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10 Correlations That Are Not CausationsBY NICHOLAS GERBIS SCIENCE | SCIENCE QUESTIONS

Browse the article 10 Correlations That Are Not Causations

The classic example of correlation not equaling causation can be found with ice cream and -- murder. That is, the ratesof violent crime and murder have been known to jump when ice cream sales do. But, presumably, buying ice creamdoesn't turn you into a killer (unless they're out of your favorite kind?). © CARLO ALLEGRI/REUTERS/CORBIS

You would think by now that we could say unequivocally what causes what. But the questionof cause, which has haunted science and philosophy from their earliest days, still dogs ourheels for numerous reasons. Humans are evolutionarily predisposed to see patterns andpsychologically inclined to gather information that supports pre-existing views, a trait knownas confirmation bias. We confuse coincidence with correlation and correlation with causality.

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For A to cause B, we tend to say that, at a minimum, A must precede B, the two must covary(vary together), and no competing explanation can better explain the covariance of A and B.Taken alone, however, these three requirements cannot prove cause; they are, as philosopherssay, necessary but not su먀icient. In any case, not everyone agrees with them.

Speaking of philosophers, David Hume argued that causation doesn't exist in any provablesense. Karl Popper and the Falsificationists maintained that we cannot prove a relationship,only disprove it, which explains why statistical analyses do not try to prove a correlation;instead, they pull a double negative and disprove that the data are uncorrelated, a processknown as rejecting the null hypothesis.

With such considerations in mind, scientists must carefully design and control theirexperiments to weed out bias, circular reasoning, self-fulfilling prophecies and hiddenvariables. They must respect the requirements and limitations of the methods used, draw fromrepresentative samples where possible, and not overstate their results.

Ready to read about 10 instances where that wasn't so easy?

The Trouble With Henry (and Hawthorne)

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Researchers investigating worker productivity on the factory floor in the early 20th century discovered the Hawthornee㈴ㄠect, or the idea that participant knowledge of an experiment can influence its results. CHRISTOPHER FURLONG/GETTYIMAGES NEWS

People are a pain to research. They react not only to the stimulus you're studying but also tothe experiment itself. Researchers today try to design experiments to control for such factors,but such was not always the case.

Take the Hawthorne Works in Cicero, Ill. In a series of experiments from 1924-1932, researchersstudied the worker productivity e먀ects associated with altering the Illinois factory'senvironment, including changing light levels, tidying up the place and moving workstationsaround. Just when they thought they were on to something, they noticed a problem: Theobserved increases in productivity flagged almost as soon as the researchers le䀀 the works,indicating that the workers' knowledge of the experiment, not the researchers' changes, hadfueled the boost. Researchers still call this phenomenon the Hawthorne E㈴ㄠect.

A related concept, the John Henry e㈴ㄠect, occurs when members of a control group try to beatthe experimental group by kicking their e먀orts into overdrive. They need not know about theexperiment; they need only see one group receive new tools or additional instruction. Like thesteel-driving man of legend, they want to prove their capabilities and earn respect [sources:Saretsky; Vogt].

Always Bet on Black?

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If red just came up seven times in a row on the roulette wheel, would you be more likely to bet on red or black beforethat eighth turn? TONY4URBAN/ISTOCK/THINKSTOCK

The titular characters of Tom Stoppard's film "Rosencrantz and Guildenstern Are Dead" beginthe film ba먀led, confused and finally frightened as each of 157 consecutive flips of a coincomes up heads. Guildenstern's explanations of this phenomenon range from time loops to "aspectacular vindication of the principle that each individual coin, spun individually, is as likelyto come down heads as tails ... "

Evolution wired humans to see patterns, and our ability to properly process that urge seems toshort-circuit the longer we spend gambling. We can rationally accept that independent eventslike coin flips keep the same odds no matter how many times you perform them. But we alsoview those events, less rationally, as streaks, making false mental correlations betweenrandomized events. Viewing the past as prelude, we keep thinking the next flip ought to betails.

Statisticians call this the gambler's fallacy, aka the Monte Carlo fallacy, a䀀 er a particularlyillustrative example occurring in that famed Monaco resort town. During the summer of 1913,bettors watched in increasing amazement as a casino's roulette wheel landed on black 26

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times in a row. Inflamed by the certainty that red was "due," the punters kept plunking downtheir chips. The casino made a mint [sources: Lehrer; Oppenheimer and Monin; Vogt].

The Hot Hand and the Monkey's Paw

Superstitions take all forms in sports, like smooching your bowling ball. © RUSSELL UNDERWOOD/CORBIS

No discussion of streaks, magical thinking or false causation would be complete without a flipthrough the sports pages. Stellar sports seasons arise from such a mysterious interplay offactors -- natural ability, training, confidence, the occasional X factor -- that we imaginepatterns in performance, even though studies repeatedly reject streak shooting and"successful" superstitions as anything more than imaginary.

The belief in streaks or slumps implies that success "causes" success and failure "causes"failure or, perhaps more reasonably, that variation in some common factor, such asconfidence, causes both. But study a䀀 er study fails to bear this out [sources: Gilovich et al.;Tversky and Gilovich]. The same holds true for superstitions, although that did not stop theCleveland Indians' Kevin Rhomberg from refusing to make right turns while on the field, orprevent Ottawa Senators center Bruce Gardiner from dunking his hockey stick in the toilet tobreak the occasional slump [source: Trex].

http://science.howstuffworks.com/innovation/science-questions/10-correlations-that-are-not-causations11.htmhttp://web.princeton.edu/sites/opplab/papers/oppenheimermonin09.pdfhttp://science.howstuffworks.com/innovation/science-questions/10-correlations-that-are-not-causations11.htmhttp://entertainment.howstuffworks.com/5-biggest-winning-streaks-in-baseball-history.htmhttp://psych.cornell.edu/sites/default/files/Gilo.Vallone.Tversky.pdfhttp://bayes.bgsu.edu/honors/the_hot_hand.pdfhttp://people.howstuffworks.com/fishing-superstition.htmhttp://online.wsj.com/news/articles/SB124640412099376447



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The sophomore slump, too, typically arises from a too-good first year. Performance swingstend to even out in the long run, a phenomenon statisticians call regression toward themean. In sports, this averaging out is aided by the opposition, which adjusts to counter thenew player's successful skill set.

Hormonal Imbalance

The story of hormone replacement therapy, once widely used to treat symptoms of menopause, turned out not to beso straightforward a吠㤷er all. CHRISTOPHER PATTBERY/ISTOCK/THINKSTOCK

Randomized controlled trials are the gold standard in statistics, but sometimes -- inepidemiology, for example -- ethical and practical considerations force researchers to analyzeavailable cases. Unfortunately, such observational studies risk bias, hidden variables and,worst of all, a study group that might not reflect the population as a whole. Studying arepresentative sample is vital; it allows researchers to apply results to people outside of thestudy, like the rest of us.

A case in point: hormone replacement therapy (HRT). Beyond treating symptoms associatedwith menopause, it was once hailed for potentially reducing coronary heart disease (CHD)risk, thanks to a much-ballyhooed 1991 observational study [source: Stampfer and Colditz].

http://health.howstuffworks.com/sexual-health/male-reproductive-system/new-fathers-testosterone.htmhttp://health.howstuffworks.com/human-body/systems/circulatory/heart.htmhttp://www.sciencedirect.com/science/article/pii/009174359190006P



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But later randomized controlled studies, including the large-scale Women's Health Initiative,revealed either a negative relationship, or a statistically insignificant one, between HRT andCHD [sources: Lawlor et al.; New York Times].

Why the di먀erence? For one thing, women who use HRT tend to come from highersocioeconomic strata and receive better quality of diet and exercise – a hidden explanatoryrelationship for which the observational study failed to fully account [source: Lawlor et al.].

Super Bowl Stock Market Shu㈴ㄠle

When John Elway and his fellow Broncos won the Super Bowl two years running in 1998 and 1999, the Super Bowl-stock market connection fell apart. DOUG COLLIER/AFP/GETTY IMAGES

In 1978, sports reporter and columnist Leonard Koppett mocked the causation-correlationconfusion by wryly suggesting that Super Bowl outcomes could predict the stock market. Itbackfired: Not only did people believe him, but it worked -- with frightful frequency.

The proposal went as follows: If one of the 16 original National Football League teams -- thosein existence before the NFL's 1966 merger with the American Football League -- won the SuperBowl, the stock market would close higher that following year than it did the preceding Dec. 31.

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If a former AFL team won, it would go down [sources: Koppett; Koppett; Koppett; Koppett;Zweig].

From 1967 to 1978, Koppett's system went 12 for 12; up through 1997, it boasted a 95 percentsuccess rate. It stumbled in 1998 and 1999, when AFL alums the Denver Broncos won and themarket went up [sources: Koppett; Koppett; Koppett; Koppett].

Some have argued that the pattern exists, driven by belief; it works, they say, because investorsbelieve it does, or because they believe that other investors believe it. This notion, thoughclever in a regressive sort of way, hardly explains the 12 years of successful correlationspredating Koppett's article. Others argue that a more relevant pattern lies in the stock market'slarge-scale upward trend, barring some short-term major and minor fluctuations, and the factthat an original NFL team won every Super Bowl from 1984 to 1998 [source: Norris].

Big Data, Little Clarity

Target is just one of many companies combing through big data to boost sales. © JOHN GRESS/CORBIS

Big data -- the process of looking for patterns in data sets so large they resist traditionalmethods of analysis -- rates big buzz in the boardroom these days [source: Arthur]. But isbigger always better?

It's a rule that's drummed into most researchers in their first stats class: When encountering asea of data, resist the urge to go on a fishing expedition. Given enough data, patience andmethodological leeway, correlations are almost inevitable, if unethical and largely useless.

A䀀 er all, the mere correlation between two variables does not imply causation; nor does it, inmany cases, point to much of a relationship. For one thing, researchers cannot use statisticalmeasures of correlation willy-nilly; each contains certain assumptions and limitations thatfishing expeditions too o䀀 en ignore, to say nothing of the hidden variables, sampling problemsand flaws in interpretation that can gum up a poorly designed study.

Granted, big data has its uses. Inventory control thrives on discovering purchasing patterns,however mysterious their underlying causes. To take a somewhat creepy example, Target hasused purchasing patterns to identify pregnant customers and then send them targetedcoupons [sources: Duhigg; Hill; Taylor]. So enjoy that rewards card -- and 10 percent o먀 yourprenatal vitamins -- but don't expect too much out of big data in the causality department.

http://sportsillustrated.cnn.com/vault/article/magazine/MAG1094842/index.htmhttp://www.dartmouth.edu/~chance/chance_news/for_chance_news/ChanceNews13.04/SportingNews.pdfhttp://www.dartmouth.edu/~chance/chance_news/for_chance_news/ChanceNews13.04/2002stocks.pdfhttp://online.wsj.com/public/resources/documents/koppett.pdfhttp://blogs.wsj.com/marketbeat/2011/01/28/super-bowl-indicator-the-secret-history/http://sportsillustrated.cnn.com/vault/article/magazine/MAG1094842/index.htmhttp://www.dartmouth.edu/~chance/chance_news/for_chance_news/ChanceNews13.04/SportingNews.pdfhttp://www.dartmouth.edu/~chance/chance_news/for_chance_news/ChanceNews13.04/2002stocks.pdfhttp://online.wsj.com/public/resources/documents/koppett.pdfhttp://www.nytimes.com/1997/01/24/business/the-super-bowl-predicts-the-market-and-vice-versa.htmlhttp://www.forbes.com/sites/lisaarthur/2013/08/15/what-is-big-data/http://health.howstuffworks.com/medicine/modern-treatments/unethical-medicine.htmhttp://health.howstuffworks.com/pregnancy-and-parenting/pregnancy/fertility/pregnant-while-breastfeeding.htmhttp://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=1&_r=2&hp&http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/http://insights.wired.com/profiles/blogs/big-data-s-slippery-issue-of-causation-versus-correlation



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Minimum Wage Equals Maximum Unemployment

Striking fast-food workers are joined by supporters, union members and activists at a rally in New York City's FoleySquare to demand an increase in the minimum wage to $15 an hour. © ANDREW LICHTENSTEIN/CORBIS

Any issue dealing with money is bound to be deeply divisive and highly politicized, andminimum wage increases are no exception. The arguments are varied and complex, butessentially one side contends that a higher minimum wage hurts businesses, which drivesdown job availability, which hurts the poor. The other side responds that there's little evidencefor this claim, and that the 3.6 million Americans working at or below minimum wage, whichsome argue is not a living wage, would benefit from such an increase. They argue that,adjusted for inflation, the federal minimum wage ($7.25 per hour in December 2013) hastobogganed downhill for the past 40 years [sources: Bureau of Labor Statistics; Irwin].

As George Bernard Shaw reportedly quipped, "If all the economists were laid end to end,they'd never reach a conclusion," and the minimum-wage debate seems to bear that out[source: Ridgers. For every analyst who says minimum wage increases drive jobs away there isanother who argues against such a correlation [sources: Baskaya and Rubinstein; Card andKrueger].

In the end, both sides share a fundamental problem, namely, the abundance of anecdotalevidence many of their talking heads rely on for support. Secondhand stories and cherry-picked data make for weak tea in any party, even when presented in pretty bar charts.

Breakfast Beats Obesity, Dinner Denies Drugs

The family that eats dinner together stays o㈴ㄠ drugs together. Er, not quite. HEMERA TECHNOLOGIES/ABLESTOCK.COM/THINKSTOCK

Between books, drugs and surgeries, weight loss in the United States is a $20-billion-per-yearindustry, with 108 million Americans bellying up to the weight-loss bar each year [source: ABCNews]. Not surprisingly, weight loss studies -- good, bad or ugly -- get a lot of press in the U.S.

Take the popular idea that eating breakfast beats obesity, a sugar-frosted nugget derived fromtwo main studies: One, a 1992 Vanderbilt University randomized controlled study, showed thatreversing normal breakfast habits, whether by eating or not eating, correlated with weight loss;

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the other, a 2002 observational study by the National Weight Control Registry, correlatedbreakfast-eating with successful weight-losers -- which is not the same as correlating it withweight loss [sources: Brown et al.; O'Connor; Schlundt et al.; Wyatt et al.].

Unfortunately, the NWCR study failed to control for other factors -- or, indeed, establish anycausal connection from its correlation. For example, a person who wants to lose weight mightwork out more, or eat breakfast, or go whole-hog protein, but without an experimental designcapable of dialing in causal links, such behaviors amount to nothing more than commonly co-occurring characteristics [sources: Brown et al.; O'Connor].

A similar problem plagues the numerous studies linking family dinners with a decreased risk ofdrug addiction for teens. Although attractive for their simple, appealing strategy, these studiesfrequently fail to control for related factors, such as strong family connections or deep parentalinvolvement in a child's life [source: Bialik].

The Suicidal Sex

Researchers studying suicide occurring across genders have to be aware that suicidal men and women may reach fordi㈴ㄠerent weapons, thus a㈴ㄠecting their outcomes. INGRAM PUBLISHING/THINKSTOCK

We o䀀 en hear it bandied about that men, especially young men, are more likely to commitsuicide than are women. In truth, such statements partake of empirical generalization -- theact of making a broad statement about a common pattern without attempting to explain it --and mask a number of known and potential confounding factors.

Take, for example, the fact that women make three times as many suicide attempts as men.How then can a higher correlation exist between the opposite sex and suicide? The answer liesin success rate, influenced by di먀erences in methodology: Women resort to pills, while mentend to favor guns [source: O'Connell].

Even if we could dispose of such confounding factors, the fact would remain that maleness,per se, is not a cause. To explain the trend, we need to instead identify factors common to men,or at least suicidal ones. The same point applies to the comparatively high rates of suicidereported among divorced men. Divorce doesn't cause men to commit suicide; if anything, thecausal variable hides among related factors, such as isolation, depression, a sense ofpowerlessness, financial stress or custody loss [sources: Kposowa; Kposowa; Reuters].

Vaccination Vexation

http://www.ncbi.nlm.nih.gov/pubmed/24004890http://well.blogs.nytimes.com/2013/09/10/myths-surround-breakfast-and-weight/http://ajcn.nutrition.org/content/55/3/645.abstract?sid=2ef145a4-5324-40d0-bead-e669e51756d1http://onlinelibrary.wiley.com/doi/10.1038/oby.2002.13/pdfhttp://health.howstuffworks.com/wellness/diet-fitness/weight-loss/real-way-to-lose-belly-fat.htmhttp://www.ncbi.nlm.nih.gov/pubmed/24004890http://well.blogs.nytimes.com/2013/09/10/myths-surround-breakfast-and-weight/http://science.howstuffworks.com/life/inside-the-mind/human-brain/addiction.htmhttp://blogs.wsj.com/numbersguy/what-family-dinners-can-and-cant-do-for-teens-1302/http://animals.howstuffworks.com/animal-facts/animals-commit-suicide.htmhttp://people.howstuffworks.com/strict-gun-laws-less-crime.htmhttp://www.nbcnews.com/health/male-suicide-growing-concern-tough-times-1C9456424http://jech.bmj.com/content/57/12/993.fullhttp://jech.bmj.com/content/54/4/254.fullhttp://www.fact.on.ca/news/news0003/yn000314.htm



Pediatrician with a vial of MMR vaccine and a 15-month-old boy. In the U.S., the Advisory Committee on ImmunizationPractices recommends a two-dose vaccine schedule for measles, mumps, rubella vaccines for children, with the firstdose at age 12-15 months and the second at age 4-6 years. © TEK IMAGE/SCIENCE PHOTO LIBRARY/CORBIS

No correlation/causation list would be complete without discussing parental concerns overvaccination safety, rooted in the idea, popularized by celebrities like Jenny McCarthy, thatmeasles, mumps and rubella (MMR) vaccinations are causally linked to autism spectrumdisorders. Despite the medical community debunking the 1998 Andrew Wakefield paper thatinspired the idea, and despite subsequent studies showing no causal link, even with multiplevaccinations, some parents remain fearful of an autism connection or other vaccine-relateddangers [sources: The Lancet; Park; Si‱ⴠerlin; Szabo].

While it's true that no vaccine is 100 percent harmless, the belief in this causal link arisesmainly from natural parental concern, burdened by confusion, fueled by anecdotal evidenceand influenced by confirmation bias, or "if I hadn't believed it I wouldn't have seen it." Furtherfueling the confusion is the fact that parents and doctors tend to recognize autism symptomslate, around the ages that children receive many vaccinations. In actuality, autism onset isquite complex and follows more than one pattern. Indeed, studies now show that onset canbegin as early as 6-12 months [sources: CDC; Johnson and Schultz; Mandell et al.; NIH;Ozono‱ⴠ et al.].

It's no harmless misunderstanding. In 2011, Time magazine reported that 13 percent of parentsskipped, delayed or split up their children's vaccinations; in some rural areas, that number shotup to between 20 and 50 percent. Meanwhile, 15 years a䀀 er this panic began, medical centersreported outbreaks of whooping cough and measles. Whether that correspondence iscoincidental, correlative or causal is well worth considering [sources: O'Connor; Park; Park].

Author's Note: 10 Correlations That Are Not CausationsAs much as I abhor poor experimental design, blind reliance on statistics and sensationalisticscience reporting, it's worth mentioning that strong correlations, while not alone su먀icient toprove cause, o䀀 en point to areas worth investigating. Clearly, by "correlations" I don't meanautocorrelations, confounding variables or other artifacts of bad design or poorly understoodmethodological requirements and constraints; nevertheless, maybe the Internet can lay o먀 the"correlation does not imply causation" slogan for a bit, or at least grow a bit more selective inits application.

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Related ArticlesAre stupid people happier?Do countries with stricter gun laws really have less crime or fewer homicides?Is there a correlation between gas prices and obesity?Is there a correlation between happiness and carbon emissions?

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