Have you ever wished you had collected more data after getting an inconclusive statistical result?
Have you wondered what to do with the non-significant fruit of your hard work?
This week's workshop will discuss how to use simulations in R to:
- Plan experiments and data collection to ensure you can detect an effect if it is there, and do not waste your efforts with work leading to inconclusive results (that is, power analysis).
- Tell whether "non-significant" results are likely a sign of a poor experimental design (see point 1) or of an effect that is biologically unimportant.
There will be a lot of time to practice basic coding and plotting.
Thinking about these questions will naturally introduce random effect and linear mixed models.
The goal of these workshops (held regularly at the Research School of Biology, ANU) is to provide a deeper understanding of statistics and proficiency in R. They are aimed at Honours, Masters and early PhD students, but everyone is welcome. The course material from previous sessions are available here. Please email Timothée Bonnet if you would like to be added to the workshop mailing list.