What is most important about statistical inference and our decision making is that the latter constantly burdens the former. In order to lessen the daunting weight of uncertainty in prediction, we must iteratively update our priors. Doing this makes our decisions more relevant , though not necessarily accurate. This relates to the knowledge of why a certain perdition holds or not; we may not be certain of the cause, but we are aware of its effect in collected data. Our decisions to impact said data may never be fully deterministic though we can infer the impact they may have.
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