Hi again! I was just wondering if you have any tool / experience / advice in terms of minimum amount of data to reach significance in an experiment. I’m aware of the bayesian use of risk of loss for calling the test, but this is something useful once the experiment has already started and there is data being collected. However, in the experiment design phase, there are some timelines (at least to be used as minimum) we need to agree with the rest of the teams. Many thanks again.

The frequentist sample size calculators are usually a good approximation for what you'll need.

That would be really interesting. Thanks a lot for your answers 🙂