For anyone looking for the resources shared in this talk, here you go: 📊interactive notebook: deepnote.com/workspace/allan-campopiano-4ca00e1d-f4d4-44a2-bcfe-b2a17a031bc6/project/robust-stats-simulator-7c7b8650-9f18-4df2-80be-e84ce201a2ff/%2Fnotebook.ipynb 🐍Python library for robust stats: github.com/Alcampopiano/hypothesize ✍Paper: conference.scipy.org/proceedings/scipy2022/pdfs/allan_campopiano.pdf
Q: How many data points are needed to tell (to some level of confidence) if they are drawn from a normal distribution or not? Is there a good procedure to answer this question?
Thanks! Yeah, that was a tiny slip up on my part. They are both measures of variability. SD reflects variability in a sample. SE reflects variability across multiple samples from the population. In the context of my notebook, I'm calling np.std() on a sampling distribution of means, hence my tiny slip up 🙂🙃!
