13 August 2021
on course website
Molecules, Mice and Math - A Statistical Toolbox for the Lab
• Why do I always have to repeat my experiments 3 times?
• How should I analyse qPCR data?
• I always see clearly the effect of the treatment on cells, however due to large variation it is never significant.
• Which statistical test should I use in that case?
• How do I determine the amount of animals I should use for my experiment?
• It feels unethical not to use the data of my animal pilot experiment, is there a solution?
These are just a few of the questions that fundamental scientists encounter daily in the laboratory. However, the common statistical courses do not address these questions. In this course we will! It is especially designed for fundamental scientists that work in a laboratory setting, for both in vitro and small scale in vivo experiments.
During the course the different aspects of experimental design and analysis will be addressed by using very identifiable problems for fundamental scientists. You can immediately implement the knowledge you will gain during this course in your daily work. There will be also ample opportunity to bring your own data and get advice of experienced statisticians. The course will be highly interactive as it will contain a combination of interactive lectures, work groups, discussions and computer practice. During computer practice real data from animal studies, cell-line data, immunohistochemistry, flow cytometry, etc. will be used to get familiar with the methods, the interpretation, and the visualization of the outcome of the analysis. We will make use of SPSS or R for the analysis. We will also briefly discuss the information you should provide in the method section of a scientific paper.
In short, we will discuss a range of different topics related to in vivo and in vitro laboratory experiments:
• How can I make a smart and efficient design for my experiment?
• What types of data will I encounter and what is the appropriate statistical analysis?
• Can I do a statistical analysis that increases the probability that I will have statistically significant results?
• How can I determine the sample size for my experiment?
• What to do with outliers?
• How to handle variation ?
• How to visualise your data for publication?
If you have specific questions about your own data, this course will have time dedicated for questions to an experienced statistician.
Anton de Haan, Assistant Professor Biostatistics
Department for Health Evidence
Radboud Institute for Health Sciences
Radboud University Medical Center
Judith de Haan, Programme Manager at the Open Science Programme
This course is especially designed for biomedical scientists that do laboratory experiments and small scale animal studies. It will be extremely valuable for PhD students, but certainly also for master students that are planning to continue doing research in the laboratory.
After this course you are able to:
1. Design laboratory and small animal studies, including sample size calculations
2. Identify the type of data that you get out of your experiments
3. Select the best way of analyzing and interpreting your in vitro and in vivo data
4. Write a proper method section for manuscripts
EUR 885: The fee includes the registration fees, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.
We offer several reduced fees:
€ 775 early bird discount- deadline 1 March 2020 (10%)
€ 752 partner + RU discount (15%)
€ 664 early bird + partner + RU discount (25%)
on course website