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Version: 1
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"Some additional points, when applying this Law inside of Science!, that might not be obvious... let me actually 'whiteboard' the three points, so I don't forget the later two while talking about the first one."


- Experimental reports usually don't assign 'priors' or calculate 'posteriors', they just report all cheap details of the raw data, and maybe calculate some 'likelihoods' from obvious hypotheses
- Separate experiments are usually supposed to avert 'conditional-dependencies', watch out for when that isn't true
- If every obvious hypothesis has low-likelihood over all the data, it means the true theory wasn't in your starting set

Version: 2
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Updated
Content

"Some additional points, when applying this Law inside of Science!, that might not be obvious... let me actually 'whiteboard' the three points, so I don't forget the later two while talking about the first one."


- 'Published-experimental-reports' usually don't assign 'priors' or calculate 'posteriors', they just report all cheap details of the raw data, and maybe calculate some 'likelihoods' from obvious hypotheses
- Separate experiments are usually supposed to avert 'conditional-dependencies', watch out for when that isn't true
- If every obvious hypothesis has unexpectedly low 'likelihood' over all the combined data, it means the true theory wasn't in your starting set, often that different experiments had different hidden conditions

Version: 3
Fields Changed Content
Updated
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"Some additional points, when applying this Law inside of Science!, that might not be obvious... let me actually 'whiteboard' the three points, so I don't forget the later two while talking about the first one."

#1 - 'Published-experimental-reports' usually don't assign 'priors' or calculate 'posteriors', they just report all cheap details of the raw data, and maybe calculate some 'likelihoods' from obvious hypotheses

#2 - Separate experiments are usually supposed to avert 'conditional-dependencies', watch out for when that isn't true

#3 - If every obvious hypothesis has unexpectedly low 'likelihood' over all the combined data, it means the true theory wasn't in your starting set, often that different experiments had different hidden conditions