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Introductory Statistics for Biologists

Type	Course
Language	English
Date	November 20, 2007 to November 22, 2007
Venue	Rewley House, 1 Wellington Square, Oxford, OX1 2JA GB
Chemistry Specialties	biological sciences
Chemistry Techniques	other
Contact	Peter Holland Oxford University CPD Littlegate House, 16/17 St Ebbes Street Oxford, OX1 1PT GB 01865 286959 (0)1865 286 956 peter.holland@conted.ox.ac.uk
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by Leanne Banns — last modified 05-22-08 03:16 AM

This course will provide delegates with an introduction to the principles of statistics, and an appreciation of why they might want to use statistics as part of their scientific research. At the end of the course, delegates should be able to use statistical measures and graphs to describe populations, apply simple hypothesis tests to analyse a variety of data types, and describe the relationship between two variables using statistical measures. The course is aimed at researchers in the biological sciences, at all levels of R&D, who find that they need to be able to use statistics to describe and analyse their data. No prior knowledge of statistics or statistics software is assumed, as the course starts from the basics and builds up. The course is highly practical in nature, with half of the course time dedicated to computer practicals so that delegates can apply the techniques they are learning to real biological problems.

£795 standard fee £695 early booking fee

Speakers

Dr Jonathan Marchini Jonathan works in the Mathematical Genetics Group in the Statistics Department at Oxford University and is a Hayward Junior Research Fellow at Oriel College. His current research interests include statistical genetics, pattern recognition, computationally-intensive statistics and medical imaging. He works in collaboration with the Wellcome Trust Centre for Human Genetics in Oxford and the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain. Dov Stekel is Lecturer in Bioinformatics at the University of Birmingham. His current research interests include stochastic modelling of transcription networks and statistical methods for the analysis of large biological data sets. He has written a leading book on microarray data analysis, Microarray Bioinformatics, and has worked in the field of statistical methods in biomedical research both in academia and in industrial settings, including Glaxo and Oxford Gene Technology.

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