Signal versus noise

Date created: 2022-11-29

The amount of noise in a signal determines how easy that signal is to detect. For example, when we measure things in the world it is likely that many things affect the outcome of interest, not only our candidate variable that we manipulate.

When we study things in a controleld lab setting we can keep the noise relatively low, but in more applied settings these “noise” variables carry a significant impact. There’s also Divergent causality at play by which small changes can have cascading effects.

In Soft Psychology…

…we do not know (a) the complete list of contextual influences, (b) the function form of context dependency for those influences that we can list, (c) the numerical values of parameters in those function forms that we know or guess, or (d) the values of the context variables if we are so fortunate as to get past Ignorances a-c.