I'm a statistically incompetent social scientist who is very much out of my depth...
I'm using R to analyse a data set, which is a 1% sample of a population showing cancer rates across 20 regions. There are parameters for male and female rates.
If I have to calculate 95% credible intervals for the mean based on the two sexes, am I better off using an arithmetic calculation or bootstrapping? I've searched high and low for something comprehensible but I'm struggling. I think I'm right in saying that bootstrapping is better when the data isn't normally distributed (this, however, very much is) and sample size is small (which this is).
On the basis of the sample size, am I justified in going down the bootstrapping route?
Any advice much appreciated!