A typical epistemological lack of understanding common to atheists is how to setup a correct methodology to find the best answers in regards of origins and reality, and to assume that given further investigations, science will or can discover with absolute certainty and tell us what has happened in the past. The truth is, science is limited in that it does not grant absolute truth, but only yields degrees of probability or likelihood. Asking theists to prove that there is a God is silly.
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
7. Darwin's Doubt pg.162:
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