Subduction Zone
Veteran Member
And this is a poorly asked question. This has been explained to you. When you ask your questions poorly you cannot get the sort of answers that you demand. Why is that so hard to understand?
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Evidence For And Against Evolution
- Thread starter Skwim
- Start date
Subduction Zone
Veteran Member
It is funny that you cannot name an example that has not already been refuted.
If your claim is not testable it is not a better explanation.
40% plus Americans reject the sciences of evolution and abiogenesis in one way or another based on a religious agenda. Many create rather imaginative versions to suite what they believe.
I have seen the posts, but they do not include what you claimed you could demonstrate.
CSI is not applied in the way you claim. You do not understand the arguments of ID even as you claim they are the best explanation.
Something that should fall under a design explanation should be explained by it. Since it cannot and the ToE can, in this case, your claim is refuted again.
No, these are not the tactics you are using. If you believe they are you are operating under a delusion. Your gallup over weeks refusing to support your claims reveals this recent claim is unsupported.
leroy
Well-Known Member
No my claim was not refuted, at most you refuted your strawman understanding of CSI.
leroy
Well-Known Member
I provided the reasons why I would claim that design is a better explanation than the one provided by pollymath.
Wether if I succeeded or not is irrelevant, you can't accuse me for not answering,
Subduction Zone
Veteran Member
Hand waving does not really count as an answer. If your idea is not testable it is inferior. If your idea does not have predictive abilities it is inferior. Just because it makes a person feel better does not make it superior.
Apologetic arguments totally lack objectivity nor objective evidence. They are simply accusations of 'My God(s) are greater than your God(s),'
. . . as I described and cited sources, Behe's and your arguments have failed all possible tests in science are not falsifiable as a scientific hypothesis.
The next reference I post will demonstrate Behe's use of statistics has failed and is an unethical use of 'probability.'
http://ramanujan.math.trinity.edu/polofsson/research/BioAndPhil.pdf
Intelligent design and mathematical statistics: a troubled alliance
Peter Olofsson
Published online: 7 August 2007 ! Springer Science+Business Media B.V. 2007
Abstract
The explanatory filter is a proposed method to detect design in nature with the aim of refuting Darwinian evolution. The explanatory filter borrows its logical structure from the theory of statistical hypothesis testing but we argue that, when viewed within this context, the filter runs into serious trouble in any interesting biological application. Although the explanatory filter has been extensively criticized from many angles, we present the first rigorous criticism based on the theory of mathematical statistics.
Hypothesis testing Introduction
A classic creationist argument against Darwinian evolution is that it is as likely as a tornado in a junkyard creating a Boeing 747. In recent years, the criticism has become more measured, coming not from young-earth creationists but from proponents of Intelligent Design (ID). The main claim of the ID proponents is that some biological phenomena are impossible to adequately explain without referring to design. The perhaps most prominent representative for the ID movement is biochemist Michael Behe whose 1996 book Darwin’s Black Box (Behe 1996) presents challenges to Darwinian evolution based on irreducibly complex biochemical systems. A system is irreducibly complex if it consists of several different parts that are such that if any of them is removed, the system loses its function altogether. The favorite biological example is the bacterial flagellum, the little ‘‘outboard motor’’ that some bacteria are equipped with and to which we will return later. Behe’s point is that Darwinian evolution cannot account for the emergence of irreducibly complex systems as all the parts need to be in place at once. Other than that, Behe seems to P. Olofsson (&) Mathematics Department, Trinity University, One Trinity Place, San Antonio, TX 78212-7200, USA e-mail: [email protected] 123 Biol Philos (2008) 23:545–553 DOI 10.1007/s10539-007-9078-6 accept most of the accounts of Darwinian evolution.
His claims in Darwin’s Black Box have been thoroughly opposed, one of the most prominent critics being biologist Kenneth Miller (2000, 2004). Whether the arguments against Darwinian evolution are based on tornadoes in junkyards or bacteria, the key concept for evolution critics is improbability. Since mathematics, probability, and statistics are highly developed disciplines, and are well established as indispensable scientific tools, it is only natural that evolution criticism has turned mathematical, trying to establish objective criteria to rule out chance explanations. The chief advocate for this approach is William Dembski whose ideas are described in his books The Design Inference (Dembski 1998) and No Free Lunch (Dembski 2002), and also in various postings on his own website (Bill Dembski – Freedom, Technology, Education). In The Design Inference, Dembski introduces the explanatory filter as a generic method to eliminate chance explanations and infer design. Inspired by principles from statistical hypothesis testing, the explanatory filter aims at ruling out chance explanations of observed phenomena based on calculating their probabilities and argues that these probabilities are so small that chance is all but impossible. The filter is further discussed in No Free Lunch although in much less detail as the focus is this book is on mathematical complexity theory and the alleged failure of evolutionary algorithms (the title refers to a class of mathematical theorems that say, in essence, that in the absence of knowledge of the location of a target, nothing can beat blind search). Dembski’s oeuvre has been attacked from many different angles. He has had to endure criticism from biologists, philosophers, and mathematicians and the criticism spans the range from accusations of quasi-philosophy to discovery of arithmetic errors. Much of the criticism has been aimed at Dembski’s forages into mathematical complexity theory and optimization theory, most notably by Jeffrey Shallit and Wesley Elsberry (Elsberry and Shallit 2003, 2004; Shallit 2002). An admirably short and surgically precise criticism of Dembski’s use of the no-free-lunch theorems is presented by Ha¨ggstro¨m (2007). The explanatory filter from The Design Inference has also been extensively criticized, perhaps most notably by philosopher Elliot Sober whose articles (Fitelson et al. 1999; Sober 2002, 2004), amongst many other things, criticize its purely eliminative nature, advocating instead that sound scientific practice require that conclusions are based on comparative reasoning. Perhaps a chance hypothesis confers a small probability on the evidence, but how do we know that a design hypothesis does not confer an even smaller probability? As the strategy of the ID movement is to try to discredit Darwinian evolution without offering any substantive alternative theory, the question is not easily answered. In No Free Lunch, Dembski argues against Sober that elimination is indeed a legitimate scientific principle. As an example, Dembski offers the hypothesis that the moon is made of cheese which he claims could be rejected without suggesting an alternative lunar material. The filter has also been criticized by Mark Perakh (2003, 2005) and by several others, for example on the websites
Talk Reason: arguments against creationism, intelligent design, and religious apologetics and The Panda’s Thumb. However, there has not yet been published a criticism of the filter from the vantage point of mathematical statistics. It is clear from Dembski’s writings that his main source of inspiration for the explanatory filter is the theory of statistical hypothesis testing and a mathematical statistician immediately recognizes it as such. We shall see that, from this particular angle, even if the filter is put in the most benevolent light, it runs into serious trouble when it comes to biological applications. The filter will be described in the next section; thereafter we will outline how it relates to statistical hypothesis testing and finally address its weaknesses."
Intelligent design and mathematical statistics: a troubled alliance
Peter Olofsson
Published online: 7 August 2007 ! Springer Science+Business Media B.V. 2007
Abstract
The explanatory filter is a proposed method to detect design in nature with the aim of refuting Darwinian evolution. The explanatory filter borrows its logical structure from the theory of statistical hypothesis testing but we argue that, when viewed within this context, the filter runs into serious trouble in any interesting biological application. Although the explanatory filter has been extensively criticized from many angles, we present the first rigorous criticism based on the theory of mathematical statistics.
Hypothesis testing Introduction
A classic creationist argument against Darwinian evolution is that it is as likely as a tornado in a junkyard creating a Boeing 747. In recent years, the criticism has become more measured, coming not from young-earth creationists but from proponents of Intelligent Design (ID). The main claim of the ID proponents is that some biological phenomena are impossible to adequately explain without referring to design. The perhaps most prominent representative for the ID movement is biochemist Michael Behe whose 1996 book Darwin’s Black Box (Behe 1996) presents challenges to Darwinian evolution based on irreducibly complex biochemical systems. A system is irreducibly complex if it consists of several different parts that are such that if any of them is removed, the system loses its function altogether. The favorite biological example is the bacterial flagellum, the little ‘‘outboard motor’’ that some bacteria are equipped with and to which we will return later. Behe’s point is that Darwinian evolution cannot account for the emergence of irreducibly complex systems as all the parts need to be in place at once. Other than that, Behe seems to P. Olofsson (&) Mathematics Department, Trinity University, One Trinity Place, San Antonio, TX 78212-7200, USA e-mail: [email protected] 123 Biol Philos (2008) 23:545–553 DOI 10.1007/s10539-007-9078-6 accept most of the accounts of Darwinian evolution.
His claims in Darwin’s Black Box have been thoroughly opposed, one of the most prominent critics being biologist Kenneth Miller (2000, 2004). Whether the arguments against Darwinian evolution are based on tornadoes in junkyards or bacteria, the key concept for evolution critics is improbability. Since mathematics, probability, and statistics are highly developed disciplines, and are well established as indispensable scientific tools, it is only natural that evolution criticism has turned mathematical, trying to establish objective criteria to rule out chance explanations. The chief advocate for this approach is William Dembski whose ideas are described in his books The Design Inference (Dembski 1998) and No Free Lunch (Dembski 2002), and also in various postings on his own website (Bill Dembski – Freedom, Technology, Education). In The Design Inference, Dembski introduces the explanatory filter as a generic method to eliminate chance explanations and infer design. Inspired by principles from statistical hypothesis testing, the explanatory filter aims at ruling out chance explanations of observed phenomena based on calculating their probabilities and argues that these probabilities are so small that chance is all but impossible. The filter is further discussed in No Free Lunch although in much less detail as the focus is this book is on mathematical complexity theory and the alleged failure of evolutionary algorithms (the title refers to a class of mathematical theorems that say, in essence, that in the absence of knowledge of the location of a target, nothing can beat blind search). Dembski’s oeuvre has been attacked from many different angles. He has had to endure criticism from biologists, philosophers, and mathematicians and the criticism spans the range from accusations of quasi-philosophy to discovery of arithmetic errors. Much of the criticism has been aimed at Dembski’s forages into mathematical complexity theory and optimization theory, most notably by Jeffrey Shallit and Wesley Elsberry (Elsberry and Shallit 2003, 2004; Shallit 2002). An admirably short and surgically precise criticism of Dembski’s use of the no-free-lunch theorems is presented by Ha¨ggstro¨m (2007). The explanatory filter from The Design Inference has also been extensively criticized, perhaps most notably by philosopher Elliot Sober whose articles (Fitelson et al. 1999; Sober 2002, 2004), amongst many other things, criticize its purely eliminative nature, advocating instead that sound scientific practice require that conclusions are based on comparative reasoning. Perhaps a chance hypothesis confers a small probability on the evidence, but how do we know that a design hypothesis does not confer an even smaller probability? As the strategy of the ID movement is to try to discredit Darwinian evolution without offering any substantive alternative theory, the question is not easily answered. In No Free Lunch, Dembski argues against Sober that elimination is indeed a legitimate scientific principle. As an example, Dembski offers the hypothesis that the moon is made of cheese which he claims could be rejected without suggesting an alternative lunar material. The filter has also been criticized by Mark Perakh (2003, 2005) and by several others, for example on the websites
Talk Reason: arguments against creationism, intelligent design, and religious apologetics and The Panda’s Thumb. However, there has not yet been published a criticism of the filter from the vantage point of mathematical statistics. It is clear from Dembski’s writings that his main source of inspiration for the explanatory filter is the theory of statistical hypothesis testing and a mathematical statistician immediately recognizes it as such. We shall see that, from this particular angle, even if the filter is put in the most benevolent light, it runs into serious trouble when it comes to biological applications. The filter will be described in the next section; thereafter we will outline how it relates to statistical hypothesis testing and finally address its weaknesses."
gnostic
The Lost One
There are huge differences between making claims about how you believe the universe was "designed", and backing up the design with EVIDENCE.
That have always been the problems with supporters of Intelligent Design and the Fine Tuning universe, they make a whole load of assumptions without any observable, measurable and testable EVIDENCE.
Michael Behe himself in 2005 even admitted that Intelligent Design have never been peer reviewed during cross examination:
Kitzmiller v Dover (2005) - Trial Transcript - Day 12 said:
This then lead to a question about Behe's own book - Darwin's Black Box (1996):
Kitzmiller v Dover (2005) - Trial Transcript - Day 12 said:
(Source: talkorigins.org, Kitzmiller v. Dover Area School District Trial transcript: Day 12 (October 19), AM Session, Part 1)
So Behe, in his book, tried to generate explanation for his Irreducible Complexity and for Intelligent Design, but he has admitted that he reported no new data or original research.
No "data", mean that there were no evidence that can be observed, measured and tested.
When you are testing any hypothesis, when there are evidence - regardless if the evidence are positive or negative - the finding must be reported,
- like where, when and how you have found the evidence (observation),
- you would also take measurements and recorded them (more observation),
- and you would test them against other findings (again, more observation).
Did observation successfully back or support the hypothesis (eg explanation, prediction, mathematical statement, etc)?
The data have to be also included with hypothesis, if that scientist(s) submit his hypothesis before Peer Review.
And no "original research" mean Behe didn't bother to find evidence or to test his model (Irreducible Complexity).
Why do you think Behe has never submitted his paper on Irreducible Complexity for Peer Review?
Because if he did submit it without data (evidence) and original research, the independent scientists (peers) would have immediately rejected his paper.
Getting to my point, I agreed with Subduction Zone's reply to you:
If Intelligent Design have no evidence, no data and haven't been peer review, how can ID be a "better explanation"?
A explantion made without evidence, then that explanation isn't science.
Intelligent Design isn't science. Irreducible Complexity isn't science.
Can anyone here explain what is the real
So what is the definitive version of the popular version of evolution? Is there a definition of the "popular version"? Perhaps you can start there by explaining what is the so-called popular version, in contrast to the "scientific version." First give the popular version, then the scientific version. Thanks.
Can you help out a little, since I'd like to know what is the "popular version" definition of evolution as Shunyadragon says there is, and then contrast that with what he calls the "scientific version." Do you know the two seemingly contrasting definitions?
So far there are at least accounts of UFO sightings not that I give much credence to these reports, but no sightings of one form changing into another. Only conjecture.
Popular version - 40% plus Americans reject the sciences of evolution and abiogenesis in one way or another based on a religious agenda. Many create rather imaginative versions to suite what they believe.
Scientific version is strictly the science of abiogenesis and evolution based on the objective verifiable evidence without any religious agenda whatsoever.
I believe the recent military sightings are actual sightings with photographic and radar correlation as evidence.
leroy
Well-Known Member
I'll say that you are raising the bar unrealistically too high.
ID supporters simply use the same methods used in other sciences to detect design, (forensic science, archeology, SETI, etc.) and apply those methods to life and the universe.
leroy
Well-Known Member
And what would be the actual (correct) version of evolution? The version that is uncontroversial and that nearly all scientists accept?