I don’t feel like I can agree with this. Even with the ‘essentially’ clause.
This brings up the topic of “Incongruent trees.” This a topic I planned on bringing up later, just not in this thread. Gosh folks, I can’t keep up with you all! I’m still working on my current homework…
But since it came up, it looks like it’s getting discussed.
For me incongruent trees are a reason to question the tree of life. But I’m open to hear from others on this topic.
@moderators : Can we make a separate thread for this.
I would ask you the same question I did @thoughtful.
Sometimes humans find "incongruent trees’ in their genealogy. That is, there might be a number of different people who may or may not be among their ancestors, and it cannot determined which are and which are not.
Does this cause you to doubt that humans are related by common ancestry? If not, why does it make you doubt common ancestry between other species?
huh? Please give an example. I missed this before. I certainly don’t know of any in my family.
Also, genealogical trees are obvious; there’s no reason to doubt trees there. Genetics are a little different. That’s why we have GAE in the first place.
Incongruency is a basic feature of most of science. I have never seen any data set that is entirely congruent with the hypothesis. For example:
Most people would agree that there is a strong correlation in the data. The data points cluster strongly around a regression line. However, the data is still incongruent because the data points don’t fall perfectly on the regression line. Does this mean there is absolutely no correlation in the data simply because there isn’t a perfect regression? Of course not.
Statistical significance is what ultimately determines whether a hypothesis is supported. You may have heard of Student’s t-test or p values. Those are statistical tests to see if the data supports your hypothesis. The real question with phylogenies is if there is a statistically significant match between them, not if there are incongruencies.
If you were to choose any 100 random people in the world and attempted to determine their genealogical relationship, do you think you would get exactly the same result no matter which technique you use? If not, does that mean humans are not related by common ancestry?
It’s possible there are people may be 2nd cousins and also 5th cousins once removed for example, but in that case, both are correct because genealogies start to collapse. But do scientists think that true for phylogenies? I’m not understanding how that makes sense. Maybe you’re thinking in a different way than I am.
If we can see that mechanisms operating in life would inexorably result in cases of incongruent trees even where common descent is directly observed, I think you’re going to have to say more about why incongruent trees constitute a valid reason to question common descent.
I am talking about the situation in which there is a single, correct relationship between the 100 individuals, but for practical reasons we cannot determine what it is. We use a number of different methods, and there are minor differences between each of them.
According to your “reasoning”, this fact means we cannot conclude that all humans are related by common descent, and that the methods cannot demonstrate any relationship with a high degree of certainty. You’re no more likely to have been descended from your grandmother than from Queen Elizabeth II.
Sorry for the delay. Responding does take me a while. I’ll try to reply to both of these in one ‘summary’ since they are similar.
Good point T_auaticus: Not if, but the statistical significance. And yes Faizal, that’s a specific example within humans.
A short answer for me is that I potentially see the incongruencies outside of ‘biblical kinds’ to be larger than within kinds.
But…that gets to a larger issue at hand: evaluating questions like “how significant?” and the bigger question “how much incongruency, or lack-there-of do I expect, or rather am I comfortable with and still affirm by stance on evolution?”
I’m finding this to be very difficult to answer. I’ve had to realize that in my research, I do a more reading on the incongruences’, and I’m sure others focus on the consiliences. We’re all examining the large elephant in different ways, coming to different conclusions. Which is why I phrased my question: “Help me see what you see”
True I have not provided details to support that. I get that.
But understand, I’ve primarily created this thread NOT to try and prove anything, or to defend myself. I’m simply wanting to learn.
I’m willing to bet most people here have heard of these arguments before, and I’m not in the mood to bring up “what about this??”… and then ride that marry-go-round.
That’s very interesting. But in order to do that you would have to identify kinds. Could you specify the kinds you’re dealing with? How do you know they’re kinds? Once we get to specifics I’d be interested in seeing the data you use to show incongruence.
This is complicated by the fact that incongruence is more likely to be published, especially in a high-impact journal, than congruence. You don’t get much press from “we did another analysis of new data, and we found what everybody else did before us”.
That is a huge debate all on it’s own. Scientists have been arguing over what is or isn’t statistically significant through the entire history of modern science. A google search for “debate over p value” should give you a taste of what the debate is all about.
The first problem is that significance can be arbitrary because someone will just pick a p value threshold and say that everything below that value is statistically significant. One of the most common p values is <0.05 which means (if my understanding is correct) there is a less than 5% chance of a false positive. If you have a p value of 0.001 then there is a 0.1% chance of a false positive. In other words, statistical significance is a way of saying “here is the probability that I’m wrong”.
That would be a good question for others here who have more experience in phylogenetics than I do.
Going back to my data plot in the previous post, you are focused on a single dot and its distance to the regression line. We are seeing the data set as a whole and the obvious correlation.
It’s a lot less challenging if you are not trying to reconcile it with YEC. Things generally are easier to comprehend when one is not assuming that they must contradict physical reality.
The same, clearly understood sources of systematic error apply to both. The most easily understood one is that a mutation and a reversion will be scored as 0 instead of 2 changes.
