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People pointing out correlation != causation are missing the point. CORRELATION AN IMPORTANT FACTOR HERE. Say you are caring for a population of elderly peopl

People pointing out correlation != causation are missing the point. CORRELATION AN IMPORTANT FACTOR HERE. Say you are caring for a population of elderly people and you need to triage who to give more stability support (say carers, walking aids, etc). Do a grip strength test! The correlation is important, it doesn't matter if the correlation is causal in nature. I challenge you dear reader, the next time there's a science article presented, to think about something more interesting to say than "correlation != causation". I challenge you to find useful ways that correlations can be harnessed.

funklute 5y ago
On the other hand, people repeating "correlation != causation" ad nauseam is, in my opinion, one of the great success stories of science communication. Proving causation is the singular most difficult general problem across many scientific disciplines, and at the same time our brains are hardwired to conflate correlation with causation. I think that it's simply awesome that so many people are aware of this issue nowadays.
- nathias 5y ago
  People mindlessly parroting anything is not a great success of anything, especially not of science communication. There is also no hardwired conflation of correlation with causation, it's just a general jumping to conclusions error.
  - cornel_io 5y ago
    Social science, health, and psychological research is 90% bad because of the correlation = causation fallacy, especially articles that claim to have "controlled for" X, Y, and Z. Even after controlling most of these studies still incorrectly suggest causation. So by default, people are correct to mindlessly parrot this, even if they don't understand when they're wrong or misapplying the maxim.
    - nathias 5y ago
      ah yes, if they could only remember that correlation !== causation, 90% of social science, health and psychological research would become good instead of bad also the irony is amazing
  - funklute 5y ago
    > There is also no hardwired conflation of correlation with causation, it's just a general jumping to conclusions error. There is plenty of literature in the neuroscience and psychology fields that show we are biased towards finding patterns where there are none. Evolutionarily speaking, this is easy to understand. Better to run away one extra time, than getting eaten by a lion. The latter is less likely to pass on their genes. > People mindlessly parroting anything is not a great success of anything, especially not of science communication. I respectfully disagree. Appreciating the subtleties of causality is beyond what you can expect from most lay people. Even many of my machine learning colleagues can get tripped up by this stuff. So even if it is simplistic, I still think it is useful that people at least understand that causality is difficult.
    - rosetremiere 5y ago
      Isn't "finding patterns where there are none" more akin to finding correlation in the first place, than to making the correlation->causation jump?
      - funklute 5y ago
        Well, both really. But in practice, erroneously identifying correlations doesn't tend to be quite so big a problem as conflating correlation with causation. The former is easy to address with strict data recording, whereas the latter is more of a conceptual thing, and requires some deeper thinking that often goes against intuition.
    - nathias 5y ago
      Excess pattern recognition isn't conflating correlation for causation.
      - funklute 5y ago
        No, but conflating correlation for causation _is_ excess pattern recognition.
        5y ago
- deltaonefour 5y ago
  It's not that difficult. It is "difficult" in the sense that many of the experiments to prove causation are cost prohibitive. But coming up with the experimental parameters needed to verify causation are trivial. In fact, ALL clinical trials for all medicine are designed to verify causation. It's that straightforward. It just happens to cost a lot of money. Think about that. Why are clinical trials much more expensive than say the experiment correlating grip strength and life span? What is the differentiating factor? This is the key. If you don't understand why/how clinical trials verify causation and what exactly is the differentiator between experiments that only correlate things then you don't truly understand the dichotomy between correlation and causation. Most people don't understand it. Even the programming crowd. I even met data scientists who don't know about it.
kashunstva 5y ago
While the correlation here turns grip strength into a useful diagnostic sign to stratify patients into risk groups for possible intervention (assistive devices etc.) the authors go on to advise the reader on improving their grip strength, on the implied hypothesis that doing so will reduce the adverse outcomes enumerated earlier in the article. Possibly the effectiveness of that sort of intervention is already know but the whiff of “correlation != causation” for me was only around that question. Possibly that too is already known; I don’t know that literature. But the authors don’t draw that connection and therefore leave the question of correlation and causation open at least from the perspective of their recommended interventions.
krisoft 5y ago
> I challenge you dear reader, the next time there's a science article presented, to think about something more interesting to say than "correlation != causation". I challenge the writers of articles to write articles which doesn’t walk into this problem. > Say you are caring for a population of elderly people and you need to triage who to give more stability support (say carers, walking aids, etc). Do a grip strength test! But that’s not what the article says, does it? “The single most effective set of muscles you can work to extend your life is in your hands.” This is the first line of the article, and it is completely unsupported by data or studies. So how are we missing the point? > The correlation is important, it doesn't matter if the correlation is causal in nature. But it does matter! If it is causal then we should give hand strengthening devices to everyone. We should have fun hand strength competitions in social settings to encurage everyone to care about their grip strength. If it is not casual then we can use it as a diagnostic indicator precisely as you say. In that case it is actually a bad idea to encourage people to strenghten their grip, because that might break the correlation between ill-health and grip strength, thus ruining the diagnostic indicator without helping anyone to live a healthier life. How can you say it doesn’t matter if the correct reaction differs this much?
deltaonefour 5y ago
Actually the term is technically incorrect. Correlation DOES IMPLY causation somewhere. It's just the causative source may not be part of the experimental parameters. Think about it. Hand grip and longer lifespan. For those two things to correlate they MUST at the very least be connected by one or several causative sources. There is no other logical explanation for it. It's just this source isn't part of the experimental parameters. On the other side of the coin if two things Do NOT correlate, it heavily implies no causative connection at all.

funklute 5y ago

On the other hand, people repeating "correlation != causation" ad nauseam is, in my opinion, one of the great success stories of science communication. Proving causation is the singular most difficult general problem across many scientific disciplines, and at the same time our brains are hardwired to conflate correlation with causation. I think that it's simply awesome that so many people are aware of this issue nowadays.

nathias 5y ago
People mindlessly parroting anything is not a great success of anything, especially not of science communication. There is also no hardwired conflation of correlation with causation, it's just a general jumping to conclusions error.
- cornel_io 5y ago
  Social science, health, and psychological research is 90% bad because of the correlation = causation fallacy, especially articles that claim to have "controlled for" X, Y, and Z. Even after controlling most of these studies still incorrectly suggest causation. So by default, people are correct to mindlessly parrot this, even if they don't understand when they're wrong or misapplying the maxim.
  - nathias 5y ago
    ah yes, if they could only remember that correlation !== causation, 90% of social science, health and psychological research would become good instead of bad also the irony is amazing
- funklute 5y ago
  > There is also no hardwired conflation of correlation with causation, it's just a general jumping to conclusions error. There is plenty of literature in the neuroscience and psychology fields that show we are biased towards finding patterns where there are none. Evolutionarily speaking, this is easy to understand. Better to run away one extra time, than getting eaten by a lion. The latter is less likely to pass on their genes. > People mindlessly parroting anything is not a great success of anything, especially not of science communication. I respectfully disagree. Appreciating the subtleties of causality is beyond what you can expect from most lay people. Even many of my machine learning colleagues can get tripped up by this stuff. So even if it is simplistic, I still think it is useful that people at least understand that causality is difficult.
  - rosetremiere 5y ago
    Isn't "finding patterns where there are none" more akin to finding correlation in the first place, than to making the correlation->causation jump?
    - funklute 5y ago
      Well, both really. But in practice, erroneously identifying correlations doesn't tend to be quite so big a problem as conflating correlation with causation. The former is easy to address with strict data recording, whereas the latter is more of a conceptual thing, and requires some deeper thinking that often goes against intuition.
  - nathias 5y ago
    Excess pattern recognition isn't conflating correlation for causation.
    - funklute 5y ago
      No, but conflating correlation for causation _is_ excess pattern recognition.
      - 5y ago
deltaonefour 5y ago
It's not that difficult. It is "difficult" in the sense that many of the experiments to prove causation are cost prohibitive. But coming up with the experimental parameters needed to verify causation are trivial. In fact, ALL clinical trials for all medicine are designed to verify causation. It's that straightforward. It just happens to cost a lot of money. Think about that. Why are clinical trials much more expensive than say the experiment correlating grip strength and life span? What is the differentiating factor? This is the key. If you don't understand why/how clinical trials verify causation and what exactly is the differentiator between experiments that only correlate things then you don't truly understand the dichotomy between correlation and causation. Most people don't understand it. Even the programming crowd. I even met data scientists who don't know about it.

kashunstva 5y ago

While the correlation here turns grip strength into a useful diagnostic sign to stratify patients into risk groups for possible intervention (assistive devices etc.) the authors go on to advise the reader on improving their grip strength, on the implied hypothesis that doing so will reduce the adverse outcomes enumerated earlier in the article. Possibly the effectiveness of that sort of intervention is already know but the whiff of “correlation != causation” for me was only around that question. Possibly that too is already known; I don’t know that literature. But the authors don’t draw that connection and therefore leave the question of correlation and causation open at least from the perspective of their recommended interventions.

krisoft 5y ago

> I challenge you dear reader, the next time there's a science article presented, to think about something more interesting to say than "correlation != causation". I challenge the writers of articles to write articles which doesn’t walk into this problem. > Say you are caring for a population of elderly people and you need to triage who to give more stability support (say carers, walking aids, etc). Do a grip strength test! But that’s not what the article says, does it? “The single most effective set of muscles you can work to extend your life is in your hands.” This is the first line of the article, and it is completely unsupported by data or studies. So how are we missing the point? > The correlation is important, it doesn't matter if the correlation is causal in nature. But it does matter! If it is causal then we should give hand strengthening devices to everyone. We should have fun hand strength competitions in social settings to encurage everyone to care about their grip strength. If it is not casual then we can use it as a diagnostic indicator precisely as you say. In that case it is actually a bad idea to encourage people to strenghten their grip, because that might break the correlation between ill-health and grip strength, thus ruining the diagnostic indicator without helping anyone to live a healthier life. How can you say it doesn’t matter if the correct reaction differs this much?

deltaonefour 5y ago

Actually the term is technically incorrect. Correlation DOES IMPLY causation somewhere. It's just the causative source may not be part of the experimental parameters. Think about it. Hand grip and longer lifespan. For those two things to correlate they MUST at the very least be connected by one or several causative sources. There is no other logical explanation for it. It's just this source isn't part of the experimental parameters. On the other side of the coin if two things Do NOT correlate, it heavily implies no causative connection at all.