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Hey folks, I'm one of the authors of the post. Would love to hear people's thoughts, and happy to answer any questions :) If you liked this, then I'd definitel

Hey folks, I'm one of the authors of the post. Would love to hear people's thoughts, and happy to answer any questions :) If you liked this, then I'd definitely recommend reading "The Flaw of Averages" by Sam Savage. It talks about this stuff in a lot more detail, and the style is very entertaining — not at all what you'd expect from a statistics book.

03199618 7y ago
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 :)
sails 7y ago
This is great. I think you're well positioned to help people understand this very important concept in a familiar way. Have you thought to incorporate the "Minimise Maximum Regret" concept? I suppose it is quite an opinionated strategy, but it is a very interesting approach to decisioning, and supposedly leads to robust decisions.
sails 7y ago
In the visualisation it would be very useful if the "best/worst" cases included the inputs that were relevant to make that happen. It is somewhat obvious, but would drive the point home that should X & Y occur, you'd be left in scenario Z.

03199618 7y ago

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 :)

sails 7y ago

This is great. I think you're well positioned to help people understand this very important concept in a familiar way. Have you thought to incorporate the "Minimise Maximum Regret" concept? I suppose it is quite an opinionated strategy, but it is a very interesting approach to decisioning, and supposedly leads to robust decisions.

sails 7y ago

In the visualisation it would be very useful if the "best/worst" cases included the inputs that were relevant to make that happen. It is somewhat obvious, but would drive the point home that should X & Y occur, you'd be left in scenario Z.