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Statistics for data analysis

The aim of this module is to give students a basic understanding of the statistical methods appropriate to data analysis in analytical science, and to provide guidance on some statistical tools for more advanced study. Topics include: basic probability; error analysis and calibration; summarising data and testing simple hypotheses; statistical computing (software and practice, including simple graphics); experimental design and analysis of variance; sampling methods and quality control; simple analysis of multivariate data. Each session will combine lecture and data analysis workshop. At the end of the course the student should be able to appreciate the added value that statistical analysis can bring to research to perform basic statistical analyses of simple data sets using statistical software to design simple experiments.

Module leader:

Dr Simon Spencer

Simon Spencer

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