about · email me · subscribe
Spurious correlation #4,720 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Libertarian Presidential candidate in Arkansas and the second variable is Jet fuel used in Paraguay.  The chart goes from 1980 to 2020, and the two variables track closely in value over that time. Small Image

AI explanation

Every time someone voted for the Libertarian candidate in Arkansas, a little paper airplane with their candidate's name on it would take flight, eventually leading to an unexpected surge in jet fuel usage in Paraguay. It seems like Libertarian support wasn't the only thing that was really taking off!

Model: dalle-3
Prompt: Create an image of a serene grassy field in Arkansas, with a line of minimalistic people patiently waiting to cast their votes. As each person drops their paper ballot into the ballot box, a delicate and stylized paper airplane adorned with the Libertarian Presidential candidate's name ascends gracefully into the air. Against a minimalist backdrop, show streamlined, abstract representations of planes landing and taking off from a sleek and modern airport in Paraguay, symbolizing the sudden surge in air traffic caused by the paper airplanes launched from Arkansas. The serene simplicity of the grassy field contrasts with the ordered chaos of the airport as a result of the paper airplanes, all rendered in a minimalist style. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: a Polaroid photo Sci-fi fantacy Magic realism inspired by bauhaus Minimalism
ChatGPT: Minimalism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay, in the following situation: Every time someone voted for the Libertarian candidate in Arkansas, a little paper airplane with their candidate's name on it would take flight, eventually leading to an unexpected surge in jet fuel usage in Paraguay. It seems like Libertarian support wasn't the only thing that was really taking off!. Keep the description simple.
ChatGPT: In a grassy field in Arkansas, people line up to vote in the election. As each person casts their vote for the Libertarian Presidential candidate, a little paper airplane adorned with the candidate's name takes flight, soaring high into the sky. Meanwhile, across the ocean in Paraguay, the unexpected surge in jet fuel usage becomes apparent as an increased number of planes land and take off from the bustling airport. The paper airplanes from Arkansas seem to have ignited an unexpected flurry of activity in Paraguay's skies.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Minimalism ] and depicting this scene: In a grassy field in Arkansas, people line up to vote in the election. As each person casts their vote for the Libertarian Presidential candidate, a little paper airplane adorned with the candidate's name takes flight, soaring high into the sky. Meanwhile, across the ocean in Paraguay, the unexpected surge in jet fuel usage becomes apparent as an increased number of planes land and take off from the bustling airport. The paper airplanes from Arkansas seem to have ignited an unexpected flurry of activity in Paraguay's skies. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a serene grassy field in Arkansas, with a line of minimalistic people patiently waiting to cast their votes. As each person drops their paper ballot into the ballot box, a delicate and stylized paper airplane adorned with the Libertarian Presidential candidate's name ascends gracefully into the air. Against a minimalist backdrop, show streamlined, abstract representations of planes landing and taking off from a sleek and modern airport in Paraguay, symbolizing the sudden surge in air traffic caused by the paper airplanes launched from Arkansas. The serene simplicity of the grassy field contrasts with the ordered chaos of the airport as a result of the paper airplanes, all rendered in a minimalist style.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Votes for the Libertarian Presidential candidate in Arkansas positively influenced Jet fuel used in Paraguay.

AI academic paper

(Because p < 0.01)
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

The Journal of Quirky Quantitative Analysis

Jan 2024
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns.

Make the title an alliteration.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9040562 and p < 0.01 for 1980 to 2020.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Welcome, dear readers, to the wacky world of statistically surprising correlations! Our present endeavor whirls around the intriguing link between the votes cast for the Libertarian presidential candidate in the fine state of Arkansas and the amount of jet fuel gleefully consumed in the far-flung lands of Paraguay. This improbable entanglement has left our research team scratching their heads, pondering the curious twists and turns of the data.

It all began with a twinkle in the eye and a daring hypothesis: could there be a connection, however whimsical, between the political proclivities of Arkansans and the fiery appetite of Paraguayan jet engines? Armed with an arsenal of data and statistics, we delved into the depths of electoral results and energy consumption, ready to uncover any hidden correlations. Little did we anticipate the merriment and marvel that lay ahead!

As we sifted through the MIT Election Data and Science Lab archives, cavorted through the Harvard Dataverse, and reveled in the Energy Information Administration’s data, our journey took an unexpected turn. Lo and behold, amidst the sea of numbers and coefficients, a correlation coefficient of 0.9040562 emerged, casting a spell of disbelief upon our merry band of researchers. The p-value, standing at less than 0.01 for the period from 1980 to 2020, invited us to indulge in an uproarious fit of statistical revelry.

Now, hold on to your lab coats and pocket protectors, folks, because we are about to spin a tale of statistical serendipity that will have you laughing in disbelief. With a twinkle in our eyes and a bounce in our step, let us journey forth to unravel the enigmatic nexus between political preferences and petroleum predilections, all while relishing the delightful absurdity of this extraordinary correlation. Join us on this merry research adventure, as we navigate the twists and turns of the data landscape and celebrate the whimsical ride of scientific exploration!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Welcome, dear readers, to the wacky world of statistically surprising correlations! Our present endeavor whirls around the intriguing link between the votes cast for the Libertarian presidential candidate in the fine state of Arkansas and the amount of jet fuel gleefully consumed in the far-flung lands of Paraguay. This improbable entanglement has left our research team scratching their heads, pondering the curious twists and turns of the data.
It all began with a twinkle in the eye and a daring hypothesis: could there be a connection, however whimsical, between the political proclivities of Arkansans and the fiery appetite of Paraguayan jet engines? Armed with an arsenal of data and statistics, we delved into the depths of electoral results and energy consumption, ready to uncover any hidden correlations. Little did we anticipate the merriment and marvel that lay ahead!
As we sifted through the MIT Election Data and Science Lab archives, cavorted through the Harvard Dataverse, and reveled in the Energy Information Administration’s data, our journey took an unexpected turn. Lo and behold, amidst the sea of numbers and coefficients, a correlation coefficient of 0.9040562 emerged, casting a spell of disbelief upon our merry band of researchers. The p-value, standing at less than 0.01 for the period from 1980 to 2020, invited us to indulge in an uproarious fit of statistical revelry.
Now, hold on to your lab coats and pocket protectors, folks, because we are about to spin a tale of statistical serendipity that will have you laughing in disbelief. With a twinkle in our eyes and a bounce in our step, let us journey forth to unravel the enigmatic nexus between political preferences and petroleum predilections, all while relishing the delightful absurdity of this extraordinary correlation. Join us on this merry research adventure, as we navigate the twists and turns of the data landscape and celebrate the whimsical ride of scientific exploration!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In the annals of research, one cannot escape the unrelenting quest for uncovering peculiar correlations - a pursuit that has led scholars to tread upon the most bewildering and bemusing paths. As we embark on our own whimsical journey to unravel the confounding link between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay, we find ourselves wading through a bevy of studies that shed light on the unexpected interplay of seemingly unrelated variables.

Smith and Doe, in their seminal work "Correlating Curiosities: An Exploration of Statistical Serendipity," underscore the baffling nature of correlations by delving into a myriad of puzzling connections that defy conventional wisdom. Little did they know that their scholarly endeavors would be mirrored by our own foray into the world of electoral preferences and energy consumption. With tongue firmly in cheek, they caution researchers to remain vigilant of the capricious whims of statistical analyses, reminding us that correlation does not imply causation - a lighthearted warning that we heeded as we embarked on our mirthful investigation.

Turning to the volumes that populate the shelves of our esteemed libraries, we encounter "Quantitative Quirks: Unraveling Statistical Oddities in Real-World Data" by Jones, a delightful tome that regales readers with tales of improbable associations and unexpected relationships. Through witty anecdotes and mischievous musings, Jones invites us to ponder the charming caprice of statistical fate, a sentiment that resonates deeply with our own laughter-laden escapade into the world of presidential peculiarities and petrol proclivities.

But let us not forget the fiction aisle, where we chance upon "The Correlation Conundrum" by Agatha Mystery, a gripping tale of improbable connections and bewildering linkages that would leave even the most ardent statistician gasping in disbelief. While the characters in this literary delight grapple with mysterious correlations of a different ilk, we cannot help but draw parallels to our own scientific revelry, as we unraveled the enigmatic ties between political predilections and petroleum practices.

Beyond the confines of scholarly tomes and fictional delights, our whimsical expedition into the interplay of electoral preferences and energy consumption found unexpected inspiration in unlikely places. For as we ventured further into the labyrinth of statistical exploration, the spirit of "Clue" infused our quest, prompting us to uncover the hidden connections and unravel the mysteries of our data landscape. With a dash of levity and a glimmer of statistical merriment, we embrace the delightful absurdity of our research endeavor, reveling in the joyous dance of correlation and causation as we journey through the whimsical world of scholarly pursuits.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 1980 to 2020

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

[[INTRODUCTION]]
Welcome, dear readers, to the wacky world of statistically surprising correlations! Our present endeavor whirls around the intriguing link between the votes cast for the Libertarian presidential candidate in the fine state of Arkansas and the amount of jet fuel gleefully consumed in the far-flung lands of Paraguay. This improbable entanglement has left our research team scratching their heads, pondering the curious twists and turns of the data.
It all began with a twinkle in the eye and a daring hypothesis: could there be a connection, however whimsical, between the political proclivities of Arkansans and the fiery appetite of Paraguayan jet engines? Armed with an arsenal of data and statistics, we delved into the depths of electoral results and energy consumption, ready to uncover any hidden correlations. Little did we anticipate the merriment and marvel that lay ahead!
As we sifted through the MIT Election Data and Science Lab archives, cavorted through the Harvard Dataverse, and reveled in the Energy Information Administration’s data, our journey took an unexpected turn. Lo and behold, amidst the sea of numbers and coefficients, a correlation coefficient of 0.9040562 emerged, casting a spell of disbelief upon our merry band of researchers. The p-value, standing at less than 0.01 for the period from 1980 to 2020, invited us to indulge in an uproarious fit of statistical revelry.
Now, hold on to your lab coats and pocket protectors, folks, because we are about to spin a tale of statistical serendipity that will have you laughing in disbelief. With a twinkle in our eyes and a bounce in our step, let us journey forth to unravel the enigmatic nexus between political preferences and petroleum predilections, all while relishing the delightful absurdity of this extraordinary correlation. Join us on this merry research adventure, as we navigate the twists and turns of the data landscape and celebrate the whimsical ride of scientific exploration!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unravel the mysterious correlation between the choice of the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay, our intrepid research team embarked on a scientific odyssey characterized by glee and a peculiar blend of curiosity and hilarity. Armed with an array of datasets from prestigious repositories including the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we harnessed the power of statistical analysis to scratch beneath the surface of this whimsical conundrum.

Our data collection strategy involved scouring the digital universe for granules of information from a time span stretching back to 1980 up to the laughter-filled year of 2020. We meticulously gathered the number of votes cast for the Libertarian presidential candidate, frolicking through election records and statistical archives with a merry spirit. Simultaneously, we gleefully amassed data on the consumption of jet fuel in Paraguay, diving into the depths of energy consumption statistics with unbridled enthusiasm.

Next, we summoned the robust marvels of statistical analysis to weave our data into a tapestry of analysis. Our approach involved gallivanting through the pasture of bivariate correlation, where we sought to discern the enchanting relationship between the aforementioned variables. With a twinkle in our eyes and an air of mischief, we calculated the correlation coefficient, wielding the tools of covariance and standard deviation to gauge the strength and direction of this mirthful connection.

For a further spectacle of statistical wizardry, we ventured into the realm of p-values, eager to uncover the significance of our findings. Through the delightful lens of hypothesis testing, we merrily frolicked with the null and alternative hypotheses, subjecting our data to a whimsical dance of significance testing that left us all in roars of laughter and wild exclamations of astonishment.

Lastly, like bold alchemists of yore, we stirred our bubbling cauldron of data and statistics, summoning the enchanting potion known as the multiple regression analysis. This mirthful incantation allowed us to unravel the contributions of additional variables, such as political climate and economic factors, to the entwining of presidential preferences and petroleum practices.

In summary, our methodology reflects the spirited dance of scientific inquiry, infused with the thrilling buzz of statistical exploration and the boundless enthusiasm of academic merriment. Join us in our journey as we unravel the whimsical tapestry of statistical absurdity, all while celebrating the wondrous joys of academic research!

(Note: This methodology section is crafted as a playful and whimsical narrative, blending scientific language with humor and imaginative flair to convey the spirit of academic exploration.)


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration .

For the time period 1980 to 2020, you found a correlation 0.9040562, r-squared of 0.8173177, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Welcome, dear readers, to the wacky world of statistically surprising correlations! Our present endeavor whirls around the intriguing link between the votes cast for the Libertarian presidential candidate in the fine state of Arkansas and the amount of jet fuel gleefully consumed in the far-flung lands of Paraguay. This improbable entanglement has left our research team scratching their heads, pondering the curious twists and turns of the data.
It all began with a twinkle in the eye and a daring hypothesis: could there be a connection, however whimsical, between the political proclivities of Arkansans and the fiery appetite of Paraguayan jet engines? Armed with an arsenal of data and statistics, we delved into the depths of electoral results and energy consumption, ready to uncover any hidden correlations. Little did we anticipate the merriment and marvel that lay ahead!
As we sifted through the MIT Election Data and Science Lab archives, cavorted through the Harvard Dataverse, and reveled in the Energy Information Administration’s data, our journey took an unexpected turn. Lo and behold, amidst the sea of numbers and coefficients, a correlation coefficient of 0.9040562 emerged, casting a spell of disbelief upon our merry band of researchers. The p-value, standing at less than 0.01 for the period from 1980 to 2020, invited us to indulge in an uproarious fit of statistical revelry.
Now, hold on to your lab coats and pocket protectors, folks, because we are about to spin a tale of statistical serendipity that will have you laughing in disbelief. With a twinkle in our eyes and a bounce in our step, let us journey forth to unravel the enigmatic nexus between political preferences and petroleum predilections, all while relishing the delightful absurdity of this extraordinary correlation. Join us on this merry research adventure, as we navigate the twists and turns of the data landscape and celebrate the whimsical ride of scientific exploration!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Prepare to be astounded and amused as we unveil the results of our investigation into the seemingly preposterous correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. After sifting merrily through swathes of data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we were met with a staggering discovery.

Behold, a correlation coefficient of 0.9040562 that defies all rational explanation, and an r-squared of 0.8173177 that elicited an outburst of both laughter and bewilderment from our delighted research team. The p-value of less than 0.01 for the period of 1980 to 2020 further flabbergasted us, leaving us in a state of gleeful disbelief.

As if this remarkable correlation weren't enough to raise an eyebrow or two, we present to you our pièce de résistance: Fig. 1. The scatterplot depicted within this wondrous illustration provides irrefutable evidence of the strong correlation between these two seemingly unrelated variables. We invite you to gaze upon this chart and revel in the absurdity of this unexpected association.

Our research has led us down a path of statistical serendipity, and we invite all fellow aficionados of scholarly whimsy to join us in celebrating the joyous discovery of this improbable relationship. As we bask in the delightfully absurd nature of this correlation, let us continue to embrace the merry dance of statistical exploration and revel in the unexpected connections that grace the realm of research.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

[[LITERATURE REVIEW]]
In the annals of research, one cannot escape the unrelenting quest for uncovering peculiar correlations - a pursuit that has led scholars to tread upon the most bewildering and bemusing paths. As we embark on our own whimsical journey to unravel the confounding link between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay, we find ourselves wading through a bevy of studies that shed light on the unexpected interplay of seemingly unrelated variables.
Smith and Doe, in their seminal work "Correlating Curiosities: An Exploration of Statistical Serendipity," underscore the baffling nature of correlations by delving into a myriad of puzzling connections that defy conventional wisdom. Little did they know that their scholarly endeavors would be mirrored by our own foray into the world of electoral preferences and energy consumption. With tongue firmly in cheek, they caution researchers to remain vigilant of the capricious whims of statistical analyses, reminding us that correlation does not imply causation - a lighthearted warning that we heeded as we embarked on our mirthful investigation.
Turning to the volumes that populate the shelves of our esteemed libraries, we encounter "Quantitative Quirks: Unraveling Statistical Oddities in Real-World Data" by Jones, a delightful tome that regales readers with tales of improbable associations and unexpected relationships. Through witty anecdotes and mischievous musings, Jones invites us to ponder the charming caprice of statistical fate, a sentiment that resonates deeply with our own laughter-laden escapade into the world of presidential peculiarities and petrol proclivities.
But let us not forget the fiction aisle, where we chance upon "The Correlation Conundrum" by Agatha Mystery, a gripping tale of improbable connections and bewildering linkages that would leave even the most ardent statistician gasping in disbelief. While the characters in this literary delight grapple with mysterious correlations of a different ilk, we cannot help but draw parallels to our own scientific revelry, as we unraveled the enigmatic ties between political predilections and petroleum practices.
Beyond the confines of scholarly tomes and fictional delights, our whimsical expedition into the interplay of electoral preferences and energy consumption found unexpected inspiration in unlikely places. For as we ventured further into the labyrinth of statistical exploration, the spirit of "Clue" infused our quest, prompting us to uncover the hidden connections and unravel the mysteries of our data landscape. With a dash of levity and a glimmer of statistical merriment, we embrace the delightful absurdity of our research endeavor, reveling in the joyous dance of correlation and causation as we journey through the whimsical world of scholarly pursuits.

[[RESULTS]]
Prepare to be astounded and amused as we unveil the results of our investigation into the seemingly preposterous correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. After sifting merrily through swathes of data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we were met with a staggering discovery.
Behold, a correlation coefficient of 0.9040562 that defies all rational explanation, and an r-squared of 0.8173177 that elicited an outburst of both laughter and bewilderment from our delighted research team. The p-value of less than 0.01 for the period of 1980 to 2020 further flabbergasted us, leaving us in a state of gleeful disbelief.
As if this remarkable correlation weren't enough to raise an eyebrow or two, we present to you our pièce de résistance: Fig. 1. The scatterplot depicted within this wondrous illustration provides irrefutable evidence of the strong correlation between these two seemingly unrelated variables. We invite you to gaze upon this chart and revel in the absurdity of this unexpected association.
Our research has led us down a path of statistical serendipity, and we invite all fellow aficionados of scholarly whimsy to join us in celebrating the joyous discovery of this improbable relationship. As we bask in the delightfully absurd nature of this correlation, let us continue to embrace the merry dance of statistical exploration and revel in the unexpected connections that grace the realm of research.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

In our uproarious voyage into the world of peculiar correlations, we set out to unravel the beguiling connection between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. As we reflect on the bemusing bounty of the literature, we are reminded of the cautionary tales of "Correlating Curiosities" by Smith and Doe, which have come to fruition in our own hilarious hijinks. By embracing the capricious whims of statistical analyses and the mirthful musings of Jones' "Quantitative Quirks," we found ourselves waltzing into the unexpected arms of statistical serendipity.

Our revelry led us to the unearthing of a correlation coefficient of 0.9040562, an enigmatic figure that stands as a testament to the delightful absurdity of statistical fate. With a p-value of less than 0.01, our results not only raise eyebrows but also elicit giggles and guffaws. Yes, dear readers, the r-squared of 0.8173177 adds another layer of merriment to this unexpected discovery, leaving us in a state of gleeful disbelief akin to solving a perplexing puzzle in "Clue."

The scatterplot, our pièce de résistance, encapsulates the very essence of this jocund correlation, inviting us to revel in the absurdity of this unlikely association. The chart stands as a joyful testament to the whimsicality of our findings, a delightful spectacle reminiscent of an unexpected and uproarious twist in "The Correlation Conundrum" by Agatha Mystery.

In conclusion, our results not only support the prior research but also pay a jubilant homage to the spirit of statistical exploration. Our journey into the world of electoral preferences and energy consumption has illuminated the winsome waltz of correlation and causation, bolstering the edifice of statistical merriment and scientific revelry. As we bid adieu to this whimsical escapade, we leave it to future researchers to carry on this merry quest and continue to unravel the delightful absurdities that grace the realm of research with jubilant laughter and unequivocal wonder. Let the statistical merriment continue!


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Libertarian Presidential candidate in Arkansas and Jet fuel used in Paraguay. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption

[[ABSTRACT]]
In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

[[INTRDUCTION]]
Welcome, dear readers, to the wacky world of statistically surprising correlations! Our present endeavor whirls around the intriguing link between the votes cast for the Libertarian presidential candidate in the fine state of Arkansas and the amount of jet fuel gleefully consumed in the far-flung lands of Paraguay. This improbable entanglement has left our research team scratching their heads, pondering the curious twists and turns of the data.
It all began with a twinkle in the eye and a daring hypothesis: could there be a connection, however whimsical, between the political proclivities of Arkansans and the fiery appetite of Paraguayan jet engines? Armed with an arsenal of data and statistics, we delved into the depths of electoral results and energy consumption, ready to uncover any hidden correlations. Little did we anticipate the merriment and marvel that lay ahead!
As we sifted through the MIT Election Data and Science Lab archives, cavorted through the Harvard Dataverse, and reveled in the Energy Information Administration’s data, our journey took an unexpected turn. Lo and behold, amidst the sea of numbers and coefficients, a correlation coefficient of 0.9040562 emerged, casting a spell of disbelief upon our merry band of researchers. The p-value, standing at less than 0.01 for the period from 1980 to 2020, invited us to indulge in an uproarious fit of statistical revelry.
Now, hold on to your lab coats and pocket protectors, folks, because we are about to spin a tale of statistical serendipity that will have you laughing in disbelief. With a twinkle in our eyes and a bounce in our step, let us journey forth to unravel the enigmatic nexus between political preferences and petroleum predilections, all while relishing the delightful absurdity of this extraordinary correlation. Join us on this merry research adventure, as we navigate the twists and turns of the data landscape and celebrate the whimsical ride of scientific exploration!

[[RESULTS]]
Prepare to be astounded and amused as we unveil the results of our investigation into the seemingly preposterous correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. After sifting merrily through swathes of data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we were met with a staggering discovery.
Behold, a correlation coefficient of 0.9040562 that defies all rational explanation, and an r-squared of 0.8173177 that elicited an outburst of both laughter and bewilderment from our delighted research team. The p-value of less than 0.01 for the period of 1980 to 2020 further flabbergasted us, leaving us in a state of gleeful disbelief.
As if this remarkable correlation weren't enough to raise an eyebrow or two, we present to you our pièce de résistance: Fig. 1. The scatterplot depicted within this wondrous illustration provides irrefutable evidence of the strong correlation between these two seemingly unrelated variables. We invite you to gaze upon this chart and revel in the absurdity of this unexpected association.
Our research has led us down a path of statistical serendipity, and we invite all fellow aficionados of scholarly whimsy to join us in celebrating the joyous discovery of this improbable relationship. As we bask in the delightfully absurd nature of this correlation, let us continue to embrace the merry dance of statistical exploration and revel in the unexpected connections that grace the realm of research.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

And so, dear readers, we find ourselves at the end of this delightful dalliance into the realm of absurd correlations and statistical surprises. With a correlation coefficient that defies logic and reason, our study has not only raised a few eyebrows but also filled our hearts with mirth and marvel. As we bid farewell to our sprightly exploration of the link between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay, we can't help but marvel at the whimsical dance of the data.
In closing, let us remember the joy of the unexpected, the wonder of statistical serendipity, and the merriment that accompanies a truly improbable correlation. We've laughed, we've marveled, and we've embraced the absurdity of this remarkable finding. As such, we assert that no further research is necessary in this truly delightful, yet confounding, area of study. After all, where else could we find such statistical amusement and scientific whimsy? Let this research be a testament to the delightful caprice of statistical exploration and the joyful surprises that await those willing to peer into the merry depths of data.


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Quantitative Analysis


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Quantitative Analysis


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Libertarian Lunacy: Linking Presidential Preference to Paraguayan Petroleum Consumption with an abstract of In this study, we embark on a whimsical journey to uncover the curious correlation between votes for the Libertarian presidential candidate in Arkansas and the consumption of jet fuel in Paraguay. Armed with data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our research team set out to explore this seemingly incongruous relationship. To our astonishment, we unearthed a correlation coefficient of 0.9040562, defying all expectations and leaving us in fits of giggles. With a p-value of less than 0.01 for the period spanning 1980 to 2020, our findings not only raise eyebrows but also elicit chuckles. Join us on this research escapade as we unravel the enigmatic connection between presidential preferences and petroleum practices, all while celebrating the delightful absurdity of statistical serendipity.

ChatGPT:

Libertarian presidential candidate, Arkansas, Paraguay, petroleum consumption, jet fuel, correlation, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, correlation coefficient, p-value, statistical serendipity

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.



Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error


Data details

Votes for the Libertarian Presidential candidate in Arkansas
Detailed data title: Percentage of all votes cast for the Libertarian Presidential candidate in Arkansas
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Libertarian Presidential candidate in Arkansas

Jet fuel used in Paraguay
Detailed data title: Volume of jet fuel used consumed in Paraguay in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Jet fuel used in Paraguay

Correlation r = 0.9040562 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r2 = 0.8173177 (Coefficient of determination)
This means 81.7% of the change in the one variable (i.e., Jet fuel used in Paraguay) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in Arkansas) over the 9 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00082. 0.0008191692787383873000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.9 in 0.082% of random cases. Said differently, if you correlated 1,221 random variables Which I absolutely did.
with the same 8 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 8 because we have two variables measured over a period of 9 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.6, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
198019841988200020042008201220162020
Votes for the Libertarian Presidential candidate in Arkansas (Percentage of votes)1.070940.2511290.3983140.3016990.222950.4395291.521882.638251.0773
Jet fuel used in Paraguay (Million Barrels/Day)0.3633030.3669720.40.2816670.3466670.5416670.60666710.543151




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations 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 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.
    no direct connection between these variables, despite what the AI says above. 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. 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 simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1.07094,0.251129,0.398314,0.301699,0.22295,0.439529,1.52188,2.63825,1.0773,])
array_2 = np.array([0.363303,0.366972,0.4,0.281667,0.346667,0.541667,0.606667,1,0.543151,])
array_1_name = "Votes for the Libertarian Presidential candidate in Arkansas"
array_2_name = "Jet fuel used in Paraguay"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)



Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:


View another random correlation

How fun was this correlation?

You're a rater extraordinaire!


Correlation ID: 4720 · Black Variable ID: 26059 · Red Variable ID: 24806
about · subscribe · emailme@tylervigen.com · twitter

CC BY 4.0