant subject. Please also check our general entry requirements (including English language requirements).
Contact details
Admissions enquiries
T: 44 (0)1227 827272
E: information@kent.ac.uk
Claire Carter
T: 44 (0)1227 824133
Key facts
- Subject area: Statistics
- Location: Canterbury
- School: School of Mathematics, Statistics and Actuarial Science
- Duration: MSc one year full-time or two years part-time, MPhil two years full-time or three years part-time, PhD registration three to four years full-time or five to six years part-time.
- Start: At any time but preferably in September.
- Fees and funding: More info
- Entry requirements: A first or 2.1 in a relevant subject. Please also check our general entry requirements (including English language requirements).
How to apply
Before applying, please read our ‘How to apply’ section.
You can then go straight to the online application form by clicking the programme below:
Key facts
- Subject area: Statistics
- Location: Canterbury
- School: School of Mathematics, Statistics and Actuarial Science
- Duration: MSc one year full-time or two years part-time, MPhil two years full-time or three years part-time, PhD registration three to four years full-time or five to six years part-time.
- Start: At any time but preferably in September.
- Fees and funding: More info
- Entry requirements: A first or 2.1 in a relevant subject. Please also check our general entry requirements (including English language requirements).