Thanks for the replies guys,

Regrettably due to the cost of genotyping offspring each male-male competition was done only once. So multi level modelling wouldn’t be an option. I’ll look into the chi sq and the zero inflated models though.

Unfortunately my supervisor is a bit clueless on stats and is away for three weeks anyway! I’ve asked a couple of fellow PhD’s in my dept but no one knows and seems a bit unwilling to help, I don’t want to pester people.
Thanks again for the help! Xx

Hi all, I'm new to this forum and could use a little help and you all seem like a friendly bunch :-). I'm just entering my 4th year in October and am now in my write up phase and have an issue with some data for one of my chapters - I don't think I can do stats on it!

I work on hybridisation in fish, and fertilised a salmon females eggs with sperm from both a hybrid male (salmon x trout) and a pure salmon male to see how many of the eggs the hybrids can win when competing against the pure males. The hybrids are pants and only 3  got any paternity at all, with a maximum of 10%.

So my answer is clear- hybrids don't appear to win in sperm competition, but my problem is the stats. I have proportion data which for a start which is always a nightmare and I have loads of zeros from the hybrids and loads of 1's from the pures. If the data were normally distributed I would just do an independent samples t-test, but even arcsine transforming doesn't produce normality due to the high number of 0's and 1's. I also have a small sample size (9) as the experiment went wrong half way through the molecular work :-(

Are stats possible? Is a simple mann whitney sufficient?! Or am I simply going to have to describe the data with graphs. Any suggestions would be so gratefully received and any solutions may prompt me to send you a pint by post!

Siany xx