A design inference from tennis: Is the fix in?

_{Denyse O'Leary

June 24, 2011

Design inference, Intelligent Design}

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The conspiracy theorists were busy last month when the Cleveland Cavaliers — spurned by Lebron, desperate for some good fortune, represented by a endearing teenager afflicted with a rare disease — landed the top pick in the NBA Draft. It seemed too perfect for some (not least, Minnesota Timberwolves executive David Kahn) but the odds of that happening were 2.8 percent, almost a lock compared to the odds of Isner-Mahut II.

Question: How come it’s legitimate to reason this way in tennis but not in biology? Oh wait, if we start asking those kinds of questions, we’ll be right back in the Middle Ages when they were so ignorant that …

Comments

Mark F: Pardon an O/T, but it seems to me that you and ilk have some fairly serious 'splainin' to do, as the mess I just linked on had its roots in your blog. G'day GEM of TKI PS: After so many years, you are still not straight on what the design inference is and tries to do, how. Your presentation above is a strawman, I am afraid; surely after all these years you can do better. It would help to start by summarising in the design thinker's own words, a true and fair view of what they are saying.kairosfocus_{July 1, 2011
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Finally got a moment to indulge in one of my favourite discussions – the foundations of hypothesis testing. Of course I agree with everything Lizzie says – but I think there is a deeper point which is more relevant to ID. Dembski’s method is very similar to Fisherian hypothesis testing and shares many of its problems. And Fisherian hypothesis testing has many severe problems. For example, 1) It depends on outcomes that never happened. The statistician Harold Jeffrey’s famously remarked: “What the use of P implies, therefore, is that a hypothesis that may be true may be rejected because it has not predicted observable results that have not occurred. This seems a remarkable procedure” 2) In some contexts the significance of an experiment can depend on the intentions of the experimenter and not just the results. See this for an explanation of both. But perhaps the most severe fault is that it does not consider whether H1 explains the data better than H0. The significance is the probability of the observed outcome falling into the rejection region given the null hypothesis H0. It is assumed that the probability of the observed outcome falling into this region is greater given H1 but no attempt is made to prove it or calculate what this value is or how much greater. The argument is purely: “it is very unlikely we should get a result this extreme if H0 is true – therefore H1 is true”. This neatly encapsulates the design argument and also one of its weaknesses. There is no attempt to even discuss whether the design hypothesis explains the data better. As Cohen puts it – the Fisherian argument is like saying: "If you are an American it is very unlikely you will be a member of Congress. X is a member of Congress. Therefore it is very unlikely X is an American." This fails because it has not considered the probability of being a member of Congress if you are not an American. The design argument says – an outcome (e.g. bacterial flagellum) is incredibly unlikely given certain “Darwinian” assumptions about how life evolved. The bacterial flagellum exists. Therefore, these Darwinian assumptions are false. It never stops to consider the probability of the bacterial flagellum existing given certain assumptions about design because it forbids formulation of a design hypothesis.Finally got a moment to indulge in one of my favourite discussions – the foundations of hypothesis testing. Of course I agree with everything Lizzie says – but I think there is a deeper point which is more relevant to ID. Dembski’s method is very similar to Fisherian hypothesis testing and shares many of its problems. And Fisherian hypothesis testing has many severe problems. For example, 1) It depends on outcomes that never happened. The statistician Harold Jeffrey’s famously remarked: “What the use of P implies, therefore, is that a hypothesis that may be true may be rejected because it has not predicted observable results that have not occurred. This seems a remarkable procedure” 2) In some contexts the significance of an experiment can depend on the intentions of the experimenter and not just the results. See this for an explanation of both. But perhaps the most severe fault is that it does not consider whether H1 explains the data better than H0. The significance is the probability of the observed outcome falling into the rejection region given the null hypothesis H0. It is assumed that the probability of the observed outcome falling into this region is greater given H1 but no attempt is made to prove it or calculate what this value is or how much greater. The argument is purely: “it is very unlikely we should get a result this extreme if H0 is true – therefore H1 is true”. This neatly encapsulates the design argument and also one of its weaknesses. There is no attempt to even discuss whether the design hypothesis explains the data better. As Cohen puts it – the Fisherian argument is like saying: If you are an American it is very unlikely you will be a member of Congress. X is a member of Congress. Therefore it is very unlikely X is an American. This fails because it has not considered the probability of being a member of Congress if you are not an American. The design argument says – an outcome (e.g. bacterial flagellum) is incredibly unlikely given certain “Darwinian” assumptions about how life evolved. The bacterial flagellum exists. Therefore, these Darwinian assumptions are false. It never stops to consider the probability of the bacterial flagellum existing given certain assumptions about design because it forbids formulation of a design hypothesis.markf_{July 1, 2011
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Dembski:
...specification constitutes a probabilistic form of warrant, transforming the suspicion of design into a warranted belief in design.
What is it that transforms suspicion of design into warranted belief? Specification. How could "design" transform the suspicion of design into a warranted belief in design? That's just absurd. It has to be something else, and that something else is, according to Dembski, specification.Mung_{July 1, 2011
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Dembski:
Since specifications are those patterns that are supposed to underwrite a design inference, they need, minimally, to entitle us to eliminate chance.
The specification underwrites the design inference. It is the specification that needs "minimally, to entitle us to eliminate chance." It's not "design" that eliminates the "null," it is specification. Therefore the null is not "no design". At best, the "null" is no specification. H0: We do not have a specification. H1: We do have a specification. How is H0 not the negation of H1? How are the two not mutually exclusive? IOW, how do they fail to meet your requirements for a null and alternate? Given H1 we can reject H0, and the inference to design is then warranted. That's Dembski.Mung_{July 1, 2011
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You are mistaking your hypotheses for your inferences.
No, I'm not. It's not called The Design Inference for nothing. The Inference to Design is what we're allowed to make once we've tested the hypotheses. Dembski:
In a moment, we’ll consider a form of specified complexity that is independent of the replicational resources associated with S’s context of inquiry and thus, in effect, independent of S’s context of inquiry period (thereby strengthening the elimination of chance and the inference to design).
Dembski:
Since specifications are those patterns that are supposed to underwrite a design inference, they need, minimally, to entitle us to eliminate chance.
Whether or not there is a specification is the hypothesis. The presence of a specification is what warrants the design inference. I still don't think you understand the argument, but hey. Dembski:
Indeed, the mere possibility that we might have missed some chance hypothesis is hardly reason to think that such a hypothesis was operating. Nor is it reason to be skeptical of a design inference based on specified complexity. Appealing to the unknown to undercut what we do know is never sound epistemological practice. Sure, we may be wrong. But unknown chance hypotheses (and the unknown material mechanisms that supposedly induce them) have no epistemic force in showing that we are wrong.
Dembski:
If, in addition, our best probabilistic analysis of the biological systems in question tells us that they exhibit high specified complexity and therefore that unguided material processes could not have produced them with anything like a reasonable probability, would a design inference only now be warranted?
I don't know how Dembki could make it any more plain, or how you could fail to read him correctly given how plainly it is stated. A design inference is what is warranted when: H1: some thing or event exhibits high specified complexity and therefore H0: that unguided material processes could not have produced them with anything like a reasonable probability. That's Dembski's argument in a nutshell. Thanks for all your help getting it out in the open and plain for all to see. :)Mung_{July 1, 2011
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Here's how it works: H0: No design. H1: Design Inference if H0 is retained: We do not have sufficient warrant to reach a design inference. Inference if H0 is rejected: We have sufficient warrant to reach a design inference. In other words, you make your inference from your test of the null. Your null is not the inference you make if you retain it :) Subtle, but nonetheless important.Elizabeth Liddle_{July 1, 2011
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You are mistaking your hypotheses for your inferences. They are not the same thing. Easily done, though :)Elizabeth Liddle_{July 1, 2011
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Elizabeth Liddle:
Well, yes, you can refuse to describe your null in words, if you like. However, that means that you cannot describe your H1 in words either!
When did I stop using words? ok, you hadn't had your coffee yet. I forgive you. This whole debate right now is revolving around which words to use, not whether words should be used. You insist that H1 must be "design" and that therefore the null must be "not design." I beg to differ. H0: We do not have sufficient warrant to reach a design inference. H1: We have sufficient warrant to reach a design inference. Is H0 the logical negation of H1 or not? H0: It is false that we have sufficient warrant to reach a design inference. H1: It is true that we have sufficient warrant to reach a design inference. Notice the complete absence of the words "not design" in H0. Why on earth would you say "ding ding ding" and then not mean it? Or what did you mean by it?
If you reject H0 you can conclude H1 is true.
I reject the hypothesis which states that it is false [not true] that we have sufficient warrant to reach a design inference. Therefore ... I reject the hypothesis that we do not have sufficient warrant to reach a design inference. Therefore ... What is the logical negation of those statements and why is the logical negation and it's alternative not mutually exclusive?Mung_{July 1, 2011
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And let me know if you find any more. (Maybe I need a shot of Aricept in my coffee....)Elizabeth Liddle_{July 1, 2011
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oops yes! Sorry (note to self: never post before coffee). Yes: Should be: If you retain H0 you cannot conclude H1 is true. But nor can you conclude that H0 is true. Glad to see people aren't snoozing at the back there :)Elizabeth Liddle_{July 1, 2011
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haha at least driver and i are paying attentionjunkdnaforlife_{July 1, 2011
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"If you retain H1 you cannot conclude H1 is true. But nor can you conclude that H0 is true." you meant ...if you retain H0... right? otherwise i'm really confused/junkdnaforlife_{July 1, 2011
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If you retain H1 you cannot conclude H1 is true. But nor can you conclude that H0 is true.
I think that's a typo. Isn't it "If you retain H0..."?Driver_{July 1, 2011
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But I really do wish you would stop calling “no design” the null. I’ve repeatedly objected to that and with good reason. So if the null can be phrased without it why not do so? Why not say “within this region design is not distinguishable from other possibilities”? Because that is the actual fact of the matter when it comes to Dembski’s work. Mung, I do appreciate your post :) And I'm not feeling quite so catty after 9 hours sleep :_ Yes, we are getting somewhere. However....
But I really do wish you would stop calling “no design” the null. I’ve repeatedly objected to that and with good reason. So if the null can be phrased without it why not do so? Why not say “within this region design is not distinguishable from other possibilities”? Because that is the actual fact of the matter when it comes to Dembski’s work.
Well, yes, you can refuse to describe your null in words, if you like :) However, that means that you cannot describe your H1 in words either! Remember that one is the negation of the other, so if you want to make an inference from support for H1 you need to articulate H1. And so, the null is "not H1". And thus, if you infer "Design" if your H1 is supported, you must also characterise your null as "no Design". Otherwise you will risk an Unexcluded middle! However, I do suggest you read my previous posts very carefully because I used all the pedagogical tricks at my disposal to try to explain to you why this does not create a problem for the inference that H1 is still possible even if H0 is not rejected. But I'll try once more:
There is a massive difference between not perceiving a thing and the thing not perceived being not present at all.
Yes. But Fisherian hypothesis testing does not allow you to distinguish between a thing not being present and the thing being present but not noticeable so. This is a really important point (indeed, it's almost my only point!) but you are still not seeing it. You cannot prove a null. But we encounter it time and time again: studies repeatedly show that there is no evidence that vaccines cause autism; yet people insist that it might. And it cannot be ruled out because you can never prove a null. You can prove (probabilistically) that the null should be rejected. But you cannot prove (even probabilistically) that the null is true. H0: Design is not distinguishable from other other possibilities/hypohteses. Well, technically that is incorrect! Is what I'm saying. It the inference you draw from rejecting the null is that "Design was responsible for the observed pattern, then your null hypothesis is that Design is NOT responsible for the observed pattern. The inference you make from failing to reject the null is that "Design may have been responsible for the observed pattern, but we cannot reject the possibilit that it was not. That is why the correct phraseology is "fail to reject the null" ("aka "retain the null") not "prove the null" or "conclude the null"). So your two hypothesis MUST be mutually exclusive; however the assymmetry comes in when you either reject the null (conclude that H1 is true), or retain the null (conclude that H0 may be true). You never conclude that H0 is true! As I say, it's weird but it works. Fairly well, anyway.
H1: Design is distinguishable from other other possibilities/hypotheses.
Well, no. See above. Feel free to ask any more questions :) It's a tricky concept, but important. But the essentials of null hypothesis testing are: Your two hypotheses (H0 and H1) have to be mutually exclusive - if one is true the other is false. If you reject H0 you can conclude H1 is true. If you retain H1 you cannot conclude H1 is true. But nor can you conclude that H0 is true. But you are not alone in finding this counterintuitive! Cheers LizzieElizabeth Liddle_{July 1, 2011
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Ding ding we have a winner!!!!
Does this mean you liked my H0 and H1? If so, I guess it demonstrates we can work together after all. :) And I hope you'll take note that I'm not all about just being disagreeable and have been trying to work towards finding something we can agree on. I'm not trying to stall the debate but rather to find ways to move it forward. But I really do wish you would stop calling "no design" the null. I've repeatedly objected to that and with good reason. So if the null can be phrased without it why not do so? Why not say "within this region design is not distinguishable from other possibilities"? Because that is the actual fact of the matter when it comes to Dembski's work. There is a massive difference between not perceiving a thing and the thing not perceived being not present at all. H0: Design is not distinguishable from other other possibilities/hypohteses. H1: Design is distinguishable from other other possibilities/hypotheses.Mung_{June 30, 2011
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All in good fun Lizzie. I'm a cat lover myself. But here the dew rises ;).Mung_{June 30, 2011
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BTW, kf and Mung: Don't mind me teasing - I've had a hard day :) And it's fun to argue of an evening, with a cat on my lap and the dew falling....Elizabeth Liddle_{June 30, 2011
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Mung:
Doesn’t look to me like he’s doing a probability calculation for a pattern.
No, he's doing a probability calculation for a class of patterns under the null hypothesis of no-Design. He's also, interestingly, computing a suitable alpha value (i.e. not only computing the pdf under the null, but the cutoff for the rejection region) by which we can be certain that the probability is so low, that there are simply not enough opportunities in the entire universe for it to have occurred with any likelihood worth mentioning. Which is not to say it didn't :) But don't let's start THAT again....Elizabeth Liddle_{June 30, 2011
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Mung:
H0: We do not have sufficient warrant to reach a design inference. H1: We have sufficient warrant to reach a design inference. William A. Dembski:
Over the last decade, much of my work has focused on design detection, that is, sifting the effects of intelligence from material causes. Within the method of design detection that I have developed, specification functions like Plantinga’s notion of warrant: just as for Plantinga warrant is what must be added to true belief before one is entitled to call it knowledge, so within my framework specification is what must be added to highly improbable events before one is entitled to attribute them to design. The connection between specification and warrant is more than a loose analogy: specification constitutes a probabilistic form of warrant, transforming the suspicion of design into a warranted belief in design.
Ding ding we have a winner!!!! And who would have thought that my first victory on UD would be persuading a UDist that Dembski was correct ;) Now, I'm going to have beer, then bed, because I've had a hard day, but maybe tomorrow I'll have a shot at persuading you that he is also wrong :)Elizabeth Liddle_{June 30, 2011
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I'll take that as a yes, then, shall I, kf? :DElizabeth Liddle_{June 30, 2011
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Mung, He is making an info beyond a threshold estimate, as the log reduction I have done shows. As a part of that,t her eis a probability estimate, which makes the "chance" hyp usual in the I = - log P explicit. In so doing this has been a great occasion for the debaters to show off their objections, not realising that this same principle is embedded in essentially all probability of symbols based information metrics. thewhole point of the estimare is that if the info is complex beyond a thershold and specific, it comes form a zone of interst unlikely to be arrived at by chance, to such a degree that it is reasonable to infer to design as best explanation. As I have shown based on VJT and Giem, 500 bits is a good threshold, and it is in fact a measure of something beyond the reasonable search resources of our solar system; our effective universe. (The next star over is several light years away. Absent discovery of somnething like the hyperspace discussed in so much popular sci fiction, we will not be visiting such any time soon.) GEM of TKIkairosfocus_{June 30, 2011
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oops, sorry Mung, hadn't noticed that 103 was not your only post since mine. OK:
Design is inferred if an observed pattern is improbable under any other hypothesis.
Hi Lizzie. At first glance I don’t think I can agree with this unless you can explain how it incorporates the idea of a specification.
Oh boy. gah. Look, I'm not asking HOW you compute the improbability at this stage, I'm just asking whether you agree, in principle, that the shape of the analysis is: Infer design (or, if you prefer, "consider a Design Inference warranted") if something a pattern is improbable under some other hypothesis. Surely you agree with this? Then we can discuss (and we should) how we figure out whether the pattern is improbable. It's the improbable part I want you to agree to. And I can't imagine won't because it's blindingly obvious!!! So please, pretty please, just give me a yes? Unless you really mean no, in which case, I think you might want to have a serious word with both Dembski and Meyer!
It’s not sufficient that the pattern be improbable. kf brings up an excellent point: In short on the available resources, the possibilities cannot be sufficiently explored on those ambits, to be sufficiently different from no search at all, to give any credible possibility of a random walk stumbling on any reasonably specific zone of interest. We should all know and accept that is a very high bar indeed. Surely things that are in fact designed and events that actually do have an intelligent cause will be missed. In other terms, they will fall outside the rejection region.
Oh, certainly. As I've said, approximately a gazillion times, just because a pattern is moderately probable under some other hypothesis, doesn't mean it wasn't due to yours. I mean, 5 heads and five tails is perfectly probable under the null of a fair toss of a fair coin, but the pattern could also have been produced by me carefully laying the coins down in a order that happened to take my fancy. So I'm NOT asking you to say: we can only infer Design if a pattern is extremely improbable under some other non-Design hypothesis. I'm simply asking you to agree that Dembski (and Kairofocus actually, and Meyer) are saying that IF a pattern is extremely improbable under some non-Design hypothesis, THEN we are warranted to infer Design. OK?
Therefore, the null cannot logically be no design.
Mung. Seriously. Yes. It. Can. Please revise your elementary stats text books! And let me remind you of Chapter 3 (the one after Means, and Standard Deviations): 1. The null hypothesis is the hypothesis that your alternative hypothesis is false. 2. If your observed data is improbable under the null, you can conclude that your alternative is supported. 3. [b]If your data are perfectly probable under the null you CAN NOT CONCLUDE that your alternative is false, even though the null is that your hypothesis is false.[/b] So, it is perfectly logical to say that the "null can be no design" because having the null as no design does not allow us to conclude "no design" just because the observed pattern is reasonably probable under the null. That's why we say we "reject the null" or "retain the null". We do not say we "reject the alternative". Actually, we never "reject the alternative" under Fisherian statistics. That is the point I've been trying to make!!!!!
All issues of mathematics and hypothesis testing aside, does that help explain where I am coming from?
Yes, it does :) It explains to me that you have forgotten your elementary stats :) But then I did know that. That's why I've been giving you a nice stats refresher course on this thread. Trouble is, you've been so twitchy about where I might be going you haven't actually taken it in - so you are still trying to tell me that "no design can't logically be the null, because if it was, that would mean that we concluded no design sometimes even where there was design". Even though I've told you for the umpteenth time that we can't do that with a null!!!!! Sheesh.
You are attempting to force Dembski into an illogical position.
No, I'm attempting to get you to see Dembski's logic.
So what you gave with one hand you took away with the other :)
lol :)
However, as the Hypothesis that Dembski considers supported if a pattern falls in the rejection region is Design, we can, by simple substitution, conclude that Design is H1 and no-Design is H0.
I don’t see how we can do so and remain logically consistent.
Well, you'd better take that up with Fisher :) Not my fault guv.
I thought we agreed long ago that the null was the logical negation of the alternate. I’m just trying to understand the ground rules.
Yes, it is. But there is a catch. The null is always the negation of the alternative (that's why actually you only need to state one and you get the other for free), but the TEST is asymmetrical. If a pattern is in the rejection region (rejection of the null) you get to claim your alternative. But if it isn't, you DON'T get to keep your null, I'm afraid. If you want life to be fair, you have to go for Bayesian methods :) But if you want Fisher (and, as Dembski says, there are good reasons for going with Fisher), then you have to put up with assymmetrical hypotheses.
And can it be just any pattern, or does it need to qualify as a specification?
So let me be as neutral as I can, and say that Dembski’s H1 is “The hypothesis that Dembski considers supported when a pattern falls in the rejection region”, and Dembski’s H0 is “the hypothesis that Dembski considers a sufficient explanation for the pattern if the pattern falls outside the rejection region”.
You are framing it as two competing hypotheses or explanations?
Well, yes, but the playing field isn't flat. It's more like that gladiatorial game where one guy gets a net and a trident and the other guy gets a dagger. The retiarius and the secutor. The advantage for the H0 (the "retiarius") is that most of the distribution is for him - he can cast his net really wide. Poor H1 (the "secutor") only gets this tiny "rejection region" to aim at - the bit the net doesn't cover. However, the secuto, H1, has a sharp dagger, and the retuarius, H0, only has a clumsy trident. If the secutor manages to hit the rejection region, it's lethal to the null I mean retuarius. Whereas if the retuarius catches the secutor, all he can do is poke him a bit with the trident. So it kind of works out fair :) The thing is rigged in favour of the null, but the quid pro quo is that if H1 wins, he really wins - H0 is considered firmly rejected. If H0 wins, he still has to concede that H1 might have been true. Cheers LizzieElizabeth Liddle_{June 30, 2011
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Let me quote me (I love to hear myself talk):
I don’t see Dembski trying to calculate the probability of a given pattern. Does he? As I think we all know, probabilities fall in the range 0 to 1. Dembski:
In other words, specifications are those patterns whose specified complexity is strictly greater than 1.
Doesn't look to me like he's doing a probability calculation for a pattern.
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Now, tell me how we calculate the probability of a pattern...
I'm sorry, but I don't understand this request. I don't see Dembski trying to calculate the probability of a given pattern. Does he?Mung_{June 30, 2011
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H0: We do not have sufficient warrant to reach a design inference. H1: We have sufficient warrant to reach a design inference. William A. Dembski:
Over the last decade, much of my work has focused on design detection, that is, sifting the effects of intelligence from material causes. Within the method of design detection that I have developed, specification functions like Plantinga’s notion of warrant: just as for Plantinga warrant is what must be added to true belief before one is entitled to call it knowledge, so within my framework specification is what must be added to highly improbable events before one is entitled to attribute them to design. The connection between specification and warrant is more than a loose analogy: specification constitutes a probabilistic form of warrant, transforming the suspicion of design into a warranted belief in design.
Mung_{June 30, 2011
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OK, so we have: “A design inference is warranted when an observed pattern is improbable under any hypothesis under which a design inference is not warranted". OK? It's a bit weird, but I guess it will do for now :) Now, tell me how we calculate the probability of a pattern "under any hypothesis under which a design inference is not warranted". Feel free to C&P from Dembski if you like :)Elizabeth Liddle_{June 30, 2011
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Design is inferred if an observed pattern is improbable under any other hypothesis.
How about we start it out like this: "A design inference is warranted when ..."Mung_{June 30, 2011
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William, We are discussing whether the EF and CSI are even valid forms of scientific inference. It would be a bit premature and somewhat an exercise in futility to apply them to an actual test case don't you think?Mung_{June 30, 2011
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Design is inferred if an observed pattern is improbable under any other hypothesis.
Hi Lizzie. At first glance I don't think I can agree with this unless you can explain how it incorporates the idea of a specification. It's not sufficient that the pattern be improbable. kf brings up an excellent point:
In short on the available resources, the possibilities cannot be sufficiently explored on those ambits, to be sufficiently different from no search at all, to give any credible possibility of a random walk stumbling on any reasonably specific zone of interest.
We should all know and accept that is a very high bar indeed. Surely things that are in fact designed and events that actually do have an intelligent cause will be missed. In other terms, they will fall outside the rejection region. Therefore, the null cannot logically be no design. All issues of mathematics and hypothesis testing aside, does that help explain where I am coming from? You are attempting to force Dembski into an illogical position. So what you gave with one hand you took away with the other :)
However, as the Hypothesis that Dembski considers supported if a pattern falls in the rejection region is Design, we can, by simple substitution, conclude that Design is H1 and no-Design is H0.
I don't see how we can do so and remain logically consistent. I thought we agreed long ago that the null was the logical negation of the alternate. I'm just trying to understand the ground rules. And can it be just any pattern, or does it need to qualify as a specification?
So let me be as neutral as I can, and say that Dembski’s H1 is “The hypothesis that Dembski considers supported when a pattern falls in the rejection region”, and Dembski’s H0 is “the hypothesis that Dembski considers a sufficient explanation for the pattern if the pattern falls outside the rejection region”. You are framing it as two competing hypotheses or explanations?
Mung_{June 30, 2011
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bornagain77
The inference is automatic through the exclusion of chance and necessity of the entire material resources of the universe,,, another inference is available, but seeing your aversion for links,,,,
Ah, my apologies. From what I had read so far I understood the EF to be a tool that can be used to determine design/not design on a arbitrary object including those of a biological nature. I had not realized it was an "automatic" inference. I expect that's because in a designed universe everything is designed? Or have I got that wrong?WilliamRoache_{June 30, 2011
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