Correlation is Not Causation
Posted on February 26, 2007 Comments (9)
Why so much medical research is rot:
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.'”
Categories: Health Care, quote, Research, Science, Students
Tags: data, quote, scientific inquiry
9 Responses to “Correlation is Not Causation”
Leave a Reply
RSS Feed
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. […]
January 5th, 2009 @ 10:25 am
Read a bit more can find a bit more on the Spanish edition… EstadÃstica para Investigadores Diseño, innovación y descubrimiento Segunda edición.
March 6th, 2009 @ 9:58 am
scientific understanding in comic form.
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…
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…
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…
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 […]
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 […]
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 […]