>Tangentially, if anybody could explain why "Granger causality" is named "causality", I'd appreciate it. From the descriptions I've found, it does not in any way require a causal relationship, and naming it as a type of "causality" would only serve to conflate correlation and causation. I cannot fathom of any reason why it should be named "causation", without assuming intent to confuse.
I'm not a scientist, but I think I know why. Think in terms of the field epidemiology. That field is largely observational. All experiments can formally only come to correlational conclusions but the intent and end goal of the field in spirit is to come to a causative conclusion.
Take for example say if I wanted to answer the question if Sexual intercourse causes people to be infected with HIV. I can't do a causative experiment here as that would involve a double blind test of actually infecting sample groups with HIV via sex. As an epidemiologist my only tools available are correlative experiments where I observe things in the real world.
You see the disconnect here right? Correlative answers are useless, we want to know what "causes" HIV, but the only thing I have as a scientist are correlative experiments. How would I come to a causative conclusion? The answer is I can't. Formally I can only establish correlations then comment about the correlations qualitatively and explain why I think there's an underlying causation underneath.
Well let's say in my experimentation (the observational one) I observe that people were randomly getting HIV before sexual intercourse and after sexual intercourse. That eliminates causality all together because we know that cause MUST come before effect.
However let's say in my experimentation everyone who got HIV, consistently got it AFTER they had sex. That does not eliminate causation... but it doesn't establish it either. However, it does informally bring the results closer to causation. So I won't call it "causation" per se. Just call it something similar "granger causation." Hence the term. That should answer your question.
Again I'm not a scientist, but I can only guess as to why a physicist never encountered these terms. I think it's because you guys only do a special type of correlative experiment where you correlate whether certain observational Data fits a mathematical model. Experimental physics isn't asking causative questions. It's more asking how well does the data fit a particular model. It's purely correlative, there's no drive to answer anything causative here because it doesn't make sense.
When experimental data closely correlates with say Newtons law of motion does it make sense to say Newtons laws caused the data to come out that way? Not really, it sounds off. Also how would you do a double blind test here?
Ultimately causative experiments involve the experimenter inserting himself into the experiment and using himself as the source of causation in order to establish causation itself. In medicine they do this by deliberately giving medicine to a group of people to see the effect and not giving it to another group of people to also see the negative effect in the data. It seems that if you were to do this with physics it would involve you removing the laws of physics from the universe then putting it back to see how it effects the experimental data... not possible and also doesn't fully align with the goal of physics experiments.
Oh, I'm not at all discounting the utility of it. As a statistical tool, being able to exclude either A->B or B->A based on the sign of the offset is really useful as a filter.
> However, it does informally bring the results closer to causation. So I won't call it "causation" per se. Just call it something similar "granger causation."
I think this is the main point where my confusion comes from. Calling it "Granger causation" makes it sound like a special case of causation, causation with a stronger condition tacked on. For something stronger than generic correlation but weaker than causation, it seems like "Granger correlation" would be a better term.
> Experimental physics isn't asking causative questions. It's more asking how well does the data fit a particular model. It's purely correlative, there's no drive to answer anything causative here because it doesn't make sense.
I don't think this is accurate. When asking how well data fits a model, typically the model asserts some causation. For a model predicting "If A, then B", an experiment would set up condition A, and observe whether B also occurs. The role of experimental design is to produce an environment in nothing else could cause B, such that a correlation could only be produced from causation.
(Granted, from an epistemological viewpoint, Descartes could still doubt such a case and call it purely correlative, but that veers from physics to philosophy.)
> When experimental data closely correlates with say Newtons law of motion does it make sense to say Newtons laws caused the data to come out that way?
No, but it would make sense to say that Newton's Laws states that a causal relationship exists. For the statement "An object at rest will stay at rest, unless acted upon by an outside force.", in an environment with no outside force, the model predicts that the effect of "an object stays at rest" is caused by the initial condition of "an object is at rest".
>The role of experimental design is to produce an environment in nothing else could cause B, such that a correlation could only be produced from causation.
Causation is not established from isolated correlation. If I completely isolate two atomic clocks but I start off those atomic clocks at the same time it does not mean one atomic clock, causes the ticking of the other even though their ticks are in sync or they have "granger causation" and can have no other form of influence.
Causation is only established by having the experimenters hand within the experiment itself. If A causes B then I have to turn A on and turn A off randomly and see if B responds as predicted. That is how causation is established. Isolation helps with this but the critical factor here is that experimental intervention is the thing that establishes causation. Remember: Correlation is an observation, causation is an intervention, then subsequent observation to see how the system reacted to the intervention.
Physics experiments focus more on the observational side of things. The causation is more meta. You're not asking if A causes B, more your asking if the concept of "A causing B" even exists.
>No, but it would make sense to say that Newton's Laws states that a causal relationship exists
This doesn't make sense. Newtons laws or physics in general define what causality means. Right? It defines the rules for how one particle "influences" another particle... hence it defines the nature of causality itself.
Do you see the difference here? You're not investigating whether or not A causes B. You're investigating the definition of "causes." Hence it's a observational experiment. It's a much more meta... and as a result becomes purely correlative as we can only observe physics, we can't change or intervene within the experiment itself to change physics.
I'm not a scientist, but I think I know why. Think in terms of the field epidemiology. That field is largely observational. All experiments can formally only come to correlational conclusions but the intent and end goal of the field in spirit is to come to a causative conclusion.
Take for example say if I wanted to answer the question if Sexual intercourse causes people to be infected with HIV. I can't do a causative experiment here as that would involve a double blind test of actually infecting sample groups with HIV via sex. As an epidemiologist my only tools available are correlative experiments where I observe things in the real world.
You see the disconnect here right? Correlative answers are useless, we want to know what "causes" HIV, but the only thing I have as a scientist are correlative experiments. How would I come to a causative conclusion? The answer is I can't. Formally I can only establish correlations then comment about the correlations qualitatively and explain why I think there's an underlying causation underneath.
Well let's say in my experimentation (the observational one) I observe that people were randomly getting HIV before sexual intercourse and after sexual intercourse. That eliminates causality all together because we know that cause MUST come before effect.
However let's say in my experimentation everyone who got HIV, consistently got it AFTER they had sex. That does not eliminate causation... but it doesn't establish it either. However, it does informally bring the results closer to causation. So I won't call it "causation" per se. Just call it something similar "granger causation." Hence the term. That should answer your question.
Again I'm not a scientist, but I can only guess as to why a physicist never encountered these terms. I think it's because you guys only do a special type of correlative experiment where you correlate whether certain observational Data fits a mathematical model. Experimental physics isn't asking causative questions. It's more asking how well does the data fit a particular model. It's purely correlative, there's no drive to answer anything causative here because it doesn't make sense.
When experimental data closely correlates with say Newtons law of motion does it make sense to say Newtons laws caused the data to come out that way? Not really, it sounds off. Also how would you do a double blind test here?
Ultimately causative experiments involve the experimenter inserting himself into the experiment and using himself as the source of causation in order to establish causation itself. In medicine they do this by deliberately giving medicine to a group of people to see the effect and not giving it to another group of people to also see the negative effect in the data. It seems that if you were to do this with physics it would involve you removing the laws of physics from the universe then putting it back to see how it effects the experimental data... not possible and also doesn't fully align with the goal of physics experiments.