Models are about what changes, and what doesn’t
Following on from last week’s post on Principled Bayesian Workflow I want to reflect on how to motivate a model.
The purpose of most models is to understand change, and yet, considering what doesn’t change and should be kept constant can be equally important.
I will go through a couple of models in this post to illustrate this idea. The purpose of the model I want to build today is to predict how much ice cream is sold for different temperatures \((t)\).
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