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Re: Scientific Method
Posted by: SJAvato (IP Logged)
Date: June 30, 2022 12:09PM
Coming in way late on this discussion but...my thoughts....
The "scientific method" is not linear, but it is iterative.
Data becomes "evidence" when it goes to either support or refute a hypothesis. Data gets meaning in the context of the fire when evaluated against a hypothesis; otherwise, data is data. For example - "The fire alarm activated at 1 am" is data that, in and of itself, only means that an alarm activated at 1 am. When evaluated against the fact that a fire occurred and the hypothesis "The fire started around 1 am" - the alarm data is now evidence that supports the hypothesis. (If there was no fire, the data may go to support a hypothesis that the alarm system is faulty.)
Hypotheses do not need to be based on evidence. (Your FINAL hypothesis should be based on evidence that supports the hypothesis - after consideration of data that potentially refutes the hypothesis.) A hypothesis can be any statement related to the incident and will either be supported by data or not. The hypothesis is only a statement against which to evaluate data or to guide further action.
I don't believe there are "invalid" hypotheses when the hypothesis suggests a known or potential cause or origin of a fire; only those that are either supported or refuted within the context of a particular incident. I can hypothesize that the fire originated in the basement of a structure. I can make that hypothesis before I even arrive on the scene, because, based on my knowledge, training and experience, fires sometimes start in basements. If I arrive at the scene and there is no basement or no evidence of fire origin or causality in the basement, the hypothesis fails and we move on to other hypotheses - it wasn't an "invalid" hypothesis, only an unsupported one and becomes useful (assuming there is a basement) in attempting to falsify the hypothesis that the fire originated on the second floor (as a fire in the basement would, potentially, falsify the second floor origin hypothesis) and in refuting confirmation or expectation bias.
Steve
The "scientific method" is not linear, but it is iterative.
Data becomes "evidence" when it goes to either support or refute a hypothesis. Data gets meaning in the context of the fire when evaluated against a hypothesis; otherwise, data is data. For example - "The fire alarm activated at 1 am" is data that, in and of itself, only means that an alarm activated at 1 am. When evaluated against the fact that a fire occurred and the hypothesis "The fire started around 1 am" - the alarm data is now evidence that supports the hypothesis. (If there was no fire, the data may go to support a hypothesis that the alarm system is faulty.)
Hypotheses do not need to be based on evidence. (Your FINAL hypothesis should be based on evidence that supports the hypothesis - after consideration of data that potentially refutes the hypothesis.) A hypothesis can be any statement related to the incident and will either be supported by data or not. The hypothesis is only a statement against which to evaluate data or to guide further action.
I don't believe there are "invalid" hypotheses when the hypothesis suggests a known or potential cause or origin of a fire; only those that are either supported or refuted within the context of a particular incident. I can hypothesize that the fire originated in the basement of a structure. I can make that hypothesis before I even arrive on the scene, because, based on my knowledge, training and experience, fires sometimes start in basements. If I arrive at the scene and there is no basement or no evidence of fire origin or causality in the basement, the hypothesis fails and we move on to other hypotheses - it wasn't an "invalid" hypothesis, only an unsupported one and becomes useful (assuming there is a basement) in attempting to falsify the hypothesis that the fire originated on the second floor (as a fire in the basement would, potentially, falsify the second floor origin hypothesis) and in refuting confirmation or expectation bias.
Steve
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