I have a dataset of the lengths of a species which has a 1-year lifespan, going back 20 years. I would like to test if the lengths recorded each year are significantly different from one another (for each sex, we already know that there is a difference between the sexes).
My length data does not have a normal distribution; therefore, I was thinking of using the Kruskal-Wallis test. However, I am not sure if that is the right way forward for the following reasons:
1) It requires an ordinal scale for the dependent variable, and I am unsure if this applies to length data
2) Is it okay that I am treating the years as a 'group' in this case? I would have ~20 groups.
3) Biologically speaking, I know that each year we are measuring different population, as this species spawns and dies (in a different location to where they are sampled) and the data is temporally independent. However, is there a way to prove this statistically? I attempted running the autocorrelation function in R but I am unsure if that is the way to go?