spurious correlations

correlation is not causation

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View details about correlation #2,695

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What else correlates?
Season rating of "Two and a Half Men" · all films & actors
Paychex's stock price (PAYX) · all stocks

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GDP per capita in Canada and the second variable is Season wins for the San Francisco 49ers. The chart goes from 2009 to 2022, and the two variables track closely in value over that time.

View details about correlation #5,909

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What else correlates?
GDP per capita in Canada · all weird & wacky
Season wins for the San Francisco 49ers · all sports

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The distance between Neptune and the Sun 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.

View details about correlation #1,035

^{Show scatterplot}

What else correlates?
The distance between Neptune and the Sun · all planets
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 first name Jack and the second variable is Number of public school students in 9th grade. The chart goes from 1990 to 2022, and the two variables track closely in value over that time.

View details about correlation #1,951

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What else correlates?
Popularity of the first name Jack · all first names
Number of public school students in 9th grade · all education

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Google searches for 'where can i stream friends' and the second variable is Lululemon's stock price (LULU). The chart goes from 2008 to 2023, and the two variables track closely in value over that time.

View details about correlation #2,694

^{Show scatterplot}

What else correlates?
Google searches for 'where can i stream friends' · all google searches
Lululemon's stock price (LULU) · all stocks

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 Number of registered Yamaha motorcycles in the UK. The chart goes from 2000 to 2021, and the two variables track closely in value over that time.

View details about correlation #1,370

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What else correlates?
GMO use in corn grown in Michigan · all food
Number of registered Yamaha motorcycles in the UK · 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 distance between Saturn and the Sun and the second variable is Biomass power generated in India. The chart goes from 1999 to 2021, and the two variables track closely in value over that time.

View details about correlation #5,931

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What else correlates?
The distance between Saturn and the Sun · all planets
Biomass power generated in India · 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 Brooklyn and the second variable is UFO sightings in Kentucky. The chart goes from 1975 to 2021, and the two variables track closely in value over that time.

View details about correlation #2,674

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What else correlates?
Popularity of the first name Brooklyn · all first names
UFO sightings in Kentucky · 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 Rainfall in San Francisco and the second variable is The number of printing press operators in Rhode Island. The chart goes from 2010 to 2022, and the two variables track closely in value over that time.

View details about correlation #2,948

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What else correlates?
Rainfall in San Francisco · all weather
The number of printing press operators in Rhode Island · 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 'success kid' meme and the second variable is Average number of comments on Numberphile YouTube videos. The chart goes from 2011 to 2023, and the two variables track closely in value over that time.

View details about correlation #5,959

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What else correlates?
Popularity of the 'success kid' meme · all memes
Average number of 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 distance between Uranus and Saturn and the second variable is Nuclear power generation in Brazil. The chart goes from 1982 to 2021, and the two variables track closely in value over that time.

View details about correlation #2,310

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What else correlates?
The distance between Uranus and Saturn · all planets
Nuclear power generation in Brazil · all energy

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Burglaries in Oregon and the second variable is Viewership count for Days of Our Lives. The chart goes from 1985 to 2021, and the two variables track closely in value over that time.

View details about correlation #1,218

^{Show scatterplot}

What else correlates?
Burglaries in Oregon · all random state specific
Viewership count for Days of Our Lives · 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 first name Tiarra and the second variable is Google searches for 'why isnt 11 pronounced onety one'. The chart goes from 2004 to 2021, and the two variables track closely in value over that time.

View details about correlation #1,041

^{Show scatterplot}

What else correlates?
Popularity of the first name Tiarra · all first names
Google searches for 'why isnt 11 pronounced onety one' · all google searches

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 GMO use in corn grown in Ohio. The chart goes from 2012 to 2021, and the two variables track closely in value over that time.

View details about correlation #1,254

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What else correlates?
Master's degrees awarded in Education · all education
GMO use in corn grown in Ohio · all food

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The distance between Saturn and Earth and the second variable is Fomento Econ's stock price (FMX). The chart goes from 2002 to 2023, and the two variables track closely in value over that time.

View details about correlation #1,526

^{Show scatterplot}

What else correlates?
The distance between Saturn and Earth · all planets
Fomento Econ's stock price (FMX) · 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 phlebotomists in Minnesota and the second variable is Arson in United States. The chart goes from 2012 to 2022, and the two variables track closely in value over that time.

View details about correlation #4,252

^{Show scatterplot}

What else correlates?
The number of phlebotomists in Minnesota · all cccupations
Arson in United States · 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 How 'hip and with it' Numberphile YouTube video titles are and the second variable is Wind power generated in Latvia. The chart goes from 2011 to 2021, and the two variables track closely in value over that time.

View details about correlation #4,554

^{Show scatterplot}

What else correlates?
How 'hip and with it' Numberphile YouTube video titles are · all YouTube
Wind power generated in Latvia · all energy

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 Popularity of the 'this is fine' meme. The chart goes from 2006 to 2021, and the two variables track closely in value over that time.

View details about correlation #5,468

^{Show scatterplot}

What else correlates?
American cheese consumption · all food
Popularity of the 'this is fine' meme · all memes

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The distance between Jupiter and Mercury and the second variable is Anheuser-Busch InBev's stock price (BUD). The chart goes from 2010 to 2023, and the two variables track closely in value over that time.

View details about correlation #2,734

^{Show scatterplot}

What else correlates?
The distance between Jupiter and Mercury · all planets
Anheuser-Busch InBev's stock price (BUD) · 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 Library science and the second variable is Google searches for 'how to hide a body'. The chart goes from 2012 to 2021, and the two variables track closely in value over that time.

View details about correlation #1,840

^{Show scatterplot}

What else correlates?
Bachelor's degrees awarded in Library science · all education
Google searches for 'how to hide a body' · all google searches

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Why this works

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.”^Note 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.
Lack of causal connection: There is probably no direct connection between these variables, despite what the AI says above.^Note 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.
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.^Note 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.
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. ^Note 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.
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.
Outliers: Some datasets here have outliers which drag up the correlation.^Note 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.
Low n: There are not many data points included in some of these charts.^Note 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:

Detailed data sources
Prompts for the AI-generated content
Explanations of each of the calculations (correlation, p-value)
Python code to calculate it yourself

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

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