>The argument may not be compelling to anyone but a stats geek, but I did pointedly raise an eyebrow at the use of the very obscure  "Shapiro–Wilk" statistical tool - it can exaggerate the actual departure from the normal distribution, and I mentioned that other statistical treatments may not produce the same result from the hive yield figures.

 Good feedback. Thank you.

While I am decidedly outside my depth on this, your commentary made me curious. After a bit of searching I stumbled on the following paper:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3693611/

In it they make the following observation about the test in question:

'The Shapiro-Wilk test is based on the correlation between the data and the corresponding normal scores (10) and provides better power than the K-S test even after the Lilliefors correction (12). Power is the most frequent measure of the value of a test for normality—the ability to detect whether a sample comes from a non-normal distribution (11). Some researchers recommend the Shapiro-Wilk test as the best choice for testing the normality of data (11).'

I welcome input on what normalcy tests between honey yield and population would be more statistically relevant or what the article above gets wrong- this is definitely above my pay grade.

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