We have – in this microseries of miniblogs – looked at data distributions and describing what we’ve got. We’re ready for the big leap now; from description into inference. What can we say about how our data relate to the world at large? And the first thing to do is to clarify a deeply unhelpful term.
Now, can you guess what non-parametric means?
Hurray! It means statistical tests for when “my data is non-Normal”. That might be skewed continuous stuff, or categorical data like dead/alive counts.
Glad we’ve cleared that up. We’ll be onto bootstrapped estimates of regression covariates before you can slip a 24G in a neonate …