Hey Guys

Firstly thanks for all of your help! I've downloaded R and started playing around with it, and whilst I can't exactly say I'm full gotten to grips with it, using the code you've provided I'm trying to grasp the basics.

So far I've decided to use GretaGarbo's suggestion and use the difference of the means to calculate the p value and CI. Thank you for taking the time to show me this method using the code, I've paid a lot of attention to what you did and tried to understand it.

I also looked at the Poisson regression code posted by CowboyBear but I think that's still a bit over my head not through lack of trying though!

Something else I would like to explore is the use of a p value on each line as suggested by katxt...

True, the Chi square test says there is some difference somewhere. Having established that, then you can do post hoc tests at each level, again using Chi square. (This is exactly the process you follow with an anova. Include Bonferroni if you like.)
So, here's a plan. Make three groups 1, 2, 3+ vs new, old, and test for some difference somewhere with a 3x2 Chi square. p = 0.0002 so yes, there is a difference somewhere.
At level 1, test old 14 vs new 35 with 1x2 Chi square. p = 0.003, so yes, new is significantly higher.
At level 2, test old 25 vs new 18 with 1x2 Chi square. p = 0.29, so can't really tell.
At level 3, test old 21 vs new 7 with 1x2 Chi square. p = 0.003, so yes, new is significantly lower.
It convinces me.
Is there any way I can out more about how Chi square and how anova allows the p to be presented by this? I'm guessing this is done in R or is there another way you can do this without using it?

Regardless of any further help from anyone, I want to thank you all again! It so nice that you've taken the time to humour a (clearly) real newbie to this like me and it's really peaked my interest in stats.