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  • Have you ever wondered how related the number of people

  • that drown in pools each year is

  • to how many Nicolas Cage films are released at the same year?

  • Turns out the 66.6% correlation between the two

  • or how about the fact that there is 99.26% correlation between the divorce rate in Maine

  • and the per capita consumption margarine

  • or %99.79 correlation between spending on science, space and technology

  • and the number of suicides by hanging, strangulation and suffocation.

  • Just because there is a correlation between two variables doesn't mean

  • that one causes the other.

  • This assumption is a logical fallacy

  • and yet we are drawn to headlines like

  • "People who have more sex make the most money."

  • Unfortunately "this" does not always equal "that".

  • Even though it may look like it cheese consumption probably isn't related to

  • how many people died tangled in their bedsheets.

  • But sometimes isn't so obvious.

  • Numerous studies found that menopausal women taking hormone replacement therapy

  • had a lower than average incidence of heart disease.

  • Leading doctors to believe that hormone replacement could protect against heart disease.

  • However when women underwent randomized controlled trials

  • they found that hormone replacement therapy actually increased the risk of heart disease.

  • When the original data was finally reanalysed, it was found that

  • women who took the therapy were of a higher socio-economic group

  • with a better diet and exercise regime.

  • This was the real cause behind decreased risk of heart disease.

  • Another case found that those who used nightlights as a kid were more likely to develop myopia.

  • But there is actually strong link between parenatal myopia

  • and the development of child myopia so in reality myopic parents simply more likely

  • to leave light on in their child's bedroom.

  • These are examples of lurking variable where A does not cause B

  • but rather C causes them both.

  • It's a little like taking people who have lung cancer

  • and thinking "Hey, they all carrying lighters in their pockets

  • so lighters must cause cancer."

  • While not realizing that smoking is the confounding variable.

  • And scientists worked hard in their studies to try avoid this.

  • But it gets worse when popular media takes advantage of these potentially coincidental correlations.

  • And one study about chocolate weight-loss connection was actually designed as

  • a way to expose how science reporting can be sensationalized.

  • A science writer with a PhD in Microbiology ran a real clinical trial

  • where participants were assigned to three groups.

  • A low carb diet, a low carb diet plus a 1.5 ounce chocolate bar

  • and the group that maintains their regular diet.

  • At the end of three weeks, the chocolate group did lose the most weight

  • but the journalists consciously used terrible science.

  • He used 15 participants and measured 18 different measurements including weight loss

  • cholesteral, sleep quality, blood pressure, well-being etc

  • and when you use small group of people and measure a large number of things

  • you're pretty much guaranteed to get a statistically significant results

  • which Veritasium has an amazing video on here if you wanna check out.

  • The result could have easily been something different

  • such as chocolate correlates to lower blood pressure.

  • If the study had been peer-reviewed by other researchers

  • it would've been called out

  • so instead he submitted it to a journal for a fee 600 Euros

  • making up a fake instutition name.

  • The Institute of diet and health.

  • He then sent out a press release to dozens of the media publications

  • and very quickly getting slim by chocolate was front page news.

  • With that in mind however we can't dismiss correlation entirely.

  • Correlative evidence is an essential part of science.

  • Double-blind studies are not always possible or ethical to run

  • often leaving correlation is the best evidence available.

  • When every possible causative relationship is systematically explored

  • correlation can be use as a powerful tool for assessing cause and effect relationships

  • and progressing science even further.

  • Big thanks to Tyler Vigen for providing his charts on this interesting correlations.

  • You can check out his website or his book "Spurious Correlations" for more peculiar examples

  • and subscribe for more weekly science videos every Thursday.

Have you ever wondered how related the number of people

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