Division of Statistics
       Dalhousie University
Department of Mathematics and Statistics
Dalhousie University, Halifax, Nova Scotia, Canada
Tel: (902) 494 - 2572
Fax: (902) 494 - 5130
   [ Home ]     [ Research ]     [ People ]     [ Programs ]    [ Resources]     [ Upcoming Seminars ]


Our interests cover a wide variety of areas in statistics, including both applied and theoretical problems. In addition, there are particularly strong groups in statistical genetics and environmental statistics. A special strength of the division is our commitment to interdisciplinary approaches to science.  It is not uncommon for faculty to collaborate on a project with scientists from two or three other academic departments at Dalhousie University.


Statistical Genetics:

The science of Genetics is dedicated to studying the structure and function of genes and genomes, as well as the way genetic information is transmitted from generation to generation.  Genetics has long been important in biology and society; however, with the rapid accumulation of gene and genome sequences, genetics has entered a new age, one which depends heavily on statistical methods. 

The statistical genetics group at Dalhousie University is comprised of a collection of faculty, staff, and graduate students who work together closely on methods for analyzing and interpreting genetic data.  Research areas include analysis of gene chip data, estimation of breeding values, QTL analysis, phylogenetic methods, estimating selection pressure on protein coding sequences, and genomic analysis.

Members of this group include Hong Gu, Chris Field, Ed Susko, David Hamilton, Christophe Herbinger, Bruce Smith, and Joseph Bielawski.

The statistical genetics group is committed to an integrated approach to genetic and genomic science. Only through the integration of statistical, biological, mathematical, and computer science disciplines can the challenges of modern genetics and genomics be met.  The statistical genetics group works to enhance the interdisciplinary environment at Dalhousie University through formal collaborations with other academic departments and with organizations such as Genome Atlantic and the CIAR Program in Evolutionary Biology.  The Statistics Division provides a home for the weekly meeting of the Statistical Evolutionary Biology Group, a group of biologists, statisticians and computer scientists interested in applying statistical modeling techniques to problems in molecular evolution and comparative genomics.

Follow this link for a list of some recent publications.


Environmental Statistics:

Environmental Statistics is concerned with the development and application of statistical methods for the environmental sciences, with the purpose of addressing pressing environmental problems facing society. Its goal is the characterization and analysis of spatial and temporal variability in environmental observations, and the development of predictive models. Such models often require the fusion of discipline specific mathematical models with the techniques of statistical data analysis. An important challenge ahead lies in the development of novel techniques for the effective treatment of the wide assortment of new data streams from advanced environmental

observing systems.


The Environmental Statistics group at Dalhousie includes Michael Dowd, Chris Field, Joanna Flemming, David Hamilton, Bruce Smith and Keith Thompson.


Current research areas are: (i) Statistical inverse problems for marine prediction; (ii) Data assimilation and the development of operational forecast systems; (iii) Satellite image analysis for ocean surface winds and waves; (iv) Analysis and modelling of bio-optical plankton observations; and (iv) Modelling extremes in atmosphere and oceans


By its nature, Environmental Statisitics is a multidisciplinary endeavour. The Environment Statistics group at Dalhousie is part of the new Centre for Marine Environmental Prediction (www.cmep.ca). Its goals are to develop and test new technologies for the observation, prediction and visualization of the marine environment. This provides a unique opportunity for practical applications of Environmental Statistics.

Follow this link for a list of some recent publications.


Individual Faculty Interests:

Click on faculty names to go to their personal web sites

J.P. Bielawski Statistical Genetics| Molecular Evolution
K.Bowen Applied Problems in Health Professions
M. Dowd Inverse problems | Environmental Statistics | Ecosystem Modeling
C.A. Field Robust Statistics  | Statistical Genetics  |  Data Analysis
J. Flemming Longitudinal data  | State space models  | Environmental risk assessment
G. Gabor Bayesian Inference
H. Gu Multivariate Statistics |Machine Learning | Bioinformatics | Molecular Evolution 
R.P. Gupta Multivariate Analysis | Distribution Theory  | Statistical Inference
C. Herbinger  Quantitative Genetics| Statistical Genetics
D. Hamilton Linear and Nonlinear Regression | Statistical Genetics | Design of Experiments | Data Analysis
B. Smith Time Series | Statistical Genetics | Clinical Trials
E. Susko Mixture Models | Machine Learning | Bioinformatics | Molecular Evolution 
K. Thompson Time Series Analysis | Applications to Oceanography


 On this page:

  >> Statistical

  >> Environmental

  >> Faculty




   ©Copyright 2003. All Rights Reserved