Correlation is Not Causation

Posted on February 26, 2007  Comments (9)

Why so much medical research is rot:

People born under the astrological sign of Leo are 15% more likely to be admitted to hospital with gastric bleeding than those born under the other 11 signs. Sagittarians are 38% more likely than others to land up there because of a broken arm. Those are the conclusions that many medical researchers would be forced to make from a set of data presented to the American Association for the Advancement of Science by Peter Austin of the Institute for Clinical Evaluative Sciences in Toronto. At least, they would be forced to draw them if they applied the lax statistical methods of their own work to the records of hospital admissions in Ontario, Canada, used by Dr Austin.

Dr Austin, of course, does not draw those conclusions. His point was to shock medical researchers into using better statistics, because the ones they routinely employ today run the risk of identifying relationships when, in fact, there are none. He also wanted to explain why so many health claims that look important when they are first made are not substantiated in later studies.

As I said in, Seeing Patterns Where None Exists: “Page 8 of Statistics for Experimenters by George Box, William Hunter (my father) and Stu Hunter (no relation) shows a graph of the population (of people) versus the number of storks which shows a high correlation. “Although in this example few would be led to hypothesize that the increase in the number of storks caused the observed increase in population, investigators are sometimes guilty of this kind of mistake in other contexts.’”

9 Responses to “Correlation is Not Causation”

  1. Curious Cat Science and Engineering Blog » Poor Reporting and Unfounded Implications
    January 1st, 2009 @ 8:31 am

    [...] Correlation is not causation. And reporting of the form, “1 time this happened” and so I report it as though it is some relevant fact, is sad. Take any incident that happened and then state random traits you want to imply there is some relevant link to (blue eyes, red hair, people that watch IT Crowd, people that bought a banana yesterday, tall, overweight, did poorly in math…) and most people will know you are ignorant. [...]

  2. Curious Cat Management Improvement Blog » Statistics for Experimenters in Spanish
    January 5th, 2009 @ 10:25 am

    Read a bit more can find a bit more on the Spanish edition… Estadística para Investigadores Diseño, innovación y descubrimiento Segunda edición.

  3. Curious Cat Management Blog » Friday Fun: Correlation
    March 6th, 2009 @ 9:58 am

    scientific understanding in comic form.

  4. Anonymous
    May 20th, 2009 @ 6:32 am

    Your article is interesting. Correlation is not causation. And reporting of the form, “1 time this happened” and so I report it as though it is some relevant fact, is sad. Take any incident that happened and then state random traits you want to imply there is some relevant link to (blue eyes, red hair, people that watch IT Crowd, people that bought a banana yesterday, tall, overweight…

  5. Curious Cat Science Blog » The Value of Displaying Data Well
    September 1st, 2009 @ 12:20 pm

    Anscombe’s quartet comprises four datasets that have identical simple statistical properties, yet are revealed to be very different when inspected graphically…

  6. The Theory of Knowledge in Deming’s Management System: How Do We Know What We Know? » Curious Cat Management Blog
    September 21st, 2011 @ 9:36 am

    I took on the task of explaining the theory of knowledge, as one article in a four part series looking at the four components of Dr. Deming’s System of Profound Knowledge…

  7. Does Diet Soda Result in Weight Gain? » Curious Cat Science and Engineering Blog
    October 29th, 2012 @ 10:26 am

    [...] am skeptical of purely correlational results. You can try to have similar subsets of people but that is actually hard and if you allow for [...]

  8. Medical Study Findings too Often Fail to Provide Us Useful Knowledge » Curious Cat Science and Engineering Blog
    July 24th, 2013 @ 11:15 am

    [...] literacy is part of the problem (especially related to things like interactions, variability, correlation that isn’t evidence of causation…). Large incentives that encourage biased research results are a huge [...]

  9. Statistical Errors in Medical Studies » Curious Cat Science and Engineering Blog
    February 25th, 2014 @ 6:22 am

    […] Insights for Scientists and Engineers, Data Can’t Lie – But People Can be Fooled, Correlation is Not Causation, Simpson’s Paradox). And also have posted about reasons for systemic reasons for medical […]

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