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Readership: Suitable for postgraduate students in science and health, quantitative researchers and final-year statistics students
Peter J. Diggle, Distinguished University Professor of Statistics, Lancaster University; Adjunct Professor of Biostatistics, Johns Hopkins University School of Public Health; Adjunct Senior Researcher, International Research Institute ofr Climate and Society, Columbia University, and Amanda G. Chetwynd, Pro-Vice-Chancellor, Lancaster University
Peter Diggle is Distinguished University Professor of Statistics and Associate Dean for Research in the School of Health and Medicine, Lancaster University, Adjunct Professor in the Department of Biostatistics, Johns Hopkins University School
of Public Health and Adjunct Senior Researcher in the International Research Institute for Climate and Society, Columbia University. Between 1974 and 1983 he was a Lecturer, then Reader, in Statistics at the University of Newcastle upon Tyne. Between 1984 and 1988 he was Senior, then Principal, then Chief Research Scientist and Chief of the Division of Mathematics and Statistics at CSIRO, Australia. He has published nine books and around 180 articles on these topics in the open literature. He was awarded the Royal Statistical Society's Guy Medal in Silver in 1997, is a former editor of the Society's Journal, Series B and is a Fellow of the American Statistical Association.
Amanda Chetwynd is Pro-Vice-Chancellor for the Student Experience and Professor of Mathematics and Statistics at Lancaster University. Before joining Lancaster University she held a Post-Doctoral position in the Mathematics Department at the University of Stockholm. She has published three books and around 80 refereed articles. Amanda was awarded a National Teaching Fellowship in 2003 and in 2005 led Lancaster's successful bid for a Postgraduate Statistics Centre of Excellence in Teaching and Learning.
"The authors have a nice writing style and explain all the important concepts well ... reader/student will gain a good understanding of the essential aspects of statistics in scientific research." - Michael R. Chernick, Significance
4: Exploratory data analysis
5: Experimental design
6: Simple comparative experiments
7: Statistical modelling
8: Survival analysis
9: Time series analysis
10: Spatial statistics