Intelligent Design, the best explanation of Origins

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Intelligent Design, the best explanation of Origins » Philosophy and God » BAYESIAN PROBABILITY AND SCIENCE

BAYESIAN PROBABILITY AND SCIENCE

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1BAYESIAN PROBABILITY AND SCIENCE Empty BAYESIAN PROBABILITY AND SCIENCE on Fri Sep 21, 2018 4:27 am

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BAYESIAN PROBABILITY AND SCIENCE

http://reasonandscience.catsboard.com/t2721-bayesian-probability-and-science

A typical misconception about science is that it can tell us what will definitely happen now or in the future given enough time, or what would certainly have happened in the past, given enough time. The truth is, science is limited in that it does not grant absolute truth, but only yields degrees of probability or likelihood. 

Science isn’t in the business of proving things. Rather, science judges the merits of competing models in terms of their simplicity, clarity, comprehensiveness, and fit to the data.

We speak in terms of “acceptance,” “confidence,” and “probability,” not “proof.” If by proof is meant the establishment of eternal and absolute truth, open to no possible exception or modification, then proof has no place in the natural sciences.

Science observes the Universe, records evidence, and strives to draw conclusions about what has happened in the past, is happening now, and what will potentially happen in the future, given the current state of scientific knowledge—which is often times woefully incomplete, and even inaccurate. The late, prominent evolutionist George Gaylord Simpson discussed the nature of science and probability several years ago in the classic textbook, Life: An Introduction to Biology, stating:

We speak in terms of “acceptance,” “confidence,” and “probability,” not “proof.” If by proof is meant the establishment of eternal and absolute truth, open to no possible exception or modification, then proof has no place in the natural sciences.

Luke A. Barnes writes:
Theory testing in the physical sciences has been revolutionized in recent decades by Bayesian approaches to probability theory.
Wiki: Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability of a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law.  .......and......... historical sciences, including intelligent design theory which tries to explain how most probably past events occurred. That is similar to abductive reasoning :
Wiki: Abductive reasoning is a form of logical inference which goes from an observation to a theory which accounts for the observation, ideally seeking to find the simplest and most likely explanation. In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. One can understand the abductive reasoning as "instant-deduction to the best explanation". 3

No one can know with absolute certainty that the design hypothesis is false.  It follows from the absence of absolute knowledge, that each person should be willing to accept at least the possibility that the design hypothesis is correct, however remote that possibility might seem to him.  Once a person makes that concession, as every honest person must, the game is up.  The question is no longer whether ID is science or non-science.  The question is whether the search for the truth of the matter about the natural world should be structurally biased against a possibly true hypothesis. 4

For, we did not – and cannot -- directly observe the remote past, so origins science theories are in the end attempted “historical” reconstructions of what we think the past may have been like. Such reconstructions are based on investigating which of the possible explanations seems "best" to us on balance in light of the evidence. However, to censor out a class of possible explanations ahead of time through imposing materialism plainly undermines the integrity of this abductive method.

Methodological naturalism is the label for the required assumption of philosophical naturalism when working with the scientific method. Methodological naturalists limit their scientific research to the study of natural causes, because any attempts to define causal relationships with the supernatural are never fruitful, and result in the creation of scientific "dead ends" and God of the gaps-type hypotheses. To avoid these traps scientists assume that all causes are empirical and naturalistic; which means they can be measured, quantified and studied methodically. 5

The first difference is that historical study is a matter of probability. Any and all historical theories are supported by evidence that is not deductive in nature. We might consider them to be inferences to the best explanation, or Bayesian probabilities but they cannot be deductions. historical theories are not based on experiments, – repeatable or otherwise – nor are historical theories subject to empirical verification. The evidence for a historical theory may be empirical, but the theory itself is not. These differences mean that one cannot simply treat science and history as similar disciplines. 6

Stephen Meyer writes:
Studies in the philosophy of science show that successful explanations in historical sciences such as evolutionary biology need to provide “causally adequate” explanations—that is, explanations that cite a cause or mechanism
capable of producing the effect in question. In On the Origin of Species, Darwin repeatedly attempted to show that his theory satisfied this criterion, which was then called the vera causa (or “true cause”) criterion. In the third chapter of the Origin, for example, he sought to demonstrate the causal adequacy of natural selection by drawing analogies between it and the power of animal breeding and by extrapolating from observed instances of small-scale evolutionary change over short periods of time. 7

2. http://www.apologeticspress.org/APContent.aspx?category=12&article=3726
3. https://arxiv.org/pdf/1704.01680.pdf
4. http://iose-gen.blogspot.com.br/2010/06/introduction-and-summary.html#methnat
5. http://rationalwiki.org/wiki/Methodological_naturalism
6. http://simplyphilosophy.org/methodological-naturalism-science-and-history/
7. Darwin's Doubt pg.162:



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2BAYESIAN PROBABILITY AND SCIENCE Empty Comparing worldviews on Fri Dec 07, 2018 10:59 am

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Comparing worldviews

Any worldview is limited in that it does not grant absolute truth, but only yields degrees of probability or likelihood. Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability of a hypothesis as more evidence or information becomes available. Bayesian inference has found application in a wide range of activities, including science, theology, and philosophy. After careful examination, all we can do is come to instant-deduction to the best explanation. Intelligent Design, for example, can be tested using scientific logic.  How? Upon the logic of mutual exclusion, design and non-design are mutually exclusive (it was one or the other) so we can use eliminative logic: if non-design is highly improbable, then design is highly probable.  Thus, evidence against non-design (against production of a feature by undirected natural process) is evidence for design. Both sides need causally adequate” explanations—that is, explanations that cite a cause or mechanism capable of producing the effect in question. 

Either there is a God - creator and causal agency of the universe, or not. God either exists or he doesn’t, and there is no halfway house. These are the only two possible explanations. Upon the logic of mutual exclusion, they are mutually exclusive (it was one or the other) so we can use eliminative logic: if no God is highly improbable, then the existence of God is highly probable.

Naturalism:
- Multiverse
- Virtual particles
- Big Bang
- Accretion theory
- Abiogenesis
- Common ancestry
- Evolution

Theism:
- Transcendent eternal God/Creator
- created the universe and stretched it out
- Created the Galaxies, Stars, Planets, the earth, and the moon
- Created life in all its variants and forms
- Created man and woman as special creation, upon his own image
- Theology and philosophy: Both lead to an eternal, self-existent, omnipresent transcendent, conscious, intelligent, personal and moral Creator.
- The Bible: The Old Testament is a catalogue of fulfilled prophecies of Jesus Christ, and his mission, death, and resurrection foretold with specificity.
- Archaeology: Demonstrates that all events described in the Bible are historical facts. 
- History: Historical evidence reveals that Jesus Christ really did come to this earth, and really did physically rise from the dead
- The Bible's witnesses: There are many testimonies of Jesus doing miracles still today, and Jesus appearing to people all over the globe, still today.
- End times: The signs of the end times that were foretold in the Bible are occuring in front of our eyes. New world order, microchip implant etc.
- After-life experiences: Credible witnesses have seen the afterlife and have come back and reported to us that the afterlife is real.

1. If the weight of the Christian worldview is making sense above 50 % compared to atheism, 
    or any different religion, then it is rational to believe in Christ, and commit living as a Christian.
2. Christianity has at least a 50 % chance of being true.
3Therefore, it is rational to commit to live as a Christian.



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3BAYESIAN PROBABILITY AND SCIENCE Empty BAYESIAN PROBABILITY AND SCIENCE on Fri Jan 11, 2019 2:44 pm

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BAYESIAN PROBABILITY AND SCIENCE

http://reasonandscience.catsboard.com/t2721-bayesian-probability-and-science#6430

Claim: Religion is a matter of personal faith and requires no proof. Science on the other hand, devoted to scientific questions. If Gods existence cannot be proven, such questions belong to Religion, not science. On the other hand, evolution is a scientific theory, and a fact.  A scientific theory is an established body of knowledge about a certain subject, supported by observable facts, repeatable experiments, and logical reasoning.
Answer:  Science has little to do with “proving” anything. 1 Mathematicians prove things, and this means something quite specific. Mathematicians lay out a particular set of ground rules, known as axioms, and determine which statements are true within the framework.

Many, but not all, rely on a particular approach to this known as Bayesian reasoning to incorporate observational and experimental evidence into what we know and to update our belief in a particular description of the universe. So, science is like an ongoing courtroom drama, with a continual stream of evidence being presented to the jury. But there is no single suspect and new suspects regularly wheeled in. In light of the growing evidence, the jury is constantly updating its view of who is responsible for the data.

But no verdict of absolute guilt or innocence is ever returned, as evidence is continually gathered and more suspects are paraded in front of the court. All the jury can do is decide that one suspect is more guilty than another.

What has science proved?
In the mathematical sense, despite all the years of researching the way the universe works, science has proved nothing. Richard Feynman, on what being a scientist is all about:
I have approximate answers and possible beliefs in different degrees of certainty about different things, but I’m not absolutely sure of anything.

"There is no such thing as proof."
Jack Fraser, Master's Physics, University of Oxford

In the scientific realm, doubt abound. Even the simple observation of two people sat in a room with your own eyes would be accepted as “proof”  in science — !

“Proof” implies that there is no room for error — that you can be 100% sure that what you have written down on the piece of paper is 100% representative of what you are talking about. And quite simply, that doesn’t exist in the real world.

I cannot prove to you that electrons exist.

No number of scientists in the world can ever prove that the stars are far away, or that the Higg’s Boson exists — or even that the Earth is round (but shh, don’t tell the Flat Earthers that!)

Nobody can prove that things will always fall down when you drop them.

Nobody can prove that energy is conserved.

Nobody can prove that dark matter exists.

Nobody can prove that quantum physics is real.

Because that’s not what science is about.

Proof can only exist when there is no doubt, and there is always doubt. You could be a brain in a vat, living in a crazy simulation. You could be hallucinating everything.

You cannot prove anything.

So, what is to be done?

Well, either you can sit down and just accept that the world is a chaotic insane place, and that since you cannot prove anything about reality, there’s really no point trying.

Or...

You can gather evidence.

That evidence will never be 100% — there’s always the chance that everything you think you know turns out to be false — but the evidence allows you to make current-best-evidence-guesses (for want of a better term) about the behavior of the universe.

We can build up piles and piles of evidence for ideas.

When the pile reaches a certain height, it behoves us to begin to take it rather seriously.

That is, until someone removes a critical piece from the bottom of the pile, and the entire edifice comes crashing down.

Then what?

Well, you start a new pile. And you have another go. And another. And another.

So what’s the lesson?
All science is merely the current best model. Science is impermanent. It is, by definition, in constant flux.
You can never have 100% proof of anything. There will always be doubt.

1. https://theconversation.com/wheres-the-proof-in-science-there-is-none-30570
2. https://www.forbes.com/sites/quora/2017/12/14/theres-no-such-thing-as-proof-in-the-scientific-world-theres-only-evidence/#7163e1575392

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4BAYESIAN PROBABILITY AND SCIENCE Empty Re: BAYESIAN PROBABILITY AND SCIENCE on Tue Apr 09, 2019 10:38 am

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BAYESIAN PROBABILITY AND SCIENCE

A typical misconception about science is that it can tell us what will definitely happen now or in the future given enough time, or what would certainly have happened in the past, given enough time. The truth is, science is limited in that it does not grant absolute truth, but only yields degrees of probability or likelihood. 

Science isn’t in the business of proving things. Rather, science judges the merits of competing models in terms of their simplicity, clarity, comprehensiveness, and fit to the data.

Science observes the Universe, records evidence, and strives to draw conclusions about what has happened in the past, is happening now, and what will potentially happen in the future, given the current state of scientific knowledge—which is often times woefully incomplete, and even inaccurate. The late, prominent evolutionist George Gaylord Simpson discussed the nature of science and probability several years ago in the classic textbook, Life: An Introduction to Biology, stating:

We speak in terms of “acceptance,” “confidence,” and “probability,” not “proof.” If by proof is meant the establishment of eternal and absolute truth, open to no possible exception or modification, then proof has no place in the natural sciences.

Luke A. Barnes writes:
Theory testing in the physical sciences has been revolutionized in recent decades by Bayesian approaches to probability theory.
Wiki: Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability of a hypothesis as more evidence or information becomes available. Bayesian inference is an important technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application in a wide range of activities, including science, engineering, philosophy, medicine, sport, and law.  .......and......... historical sciences, including intelligent design theory which tries to explain how most probably past events occurred. That is similar to abductive reasoning :
Wiki: Abductive reasoning is a form of logical inference which goes from an observation to a theory which accounts for the observation, ideally seeking to find the simplest and most likely explanation. In abductive reasoning, unlike in deductive reasoning, the premises do not guarantee the conclusion. One can understand the abductive reasoning as "instant-deduction to the best explanation". 3

No one can know with absolute certainty that the design hypothesis is false.  It follows from the absence of absolute knowledge, that each person should be willing to accept at least the possibility that the design hypothesis is correct, however remote that possibility might seem to him.  Once a person makes that concession, as every honest person must, the game is up.  The question is no longer whether ID is science or non-science.  The question is whether the search for the truth of the matter about the natural world should be structurally biased against a possibly true hypothesis. 4

For, we did not – and cannot -- directly observe the remote past, so origins science theories are in the end attempted “historical” reconstructions of what we think the past may have been like. Such reconstructions are based on investigating which of the possible explanations seems "best" to us on balance in light of the evidence. However, to censor out a class of possible explanations ahead of time through imposing materialism plainly undermines the integrity of this abductive method.

Methodological naturalism is the label for the required assumption of philosophical naturalism when working with the scientific method. Methodological naturalists limit their scientific research to the study of natural causes, because any attempts to define causal relationships with the supernatural are never fruitful, and result in the creation of scientific "dead ends" and God of the gaps-type hypotheses. To avoid these traps scientists assume that all causes are empirical and naturalistic; which means they can be measured, quantified and studied methodically. 5

The first difference is that historical study is a matter of probability. Any and all historical theories are supported by evidence that is not deductive in nature. We might consider them to be inferences to the best explanation, or Bayesian probabilities but they cannot be deductions. historical theories are not based on experiments, – repeatable or otherwise – nor are historical theories subject to empirical verification. The evidence for a historical theory may be empirical, but the theory itself is not. These differences mean that one cannot simply treat science and history as similar disciplines. 6

Stephen Meyer writes: 
Studies in the philosophy of science show that successful explanations in historical sciences such as evolutionary biology need to provide “causally adequate” explanations—that is, explanations that cite a cause or mechanism
capable of producing the effect in question. In On the Origin of Species, Darwin repeatedly attempted to show that his theory satisfied this criterion, which was then called the vera causa (or “true cause”) criterion. In the third chapter of the Origin, for example, he sought to demonstrate the causal adequacy of natural selection by drawing analogies between it and the power of animal breeding and by extrapolating from observed instances of small-scale evolutionary change over short periods of time. 7

2. http://www.apologeticspress.org/APContent.aspx?category=12&article=3726
3. https://arxiv.org/pdf/1704.01680.pdf
4. http://iose-gen.blogspot.com.br/2010/06/introduction-and-summary.html#methnat
5. http://rationalwiki.org/wiki/Methodological_naturalism
6. http://simplyphilosophy.org/methodological-naturalism-science-and-history/
7. Darwin's Doubt pg.162:

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