Spurious correlation #4,659 · 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 North Carolina and the second variable is Liquefied petroleum gas used in Haiti. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

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 North Carolina and the second variable is Liquefied petroleum gas used in Haiti. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The increased hot air from the campaign trail and debates was inadvertently being captured and shipped to Haiti, where it was used to power the production of LPG. The fiery passion for political freedom was manifesting in the form of actual heat, leading to a surge in LPG production in Haiti. As the Libertarian candidate gained more support in North Carolina, the connection with Haiti strengthened, creating a bizarre yet undeniably gassy political alliance. It's a classic case of political gasbaggery leading to a real gas boom!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of exuberant voters casting their ballots in North Carolina, set against the backdrop of a bustling political campaign scene. Meanwhile, harness the imagery of industrious workers in Haiti utilizing the hot air and energy generated from political debates to produce Liquefied Petroleum Gas (LPG). The juxtaposition of these two parallel events should be visually intriguing, portraying the unlikely alliance between political fervor and a gas production surge. 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 North Carolina and Liquefied petroleum gas used in Haiti. 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: Cubism inspired by bauhaus High-tech A Discovery magazine cover image Macabre
ChatGPT: A Discovery magazine cover image

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 North Carolina and Liquefied petroleum gas used in Haiti, in the following situation: The increased hot air from the campaign trail and debates was inadvertently being captured and shipped to Haiti, where it was used to power the production of LPG. The fiery passion for political freedom was manifesting in the form of actual heat, leading to a surge in LPG production in Haiti. As the Libertarian candidate gained more support in North Carolina, the connection with Haiti strengthened, creating a bizarre yet undeniably gassy political alliance. It's a classic case of political gasbaggery leading to a real gas boom!. Keep the description simple.
ChatGPT: In North Carolina, voters enthusiastically cast their ballots for the Libertarian Presidential candidate, while in Haiti, an industrious scene unfolds as hot air from the political campaign trail and debates is harnessed, creating a surge in Liquefied Petroleum Gas (LPG) production. The two distant yet parallel events intertwine, showcasing a bizarre alliance where political fervor fuels an unexpected gas boom.

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: [ A Discovery magazine cover image ] and depicting this scene: In North Carolina, voters enthusiastically cast their ballots for the Libertarian Presidential candidate, while in Haiti, an industrious scene unfolds as hot air from the political campaign trail and debates is harnessed, creating a surge in Liquefied Petroleum Gas (LPG) production. The two distant yet parallel events intertwine, showcasing a bizarre alliance where political fervor fuels an unexpected gas boom. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of exuberant voters casting their ballots in North Carolina, set against the backdrop of a bustling political campaign scene. Meanwhile, harness the imagery of industrious workers in Haiti utilizing the hot air and energy generated from political debates to produce Liquefied Petroleum Gas (LPG). The juxtaposition of these two parallel events should be visually intriguing, portraying the unlikely alliance between political fervor and a gas production surge.

*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.
^{Show prompt for explanation} 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 North Carolina positively influenced Liquefied petroleum gas used in Haiti.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti

The Journal of Eclectic Economic Research

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} 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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 North Carolina and Liquefied petroleum gas used in Haiti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti"

[[ABSTRACT]]
In this paper, we delve into the curious correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. While this connection may seem as improbable as finding a needle in a haystack, our research aims to shed light on this peculiarity. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncover a correlation coefficient of 0.9587247 and p < 0.01 for the years spanning from 1980 to 2020.

Through our rigorous analysis, we aim to dispel any lingering doubts and dispense with the notion that these two seemingly disparate phenomena are mere happenstance. Our findings provide a glimpse into the fascinating world of regional political preferences and energy consumption patterns, illuminating unexpected connections that might otherwise be overlooked. We hope this study not only provides valuable insights into the seemingly unrelated, but also sparks further interest in the colorful tapestry of human behavior and societal interactions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As we embark on a scholarly journey of statistical analysis and serendipitous discoveries, we find ourselves drawn to the perplexing correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. While the mere mention of this connection might prompt some to raise an eyebrow (or perhaps even two), our inquisitive minds have led us to investigate this unusual pairing with keen interest and a healthy dose of skepticism.
It is not often that one finds themselves walking down the path of statistical analysis and suddenly stumbling upon a connection that seems as unlikely as spotting a flamingo in a snowstorm. However, armed with an arsenal of data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we embarked on our academic escapade to uncover the enigmatic relationship between political proclivities in the Tar Heel State and the consumption of LPG in the far-flung reaches of Haiti.
We are well aware that delving into such peculiar connections and correlations may appear akin to pursuing a scientific wild goose chase. However, our pursuit of knowledge knows no bounds, and we stand before you today with a robust correlation coefficient of 0.9587247 and a p-value of less than 0.01 to support our seemingly outlandish claims. It is with a mix of excitement and bewilderment that we present our findings, with the hope of leaving no stone unturned and no hypothesis unexplored.
As we venture into the labyrinth of numerical data and statistical models, we aim to unravel the mystery behind this unlikely pairing and provide a peek into the whimsical world of human behavior and societal peculiarities. So, dear reader, fasten your seatbelts and prepare to be whisked away into the kaleidoscopic realm of improbable correlations and unexpected associations. For in the realm of scholarly pursuits, the unexpected often yields the most intriguing revelations.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The curious case of the connection between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti has prompted both bemusement and intrigue among scholarly circles. While the initial reaction to such an association may border on incredulity, the authors find ample evidence to support this unlikely correlation, leading to a fascinating exploration of the interplay between political preferences and energy consumption patterns.

Smith (2015) delves into the intricate relationship between regional political affiliations and their impact on energy usage, shedding light on the potential influences that political ideologies can exert on environmental and energy-related choices. Meanwhile, Doe (2017) offers a comprehensive analysis of voting patterns and their unexpected consequences on international trade, providing a thought-provoking backdrop to our examination of North Carolina's political landscape and Haiti's LPG consumption.

Jones (2020) further contributes to the discourse by examining the ripple effects of political movements on global energy markets, offering insights into the far-reaching ramifications of seemingly localized political phenomena. These seminal works set the stage for our investigation into the peculiar connection between the Tar Heel State and the Caribbean nation, paving the way for a deeper understanding of the intertwining factors at play.

Turning to non-fiction publications that offer a tangential insight into our study, "Energy Politics" by Davis (2018) provides a thorough exploration of the political dynamics shaping energy policies, although it regrettably fails to delve into the specific nuances of the Libertarian influence in North Carolina. In a similar vein, "Haiti: A Political History" by Bell (2016) offers a comprehensive overview of the socio-political landscape of Haiti, providing context for the consumption patterns that form a crucial part of our investigation.

On a more speculative note, the works of fiction such as "The Fountainhead" by Ayn Rand and "The Comedians" by Graham Greene, though not directly related to our empirical analysis, offer intriguing glimpses into political ideologies and their impact on societal structures. While one may argue that these literary works are on the periphery of our research focus, the parallels between fictional narratives and real-world phenomena often blur in unforeseen ways, much like the unexpected correlations we aim to unravel.

In the realm of cinematic portrayals that echo our themes, "Thank You for Smoking" and "The Motorcycle Diaries" stand out as thought-provoking depictions of political influence and societal dynamics, offering nuanced perspectives that resonate with the intricacies of our investigation. While the silver screen may seem worlds apart from statistical analyses, the ability of film to capture the complexities of human behavior and its manifold influences cannot be underestimated.

As we traverse through the spectrum of literature, both scholarly and speculative, we find ourselves on a path laced with unexpected connections and serendipitous revelations. The insightful works of esteemed authors and the imaginative realms of fiction and film serve as beacons in our quest to unravel the enigmatic link between the voting trends in North Carolina and the consumption of LPG in Haiti. With each page turned and each reel unspooled, we inch closer to unraveling the Gordian knot of improbable correlations, eager to uncover the hidden threads that bind together the seemingly disparate elements of political preferences and energy consumption.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 North Carolina and Liquefied petroleum gas used in Haiti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti"

[[ABSTRACT]]
In this paper, we delve into the curious correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. While this connection may seem as improbable as finding a needle in a haystack, our research aims to shed light on this peculiarity. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncover a correlation coefficient of 0.9587247 and p < 0.01 for the years spanning from 1980 to 2020.

Through our rigorous analysis, we aim to dispel any lingering doubts and dispense with the notion that these two seemingly disparate phenomena are mere happenstance. Our findings provide a glimpse into the fascinating world of regional political preferences and energy consumption patterns, illuminating unexpected connections that might otherwise be overlooked. We hope this study not only provides valuable insights into the seemingly unrelated, but also sparks further interest in the colorful tapestry of human behavior and societal interactions.

[[LITERATURE REVIEW]]
The curious case of the connection between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti has prompted both bemusement and intrigue among scholarly circles. While the initial reaction to such an association may border on incredulity, the authors find ample evidence to support this unlikely correlation, leading to a fascinating exploration of the interplay between political preferences and energy consumption patterns.
Smith (2015) delves into the intricate relationship between regional political affiliations and their impact on energy usage, shedding light on the potential influences that political ideologies can exert on environmental and energy-related choices. Meanwhile, Doe (2017) offers a comprehensive analysis of voting patterns and their unexpected consequences on international trade, providing a thought-provoking backdrop to our examination of North Carolina's political landscape and Haiti's LPG consumption.
Jones (2020) further contributes to the discourse by examining the ripple effects of political movements on global energy markets, offering insights into the far-reaching ramifications of seemingly localized political phenomena. These seminal works set the stage for our investigation into the peculiar connection between the Tar Heel State and the Caribbean nation, paving the way for a deeper understanding of the intertwining factors at play.
Turning to non-fiction publications that offer a tangential insight into our study, "Energy Politics" by Davis (2018) provides a thorough exploration of the political dynamics shaping energy policies, although it regrettably fails to delve into the specific nuances of the Libertarian influence in North Carolina. In a similar vein, "Haiti: A Political History" by Bell (2016) offers a comprehensive overview of the socio-political landscape of Haiti, providing context for the consumption patterns that form a crucial part of our investigation.
On a more speculative note, the works of fiction such as "The Fountainhead" by Ayn Rand and "The Comedians" by Graham Greene, though not directly related to our empirical analysis, offer intriguing glimpses into political ideologies and their impact on societal structures. While one may argue that these literary works are on the periphery of our research focus, the parallels between fictional narratives and real-world phenomena often blur in unforeseen ways, much like the unexpected correlations we aim to unravel.
In the realm of cinematic portrayals that echo our themes, "Thank You for Smoking" and "The Motorcycle Diaries" stand out as thought-provoking depictions of political influence and societal dynamics, offering nuanced perspectives that resonate with the intricacies of our investigation. While the silver screen may seem worlds apart from statistical analyses, the ability of film to capture the complexities of human behavior and its manifold influences cannot be underestimated.
As we traverse through the spectrum of literature, both scholarly and speculative, we find ourselves on a path laced with unexpected connections and serendipitous revelations. The insightful works of esteemed authors and the imaginative realms of fiction and film serve as beacons in our quest to unravel the enigmatic link between the voting trends in North Carolina and the consumption of LPG in Haiti. With each page turned and each reel unspooled, we inch closer to unraveling the Gordian knot of improbable correlations, eager to uncover the hidden threads that bind together the seemingly disparate elements of political preferences and energy consumption.

[[RESULTS]]
The results of our investigation into the correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti left us both baffled and amused. To our astonishment, we uncovered a correlation coefficient of 0.9587247, an r-squared value of 0.9191531, and a p-value of less than 0.01 for the period spanning from 1980 to 2020. It seems that the unpredictable nature of human behavior and societal dynamics has once again defied our expectations, leading us down an unexpected yet intriguing path of discovery.
Upon careful examination of the data, it became apparent that the relationship between these two variables is as robust as a well-constructed statistical model. The scatterplot presented in Figure 1 illustrates the strikingly strong correlation between votes for the Libertarian candidate in North Carolina and LPG consumption in Haiti. One might even say that the correlation is as clear as a crystal ball in the hands of a fortuneteller.
As we take a moment to reflect on these findings, it is worth noting that while correlation does not imply causation, it certainly piques our interest and ignites our curiosity. The intricate dance of data points on the scatterplot brings to mind the harmonious movements of celestial bodies in the night sky, captivating our attention with their mesmerizing patterns and unexpected connections.
In conclusion, our research has unearthed a surprising link between political inclinations in North Carolina and the consumption of LPG in Haiti. This discovery serves as a testament to the untamed complexity of human behaviors and the fascinating interplay of diverse variables on a global scale. As we eagerly anticipate further explorations in the realm of improbable correlations, we are reminded that the world of statistical analysis is full of delightful surprises, waiting to be uncovered by intrepid researchers and curious minds.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The uncanny correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti has left us marveling at the unexpected ways in which disparate variables can intertwine. While our research initially set out to explore an eyebrow-raising connection, the robust statistical evidence we have uncovered supports the notion that there is indeed more than meets the eye, much like a magician's sleight of hand that leaves audiences both bewildered and intrigued.

Drawing from the diverse web of scholarly literature, we now find ourselves in the remarkable position of substantiating the seemingly whimsical link that had initially captured our collective imagination. The playful musings on the interplay between political turbulence and energy landscapes, as hinted at by Smith's (2015) exploration, have evolved into a tangible manifestation of statistical significance. Similarly, Doe's (2017) insightful analysis of voting patterns echoes in our findings, demonstrating that electoral decisions may indeed cast unexpected shadows in the far reaches of international energy consumption.

The meandering path through non-fiction works further deepens the empirical groundwork laid by our investigation, shedding light on the multifaceted dynamics at play. The tangential nod to the literary world, while seemingly whimsical, holds a mirror to the entwined fabric of reality and rumor. It is as if the whimsical inventions of Ayn Rand and Graham Greene, intended as mere flights of fancy, have assumed a measure of tangible relevance in our scientific pursuits, much like the unexpected coherence we have unraveled in our data.

As we delve deeper into the implications of our findings, it becomes clear that the relationship between political leanings in North Carolina and LPG consumption in Haiti is not a mere statistical artifact, but a fascinating window into the nuanced interconnections that thread through the tapestry of human behavior. It is akin to stumbling upon an unexpected punchline that offers a moment of revelation, blending the gravity of research with the lighthearted delight of discovery.

In this pursuit of knowledge, we are reminded that the realm of statistical analysis is akin to a whimsical playground, where unexpected connections and curious correlations lie in wait, ready to surprise and delight those who venture forth with inquisitive minds. As we ponder the implications of this unlikely link, we are reminded that the tapestry of human behavior and societal interactions is a canvas painted with vibrant hues of unpredictability and fascination. In unraveling the enigma of improbable correlations, we find ourselves not only as researchers seeking answers but as curious wanderers in the maze of human curiosities, navigating through the hidden pathways that link together the seemingly unconnected facets of our world.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 North Carolina and Liquefied petroleum gas used in Haiti. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti"

[[ABSTRACT]]
In this paper, we delve into the curious correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. While this connection may seem as improbable as finding a needle in a haystack, our research aims to shed light on this peculiarity. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncover a correlation coefficient of 0.9587247 and p < 0.01 for the years spanning from 1980 to 2020.

Through our rigorous analysis, we aim to dispel any lingering doubts and dispense with the notion that these two seemingly disparate phenomena are mere happenstance. Our findings provide a glimpse into the fascinating world of regional political preferences and energy consumption patterns, illuminating unexpected connections that might otherwise be overlooked. We hope this study not only provides valuable insights into the seemingly unrelated, but also sparks further interest in the colorful tapestry of human behavior and societal interactions.

[[INTRDUCTION]]
As we embark on a scholarly journey of statistical analysis and serendipitous discoveries, we find ourselves drawn to the perplexing correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. While the mere mention of this connection might prompt some to raise an eyebrow (or perhaps even two), our inquisitive minds have led us to investigate this unusual pairing with keen interest and a healthy dose of skepticism.
It is not often that one finds themselves walking down the path of statistical analysis and suddenly stumbling upon a connection that seems as unlikely as spotting a flamingo in a snowstorm. However, armed with an arsenal of data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we embarked on our academic escapade to uncover the enigmatic relationship between political proclivities in the Tar Heel State and the consumption of LPG in the far-flung reaches of Haiti.
We are well aware that delving into such peculiar connections and correlations may appear akin to pursuing a scientific wild goose chase. However, our pursuit of knowledge knows no bounds, and we stand before you today with a robust correlation coefficient of 0.9587247 and a p-value of less than 0.01 to support our seemingly outlandish claims. It is with a mix of excitement and bewilderment that we present our findings, with the hope of leaving no stone unturned and no hypothesis unexplored.
As we venture into the labyrinth of numerical data and statistical models, we aim to unravel the mystery behind this unlikely pairing and provide a peek into the whimsical world of human behavior and societal peculiarities. So, dear reader, fasten your seatbelts and prepare to be whisked away into the kaleidoscopic realm of improbable correlations and unexpected associations. For in the realm of scholarly pursuits, the unexpected often yields the most intriguing revelations.

[[RESULTS]]
The results of our investigation into the correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti left us both baffled and amused. To our astonishment, we uncovered a correlation coefficient of 0.9587247, an r-squared value of 0.9191531, and a p-value of less than 0.01 for the period spanning from 1980 to 2020. It seems that the unpredictable nature of human behavior and societal dynamics has once again defied our expectations, leading us down an unexpected yet intriguing path of discovery.
Upon careful examination of the data, it became apparent that the relationship between these two variables is as robust as a well-constructed statistical model. The scatterplot presented in Figure 1 illustrates the strikingly strong correlation between votes for the Libertarian candidate in North Carolina and LPG consumption in Haiti. One might even say that the correlation is as clear as a crystal ball in the hands of a fortuneteller.
As we take a moment to reflect on these findings, it is worth noting that while correlation does not imply causation, it certainly piques our interest and ignites our curiosity. The intricate dance of data points on the scatterplot brings to mind the harmonious movements of celestial bodies in the night sky, captivating our attention with their mesmerizing patterns and unexpected connections.
In conclusion, our research has unearthed a surprising link between political inclinations in North Carolina and the consumption of LPG in Haiti. This discovery serves as a testament to the untamed complexity of human behaviors and the fascinating interplay of diverse variables on a global scale. As we eagerly anticipate further explorations in the realm of improbable correlations, we are reminded that the world of statistical analysis is full of delightful surprises, waiting to be uncovered by intrepid researchers and curious minds.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In culmination, our study has brought to light a compelling correlation between votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. Like a pair of mismatched socks, these seemingly unrelated phenomena have revealed a remarkably strong and improbable bond, leaving us both puzzled and amused. Our findings, with a correlation coefficient of 0.9587247 and a p-value of less than 0.01, serve as a testament to the whimsical nature of statistical analysis and the unpredictable connections that lie beneath the surface of seemingly disparate variables.

As we bring this scholarly escapade to a close, we are left with a sense of awe and wonder at the enigmatic interplay of human behavior, regional preferences, and energy consumption patterns. It is akin to unravelling a mystery novel, only to find that the most improbable suspect turns out to be the culprit.

In the spirit of scientific inquiry, we must acknowledge that correlation does not imply causation. However, the unanticipated harmony between these variables sparks the flames of curiosity, much like a Bunsen burner in a high school chemistry lab.

While our research has shed light on this unlikely correlation, we assert that further exploration in this peculiar realm may yield diminishing returns. Like a well-crafted joke, some enigmas are best left to intrigue and baffle without the need for exhaustive explanation. Therefore, we confidently declare that no additional research in this area is warranted, as sometimes the wondrous mysteries of statistical analysis are best left untouched.

In the words of Albert Einstein, "The most beautiful thing we can experience is the mysterious. It is the source of all true art and science." And indeed, in the realm of scholarly pursuits, the bizarre and improbable often yield the most delightful and unforeseen discoveries. With this, we bid adieu to the curious correlation between votes for the Libertarian candidate in North Carolina and LPG consumption in Haiti, leaving it to thrive in the annals of statistical oddities.

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 Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eclectic Economic Research

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 Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Appalachian Economic and Environmental Studies

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 Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti with an abstract of In this paper, we delve into the curious correlation between the votes for the Libertarian presidential candidate in North Carolina and the consumption of liquefied petroleum gas (LPG) in Haiti. While this connection may seem as improbable as finding a needle in a haystack, our research aims to shed light on this peculiarity. Utilizing data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we uncover a correlation coefficient of 0.9587247 and p < 0.01 for the years spanning from 1980 to 2020.
Through our rigorous analysis, we aim to dispel any lingering doubts and dispense with the notion that these two seemingly disparate phenomena are mere happenstance. Our findings provide a glimpse into the fascinating world of regional political preferences and energy consumption patterns, illuminating unexpected connections that might otherwise be overlooked. We hope this study not only provides valuable insights into the seemingly unrelated, but also sparks further interest in the colorful tapestry of human behavior and societal interactions.

ChatGPT:

Libertarian presidential candidate, North Carolina, LPG consumption, Haiti, correlation, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, correlation coefficient, regional political preferences, energy consumption patterns, human behavior, societal interactions.

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

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Data details

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

Liquefied petroleum gas used in Haiti
Detailed data title: Volume of liquefied petroleum gas used consumed in Haiti in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Liquefied petroleum gas used in Haiti

Correlation r = 0.9587247 (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 = 0.9191531 (Coefficient of determination)
This means 91.9% of the change in the one variable (i.e., Liquefied petroleum gas used in Haiti) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in North Carolina) over the 10 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.21E-5.^Show 0.0000120799100263146390000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.96 in 0.00121% of random cases. Said differently, if you correlated 82,782 random variables^Note You don't actually need 82 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 9 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.83, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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.

	1980	1984	1992	1996	2000	2004	2008	2012	2016	2020
Votes for the Libertarian Presidential candidate in North Carolina (Percentage of votes)	0.521437	0.174408	0.197982	0.347403	0.476537	0.335075	0.59668	0.988043	2.74437	0.881081
Liquefied petroleum gas used in Haiti (Million Barrels/Day)	0.122449	0.0816327	0.2	0.2	0.380328	0.126776	0.31694	0.412283	1	0.321184

Why this works

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.
Lack of causal connection: There is probably^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.
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.
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^Note 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.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} 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([0.521437,0.174408,0.197982,0.347403,0.476537,0.335075,0.59668,0.988043,2.74437,0.881081,])
array_2 = np.array([0.122449,0.0816327,0.2,0.2,0.380328,0.126776,0.31694,0.412283,1,0.321184,])
array_1_name = "Votes for the Libertarian Presidential candidate in North Carolina"
array_2_name = "Liquefied petroleum gas used in Haiti"

# 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. ^Note 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:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Votes for the Libertarian Presidential candidate in North Carolina
Line chart for only Liquefied petroleum gas used in Haiti
AI-generated correlation image
The spurious research paper: Up in Smoke: Uncovering the Libertarian Link between the Tar Heel State and LPG Consumption in Haiti

View another random correlation

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Correlation ID: 4659 · Black Variable ID: 26146 · Red Variable ID: 24510


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