this post was submitted on 22 Jun 2026
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Maybe we use these terms differently in different domains. In my field, stochastic means that repeating the same experiment under the same conditions doesn't guarantee the same results (e.g. rolling a die). The opposite of stochastic is deterministic. Something that changes depending on the day would be "a function of the date" or something that is "conditional on the date". This can either be a deterministic function (e.g. calling
date.today().dayin Python, or a mapping from the date to a uniform distribution ranging from0todate.today().day) or a stochastic function (e.g. sample a uniform random integer between0anddate.today().day).Edit: I think what you're talking about is the deterministic mapping from some variable into a distribution. We (as in my field specifically) do sometimes call that "stochastic" too, even though that mapping is deterministic. There may be a bit of terminology overloading here because what we care about in the end is the sample drawn from that distribution, which is actually stochastic.
No, that's exactly what I mean and exactly what I think you are missing: quantum mechanical experiments have been reproduced thousands of times, and even as measuring instruments became sensitive, the predictions have held true. The statistical nature of it doesn't make it any less predictable, and an experiment proving a different statistical value of an event than QM predicts would be world news.
Exactly. Similarly, an all-powerful being messing with our world doesn't mean we can no longer make predictions. We just end up with a model with hidden variables that change over time.