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Is there anything causal as in Pearl’s graphical models or the potential outcome framework?

• refrigerator 7y ago
  Afraid not, sorry — right now it's more of a Monte Carlo simulation tool. Can see how the name might be a bit misleading!
  • 03199618 7y ago
    If causal.app does not make causal statements of that kind, which kind of causal statements can it make then?
    • _delirium 7y ago
      Not involved with causal.app, but I see it as going the other way as far as causality goes. Pearl-style models are trying to infer causation from data. Here, you give it a causal model that encapsulates how you think a scenario works (which variables affect the outcome, how, and a range of likely values for them), and it simulates your model to give you ranges of likely outcomes, plus some other things like sensitivity analysis (which variables impact likely outcomes the most). I like the comparison they make to spreadsheet models. It's that style of modeling but with Monte Carlo simulations, so you can put ranges instead of single numbers in cells, and the ranges propagate through the model to output ranges.
      • refrigerator 7y ago
        Couldn't have put it better myself :)