Principles of Applied Statistics

Häftad, Engelska, 2011

AvD. R. Cox,Christl A. Donnelly,D. R. (University of Oxford) Cox,Imperial College London) Donnelly, Christl A. (Professor

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Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.

Produktinformation

Utgivningsdatum2011-07-28
Mått152 x 228 x 11 mm
Vikt350 g
FormatHäftad
SpråkEngelska
Antal sidor212
FörlagCambridge University Press
ISBN9781107644458

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D. R. Cox is one of the world's pre-eminent statisticians. Author or co-author of numerous books and papers, his work on the proportional hazards regression model is one of the most-cited and most influential papers in modern statistics. In 2010 he won the Copley Medal of the Royal Society 'for his seminal contributions to the theory and application of statistics'. Christl A. Donnelly is a Professor of Statistical Epidemiology in the MRC Centre for Outbreak Analysis and Modelling at Imperial College London and was deputy chair of the Independent Scientific Group on Cattle TB (1998 to 2007). She has worked on a range of other infectious diseases including BSE/vCJD, foot and mouth disease, SARS, influenza, malaria and neglected tropical diseases.

"This is an outstanding book in search of a proper audience. ... The authors do a really outstanding job of covering key elements of practice; they illustrate each point with examples (often more than one) nicely offset in gray boxes, and drawn from a huge range of fields. There are insights throughout the book, often ones that are not covered by more typical texts or courses. Despite being a statistical consultant for more than a decade, I learned a good deal and was, perhaps more importantly, given much to think about." Peter Flom, Significance

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