Petros Agapetos
10-22-2019, 12:09 AM
The Logic of Theory Testing In Science
No theory in science can be proven true, but they can be proven false!
No amount of experiments can prove a scientific theory true, but one experiment can prove it false!
Falsifiability is the demarcation criterion which distinguishes science from pseudoscience. Falsifiability is the capacity of a proposition, hypothesis, or theory to be proven false. A scientific statement is one that can possibly be proven wrong. Falsifiability is closely related to testability. If a theory is not falsifiable, it is not scientifically sound.
Soft Atheism = I do not believe god exists. Has no burden of proof, and is in fact the default position.
Hard Atheism = I believe that there is no god. Is an assertive position to hold which does carry the burden of proof.
Theistic claims about god can be falsifiable, and therefore be under the purview of science.
Other theistic claims about god are unfalsifiable, which means god cannot be proven to exist because no data point or counter-example exists that could even potentially prove the claim false, therefore we have no way of telling when the claim is true.
Consider... the Null and Research Hypotheses
The Null Hypothesis =
“There is no god”
The Research Hypothesis = “There is a god”.
If one gathers sufficient evidence in favour of the research hypothesis, satisfying a particular standard of proof, then the null hypothesis is rejected, otherwise we fail to reject the null hypothesis, instead of accepting the null! The null hypothesis cannot be proven true, but it can be proven false. No amount of positive evidence can prove a negative claim! One would need negative evidence or a proof by contradiction, such as a reductio ad absurdum - a reduction to absurdity argument, which argues something must not be the case due to the impossibility of the contrary.
Null: This drug has no effect.
Research: This drug has an effect.
An experiment cannot prove a drug has no effect; the effect may merely be too weak to be detected. However, an experiment can prove that a drug has an effect. Absence of evidence is not evidence of absence. No amount of absence of evidence that a drug has a measurable effect can guarantee that the drug in fact has no effect.
Hypothesis testing in science is based on the logic of falsification!
If someone claims that all swans are white, confirmatory evidence (in the form of lots of white swans) cannot prove the assertion to be true, due to the nature of induction. No amount of experience establishes as a matter of certainty that the conclusion of an inductive argument is true. Inductive arguments can be either strongly or weakly supported by the premises, however the premises cannot guarantee the truth of the conclusion.
Example of induction:
Premise 1. All swans that I have seen (thus far) have been white.
Conclusion. Therefore (I conclude) all swans must be white.
This is an inductive inference from the particular to the general.
The statement "all swans are white" is a scientific statement, because it can be falsified! No amount of confirmatory evidence in the form of many white swans can guarantee that therefore all swans must be white. However, contradictory evidence (in the form of a single non-white swan) makes it clear that the claim “all swans are white” is false. For falsifiability, one need only come up with a single counter-example (data point) in the form of a non-white swan, which if true (existent) would falsify the statement “all swans are white”. Falsifiability is closely related to testability!
Another Example of an Inductive Argument: Every time I let go of my pen, it drops. Therefore, I conclude that the next time I let go of my pen it will drop again.
One thereby infers from the finite past observations to the next observation.
Similarly one can make an inductive generalization from the particular to the general:
Premise 1. Every time I let go of my pen in the past, it has fallen down.
Conclusion. Therefore I infer that every time I let go of my pen in the future, it will always drop.
In an inductive argument, the conclusion has more information than the premises! Note that inductive inferences cannot guarantee the truth of the conclusion. This is why the theory of gravity has never been proven true, but it can be proven false.
No theory in science can be proven true, but they can be proven false!
No amount of experiments can prove a scientific theory true, but one experiment can prove it false!
Falsifiability is the demarcation criterion which distinguishes science from pseudoscience. Falsifiability is the capacity of a proposition, hypothesis, or theory to be proven false. A scientific statement is one that can possibly be proven wrong. Falsifiability is closely related to testability. If a theory is not falsifiable, it is not scientifically sound.
Soft Atheism = I do not believe god exists. Has no burden of proof, and is in fact the default position.
Hard Atheism = I believe that there is no god. Is an assertive position to hold which does carry the burden of proof.
Theistic claims about god can be falsifiable, and therefore be under the purview of science.
Other theistic claims about god are unfalsifiable, which means god cannot be proven to exist because no data point or counter-example exists that could even potentially prove the claim false, therefore we have no way of telling when the claim is true.
Consider... the Null and Research Hypotheses
The Null Hypothesis =
“There is no god”
The Research Hypothesis = “There is a god”.
If one gathers sufficient evidence in favour of the research hypothesis, satisfying a particular standard of proof, then the null hypothesis is rejected, otherwise we fail to reject the null hypothesis, instead of accepting the null! The null hypothesis cannot be proven true, but it can be proven false. No amount of positive evidence can prove a negative claim! One would need negative evidence or a proof by contradiction, such as a reductio ad absurdum - a reduction to absurdity argument, which argues something must not be the case due to the impossibility of the contrary.
Null: This drug has no effect.
Research: This drug has an effect.
An experiment cannot prove a drug has no effect; the effect may merely be too weak to be detected. However, an experiment can prove that a drug has an effect. Absence of evidence is not evidence of absence. No amount of absence of evidence that a drug has a measurable effect can guarantee that the drug in fact has no effect.
Hypothesis testing in science is based on the logic of falsification!
If someone claims that all swans are white, confirmatory evidence (in the form of lots of white swans) cannot prove the assertion to be true, due to the nature of induction. No amount of experience establishes as a matter of certainty that the conclusion of an inductive argument is true. Inductive arguments can be either strongly or weakly supported by the premises, however the premises cannot guarantee the truth of the conclusion.
Example of induction:
Premise 1. All swans that I have seen (thus far) have been white.
Conclusion. Therefore (I conclude) all swans must be white.
This is an inductive inference from the particular to the general.
The statement "all swans are white" is a scientific statement, because it can be falsified! No amount of confirmatory evidence in the form of many white swans can guarantee that therefore all swans must be white. However, contradictory evidence (in the form of a single non-white swan) makes it clear that the claim “all swans are white” is false. For falsifiability, one need only come up with a single counter-example (data point) in the form of a non-white swan, which if true (existent) would falsify the statement “all swans are white”. Falsifiability is closely related to testability!
Another Example of an Inductive Argument: Every time I let go of my pen, it drops. Therefore, I conclude that the next time I let go of my pen it will drop again.
One thereby infers from the finite past observations to the next observation.
Similarly one can make an inductive generalization from the particular to the general:
Premise 1. Every time I let go of my pen in the past, it has fallen down.
Conclusion. Therefore I infer that every time I let go of my pen in the future, it will always drop.
In an inductive argument, the conclusion has more information than the premises! Note that inductive inferences cannot guarantee the truth of the conclusion. This is why the theory of gravity has never been proven true, but it can be proven false.