I'm quite new to stats, and still puzzled on uneven samples testing. I have a database containing quantities of plastic debris found on a beach. I have 15 types of debris (bottles, plastic tubes, caps, lids etc.), but with an uneven number of counts for each, and therefore different quantities. For example bottles have 14 data entries with a total number of 56 bottles found, lids have 5 data entries with a total of 37 lids found, and so on. This is a result of a clean-up effort where each participant reported total quantities of waste picked-up per plastic type, for example one person finding 10 bottles during his clean-up corresponding to one data entry. I was reading this post which answered some of my questions: Statistical tests for uneven groups
I've inserted the data into SPSS, and ran a normality test to understand more about the data. However; I have different levels of significance for each type, which in some cases reject the null hypothesis or not. I was wondering what are the next steps when it comes to data with different levels of significance in the output of the normality test? If there are more non-normal data should I carry on with non-parametric tests? Sorry if this question is not relevant, I've been trying to read more on this but haven't manage to find anything useful.