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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 Stevie and the second variable is Amazon.com's stock price (AMZN).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,883


Stevie Takes the Stock Stage: A Quantitative Analysis of the Relationship Between the Popularity of the Name 'Stevie' and Amazon's Stock Price
As the popularity of the name Stevie rises, more and more parents are subconsciously drawn to buy baby products. This leads to an unexpected surge in demand for diapers, baby formula, and children's books on Amazon. The sudden baby boom market on Amazon causes a ripple effect, prompting investors to pump money into the company, thus driving up its stock price. Who would have thought that the name Stevie could have such a 'baby' effect on Amazon's financial success!




What else correlates?
Popularity of the first name Stevie · all first names
Amazon.com's stock price (AMZN) · all stocks

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 Beau and the second variable is Brown-Forman's stock price (BF.B).  The chart goes from 2002 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #4,253


Beau the Name, BF.B the Stock: A Beau-tiful Connection?
The more babies named Beau, the higher the demand for cute monogrammed baby bibs, leading to a spike in sales for Brown-Forman's subsidiary, Baby Bourbon Bibs Inc. This unexpected revenue boost sent Brown-Forman's stock price soaring, much to the bewilderment of the financial world.




What else correlates?
Popularity of the first name Beau · all first names
Brown-Forman's stock price (BF.B) · 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 social services and the second variable is The number of gas plant operators in Alabama.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,317


From Degrees to Deeds: Public Administration and Social Services Graduates Leading Gas Plant Operaters to Fate's Beats
As the number of Bachelor's degrees in Public administration and social services rose, so did the enthusiasm for making a *career switch*. It seems that the graduates were well-versed in *managing gas emissions* and had a *knack for handling pressure* in the industry. This unexpected correlation suggests that when it comes to running gas plants, a background in public administration and social services might just be the *fuel for success*.




What else correlates?
Bachelor's degrees awarded in social services · all education
The number of gas plant operators in Alabama · 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 'slaps roof of car' meme and the second variable is Divorce rates in the United Kingdom.  The chart goes from 2006 to 2012, and the two variables track closely in value over that time. Small Image
View details about correlation #5,009


Roof-Raising Resonance: Exploring the Tenuous Link between the 'Slaps Roof of Car' Meme and Divorce Rates in the United Kingdom
As the 'slaps roof of car' meme lost its appeal, spouses across the UK found themselves refraining from using meme references during arguments, leading to improved communication and fewer reasons to split. Looks like the meme's declining popularity paved the way for marital harmony. Remember, a meme in time saves matrimony!




What else correlates?
Popularity of the 'slaps roof of car' meme · all memes
Divorce rates in the United Kingdom · 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 Breweries in the United States and the second variable is Solar power generated in Peru.  The chart goes from 2000 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #3,384


Brewing Up a Solar Storm: The Surprising Relationship Between U.S. Breweries and Solar Power Generation in Peru
As the number of breweries in the United States increased, so did the demand for beer. This led to a surge in hop production, creating a need for more agricultural labor in Peru. With more people working outdoors, the Peruvian solar power industry experienced a boost in productivity from all the extra sunshine beer as the real power source!




What else correlates?
The number of Breweries in the United States · all food
Solar power generated in Peru · 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 Library science and the second variable is Ticket sales for Oakland Athletics games.  The chart goes from 2012 to 2019, and the two variables track closely in value over that time. Small Image
View details about correlation #2,724


Dewey Decimals and Dingers: Exploring the Relationship Between Library Science Bachelor's Degrees and Oakland Athletics Ticket Sales
As the number of library science graduates rises, so does the world's appreciation for organization and categorization. This heightened sense of order subtly influences baseball fans, leading to a greater desire to see the players neatly 'cataloged' on the field. It's like the Dewey Decimal System of entertainment - everyone just wants to 'check out' a game! Plus, with their finely honed research skills, these grads may have uncovered the hidden 'book' on how to win at baseball, making the Athletics games a hot ticket!




What else correlates?
Bachelor's degrees awarded in Library science · all education
Ticket sales for Oakland Athletics games · all sports

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Dried manure used for fertilizer in the US and the second variable is Customer satisfaction with Target.  The chart goes from 2004 to 2015, and the two variables track closely in value over that time. Small Image
View details about correlation #1,622


Smell in the Air: Exploring the Fertilizing Effects of Dried Manure on Customer Satisfaction with Target
As the dried manure supply dwindled, farmers had to get creative with their fertilizer choices. This led to an increase in the use of unconventional fertilizers, ultimately affecting the aroma around Target stores. In other words, as the manure decreased, so did the 'manure-ity' of the shopping experience at Target. This correlation stinks!




What else correlates?
Dried manure used for fertilizer in the US · all weird & wacky
Customer satisfaction with Target · 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 transit police in Texas and the second variable is Google searches for 'how to do magic'.  The chart goes from 2004 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,285


The Magic of Public Transit: Conjuring the Connection Between Transit Police Numbers in Texas and Google Searches for 'how to do magic'
Without transit police around, there were fewer people to saw in half during their magic acts, leading to a decline in interest in magic tricks and illusions. Guess the real disappearing act is the interest in magic!




What else correlates?
The number of transit police in Texas · all cccupations
Google searches for 'how to do magic' · all google searches

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 Michigan and the second variable is Enbridge's stock price (ENB).  The chart goes from 2002 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #2,697


Amaizeing Connections: Analyzing the GMO Effect on Corn and Its Impact on Enbridge's Stock Price
As the GMO corn in Michigan proliferated, it developed a secret ability to emit tiny amounts of positive energy, inadvertently boosting the stock price of Enbridge. It seems their corny connection led to a-maize-ing results for the stock market! Corn-gratulations, GMOs!




What else correlates?
GMO use in corn grown in Michigan · all food
Enbridge's stock price (ENB) · all stocks

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 journalism and the second variable is Solar power generated in Malta.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #1,874


Shine a Light on the Connection: Master's Degrees in Communication, journalism, and related programs and Solar Power Generation in Malta
As more people mastered the art of communication, they were able to convince the sun to shine brighter and longer specifically on Malta. It turns out, the real power of journalism and communication lies in influencing celestial bodies!




What else correlates?
Master's degrees awarded in journalism · all education
Solar power generated in Malta · 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 Sarah and the second variable is Remaining Forest Cover in the Brazilian Amazon.  The chart goes from 1987 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #4,241


The Sarah Effect: Surprising Association of Sarah's Popularity and Sizable Amazonian Arboreal Attendance
As the popularity of the name Sarah waned, so too did the number of Sarahaus trees, a rare and beloved species found only in the Brazilian Amazon. Local legend has it that these trees whispered the name "Sarah" every time a woodcutter approached, leading to a swift and unintentional protection of the remaining forest cover. Remember, every time a Sarah loses its 'h', a Sarahaus tree loses its leaves!




What else correlates?
Popularity of the first name Sarah · all first names
Remaining Forest Cover in the Brazilian Amazon · 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 'matt levine' and the second variable is The number of college administrators in Ohio.  The chart goes from 2004 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,895


The (Non) Noble Nexus: Navigating the Nexus between Google Searches for 'Matt Levine' and The Number of college administrators in Ohio
As more people delved into the world of finance through Matt Levine's writings, they were inspired to apply their newfound knowledge in unexpected ways. This led to a surge in individuals creating their own financial theories, prompting colleges in Ohio to hire additional administrators to review and integrate these unconventional ideas into their academic programs. It's a case of Matt-ematical expansion in the education sector!




What else correlates?
Google searches for 'matt levine' · all google searches
The number of college administrators in Ohio · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Difference in score of Steinfeld Cup Final teams and the second variable is Tickets Sold for the Top Movie of the Year.  The chart goes from 2001 to 2013, and the two variables track closely in value over that time. Small Image
View details about correlation #2,401


The Big Score: Analyzing the Reel Connection Between Steinfeld Cup Final Teams and Box Office Booms
As the difference in score decreased, fans of the losing team were feeling more down, leading to a decrease in overall enthusiasm. This disparity in team performance really affected the box office, creating a net loss in ticket sales for the top movie of the year. We can say it really threw a 'fowl' on the whole movie-going experience.




What else correlates?
Difference in score of Steinfeld Cup Final teams · all sports
Tickets Sold for the Top Movie of the Year · all films & actors

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is Biomass power generated in Lithuania.  The chart goes from 2001 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #1,709


Spreading Power: Uncovering the Butterly Connection Between Butter Consumption and Biomass Power Generation in Lithuania
The extra butter intake led to an increase in flatulence, creating more methane for biomass power generation in Lithuania. Looks like butter really is the greener spread!




What else correlates?
Butter consumption · all food
Biomass power generated in Lithuania · 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 Tristen and the second variable is Asthma attacks in American children.  The chart goes from 1997 to 2019, and the two variables track closely in value over that time. Small Image
View details about correlation #2,596


The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children
Fewer Tristens meant less air was being taken up by dramatic sighs, thereby reducing the overall respiratory distress in the country.




What else correlates?
Popularity of the first name Tristen · all first names
Asthma attacks in American children · all weird & wacky

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is How 'hip and with it' LockPickingLawyer YouTube video titles are and the second variable is Popularity of the 'y u no' meme.  The chart goes from 2015 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #5,142


LockPickingLawyer's Clickbait Capers and the 'Y U No' Meme: A Hip Connection Analysis
As the 'y u no' meme started to fade, it took with it the very essence of hipness, leaving the LockPickingLawyer feeling oddly less trendy with each video he titled. It seems the meme magic was the key to his coolness all along. Remember, when it comes to internet culture, memes may come and go, but the adept art of lock picking is always on trend!




What else correlates?
How 'hip and with it' LockPickingLawyer YouTube video titles are · all YouTube
Popularity of the 'y u no' meme · all memes

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 Legal professions and studies and the second variable is Cenovus Energy's stock price (CVE).  The chart goes from 2011 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,906


Associates Awards in Adjudication: An Analysis of the Alleged Impact on Cenovus Energy's Stock Price
As the number of legal associates dwindled, there was a sharp rise in courtroom antics. With fewer qualified professionals, the legal system became a full-blown circus. Amidst all the chaos, Cenovus Energy found themselves in the middle of a ridiculous lawsuit. It turns out, the case revolved around the rights to a long-lost, highly sought-after oil well, which was accidentally built upon by a clown academy. The whole debacle not only drained Cenovus Energy of resources but also left investors juggling their priorities, ultimately leading to a slippery slope for their stock price.




What else correlates?
Associates degrees awarded in Legal professions and studies · all education
Cenovus Energy's stock price (CVE) · all stocks

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 Franklin and the second variable is Season rating of Two and a Half Men.  The chart goes from 2004 to 2015, and the two variables track closely in value over that time. Small Image
View details about correlation #1,403


Franklin, My Dear Watson: Exploring the Fickle Nature of Names and TV Fame in 'Two and a Half Men' Season Ratings
Every time someone named Franklin tuned in to watch, they couldn't help but laugh at all the puns and dad jokes, creating a subconscious laugh track that boosted the ratings. Additionally, the influx of Franklins sparked a new fan theory that the show was secretly an allegory for Benjamin Franklin's life, leading to renewed interest and speculation. The name Franklin just had a magnetic pull on the success of the show, like a quirky sitcom magnet.




What else correlates?
Popularity of the first name Franklin · all first names
Season rating of "Two and a Half Men" · all films & actors

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 laundry and cleaning supplies and the second variable is Google searches for 'flights to Antarctica'.  The chart goes from 2004 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #1,045


The Dirty Laundry of Travel Aspirations: Exploring the Relationship between US Household Spending on Cleaning Supplies and Google Searches for 'Flights to Antarctica'
As US households spent more on laundry and cleaning supplies, they became obsessed with achieving the freshest, cleanest scent possible. This obsession extended to wanting the ultimate fresh air experience, leading people to search for flights to Antarctica, known for its crisp, pure air. After all, if your laundry smells like a refreshing polar breeze, why not experience the real deal, right? And who wouldn't want to see penguins rocking their spotless tuxedos in person? Maybe it's time for a new marketing slogan: "Antarctica: Because Freshness Matters!"




What else correlates?
Annual US household spending on laundry and cleaning supplies · all weird & wacky
Google searches for 'flights to Antarctica' · all google searches

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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