Description

This course has two objectives. First, it will introduce the participants to the basics of statistical experimental design, data analysis, and statistical inference. It will cover topics such as optimal allocation of resources, confidence intervals, hypothesis testing, and linear regression. Second, it will introduce the practical steps of statistical analysis using the open-source environment R. In addition to discussing basic data management tasks in R, such as reading in data and performing basic analysis, it also contains introduction to reproducible research using R markdown. The course will contain both lectures and practical hands-on exercises.

Target audience

    Target audience are experimental scientists with no prior knowledge of statistics or R.

References

Susan Holmes and Wolfgang Huber. Modern Statistics for Modern Biology. Cambridge University Press, 2109. ONLINE version and PAPER version.

‘Points of Significance’ in Nature Methods

Speakers

    Meena Choi, Laurent Gatto, Olga Vitek