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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 Violet and the second variable is Fossil fuel use in Equatorial Guinea.  The chart goes from 1980 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #3,022


Violet's Vortex: A Correlative Analysis of the Name Popularity and Fossil Fuel Use in Equatorial Guinea
As more and more people were named Violet, the demand for violet-colored cars skyrocketed. This led to a global shortage of violet automotive paint, prompting intensified drilling for the rare violet fossil fuel in Equatorial Guinea. Remember, when it comes to naming trends, the fuel-ty's the limit!




What else correlates?
Popularity of the first name Violet · all first names
Fossil fuel use in Equatorial Guinea · 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 Camden and the second variable is UFO sightings in Florida.  The chart goes from 1975 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #3,011


Camden's Cosmic Connection: Correlating the Popularity of the Name Camden with UFO Sightings in Florida
As the name Camden rose in popularity, more parents were subconsciously drawn to space-themed nurseries, leading to an influx of UFO decor sales. This sudden spike in households with intergalactic aesthetics created confusion for passing UFOs, who mistook the Sunshine State for a cosmic pit stop. It seems like little Camdens were truly out of this world, sparking a nursery trend that was simply 'alien' to Florida's usual style.




What else correlates?
Popularity of the first name Camden · all first names
UFO sightings in Florida · 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 Parks & Recreation and the second variable is Alphabet's stock price (GOOGL).  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,298


Par-Fecting the Market: A Link Between Master's Degrees in Parks & Recreation and GOOGL Stock Price
As the number of Parks & Recreation Master's degree holders rose, so did the demand for alphabetically organized activities in public spaces. This led to a surge in people seeking out leisurely pursuits like birdwatching, creating a higher need for Google searches. The correlation between these educated park planners and the stock price of Alphabet was in-tents, because when it comes to boosting Google, they really knew how to *recreate* some positive outcomes.




What else correlates?
Master's degrees awarded in Parks & Recreation · all education
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 Kerosene used in El Salvador and the second variable is Google searches for 'attacked by a squirrel'.  The chart goes from 2004 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #1,069


Burning Questions: The Kerosene Connection - A Squirrely Correlation?
As kerosene usage decreased in El Salvador, there were fewer open flames to attract the attention of the power-hungry squirrel overlords, leading to a decrease in their organized attacks on unsuspecting individuals. Without the allure of fiery chaos, the squirrels decided to pursue more peaceful activities like acorn gathering and competitive tree climbing, leaving the people of El Salvador with a slightly lower risk of encountering vengeful, flame-loving squirrels. Remember, a squirrel's plans can be easily derailed when there are no kerosene-fueled sparks flying to ignite their bushy-tailed ambitions!




What else correlates?
Kerosene used in El Salvador · all energy
Google searches for 'attacked by a squirrel' · all google searches

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 Nicolas Cage appeared in and the second variable is The number of transportation security screeners in North Dakota.  The chart goes from 2012 to 2022, and the two variables track closely in value over that time. Small Image
View details about correlation #5,837


Nicolas Cage on Stage: The Movie Craze and North Dakota's Screeners' Raise
The heightened state of unease over the possibility of a 'Con Air' sequel resulted in an influx of security personnel. It just goes to show, when it comes to Nic Cage, the need for increased security is always 'Raising Arizona.'




What else correlates?
The number of movies Nicolas Cage appeared in · all films & actors
The number of transportation security screeners in North Dakota · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'im not even mad' and the second variable is Popularity of the 'whip nae nae' 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 #5,952


I'm Not Even Mad, Said Rad, So Whip, Nae-Nae: A Correlational Study of Google Searches and Internet Memes
As people's ability to stay chill and not get worked up decreased, they were no longer in the right mindset to whip and/or nae nae with the same level of enthusiasm. The lack of 'not even mad' energy was a major hit to the whip nae nae community, leading to a decline in its overall coolness. Less zen led to less swag, and the meme just couldn't keep its groove without that tranquil vibe.




What else correlates?
Google searches for 'im not even mad' · all google searches
Popularity of the 'whip nae nae' meme · all memes

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 Harmony and the second variable is Associates degrees awarded in Agriculture and natural resources.  The chart goes from 2011 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,129


The Harmony Name Game: A Melodic Analysis of Associates Degrees in Agriculture and Natural Resources
As more people were named Harmony, a wave of peaceful and cooperative vibes swept through the agricultural community, leading to a surge in knowledge sharing and mutual support among aspiring agronomists and environmentalists. It's as if the fields were harmonically cultivated for success!




What else correlates?
Popularity of the first name Harmony · all first names
Associates degrees awarded in Agriculture and natural resources · all education

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Bloomberg Money Stuff articles about insider trading and the second variable is Banco Bilbao Vizcaya Argentaria's stock price (BBVA).  The chart goes from 2014 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #5,892


The Insider Scoop: Money Stuff Articles and Banco Bilbao Vizcaya Argentaria's Stock Price Dance
As the number of articles about insider trading on Bloomberg Money Stuff decreased, investors began to suspect that something fishy was going on at Banco Bilbao Vizcaya Argentaria (BBVA). With less information about sneaky stock shenanigans, confidence in the bank's transparency also decreased, leading to a sell-off of BBVA shares. Who knew that a lack of white-collar crime news could lead to a bank account that's feeling a little blue?




What else correlates?
Bloomberg Money Stuff articles about insider trading · all weird & wacky
Banco Bilbao Vizcaya Argentaria's stock price (BBVA) · all stocks

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 Ticket prices at North American movie theaters.  The chart goes from 2001 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #1,604


Popcorn or Pop-Myth: A Butter Truth Serum or a Margarine of Error? Examining the Correlation Between Butter Consumption and Ticket Prices at North American Movie Theaters
As people started slathering on more buttery toppings at the movie theater, there was a sudden surge in demand for extra napkins. This napkin shortage led to an increase in production costs for napkin manufacturers. To offset these rising expenses, the movie theaters had to raise ticket prices in order to cover the cost of the now luxurious, butter-absorbing, premium napkins. Remember, it's not just about the buttery popcorn anymore - it's about the whole buttery experience!




What else correlates?
Butter consumption · all food
Ticket prices at North American movie theaters · 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 'like a boss' meme and the second variable is Google searches for 'how to cut own hair'.  The chart goes from 2006 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #4,994


Hair Today, Like a Boss Tomorrow: The Curious Connection Between 'Like a Boss' Meme Popularity and DIY Haircut Searches
As the 'like a boss' meme gained traction, people's confidence levels soared, leading to a spike in the belief that they could tackle haircuts with the same swag. And, as more folks tried to emulate the fearlessness of 'bosses' in the meme, they bossed up their hair cutting skills, proving that when it comes to DIY haircuts, attitude really does clip-ly everything!




What else correlates?
Popularity of the 'like a boss' meme · all memes
Google searches for 'how to cut own hair' · all google searches

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 interdisciplinary studies and the second variable is Electricity generation in Angola.  The chart goes from 2012 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #2,666


Voltage Variety: The Shocking Connection Between Multi/Interdisciplinary Studies Bachelor's Degrees and Electricity Generation in Angola
As more students delved into the vast and varied world of Multi/interdisciplinary studies, they sparked a surge in brainpower. This intellectual firestorm led to an influx of innovative ideas for improving efficiency in electricity generation. It's shocking how these interdisciplinary graduates connected the dots to current flow in Angola's power sector, igniting a revolution in energy production. You could say they truly sparked a bright idea or two!




What else correlates?
Bachelor's degrees awarded in interdisciplinary studies · all education
Electricity generation in Angola · 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 Ariel and the second variable is The number of fashion designers in Michigan.  The chart goes from 2003 to 2020, and the two variables track closely in value over that time. Small Image
View details about correlation #2,985


Ariels in Michigan: Making Waves in Fashion Design
As the name Ariel gained popularity, more and more people were inspired by the fashionable and stylish image of the Disney princess. This led to a surge in interest in fashion and design, including in Michigan. It's as if the trend was making waves in the world of fashion, and the designers just couldn't flounder in their pursuit of creating fabulous looks!




What else correlates?
Popularity of the first name Ariel · all first names
The number of fashion designers in Michigan · all cccupations

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Number of competing nations in the Summer Olympics and the second variable is Nielsen Ranking of Smallville Season Finale.  The chart goes from 2002 to 2011, and the two variables track closely in value over that time. Small Image
View details about correlation #2,648


The Olympics Effect: The Interplay between International Sporting Events and Small-Town Dramas
As the international rivalry heated up, more people tuned in to the epic competition between Smallville's superheroes and supervillains. Who knew that Clark Kent's quest for gold would be the ultimate ratings booster for Smallville? As they say, it's not the size of the nation in the Olympics, it's the TV ratings of Smallville's finale that really matters!




What else correlates?
Number of competing nations in the Summer Olympics · all weird & wacky
Nielsen Ranking of Smallville Season Finale · all weird & wacky

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Appleton, Wisconsin and the second variable is Google searches for 'ice bath'.  The chart goes from 2004 to 2023, and the two variables track closely in value over that time. Small Image
View details about correlation #2,867


Chilling Consequences: Uncovering the Icy Relationship between Air Pollution and 'Ice Bath' Google Searches in Appleton, Wisconsin
As the air quality dipped, residents of Appleton, Wisconsin found themselves taking 'chill pills' in the form of ice baths. It seems like the smog just couldn't take a hint and decided to 'mist' with people's routines, leading them to seek refreshing relief in a tub of ice. It's a classic case of pollution causing a cool-ution, as the city's air became more inhospitable, driving folks to 'cool off' in the most literal way possible. Who knew that as the pollution levels rose, so did the temptation to take the plunge into an icy situation? It's enough to make you say, "What in the world is 'smog-nifying' this frosty trend?" But hey, when the going gets 'foggy,' the foggy get going... straight to the freezer for an impromptu arctic dip.




What else correlates?
Air pollution in Appleton, Wisconsin · all weather
Google searches for 'ice bath' · 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 'we live in a society' meme and the second variable is Wind power generated in Namibia.  The chart goes from 2006 to 2021, and the two variables track closely in value over that time. Small Image
View details about correlation #4,950


We Live in a Current-Generating Society: The Shocking Connection Between 'We Live in a Society' Meme Popularity and Wind Power Generated in Namibia
As the 'we live in a society' meme gained traction, it created a whirlwind of attention. People all over were embracing the idea and it blew a breath of fresh air into the internet. This societal reflection led to a surge in demand for clean energy and a realization that we truly do 'reap what we sow.' In Namibia, this meant a gust of support for wind power, propelling the industry forward. It's a true testament to the power of memes - they can really turbine things around for the better!




What else correlates?
Popularity of the 'we live in a society' meme · all memes
Wind power generated in Namibia · all energy

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
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