3 hours ago
(This post was last modified: 3 hours ago by npcompl33t.)
First: I think P has enough data to do statistics on, especially if they are pooled to the bifolia and bifolia show similar patterns. I agree F does not have enough data analyze alone.
Second: Wow you are right though about the ok/ot and k/t .
I applied the same method as above, but instead of from P/F -> K/T , i did k/t->ok/ot
Something really interesting happens. the nature of the relationship between K/ok and the gradient actually inverts. Look at the angle chart on the bottom. In herbal 1a, oG and G are roughly equal, or uncorrelated with the gradient, and starting in Pharma the O variants to a consistent lead.
So at any given point from Pharma On, oG would would be 'different' from G in the way the same ways the overall gradient is moving. The changes must be hitting oG before G words.
Some interesting stuff here, but it might take me a bit of time to dig into it more and fully understand what is going on.
EDIT sorry i got my charts mixed up, this one maps k/t (excluding ok/ot) onto ok/ot , so comparing the relationship between the non O and O groups.
Second: Wow you are right though about the ok/ot and k/t .
I applied the same method as above, but instead of from P/F -> K/T , i did k/t->ok/ot
Something really interesting happens. the nature of the relationship between K/ok and the gradient actually inverts. Look at the angle chart on the bottom. In herbal 1a, oG and G are roughly equal, or uncorrelated with the gradient, and starting in Pharma the O variants to a consistent lead.
So at any given point from Pharma On, oG would would be 'different' from G in the way the same ways the overall gradient is moving. The changes must be hitting oG before G words.
Some interesting stuff here, but it might take me a bit of time to dig into it more and fully understand what is going on.
EDIT sorry i got my charts mixed up, this one maps k/t (excluding ok/ot) onto ok/ot , so comparing the relationship between the non O and O groups.