Basically, it applies the likelihood-based and Bayesian phylogenetic techniques that have been developed over the last decade or two, adds in some standard model-selection theory, and uses these to assess "universal common ancestry" (UCA). A lot of arguments "for common ancestry", e.g. biogeography, are really arguments for the common ancestry of groups of modern-day organisms – like mammals – rather than arguments that every living thing we know about shares common ancestry. There have been some powerful arguments for UCA over the years – e.g. the extremely conserved (if not quite identical) genetic code (and as everyone except Paul Nelson knows, "almost identical" and "identical" are virtually the same thing statistically, so his decade of yammering about the non-universality of the genetic code has had no impact on this evidence). However, although the arguments remain powerful and convincing, they weren't usually quantitative and statistical, and it takes some serious work to construct a statistical assessment of something as deep and universal as common ancestry. This is what Doug has done.
So that you can follow the chaos, here's a quickie for those who didn't learn this stuff in kindergarten or in frequentist-dominated intro stats classes:
1. likelihood = the probability of the data, given a model = P(data|model)
2. Two (or more) models* can be compared by taking a single dataset** and calculating the likelihood under each model. The highest likelihood model confers the highest probability on the data, and is considered to be the model that best explains the data. If the difference in likelihoods is big enough, one can say (using various tests) that one model is statistically significantly better than another model.
* Models like, say, different phylogenetic trees and/or different sets of transition probabilities between DNA or amino acid sequences.
** A single dataset like, for example, an alignment of a bunch of gene or protein sequences.
3. posterior probability = probability of the model, given the data = P(model|data)
4. Bayes' Theorem allows you to take a prior probability of a model (P(model), e.g. your model could be "this coin has a 50% chance of landing heads on a toss" – these are your initial beliefs), add some data (say, coin tosses), calculate the likelihood of that data given the model, and then calculate a posterior probability (your updated beliefs).
5. So probability, likelihood, and posterior probability are related, but they are not the same thing.
6. For much more, including a primer on the differences between frequentist, likelihoodist, and Bayesian schools of thought in statistics (I get these categories from Sober 2008, Evolution and Evidence, so please argue with me about something other than this), please see these lecture notes for a introductory lecture I recently gave on Bayesian phylogenetics: http://ib.berkeley.edu/courses/ib20[…]ndouts.shtml, Tuesday, March 9 (PDF).
1 comment:
EOTOE.
Embarrassingly obvious TOE, expanding the horizon beyond Darwin And Einstein.
It is spacedistance, NOT spacetime, that does it:
Theory Of Everything Without Strings Attached.
Embarrassingly Obvious And Simple.
See the signature links.
A. First Large-Scale Formal Quantitative Test Confirms Darwin's Theory of Universal Common Ancestry
http://www.sciencedaily.com/releases/2010/05/100512131513.htm
Life's Genesis Was Not Cells But First Gene's Self Reproduction.
Life Is Just Another Mass Format.
B. Since July 5 1997 I have developed and been proposing the following scenario of life's genesis:
* Life's genesis was not cell(s), but the self reproduction of yet uncelled ungenomed gene(s).
* There was NOT any "Pre-History Of Life" evolving in an archaic pre-modern life cell.
* Cells were definitely NOT life's genesis. Cells were products of evolution of Earth's primal organisms, of Earth's first stratum organisms, the RNA genes that have always been and still are running the show of life, the energy-storing biosphere survival, since Earth life's day one.
* A gene's self reproduction was distinctly an evolutionary, enhanced energy constraint event, above the earlier, random, radiated-energy-induced genes formations.
* Every evolutionary step is inherently an event of an enhanced energy constraint.
* Genomes, RNA and DNA, are functional organs evolved by the primary RNA genes. Cell membranes are also functional organs evolved by the primary RNA gene.
* Life is but one of the many many mass formats in the universe, and its evolution is driven as the evolution of all cosmic mass formats, to gain temporary enhanced energy constraint, i.e. to survive as long as possible.
Dov Henis
(Comments From The 22nd Century)
03.2010 Updated Life Manifest
http://www.the-scientist.com/community/posts/list/54.page#5065
Cosmic Evolution Simplified
http://www.the-scientist.com/community/posts/list/240/122.page#4427
Gravity Is The Monotheism Of The Cosmos
http://www.the-scientist.com/community/posts/list/260/122.page#4887
PS1:
This Theory Of Everything, with definition of evolution, covers also ALL aspects of anthropology. DH
PS2:
TOE: Religion Or Science?
(Fwd from the-scientist.com:)
I.
[quote=BobTS1162939] This is the Theory Of Everything In A Nutshell (TOEIANS):
Basic construction of the universe: 1. Particles 2. Strings 3. Frames.
Etc., ....
.[/quote]
II. My comment
A) Since Life is, by our sensory conception, a virtual reality affair, religion is a legitimate virtual reality tool for going through life. But I am not religious. My senses do not become affected by the above TOEIANS. I embarassingly admit that hard as I try I am unable to comprehend the above TOEIANS.
B) My own conception of TOE is scientific, not religious, based strictly on data recorded and observed, of ubiquitous cosmic phenomena. And in presenting my TOE conception I do not deal with mechanisms but with the base processes.
Dov Henis
(Comments From The 22nd Century)
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