I want to compare if two groups of counts per person hour are the same. Say I send 500 people out to orchard A to pick apples for three hours each, and the same for orchard B. Then I compute the number of apples picked by each person divided by the time they spent searching. Each person spends approximately three hours searching but I'm keeping track of seconds so there is a tiny bit of variation.

The apples-per-person-hour datasets for orchard A and orchard B turn out to be fairly normally distributed. However, there is some repetitions in the data because for example, lots of people find 3 apples in 3 hours, so they have 1 apple-per-person-hour, and then the next option is to find 2 apples so those folks have 0.66 apples-per-person-hour. Also, one dataset contains a lot more variance than the other.

This scenario is hypothetical, but here is a QQ plot from my data showing how many values are the same or nearly the same due to apple counts being discrete and person hours being approximately equal.

My null hypothesis is that apples-per-person hour is the same at each orchard.

I'm debating between a Welch's two sample t-test, a two sample Kolmogorov–Smirnov test, or a chi-squared goodness of fit test.

Welch's Two Sample t-test I'm okay with comparing just means, but does the data having a bunch of nearly similar values make it non-parametric? The data is technically continuous, but it is derived from discrete data. Note, running a welch's t-test on my real data showed that the two means were significantly different.

Kolmogorov–Smirnov test I'm also okay with comparing distributions and locations, but do the repeating or nearly repeating datapoints mean that I can't accurately compute a p-value for this test? Note, the estimated p-value showed that the two distributions were significantly different, but using the ks.test function in R, I got a warning about repeating values.

Chi-squared goodness of fit test In theory, I know I can use this test for counts, but I'm a bit lost on how to compare two sets of counts...and my data isn't technically counts anymore.

I am also open to considering other statistical tests. Let me know if I can provide more information.

Thanks!