Spurious correlation #4,448 · 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 Democratic Presidential candidate in Arkansas and the second variable is Kerosene used in Philippines. 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 Democratic Presidential candidate in Arkansas and the second variable is Kerosene used in Philippines. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the excitement for the Democrat candidate waned in Arkansas, so did the interest in political debates. With fewer debates, there was a reduced need for fiery rhetoric. This led to a sudden surplus of unused political fuel. To prevent this unbridled energy from contaminating the political landscape, it was promptly packaged and sent as 'aid' to the Philippines. Little did they know, this unconventional shipment of passion-infused kerosene sparked a wave of unexpected unity and ignited a spirit of compromise. As the flames of political fervor flickered in households across the Philippines, so did the consumption of kerosene, proving that even in the most politically charged situations, there's always a bright side. The moral of the story? When it comes to the interplay of American votes and Filipino kerosene, it seems that in the game of global connections, all's fair in love and pyrotechnics!

^{Show image generation prompt} Model: dalle-3
Prompt: Image generation prompt: Generate an image inspired by a TIME magazine cover depicting the scene of a glowing crate of packaged political fuel being shipped from Arkansas to the Philippines. The unconventional shipment is shown to spark unexpected unity and compromise in the Philippines, with the passion-infused kerosene causing flames of political fervor and the consumption of kerosene to flicker. 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 Democrat Presidential candidate in Arkansas and Kerosene used in Philippines. 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 photo-realistic image Surrealism a Polaroid photo a funny image you would see on reddit A TIME magazine cover image
ChatGPT: A TIME 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 Democrat Presidential candidate in Arkansas and Kerosene used in Philippines, in the following situation: As the excitement for the Democrat candidate waned in Arkansas, so did the interest in political debates. With fewer debates, there was a reduced need for fiery rhetoric. This led to a sudden surplus of unused political fuel. To prevent this unbridled energy from contaminating the political landscape, it was promptly packaged and sent as 'aid' to the Philippines. Little did they know, this unconventional shipment of passion-infused kerosene sparked a wave of unexpected unity and ignited a spirit of compromise. As the flames of political fervor flickered in households across the Philippines, so did the consumption of kerosene, proving that even in the most politically charged situations, there's always a bright side. The moral of the story? When it comes to the interplay of American votes and Filipino kerosene, it seems that in the game of global connections, all's fair in love and pyrotechnics!. Keep the description simple.
ChatGPT: In Arkansas, as the interest in the Democrat Presidential candidate waned, fewer political debates were held. This led to a surplus of unused political fuel. This surplus was then packaged and sent as 'aid' to the Philippines. In the Philippines, the unconventional shipment of passion-infused kerosene sparked unexpected unity and compromise – as the flames of political fervor flickered, so did the consumption of kerosene.

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 TIME magazine cover image ] and depicting this scene: In Arkansas, as the interest in the Democrat Presidential candidate waned, fewer political debates were held. This led to a surplus of unused political fuel. This surplus was then packaged and sent as 'aid' to the Philippines. In the Philippines, the unconventional shipment of passion-infused kerosene sparked unexpected unity and compromise – as the flames of political fervor flickered, so did the consumption of kerosene. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Image generation prompt: Generate an image inspired by a TIME magazine cover depicting the scene of a glowing crate of packaged political fuel being shipped from Arkansas to the Philippines. The unconventional shipment is shown to spark unexpected unity and compromise in the Philippines, with the passion-infused kerosene causing flames of political fervor and the consumption of kerosene to flicker.

*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 a decrease in Votes for the Democrat Presidential candidate in Arkansas caused Kerosene used in Philippines to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines

The Journal of Absurd Sociopolitical Correlations

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Democrat Presidential candidate in Arkansas and Kerosene used in Philippines. 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. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
"Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines"

[[ABSTRACT]]
This paper presents an unexpected and eyebrow-raising study on the relationship between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration were utilized to explore this unorthodox connection. Surprisingly, our research team found a remarkably high correlation coefficient of 0.9235069 and statistical significance with p < 0.01 for the years 1980 to 2020. While the findings may seem as improbable as a penguin in the Sahara, this study underscores the importance of carefully examining unexpected correlations and the need for further investigation into the global impact of seemingly unrelated events.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of statistical analysis, researchers often seek to uncover meaningful correlations between seemingly disparate variables. Imagine our surprise when, with a fervor rivaling that of a game show contestant uncovering the grand prize, our investigations revealed an unforeseen link between two seemingly unrelated phenomena: the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Our initial response mirrored that of a person finding a polar bear in their bathtub - incredulity mixed with a touch of amusement.
The aim of this study is to systematically explore this eyebrow-raising connection and shed light on the unexpected relationship between political preferences in the United States and household energy choices in the Philippines. Although the association between voting behavior and energy consumption may sound as improbable as finding a unicorn grazing in your backyard, our rigorous analysis has shown a striking correlation that demands further examination.
As the old adage goes, "correlation does not imply causation." However, the robust statistical relationship we have unearthed cannot be dismissed as easily as a joke at a comedy roast. Thus, we embarked on this research journey with the determination of a detective pursuing a perplexing case, ready to delve into the labyrinth of data and unravel the enigma surrounding these seemingly incongruous variables.
While our findings initially raised eyebrows among our colleagues, we believe that this investigation serves as a reminder of the serendipitous nature of scientific inquiry. Moreover, it highlights the importance of approaching data with an open mind, as even the most unusual correlations may hold valuable insights. As we embark on this odyssey of statistical examination, we invite readers to join us in unraveling this curious tale of Democrat votes and glowing kerosene lamps.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The unexpected correlation between votes for the Democratic presidential candidate in Arkansas and kerosene consumption in the Philippines has sparked scholarly interest and curiosity. Initial literature brought to light by Smith et al. (2015) and Doe (2018) focused on the separate phenomena of political voting behavior and energy consumption patterns but failed to explore any possible interrelationship between the two. Jones (2020) offered a comprehensive analysis of political preferences in the United States but did not venture into the realms of international energy usage. However, as we delved deeper into the literature, we encountered surprising connections and eyebrow-raising insights that would make even the most seasoned statistician do a double-take.

Turning to non-fiction works, "Energy Economics and Policy" by Johnson delves into the intricate dynamics of global energy markets, shedding light on the complexities of energy consumption patterns. Similarly, in "The American Political Tradition" by Hofstadter, the authors provide detailed accounts of political voting behavior and ideological shifts throughout U.S. history. These works contribute to our understanding of the individual variables at play, but the surprising connection between the two variables we investigate here remains unexplored.

Furthermore, fictional works such as "The Kerosene Heir" by Watson and "The Democratic Dilemma" by Garcia unexpectedly offered intriguing perspectives. Although fictional in nature, these novels inadvertently sparked our curiosity, leading to the exploration of uncommon correlations that would make Sherlock Holmes raise an eyebrow in contemplation.

However, as we widened our scope, our investigation led us to unexpected sources of insight. Scrutinizing disparate documents such as grocery lists, tabloid gossip columns, and even the enigmatic contents of a series of CVS receipts, we stumbled upon startling revelations that seemed to hold potential significance in our quest for understanding. While these sources may raise a skeptical eyebrow, their unconventional nature offered a whimsical touch to our scholarly pursuit, infusing our research with a dash of unpredictability.

In the pursuit of understanding this uncanny relationship, our investigation urges readers to adopt a lighthearted perspective and embrace the serendipitous nature of scholarly discovery. As we delve deeper into the intricacies of this unexpected correlation, we invite our fellow academics to join us in unraveling the enigma of Democrat votes and glowing kerosene lamps, with a hint of whimsy and an open mind.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Democrat Presidential candidate in Arkansas and Kerosene used in Philippines. Make lots of jokes, goofy observations, and puns.

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]]
"Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines"

[[ABSTRACT]]
This paper presents an unexpected and eyebrow-raising study on the relationship between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration were utilized to explore this unorthodox connection. Surprisingly, our research team found a remarkably high correlation coefficient of 0.9235069 and statistical significance with p < 0.01 for the years 1980 to 2020. While the findings may seem as improbable as a penguin in the Sahara, this study underscores the importance of carefully examining unexpected correlations and the need for further investigation into the global impact of seemingly unrelated events.

[[INTRODUCTION]]
In the realm of statistical analysis, researchers often seek to uncover meaningful correlations between seemingly disparate variables. Imagine our surprise when, with a fervor rivaling that of a game show contestant uncovering the grand prize, our investigations revealed an unforeseen link between two seemingly unrelated phenomena: the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Our initial response mirrored that of a person finding a polar bear in their bathtub - incredulity mixed with a touch of amusement.
The aim of this study is to systematically explore this eyebrow-raising connection and shed light on the unexpected relationship between political preferences in the United States and household energy choices in the Philippines. Although the association between voting behavior and energy consumption may sound as improbable as finding a unicorn grazing in your backyard, our rigorous analysis has shown a striking correlation that demands further examination.
As the old adage goes, "correlation does not imply causation." However, the robust statistical relationship we have unearthed cannot be dismissed as easily as a joke at a comedy roast. Thus, we embarked on this research journey with the determination of a detective pursuing a perplexing case, ready to delve into the labyrinth of data and unravel the enigma surrounding these seemingly incongruous variables.
While our findings initially raised eyebrows among our colleagues, we believe that this investigation serves as a reminder of the serendipitous nature of scientific inquiry. Moreover, it highlights the importance of approaching data with an open mind, as even the most unusual correlations may hold valuable insights. As we embark on this odyssey of statistical examination, we invite readers to join us in unraveling this curious tale of Democrat votes and glowing kerosene lamps.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To embark on our quest to unravel the mysterious connection between Democrat votes in Arkansas and kerosene consumption in the Philippines, a multi-faceted approach was essential. The first step involved sourcing data from reputable repositories, akin to a dedicated collector assembling an eclectic assortment of curious artifacts. We gathered data from the MIT Election Data and Science Lab, the Harvard Dataverse, and the Energy Information Administration, covering the expanse of years from 1980 to 2020. These diverse datasets were akin to a rich tapestry, woven from the threads of political participation and energy consumption.

Our next endeavor was to ascertain the integrity of the collected datasets. Visualization and exploratory data analysis served as our trusty sidekicks in this endeavor, akin to the Sherlock Holmes and Dr. Watson of statistical investigation. Before delving into the statistical abyss, we meticulously examined the datasets for anomalies and outliers, ensuring that our analysis would not be thwarted by mischievous data points that could lead us astray, much like a red herring in a detective novel.

With data integrity confirmed, we employed the mathematical wizardry of correlation analysis to unveil the hidden relationship between these seemingly unrelated variables. Employing the Pearson correlation coefficient, we quantified the strength and direction of the association, much like a skilled astronomer determining the magnitude and trajectory of celestial bodies. The statistical significance of the correlation was evaluated using a two-tailed t-test, allowing us to discern whether our findings were as substantial as an elephant in a room or as tenuous as a gossamer thread.

Additionally, we undertook a time-series analysis to capture the dynamic nature of the relationship across the decades, akin to capturing the ebb and flow of the tides in an ever-changing sea. This approach allowed us to discern whether the correlation remained steadfast or wavered over time, shedding light on the temporal nuances of this unexpected phenomenon.

In the noble tradition of scientific inquiry, we acknowledge the limitations of our study. While our analysis reveals a striking correlation, it remains imperative to tread cautiously and refrain from hasty conclusions. Furthermore, the nature of our investigation precludes causal inferences, as the adage "correlation does not imply causation" echoes in the hallowed halls of statistical scrutiny.

In summation, this interdisciplinary expedition encompassed the realms of political science, economics, and statistics, joining forces to unravel the enigmatic nexus between Democrat votes in Arkansas and kerosene consumption in the Philippines. With a blend of rigor, curiosity, and a dash of serendipity, our approach to this unorthodox investigation mirrors the spirit of scientific exploration – embracing the unexpected and unearthing the remarkable amidst the seemingly mundane.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Democrat Presidential candidate in Arkansas and Kerosene used in Philippines. Make lots of jokes, goofy observations, and puns.

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]]
"Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines"

[[ABSTRACT]]
This paper presents an unexpected and eyebrow-raising study on the relationship between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration were utilized to explore this unorthodox connection. Surprisingly, our research team found a remarkably high correlation coefficient of 0.9235069 and statistical significance with p < 0.01 for the years 1980 to 2020. While the findings may seem as improbable as a penguin in the Sahara, this study underscores the importance of carefully examining unexpected correlations and the need for further investigation into the global impact of seemingly unrelated events.

[[LITERATURE REVIEW]]
The unexpected correlation between votes for the Democratic presidential candidate in Arkansas and kerosene consumption in the Philippines has sparked scholarly interest and curiosity. Initial literature brought to light by Smith et al. (2015) and Doe (2018) focused on the separate phenomena of political voting behavior and energy consumption patterns but failed to explore any possible interrelationship between the two. Jones (2020) offered a comprehensive analysis of political preferences in the United States but did not venture into the realms of international energy usage. However, as we delved deeper into the literature, we encountered surprising connections and eyebrow-raising insights that would make even the most seasoned statistician do a double-take.
Turning to non-fiction works, "Energy Economics and Policy" by Johnson delves into the intricate dynamics of global energy markets, shedding light on the complexities of energy consumption patterns. Similarly, in "The American Political Tradition" by Hofstadter, the authors provide detailed accounts of political voting behavior and ideological shifts throughout U.S. history. These works contribute to our understanding of the individual variables at play, but the surprising connection between the two variables we investigate here remains unexplored.
Furthermore, fictional works such as "The Kerosene Heir" by Watson and "The Democratic Dilemma" by Garcia unexpectedly offered intriguing perspectives. Although fictional in nature, these novels inadvertently sparked our curiosity, leading to the exploration of uncommon correlations that would make Sherlock Holmes raise an eyebrow in contemplation.
However, as we widened our scope, our investigation led us to unexpected sources of insight. Scrutinizing disparate documents such as grocery lists, tabloid gossip columns, and even the enigmatic contents of a series of CVS receipts, we stumbled upon startling revelations that seemed to hold potential significance in our quest for understanding. While these sources may raise a skeptical eyebrow, their unconventional nature offered a whimsical touch to our scholarly pursuit, infusing our research with a dash of unpredictability.
In the pursuit of understanding this uncanny relationship, our investigation urges readers to adopt a lighthearted perspective and embrace the serendipitous nature of scholarly discovery. As we delve deeper into the intricacies of this unexpected correlation, we invite our fellow academics to join us in unraveling the enigma of Democrat votes and glowing kerosene lamps, with a hint of whimsy and an open mind.

[[RESULTS]]
In delving into the perplexing realm of unexpected correlations, our research team unearthed a truly astonishing finding: a substantial correlation between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. The correlation coefficient of 0.9235069 and an r-squared of 0.8528649 for the period spanning 1980 to 2020 left us as gobsmacked as a magician who accidentally made a rabbit disappear into thin air. The p-value of less than 0.01 further cemented the statistical significance of this eyebrow-raising relationship, leaving us scratching our heads in bemusement.
Visualizing this surprising correlation in a scatterplot (refer to Fig. 1) reveals a clear and robust association, reminiscent of a well-choreographed dance between political preferences and household energy choices. As remarkable as finding a pot of gold at the end of a statistical rainbow, this unexpected finding emphasizes the need to approach data with an open mind, acknowledging that even the most seemingly incongruous variables may indeed be interconnected.
While our initial reaction to this finding was one of incredulity and amusement akin to discovering a talking parrot in a library, this study offers an important lesson in the unpredictable nature of scientific inquiry. The substantial correlation between democratic votes and kerosene consumption, though as seemingly disconnected as a fish riding a bicycle, underscores the importance of unearthing hidden relationships that may hold crucial implications for understanding global phenomena.
In summary, the correlation between democrat votes in Arkansas and kerosene consumption in the Philippines, while initially raising eyebrows and prompting a few raised bemused chuckles, warrants further investigation and consideration. Our surprising discovery emphasizes the need for continued exploration of unexpected correlations and invites researchers and stakeholders to ponder the intricate interplay of seemingly unrelated events.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The remarkable correlation between votes for the Democratic presidential candidate in Arkansas and kerosene consumption in the Philippines may initially appear as incongruous as a penguin in the Sahara, but our results have provided unequivocal support for this unexpected association. Our findings not only bolster the prior research that hinted at this peculiar relationship but also lend credence to the idea that sometimes, connections between seemingly unrelated phenomena can be as clear as a day at the beach, even if they are as surprising as finding a kangaroo in the Arctic.

Our study's robust correlation coefficient of 0.9235069, akin to finding the missing piece to a complex puzzle moonlighting as a paperweight, aligns with prior work by Smith et al. (2015) and Doe (2018), who inadvertently laid the groundwork for our eyebrow-raising discovery. While their research primarily focused on distinct aspects of political voting behavior and energy consumption patterns, our study leaps into uncharted territory, shedding light on the mysterious dance between democratic preferences and kerosene-fueled illumination in Filipino households.

The statistical significance of our findings, with a p-value of less than 0.01, serves as a resounding confirmation of the unexpected connection between these two seemingly disparate variables. This statistical significance, comparable to stumbling upon a four-leaf clover in a field of three-leaf variants, underscores the need to approach serendipitous correlations with the same gravity and curiosity as we do with more conventional relationships.

While our results may prompt a few raised eyebrows and bemused chuckles reminiscent of a circus audience discovering a clown with a Ph.D., they emphasize the paramount importance of embracing unpredictability in the realm of academic inquiry. The unexpected correlation between democrat votes in Arkansas and kerosene consumption in the Philippines serves as a whimsical reminder that scholarly discoveries can sprout from the most unlikely sources, much like finding a fruitful garden in the middle of a desert.

In unraveling this enigmatic relationship, our research advocates for a lighthearted approach, akin to discovering a hidden treasure where least expected. By encouraging a playful engagement with unconventional correlations, we hope to spark scholarly curiosity and prompt fellow researchers to chart a course into unexplored territories, much like intrepid explorers setting sail for new and uncharted lands.

This unexpected correlation, as confounding as a riddle wrapped in a mystery inside an enigma, calls for continued investigation and consideration. As we invite our fellow academics to join us in this scholarly pursuit, we emphasize the importance of acknowledging the whimsy and wonder that can accompany the unearthing of unexpected relationships - after all, scholarly inquiry can be as surprising as finding a pancake in the shape of the Mona Lisa.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Democrat Presidential candidate in Arkansas and Kerosene used in Philippines. Make lots of jokes, goofy observations, and puns.

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]]
"Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines"

[[ABSTRACT]]
This paper presents an unexpected and eyebrow-raising study on the relationship between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration were utilized to explore this unorthodox connection. Surprisingly, our research team found a remarkably high correlation coefficient of 0.9235069 and statistical significance with p < 0.01 for the years 1980 to 2020. While the findings may seem as improbable as a penguin in the Sahara, this study underscores the importance of carefully examining unexpected correlations and the need for further investigation into the global impact of seemingly unrelated events.

[[INTRDUCTION]]
In the realm of statistical analysis, researchers often seek to uncover meaningful correlations between seemingly disparate variables. Imagine our surprise when, with a fervor rivaling that of a game show contestant uncovering the grand prize, our investigations revealed an unforeseen link between two seemingly unrelated phenomena: the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Our initial response mirrored that of a person finding a polar bear in their bathtub - incredulity mixed with a touch of amusement.
The aim of this study is to systematically explore this eyebrow-raising connection and shed light on the unexpected relationship between political preferences in the United States and household energy choices in the Philippines. Although the association between voting behavior and energy consumption may sound as improbable as finding a unicorn grazing in your backyard, our rigorous analysis has shown a striking correlation that demands further examination.
As the old adage goes, "correlation does not imply causation." However, the robust statistical relationship we have unearthed cannot be dismissed as easily as a joke at a comedy roast. Thus, we embarked on this research journey with the determination of a detective pursuing a perplexing case, ready to delve into the labyrinth of data and unravel the enigma surrounding these seemingly incongruous variables.
While our findings initially raised eyebrows among our colleagues, we believe that this investigation serves as a reminder of the serendipitous nature of scientific inquiry. Moreover, it highlights the importance of approaching data with an open mind, as even the most unusual correlations may hold valuable insights. As we embark on this odyssey of statistical examination, we invite readers to join us in unraveling this curious tale of Democrat votes and glowing kerosene lamps.

[[RESULTS]]
In delving into the perplexing realm of unexpected correlations, our research team unearthed a truly astonishing finding: a substantial correlation between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. The correlation coefficient of 0.9235069 and an r-squared of 0.8528649 for the period spanning 1980 to 2020 left us as gobsmacked as a magician who accidentally made a rabbit disappear into thin air. The p-value of less than 0.01 further cemented the statistical significance of this eyebrow-raising relationship, leaving us scratching our heads in bemusement.
Visualizing this surprising correlation in a scatterplot (refer to Fig. 1) reveals a clear and robust association, reminiscent of a well-choreographed dance between political preferences and household energy choices. As remarkable as finding a pot of gold at the end of a statistical rainbow, this unexpected finding emphasizes the need to approach data with an open mind, acknowledging that even the most seemingly incongruous variables may indeed be interconnected.
While our initial reaction to this finding was one of incredulity and amusement akin to discovering a talking parrot in a library, this study offers an important lesson in the unpredictable nature of scientific inquiry. The substantial correlation between democratic votes and kerosene consumption, though as seemingly disconnected as a fish riding a bicycle, underscores the importance of unearthing hidden relationships that may hold crucial implications for understanding global phenomena.
In summary, the correlation between democrat votes in Arkansas and kerosene consumption in the Philippines, while initially raising eyebrows and prompting a few raised bemused chuckles, warrants further investigation and consideration. Our surprising discovery emphasizes the need for continued exploration of unexpected correlations and invites researchers and stakeholders to ponder the intricate interplay of seemingly unrelated events.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has unraveled a connection between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines that is as unlikely as finding a unicorn in a petting zoo. The robust correlation coefficient of 0.9235069 and statistical significance with p < 0.01 for the years 1980 to 2020 has left us as astonished as a magician who accidentally sawed their assistant in half.

As we attempted to wrap our minds around this improbable link between political preferences in the United States and household energy choices in the Philippines, we couldn't help but feel like detectives stumbling upon a pink elephant while solving a case.

The visual representation of this unexpected correlation in a scatterplot (refer to Fig. 1) is as clear as a carefully crafted punchline at a comedy club, indicating a strong association between the two variables. Our findings emphasize the importance of staying open-minded, as even the most peculiar correlations may hold valuable insights, much like discovering a treasure map in a bottle on a desert island.

While our initial reaction to this discovery was one of skepticism and amusement akin to finding a penguin in the tropics, this study offers a valuable lesson in the unpredictable nature of scientific inquiry. Much like a plot twist in a mystery novel, the substantial correlation we have uncovered between democratic votes and kerosene consumption underscores the need to delve deeper into seemingly incongruous connections that may have far-reaching implications.

In light of these surprising findings, we assert with confidence that no further research is needed in this area. The correlation between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines is a fascinating anomaly that should be celebrated for its unexpectedness. With a conclusion as clear as a knock-knock joke, we implore future researchers to seek out similarly quirky connections, for it is in these unexpected places that the most fascinating discoveries lie.

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 Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Absurd Sociopolitical Correlations

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 Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Absurd Social Science Research

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 Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines with an abstract of This paper presents an unexpected and eyebrow-raising study on the relationship between the number of votes for the Democratic presidential candidate in Arkansas and the consumption of kerosene in the Philippines. Data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration were utilized to explore this unorthodox connection. Surprisingly, our research team found a remarkably high correlation coefficient of 0.9235069 and statistical significance with p < 0.01 for the years 1980 to 2020. While the findings may seem as improbable as a penguin in the Sahara, this study underscores the importance of carefully examining unexpected correlations and the need for further investigation into the global impact of seemingly unrelated events.

ChatGPT:

Democratic votes Arkansas, kerosene consumption Philippines, correlation study, unexpected correlations, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, statistical significance, global impact, unorthodox connection, research findings

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

Kerosene used in Philippines
Detailed data title: Volume of kerosene used consumed in Philippines in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Kerosene used in Philippines

Correlation r = 0.9235069 (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 = 0.8528649 (Coefficient of determination)
This means 85.3% of the change in the one variable (i.e., Kerosene used in Philippines) is predictable based on the change in the other (i.e., Votes for the Democratic Presidential candidate in Arkansas) over the 11 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.0E-5.^Show 0.0000495972436932481840000000
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 0.92 in 0.005% of random cases. Said differently, if you correlated 20,162 random variables^Note You don't actually need 20 thousand variables to find a correlation like this one. 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.

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 10 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.73, 0.98 ] 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	1988	1992	1996	2000	2004	2008	2012	2016	2020
Votes for the Democratic Presidential candidate in Arkansas (Percentage of votes)	47.5226	38.2908	42.1917	53.208	53.7365	45.8643	44.5476	38.8647	36.879	33.6531	34.7751
Kerosene used in Philippines (Million Barrels/Day)	8.81238	6.54075	7.6	11	13	11.9118	7.79336	6.37831	2.61891	2	1.45564

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

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([47.5226,38.2908,42.1917,53.208,53.7365,45.8643,44.5476,38.8647,36.879,33.6531,34.7751,])
array_2 = np.array([8.81238,6.54075,7.6,11,13,11.9118,7.79336,6.37831,2.61891,2,1.45564,])
array_1_name = "Votes for the Democratic Presidential candidate in Arkansas"
array_2_name = "Kerosene used in Philippines"

# 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 Democratic Presidential candidate in Arkansas
Line chart for only Kerosene used in Philippines
AI-generated correlation image
The spurious research paper: Burning Questions: An Examination of the Surprising Correlation Between Democrat Votes in Arkansas and Kerosene Consumption in the Philippines

View another random correlation

How fun was this correlation?

I'm grateful for your review!

Correlation ID: 4448 · Black Variable ID: 26058 · Red Variable ID: 24816


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: