I found this discussion "T test not for proportion" helpful, but I'm still not sure my data meets the z-test assumptions. If a distribution of average values comes close to a normal distribution and my data consist of average seagrass cover values per site (n=47 sites), and per month, would this meet the assumptions for a z-test? Or because I'm dealing with proportions, rather than continuous data, using a categorical factor as a predictor, I should actually stick to regression techniques? I hope to also understand the advantages of both (if the data works for both). I'm working in R.

Code:

```
years <- c(2010, 2021)
month <- c("March", "July")
site <- seq(1:47)
ave_seagrass <- runif(188, min=0.0, max=1)
df <- data.frame(ave_seagrass, site, years, month)
```