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spurious correlations

correlation is not causation

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don't miss spurious scholar,
where each of these is an academic paper

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Johnny and the second variable is Burglaries in New Hampshire.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #2,496


Johnny's Jinx: Unveiling the Link Between Johnny's Popularity and Burglaries in New Hampshire
It turns out there was a secret underground network of mischievous Johnnys who were all about causing trouble. With fewer Johnnys around, there was a notable decrease in rogue antics and shenanigans. The Johnny Effect strikes again!




What else correlates?
Popularity of the first name Johnny · all first names
Burglaries in New Hampshire · all random state specific

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Per capita consumption of margarine and the second variable is The divorce rate in Maine.  The chart goes from 2000 to 2009, and the two variables track closely in value over that time. Small Image
View details about correlation #5,920


Spreading Love and Margarine: An Examination of the Butter-Splitter Correlation in Maine
Perhaps as people used less margarine, they became less slippery in their relationships. The lack of artificial spread may have kept the couples from buttering each other up, leading to a decrease in overall marital strife. That's the reality when you can't believe it's not butter - it's a recipe for marital success. Alternatively, it could be that as the margarine consumption decreased, so did the overall slickness in the state, leading to fewer instances of partners feeling like they couldn't grip the marriage.




What else correlates?
Per capita consumption of margarine · all food
The divorce rate in Maine · all random state specific

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The distance between Uranus and Earth and the second variable is Electricity generation in Paraguay.  The chart goes from 1980 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,727


Shocking Connection: An Electrifying Correlation Between The Distance Between Uranus and Earth and Electricity Generation in Paraguay
The greater separation allowed for smoother cosmic energy flow, boosting power production in Paraguay.




What else correlates?
The distance between Uranus and Earth · all planets
Electricity generation in Paraguay · all energy

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'cute cats' and the second variable is Amazon's Annual Outbound Shipping Expenditure in Millions.  The chart goes from 2006 to 2016, and the two variables track closely in value over that time. Small Image
View details about correlation #5,231


Fur-real Friends: Exploring the Purr-suasive Connection Between 'Cute Cats' Google Searches and Amazon's Annual Outbound Shipping Expenditure
Because as the search for cute cats increased, so did the demand for cat-themed products. And as more people bought adorable cat toys and accessories on Amazon, the company had to spend more on shipping these purr-chases! After all, it's a whisker-y business!




What else correlates?
Google searches for 'cute cats' · all google searches
Amazon's Annual Outbound Shipping Expenditure in Millions · all weird & wacky

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the 'change my mind' meme and the second variable is The number of pipelayers in West Virginia.  The chart goes from 2006 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,128


Changing Minds, Laying Pipes: Exploring the Correlation Between the 'Change My Mind' Meme and Pipelayers in West Virginia
As the 'change my mind' meme gained traction, it sparked an unforeseen interest in persuasive debate. This led to an influx of individuals honing their argumentative skills, inadvertently creating a boom in the pipeline industry in West Virginia. You could say the meme not only changed minds, but also laid the groundwork for a whole new set of pipelayers!




What else correlates?
Popularity of the 'change my mind' meme · all memes
The number of pipelayers in West Virginia · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Annual US household spending on used cars and the second variable is Solar power generated in Grenada.  The chart goes from 2007 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #5,900


From Exhaust to Electrifying: The Shining Connection between Used Cars and Solar Power
As household spending on used cars goes up, more and more families end up with those 70s and 80s classics that come equipped with a solar panel calculator on the dashboard. As these vintage beauties hit the roads, their sun-soaking power contributes to a surge in solar energy production in Grenada, effectively reviving the island's solar power game one retro ride at a time! It's a shining example of how the path to a greener future might just be paved with a whole lot of old wheels and solar deals!




What else correlates?
Annual US household spending on used cars · all weird & wacky
Solar power generated in Grenada · all energy

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Bachelor's degrees awarded in social services and the second variable is The number of phlebotomists in Florida.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,395


Poking into the Connection between Public Administration and Phlebotomists: A Profound Probing
As the number of public administration and social services graduates rose, there was a corresponding surge in blood drives and health initiatives. This led to a dire need for more phlebotomists in Florida, creating a vein of employment opportunities. It seems like these graduates really know how to *draw* in the workforce demand!




What else correlates?
Bachelor's degrees awarded in social services · all education
The number of phlebotomists in Florida · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Christopher and the second variable is Burglaries in Oklahoma.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #2,487


Christopher's Popularity and Burglaries in Oklahoma: A Rhyming Analysis
When there are fewer Christophers, there are fewer people asking, "Chris, for sure, did you hear something?", ultimately making it harder for burglars to fly under the radar. After all, if you can't trust a Chris, can you really trust anyone?




What else correlates?
Popularity of the first name Christopher · all first names
Burglaries in Oklahoma · all random state specific

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the 'first world problems' meme and the second variable is Google searches for 'vihart'.  The chart goes from 2006 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #5,130


First World Problems: An Analysis of the 'Vihart' Connection
The 'first world problems' meme sparked a wave of interest in trivial, yet relatable issues, priming people to seek out similarly lighthearted content. As a pun-loving mathematician, Vi Hart's unique and quirky approach to math struck a chord with those looking for a prime source of both education and entertainment. It all adds up to a positive correlation between meme popularity and Vi Hart searches – a meme-rable connection, indeed!




What else correlates?
Popularity of the 'first world problems' meme · all memes
Google searches for 'vihart' · all google searches

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Sales of LP/Vinyl Albums and the second variable is Costco Wholesale's stock price (COST).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #1,636


Spinning Wealth: The Groovy Relationship Between Vinyl Sales and Costco Wholesale's Stock Price
The larger album artwork acted as a form of cheap, subconscious store decoration, luring more customers into the aisles. As customers browsed for records, they ended up adding more items to their carts, ultimately boosting Costco's overall sales and stock price.




What else correlates?
Sales of LP/Vinyl Albums · all weird & wacky
Costco Wholesale's stock price (COST) · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Bachelor's degrees awarded in Education and the second variable is The number of proofreaders in Kansas.  The chart goes from 2012 to 2020, and the two variables track closely in value over that time. Small Image
View details about correlation #3,361


Education Bachelor's: More Proofreaders' Fathers? The Kansas Cadence
As the number of Education degrees dropped, there was a significant decline in grammar school attendance. This led to a surplus of unemployed proofreaders in Kansas, who found themselves at a loss for words.




What else correlates?
Bachelor's degrees awarded in Education · all education
The number of proofreaders in Kansas · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Lamont and the second variable is Burglary rates in the US.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,950


Larceny and Lamont: An Analysis of the Link between the Popularity of the First Name Lamont and Burglary Rates in the United States
Fewer people named Lamont means fewer people are saying "Lamont, it's time to steal some stuff" in a sneaky, incriminating tone. And that's a lot less motivation for burglary right there!




What else correlates?
Popularity of the first name Lamont · all first names
Burglary rates in the US · all random state specific

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the 'one does not simply' meme and the second variable is Total comments on Numberphile YouTube videos.  The chart goes from 2011 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #4,995


One Does Not Simply Quantify Internet Culture: Exploring the Correlation Between 'One Does Not Simply' Meme Popularity and Total Comments on Numberphile YouTube Videos.
As the 'one does not simply' meme gained popularity, it sparked a wave of interest in complex and seemingly insurmountable tasks. This indirectly led to an increase in people seeking out Numberphile videos, as they were drawn to the challenge of understanding and conquering the world of numbers and mathematics. In essence, the meme inadvertently became a gateway to a newfound appreciation for numerical discussions, creating a ripple effect that boosted the total comments on Numberphile YouTube videos.




What else correlates?
Popularity of the 'one does not simply' meme · all memes
Total comments on Numberphile YouTube videos · all YouTube

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of judges in Indiana and the second variable is Viewership of The Big Bang Theory.  The chart goes from 2008 to 2019, and the two variables track closely in value over that time. Small Image
View details about correlation #1,859


The Justice Judgement: A Case Study of Indiana Judges and 'The Big Bang Theory' Viewership
As the number of judges in Indiana increased, so did the viewership of "The Big Bang Theory." This is due to the little-known fact that judges have a penchant for high-brow humor and intellectual puns. With their gavel-wielding expertise, they have inadvertently ruled in favor of promoting the show, leading to a surge in viewers who just can't object to its comedic appeal. Clearly, this correlation proves that when it comes to TV preferences, the judicial system holds all the verdicts!




What else correlates?
The number of judges in Indiana · all cccupations
Viewership of "The Big Bang Theory" · all films & actors

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Sunny and the second variable is Solar power generated in Egypt.  The chart goes from 1983 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #1,902


Sunny Side Up: Illuminating the Correlation Between the Name Sunny and Solar Power Generation in Egypt
As the number of Sunnys rose, so did their radiant personalities, leading to an increased demand for positivity. This surge in positivity somehow translated to a boost in solar power generation in Egypt. It's as if their sunny dispositions were literally shining a light on the potential of solar energy. It seems that with more Sunnys around, the future's looking brighter and sunnier in more ways than one!




What else correlates?
Popularity of the first name Sunny · all first names
Solar power generated in Egypt · all energy

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Frozen yogurt consumption and the second variable is Violent crime rates.  The chart goes from 1990 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #5,905


Chilling Crime: The Frozen Yogurt Factor in Violent Crime Rates
As Frozen yogurt consumption decreased, people's brains were no longer chilled to the point of committing heinous acts, leading to a decrease in violent crime rates. The lack of fro-yo-induced inner peace and tranquility meant that individuals were too busy mourning the absence of delicious, creamy goodness to engage in acts of aggression. This sparked a nationwide movement of peaceful protests, where instead of fighting, people hugged it out while licking imaginary cones of their favorite fro-yo flavors. It turns out, the real spooning happened as a form of therapy, and the only things getting whipped were toppings on a swirl of non-violence. In the end, the only thing that was iced out was an entire criminal element, as society collectively realized that the true spoonful of justice was the one they didn’t take from the fro-yo shop.




What else correlates?
Frozen yogurt consumption · all food
Violent crime rates · all random state specific

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is London Gold Prices and the second variable is Customer satisfaction with Whole Foods .  The chart goes from 2007 to 2012, and the two variables track closely in value over that time. Small Image
View details about correlation #5,942


Linking London Gold Prices and Loyal Whole Foods Lovers: A Lighthearted Look at the Connection
As the shiny gold prices rose, so did the moods of the Whole Foods customers, who felt like they struck it rich with their premium groceries. It's like they say, when the bling goes up, so does the zing in your grocery shopping experience!




What else correlates?
London Gold Prices · all weird & wacky
Customer satisfaction with Whole Foods · all weird & wacky

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of movies Mila Kunis appeared in and the second variable is POSCO Holdings' stock price (PKX).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,882


The Mila Kunis Effect: A Reel Connection to Stock Reel-itivity
As Kunis's filmography expanded, so did the appeal of POSCO's holdings, leading to a Kutis-effect on the stock price. It seems her performances weren't just box office hits, but also stock exchange sensations. Perhaps her stellar acting was the real steel driving force behind POSCO's market success, proving that in the world of finance, she truly is the Kunis-essential asset.




What else correlates?
The number of movies Mila Kunis appeared in · all films & actors
POSCO Holdings' stock price (PKX) · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Per capita consumption of margarine and the second variable is The divorce rate in Maine.  The chart goes from 2000 to 2009, and the two variables track closely in value over that time. Small Image
View details about correlation #5,920


Spreading Love and Margarine: An Examination of the Butter-Splitter Correlation in Maine
Perhaps as people used less margarine, they became less slippery in their relationships. The lack of artificial spread may have kept the couples from buttering each other up, leading to a decrease in overall marital strife. That's the reality when you can't believe it's not butter - it's a recipe for marital success. Alternatively, it could be that as the margarine consumption decreased, so did the overall slickness in the state, leading to fewer instances of partners feeling like they couldn't grip the marriage.




What else correlates?
Per capita consumption of margarine · all food
The divorce rate in Maine · all random state specific

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Why this works

  1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Fun fact: the chart used on the wikipedia page to demonstrate data dredging is also from me. I've been being naughty with data since 2014.
    Instead of starting with a hypothesis and testing it, I instead tossed a bunch of data in a blender to see what correlations would shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably no direct connection between these variables, despite what the AI says above. Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. You will often see trend-lines form. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A naive p-value calculation does not take this into account. You will calculate a lower chance of "randomly" achieving the result than represents reality.

    To be more specific: p-value tests are probability values, where you are calculating the probability of achieving a result at least as extreme as you found completely by chance. When calculating a p-value, you need to assert how many "degrees of freedom" your variable has. I count each year (minus one) as a "degree of freedom," but this is misleading for continuous variables.

    This kind of thing can creep up on you pretty easily when using p-values, which is why it's best to take it as "one of many" inputs that help you assess the results of your analysis.
  4. Y-axes doesn't start at zero: I truncated the Y-axes of the graphs above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. If you click on any of the charts that abuse this, you can scroll down to see a version that starts at zero.
  5. Confounding variable: Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.
  6. Outliers: Some datasets here have outliers which drag up the correlation. In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

    Because this page is automatically generated, I don't know whether any of the charts displayed on it have outliers. I'm just a footnote. ¯\_(ツ)_/¯
    I intentionally mishandeled outliers, which makes the correlation look extra strong.
  7. Low n: There are not many data points included in some of these charts. You can do analyses with low ns! But you shouldn't data dredge with a low n.
    Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.


Pro-tip: click on any correlation to see:

Project by Tyler Vigen
emailme@tylervigen.com · about · subscribe


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