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Research Informatics Training

 

These courses provide a strong foundation in practical statistics and data analysis. They treat statistics as a practical skill rather than as a purely theoretical subject.

Recommended starting point

 Core Statistics

Classical statistical analysis techniques including hypothesis testing, linear models and power analyses, with an emphasis on practical implementation and robust analysis skills.

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Building on from Core Statistics

 Generalised Linear Models

Practical introduction to generalised linear models, focusing on real-life applications in the biological sciences.

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 Linear Mixed Effects Models

Introduction to mixed effects, multilevel and hierarchical models for use in research and data analysis.

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Related courses

 Experimental Design for Statistical Analysis

Practical course on designing effective experiments and linking experimental design to a clear statistical analysis strategy.

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 Introduction to Bayesian Inference

Introduction to the tools needed to conduct Bayesian inference in common research settings.

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