I am investigating the germination of Berberis wilsonii seeds under varied conditions. For this particular part of the work my hypothesis is that there will be a significant association between the length of time the seeds are cold stratified and the germination rate. I have 6 petri-dishes, each with 50 seeds in. one is control, the others are subjected to 2wks, 4wks, 8wks, 12wks and 16wks refrigeration before being germinated...

So, the independant variable here is continuous ratio, the dependant variable discrete count.

I was pointed towards both Pearsons & Spearmans correlations, but as far as I can see, neither will fit my data type. Logistic regression was also suggested, but I can't see how this would fit either.

Now, if I simply divide the total germination figure for each petri dish by 50, I get a figure between 0 & 1 describing the probability of the event occurring; this would be continuous. Now I have both dependant and independant variables continuous. So my question is this: what test should I use to investigate the level of significance compared to the control for each of my five results? How do I work out whether the length of time the seeds are stratified for is significant compared to the control?

All help, as ever, much appreciated.