Crohns-disease
发表于 2025-3-23 13:38:10
Chance and Randomness,ontologically real, they cannot cause anything to happen. Immaterial measures of information are never and can never be physically operative. It is always a mistake, and the cause of vast confusion, to say things like “due to chance”, “games of chance”, “caused by random (chance, spontaneous) mutati
Insufficient
发表于 2025-3-23 15:54:51
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撤退
发表于 2025-3-23 20:32:24
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晚间
发表于 2025-3-23 22:52:19
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换话题
发表于 2025-3-24 06:04:02
Modelling Goals, Strategies, and Mistakes,results should be communicated. The goal of probability models is to quantify uncertainty in an observable Y given assumptions or observations X. That and nothing more. This, and only this, form of model result should be presented. Regression is of paramount importance. The horrors to thought and cl
Arrhythmia
发表于 2025-3-24 10:02:17
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nitric-oxide
发表于 2025-3-24 10:42:46
What Probability Is,now the major part of the premise is ontologically false because there are no dragons, green or otherwise. Counterfactuals are always ontologically false; i.e. they begin with premises known observationally to be false. Yet counterfactuals can have meaningful (epistemological) probabilities. Counter
有其法作用
发表于 2025-3-24 18:53:35
What Probability Is Not, understanding. Subjective probability is therefore a fallacy. The most common interpretation of probability, limited relative frequency, also confuses ontology with epistemology and therefore gives rise to many fallacies.
Cursory
发表于 2025-3-24 20:30:27
Causality,and express true understanding of the nature of a thing. Causes, if they exist and are present, must always be operative, a proposition that has deep consequences for probability modeling. Falsifiability is rarely of interest, and almost never happens in practice. And under-determination, i.e. the p
泥土谦卑
发表于 2025-3-24 23:30:01
Probability Models,istic in the sense given last chapter, but which are treated as probabilistic in practice. Tacit premises are added to the predictions from these models which adds uncertainty. Bayes is not all its cracked up to be. The origin and limitations of parameters and parametric models are given.