17 Jan 2023
Laboratory experiments are best designed with their analysis in mind to avoid errors, noise and bias. Especially large scale or high throughput experiments often require appropriate computational techniques and tools for analysing the data - and it is not always obvious which method to choose best.
This webinar aims to provide an overview on good statistical practice for students and researchers who are planning to perform experiments resulting in large biological datasets. We discuss efficient workflow design, iterative analyses, data representation, computational methods and most importantly, we will address the question of “how many replicates?”.
The seminar was given by GHGA-affiliated Principal Investigator Wolfgang Huber (Head of Group, Quantitative Biology and Statistics), based on the book “Modern Statistics for Modern Biology”, which he co-authored with Susan Holmes.
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27 April 2023
Having a good understanding of statistics is vital for Biologists designing and analysing their own experiments.
To get you started, this webinar covers the general concepts behind hypothesis testing workflows, including summary statistics, null and alternative hypotheses, and p-values. We focus specifically on what you should pay attention to when you interpret results from a biostatistical analysis. We're using gene expression as an example, and work with visuals rather than equations, to make the topic accessible to a broader audience.
This webinar was given by Sarah Kaspar from the Centre for Statistical Data Analysis, EMBL.
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