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spurious correlations

correlation is not causation

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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 Stevie and the second variable is Netflix's stock price (NFLX).  The chart goes from 2003 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #3,268


Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX
The soothing sound of the name Stevie resulted in a nation-wide decrease in stress levels, leading to more people unwinding with Netflix, and therefore driving up the stock price. Plus, there's a rumor that Stevie Wonder's secret side gig is writing Netflix original series, and everyone's loving them.




What else correlates?
Popularity of the first name Stevie · all first names
Netflix's stock price (NFLX) · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of art directors in Arkansas and the second variable is Yearly peak of NYSE composite index.  The chart goes from 2003 to 2012, and the two variables track closely in value over that time. Small Image
View details about correlation #2,581


Art Directing the Stock Market: An Unconventional Connection between Arkansas and the NYSE Composite Index
As the number of art directors in Arkansas increased, so did the demand for their creative services. This led to a spike in advertising and marketing campaigns, which captured the public's attention in innovative ways. As consumer confidence and spending rose, the companies behind these artistic endeavors saw record profits, driving up stock prices and ultimately boosting the NYSE composite index. It's as if the state's newfound artistic flair painted a masterpiece of economic growth, creating a bull market fueled by a blend of creativity and commerce.




What else correlates?
The number of art directors in Arkansas · all cccupations
Yearly peak of NYSE composite index · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Average views of SciShow Space YouTube videos and the second variable is Popularity of the 'willy wonka' meme.  The chart goes from 2014 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #5,013


The Milky Way: Exploring the Correlation Between SciShow Space YouTube Video Views and the Golden Ticket to 'Willy Wonka' Meme Popularity
It turns out, as people watched fewer space videos, their interest in all things 'wonka' dwindled. It seems there's a hole in the market for space-themed memes, and without those astronomical numbers, the 'willy wonka' meme just couldn't rocket to the same heights of popularity. It's a classic case of when the SciShow Space views go down, the willy wonka meme just doesn't have the same universal appeal. In other words, without the stellar content from SciShow Space, the 'willy wonka' meme couldn't maintain its Milky Way of popularity. It's a meme-orable connection, for sure!




What else correlates?
Average views of SciShow Space YouTube videos · all YouTube
Popularity of the 'willy wonka' meme · all memes

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GMO use in corn grown in Minnesota and the second variable is Pirate attacks globally.  The chart goes from 2009 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #2,052


Grain and Rum: Unearthing the Nexus Between GMO Corn Cultivation in Minnesota and Global Pirate Raids
As GMO use in Minnesota decreased, the corn stalks started resembling traditional masts, confusing the pirates. This led to a global decrease in pirate attacks as they couldn't distinguish between actual ships and the corn fields.




What else correlates?
GMO use in corn grown in Minnesota · all food
Pirate attacks globally · all weird & wacky

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'how much wood can a woodchuck chuck' and the second variable is Kerosene used in Venezuela.  The chart goes from 2004 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #4,245


How Much Kerosene for a Woodchuck Spleen: The Correlation Between Google Searches for 'How Much Wood Can a Woodchuck Chuck' and Kerosene Usage in Venezuela
As the woodchucks realized the futility of their chucking efforts, they shifted their focus to alternative energy sources, leading to a surplus of kerosene in Venezuela. One-liner: It's a case of supply and demand being influenced by woodchuck contemplation!




What else correlates?
Google searches for 'how much wood can a woodchuck chuck' · all google searches
Kerosene used in Venezuela · all energy

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 Tom Hanks appeared in and the second variable is The number of special education teachers in Georgia.  The chart goes from 2012 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,857


Forrest Grump: The Impact of Tom Hanks' Movie Appearances on Special Education Teachers in Georgia
As the number of Tom Hanks movies climbs, more people are inspired to pursue careers in the film industry. This leads to a higher demand for special effects and production crew members. With Georgia being a popular filming location, the need for specialized education in these fields also grows, prompting an increase in special education teachers to meet the unique learning needs of future film professionals.




What else correlates?
The number of movies Tom Hanks appeared in · all films & actors
The number of special education teachers in Georgia · 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 Katherine and the second variable is Burglaries in Hawaii.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #3,951


Breaking and Entering Katherine: An Unconventional Connection Between Name Popularity and Burglaries in Hawaii
As the saying goes, "Kat's out of the bag," and it seems that also applies to burglars in Hawaii! With fewer Katherines around, there were less Kat burglars trying to pull off heists in the sunny state. It appears that the name Katherine was previously a common alias for cat burglars with a penchant for pilfering pineapples. However, with this name falling out of favor, it seems the purr-petrators have also disappeared, leading to a decrease in burglaries. It's a feline mystery, but it looks like Hawaii can rest easy knowing that the Katherine connection has been pawsitively purr-vented!




What else correlates?
Popularity of the first name Katherine · all first names
Burglaries in Hawaii · 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 Master's degrees awarded in Education and the second variable is US bank failures.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,718


Masters in Money Matters: Mapping the Marvelous Mistake in the Marriage of Education and Economic Meltdown
As the number of Master's degrees awarded in Education decreased, there were fewer people able to comprehend the concept of "fractional reserve banking." This led to a decrease in risky financial practices and ultimately contributed to a lower rate of US bank failures. After all, you can't spell "financial stability" without "STEM education" - or so the bankers now realize!




What else correlates?
Master's degrees awarded in Education · all education
US bank failures · all weird & wacky

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is American cheese consumption and the second variable is Alphabet's stock price (GOOGL).  The chart goes from 2005 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #5,884


The Big Cheese Squeeze: How American Cheese Consumption Swings Alphabet's Stock Price
As American cheese consumption melted, so did the hearts of investors, causing a ripple effect in the stock market. As more people savored the idea of a cheesy investment, the demand for Alphabet's stock increased, leading to a gouda rise in their stock price. It seems like the secret to their success was simply to brie-lieve in the power of dairy deliciousness!




What else correlates?
American cheese consumption · all food
Alphabet's stock price (GOOGL) · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Albuquerque and the second variable is Google searches for 'who is prince william'.  The chart goes from 2008 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #2,863


A Breath of Fresh Heir: Investigating the Relationship Between Air Pollution in Albuquerque and Google Searches for 'Who is Prince William'
As air pollution in Albuquerque increased, more people sought refuge indoors. With limited entertainment options, they turned to browsing the internet. This led to an uptick in searches for 'who is prince william' as a way to pass the time. This is a prime example of how environmental factors can directly impact our curiosity about the British royal family.




What else correlates?
Air pollution in Albuquerque · all weather
Google searches for 'who is prince william' · all google searches

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is UFO sightings in New Mexico and the second variable is Patents granted in the US.  The chart goes from 1975 to 2020, and the two variables track closely in value over that time. Small Image
View details about correlation #3,099


The New Mexico Extraterrestrial Effect: Unveiling The Otherworldly Influence on Patent Granting in the United States
The influx of intergalactic inspiration in New Mexico led to an explosion of creative scientific ideas, spurring a wave of groundbreaking inventions and technological advancements. It turns out, alien innovation is the real secret behind some of our greatest patented achievements!




What else correlates?
UFO sightings in New Mexico · all random state specific
Patents granted in the US · 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 Michael Caine appeared in and the second variable is Votes for the Democratic Presidential candidate in Maryland.  The chart goes from 1976 to 2020, and the two variables track closely in value over that time. Small Image
View details about correlation #5,851


In Caine Sight: The Astonishing Correlation Between Michael Caine's Film Appearances and Democratic Votes in Maryland
Michael Caine's unmatchable on-screen charm and wit inadvertently wooed the residents of Maryland, prompting them to lean towards the charismatic and confident demeanor often exhibited by Democratic candidates. As Caine graced the silver screen, his subtle influence seeped into the subconscious of Marylanders, swaying their political preferences towards the party that exuded a similar aura of sophistication and poise. His prolific presence in films became the reel reason behind the unexpected surge in Democratic votes in the state, proving that in the game of politics, as in the art of acting, sometimes, it's simply a matter of mastering the Caine effect.




What else correlates?
The number of movies Michael Caine appeared in · all films & actors
Votes for the Democratic Presidential candidate in Maryland · all elections

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Associates degrees awarded in Music and dance and the second variable is Solar power generated in Costa Rica.  The chart goes from 2011 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,810


Harmonious Degrees and Radiant Beams: A Melodious Study of Music and Dance Degrees and Solar Power in Costa Rica
As the number of music and dance graduates boogied on up, they created a high-energy, solar-powered dance revolution. These bright sparks brought a whole new meaning to the term "solar panel" as they tapped into renewable rhythms, proving that when it comes to groovy moves and solar grooves, the sky's the limit!




What else correlates?
Associates degrees awarded in Music and dance · all education
Solar power generated in Costa Rica · all energy

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 Aubrey and the second variable is Exxon Mobil's stock price (XOM).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #4,112


Aubrey's Energizing Effect: An Examination of the Relationship Between the Popularity of the Name Aubrey and Exxon Mobil's Stock Price
Parents naming their kids Aubrey are investing more in fancy cars, leading to an increase in gas consumption and therefore, an uptick in demand for Exxon Mobil's products. Looks like the name Aubrey is driving more than just social media popularity!




What else correlates?
Popularity of the first name Aubrey · all first names
Exxon Mobil's stock price (XOM) · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is US household spending on processed fruits and the second variable is GMO use in cotton in Louisiana.  The chart goes from 2000 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #2,848


Feeling Ginned Up: The Cotton Connection Between GMOs and Processed Fruit Spending in US Households
As households spent less on processed fruits, there was a decrease in fruit sticker production. This led to a nationwide sticker shortage. To fill the sticker gap, cotton in Louisiana was genetically modified to produce sticker-like tags, but it unexpectedly led to a decrease in GMO use in cotton.




What else correlates?
US household spending on processed fruits · all weird & wacky
GMO use in cotton in Louisiana · all food

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Des Moines and the second variable is The number of postmasters in Iowa.  The chart goes from 2003 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #2,461


Air-Mail Pollution: A Postmasterful Analysis of the Relationship Between Air Pollution in Des Moines and the Number of Postmasters in Iowa
As the air cleared in Des Moines, it seems the postmasters weren't the only ones feeling a bit "un-stationed." It's possible that with cleaner air, postal workers and machinery were operating more efficiently, leading to a reduced need for postmasters statewide. It's a classic case of smog being the only thing propping up those postage-oriented job positions!




What else correlates?
Air pollution in Des Moines · all weather
The number of postmasters in Iowa · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Biomass power generated in Philippines and the second variable is Google searches for 'avocado toast'.  The chart goes from 2009 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #1,705


Smashing Avocado Toast and Flipping Biomass: An Unlikely Connection
The avocado trees were loving the sustainable energy vibes and producing extra delicious avocados for the toast!




What else correlates?
Biomass power generated in Philippines · all energy
Google searches for 'avocado toast' · all google searches

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the 'expanding brain' meme and the second variable is Votes for Democratic Senators in Mississippi.  The chart goes from 2006 to 2020, and the two variables track closely in value over that time. Small Image
View details about correlation #4,852


Mirthful Memes and Mississippi's Senatorial Selections: A Playful Probing of the Expanding Brain Phenomenon
As the 'expanding brain' meme gained traction, it sparked a surge in cognitive activity, leading Mississippi Democrats to make the biggest brain move of all: casting their votes for Senators who aligned with their values. It's like they say, when the expanding brain meme goes up, Democratic turnout in Mississippi goes up even more!




What else correlates?
Popularity of the 'expanding brain' meme · all memes
Votes for Democratic Senators in Mississippi · all elections

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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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