Spurious correlation #5,606 · 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 Democratic Senators in Wyoming and the second variable is Jet fuel used in Niue. The chart goes from 2000 to 2018, 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 Democratic Senators in Wyoming and the second variable is Jet fuel used in Niue. The chart goes from 2000 to 2018, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the Democratic support soared in the Cowboy State, so did the demand for fancy Democratic campaign events. This led to an influx of private jets flying in, consequently boosting the consumption of jet fuel. It seems like the blue wave didn't just impact the political landscape, but also created some turbulence in the skies above Niue!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that combines the iconic style of a TIME magazine cover with the following scene: In a wide open Wyoming field, a line of voters snakes out of a polling station, with a bright blue Democratic banner fluttering in the crisp breeze. Meanwhile, above the lush, green landscape of Niue, a cluster of private jets descend in the sky, leaving behind a trail of jet fuel as they approach the island's runway. The image should be visually striking and show these two distinct scenes blending seamlessly. 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 Democratic Senators in Wyoming and Jet fuel used in Niue. 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: Photorealism An image that looks like it is a scene from a Pixar movie Psychedelic A TIME magazine cover image A scene from Skyrim
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 Democratic Senators in Wyoming and Jet fuel used in Niue, in the following situation: As the Democratic support soared in the Cowboy State, so did the demand for fancy Democratic campaign events. This led to an influx of private jets flying in, consequently boosting the consumption of jet fuel. It seems like the blue wave didn't just impact the political landscape, but also created some turbulence in the skies above Niue!. Keep the description simple.
ChatGPT: In a wide open Wyoming field, a line of voters snakes out of a polling station, with a bright blue Democratic banner fluttering in the crisp breeze. Meanwhile, above the lush, green landscape of Niue, a cluster of private jets descend in the sky, leaving behind a trail of jet fuel as they approach the island's runway.

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 a wide open Wyoming field, a line of voters snakes out of a polling station, with a bright blue Democratic banner fluttering in the crisp breeze. Meanwhile, above the lush, green landscape of Niue, a cluster of private jets descend in the sky, leaving behind a trail of jet fuel as they approach the island's runway. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that combines the iconic style of a TIME magazine cover with the following scene: In a wide open Wyoming field, a line of voters snakes out of a polling station, with a bright blue Democratic banner fluttering in the crisp breeze. Meanwhile, above the lush, green landscape of Niue, a cluster of private jets descend in the sky, leaving behind a trail of jet fuel as they approach the island's runway. The image should be visually striking and show these two distinct scenes blending seamlessly.

*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 Democrat votes for Senators in Wyoming positively influenced Jet fuel used in Niue. Include one good pun.

AI academic paper

(Because p < 0.05)

Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue

The Journal of Political Meteorology

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 Democrat votes for Senators in Wyoming and Jet fuel used in Niue. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue"

[[ABSTRACT]]
This research examines the peculiar relationship between the voting preferences of Democrats for Senators in Wyoming and the amount of jet fuel used in the obscure island nation of Niue, nestled in the South Pacific. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our study reveals a surprising connection between these seemingly unrelated elements. The correlation coefficient of 0.8650622 and a p-value of less than 0.05 for the years 2000 to 2018 provide strong statistical evidence of this unexpected association.

Utilizing rigorous statistical analysis, we found that as the number of Democrat votes for Senators in Wyoming increased, there was a corresponding rise in the amount of jet fuel utilized in Niue. This phenomenon defies conventional wisdom and uncovers an intriguing interplay between political leanings in landlocked Wyoming and aviation fuel consumption in the far-off island of Niue.

In light of these findings, we propose that further investigation is warranted to unravel the mechanisms underlying this unlikely correlation, taking into account the landlocked nature of Wyoming, the remoteness of Niue, and potential confounding variables. As we dig into these peculiar connections, it becomes clear that there is more than meets the eye, much like the father who can channel the voting tendencies of Wyoming and the jet fuel of Niue into a single pun.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the world of scientific research, one often comes across unexpected connections and peculiar correlations that boggle the mind and challenge conventional wisdom. It is akin to stumbling upon a statistical anomaly that leaves one scratching their head in bewilderment, much like the perplexing relationship between the voting patterns of Democrats in Wyoming and the jet fuel consumption in the remote island nation of Niue.
Now, I may not be a dad myself, but I must say, uncovering the connection between these seemingly disparate variables was as surprising as finding an electron in a hayfield – quite the "negative" search result for the protons out there. The statistical analysis revealed a correlation that was stronger than the caffeine content in a freshly brewed cup of coffee – a caffeinated relationship, if you will.
The findings of this research project have stirred up more curiosity than a beaker of vinegar and baking soda in a middle school science fair volcano demonstration. The statistical evidence suggests a connection as robust as the polymer chains in a well-constructed DNA helix – binding together two distant entities in an unanticipated manner.
As we embark on this scholarly exploration, let us remember that science often surprises us in ways that are as mind-bending as a Möbius strip – bending reality in unexpected ways, much like the enigmatic relationship between Wyoming's voting behaviors and Niue's jet fuel usage. This investigation aims to shed light on the intricacies of these unexpected connections, much like a beacon guiding lost statistical travelers through the fog of uncertainty.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The connection between the Democratic votes for Senators in Wyoming and the amount of jet fuel used in Niue has spawned a unique area of research that has attracted the attention of scholars from diverse disciplines. Smith et al. (2010) investigated the potential influences of political inclinations in the continental United States on distant ecological systems, while Doe (2012) scrutinized the global effects of micro-level political decisions on transoceanic transportation fuel consumption. Furthermore, Jones (2015) delved into the socio-political dynamics of remote island nations and their unexpected interplay with electoral behaviors in American heartland states.

Turning to the interdisciplinary nature of this topic, it is evident that a multitude of non-fiction books have addressed similar phenomena. "The Butterfly Effect" by Gleick (1987) explores the interconnectedness of seemingly unrelated events, akin to the surprising association between voting patterns in Wyoming and jet fuel usage in Niue. Additionally, "Freakonomics" by Levitt and Dubner (2005) delves into the unexpected correlations that underpin complex societal interactions, offering a lens through which to view the unanticipated relationship at the heart of this investigation.

In the realm of fiction, works such as "Cloud Atlas" by David Mitchell and "American Gods" by Neil Gaiman illustrate the unexpected interweaving of disparate elements, resonating with the enigmatic correlation under scrutiny in this study. These literary works provide an allegorical backdrop for understanding the intricacies of the relationship between political preferences in landlocked Wyoming and aviation fuel consumption in the remote expanse of Niue.

Furthermore, cinematic productions such as "The Secret Life of Walter Mitty" and "Up in the Air" offer narratives that touch on themes of unexpected connections and far-reaching impacts, analogous to the surprising linkage between political voting behavior and jet fuel usage. These films contribute a visual dimension to the perplexing relationship explored in this research, reminding us that truth can indeed be stranger than fiction.

As the scholarly investigation of the peculiar correlation between Democrat votes for Senators in Wyoming and the consumption of jet fuel in Niue unfolds, it becomes apparent that this area of inquiry extends beyond the realms of conventional scientific understanding and ventures into the territory of the absurd and the unexpected – much like a punchline that catches you off guard.

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 Democrat votes for Senators in Wyoming and Jet fuel used in Niue. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 2000 to 2018

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]]
"Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue"

[[ABSTRACT]]
This research examines the peculiar relationship between the voting preferences of Democrats for Senators in Wyoming and the amount of jet fuel used in the obscure island nation of Niue, nestled in the South Pacific. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our study reveals a surprising connection between these seemingly unrelated elements. The correlation coefficient of 0.8650622 and a p-value of less than 0.05 for the years 2000 to 2018 provide strong statistical evidence of this unexpected association.

Utilizing rigorous statistical analysis, we found that as the number of Democrat votes for Senators in Wyoming increased, there was a corresponding rise in the amount of jet fuel utilized in Niue. This phenomenon defies conventional wisdom and uncovers an intriguing interplay between political leanings in landlocked Wyoming and aviation fuel consumption in the far-off island of Niue.

In light of these findings, we propose that further investigation is warranted to unravel the mechanisms underlying this unlikely correlation, taking into account the landlocked nature of Wyoming, the remoteness of Niue, and potential confounding variables. As we dig into these peculiar connections, it becomes clear that there is more than meets the eye, much like the father who can channel the voting tendencies of Wyoming and the jet fuel of Niue into a single pun.

[[INTRODUCTION]]
In the world of scientific research, one often comes across unexpected connections and peculiar correlations that boggle the mind and challenge conventional wisdom. It is akin to stumbling upon a statistical anomaly that leaves one scratching their head in bewilderment, much like the perplexing relationship between the voting patterns of Democrats in Wyoming and the jet fuel consumption in the remote island nation of Niue.
Now, I may not be a dad myself, but I must say, uncovering the connection between these seemingly disparate variables was as surprising as finding an electron in a hayfield – quite the "negative" search result for the protons out there. The statistical analysis revealed a correlation that was stronger than the caffeine content in a freshly brewed cup of coffee – a caffeinated relationship, if you will.
The findings of this research project have stirred up more curiosity than a beaker of vinegar and baking soda in a middle school science fair volcano demonstration. The statistical evidence suggests a connection as robust as the polymer chains in a well-constructed DNA helix – binding together two distant entities in an unanticipated manner.
As we embark on this scholarly exploration, let us remember that science often surprises us in ways that are as mind-bending as a Möbius strip – bending reality in unexpected ways, much like the enigmatic relationship between Wyoming's voting behaviors and Niue's jet fuel usage. This investigation aims to shed light on the intricacies of these unexpected connections, much like a beacon guiding lost statistical travelers through the fog of uncertainty.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The data for this research was amassed through a rigorous and somewhat unconventional process, involving a blend of digital archaeology, statistical sorcery, and a liberal sprinkling of luck. Our dexterous team of researchers scoured the MIT Election Data and Science Lab, the Harvard Dataverse, and the Energy Information Administration to unearth the relevant datasets spanning the years 2000 to 2018. This involved navigating through more data points than there are grains of sand on a statistical beach, but we persisted with the determination of a determined squirrel seeking out the elusive nut of knowledge.

Having gathered the requisite data, we then embarked on a voyage into the labyrinthine corridors of statistical analysis, armed with an arsenal of scientific tools and a healthy dose of skepticism. Our journey led us through the winding pathways of correlation analysis, where we sought to quantify the strength and direction of the relationship between Democrat votes for Senators in Wyoming and the jet fuel consumption in Niue. Much like a cartographer mapping uncharted territories, we employed the Pearson correlation coefficient to measure the degree of association between these enigmatic variables.

In addition to quantifying the correlation, we wielded the formidable weapon of hypothesis testing to ascertain the statistical significance of our findings. This involved subjecting our data to the relentless scrutiny of p-values, ensuring that the relationship we uncovered was not merely a statistical fluke but a bona fide connection worthy of scientific attention. The use of hypothesis testing was especially crucial in this study, as we sought to distinguish between a meaningful correlation and a "spurious" relationship that would be as credible as claiming that correlation equals causation – a cardinal sin in the realm of empirical inquiry.

The final stage of our methodological odyssey comprised a thorough examination of potential confounding variables, aiming to mitigate the lurking specter of spurious correlations and establish a more robust foundation for our findings. We scrutinized a constellation of socio-economic, geographical, and meteorological factors, weaving a protective web of control variables to shield our analysis from the pernicious influence of lurking confounders.

As we ventured through this methodological labyrinth, we encountered more twists and turns than a rollercoaster designed by a mischievous statistician. Our approach, though unorthodox at times, embodied the spirit of scientific inquiry with a touch of humor – much like a dad joke skilfully interwoven into an academic discussion, eliciting a wry smile from the stoic faces of scholarly readers.

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 Democrat votes for Senators in Wyoming and Jet fuel used in Niue. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue"

[[ABSTRACT]]
This research examines the peculiar relationship between the voting preferences of Democrats for Senators in Wyoming and the amount of jet fuel used in the obscure island nation of Niue, nestled in the South Pacific. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our study reveals a surprising connection between these seemingly unrelated elements. The correlation coefficient of 0.8650622 and a p-value of less than 0.05 for the years 2000 to 2018 provide strong statistical evidence of this unexpected association.

Utilizing rigorous statistical analysis, we found that as the number of Democrat votes for Senators in Wyoming increased, there was a corresponding rise in the amount of jet fuel utilized in Niue. This phenomenon defies conventional wisdom and uncovers an intriguing interplay between political leanings in landlocked Wyoming and aviation fuel consumption in the far-off island of Niue.

In light of these findings, we propose that further investigation is warranted to unravel the mechanisms underlying this unlikely correlation, taking into account the landlocked nature of Wyoming, the remoteness of Niue, and potential confounding variables. As we dig into these peculiar connections, it becomes clear that there is more than meets the eye, much like the father who can channel the voting tendencies of Wyoming and the jet fuel of Niue into a single pun.

[[LITERATURE REVIEW]]
The connection between the Democratic votes for Senators in Wyoming and the amount of jet fuel used in Niue has spawned a unique area of research that has attracted the attention of scholars from diverse disciplines. Smith et al. (2010) investigated the potential influences of political inclinations in the continental United States on distant ecological systems, while Doe (2012) scrutinized the global effects of micro-level political decisions on transoceanic transportation fuel consumption. Furthermore, Jones (2015) delved into the socio-political dynamics of remote island nations and their unexpected interplay with electoral behaviors in American heartland states.
Turning to the interdisciplinary nature of this topic, it is evident that a multitude of non-fiction books have addressed similar phenomena. "The Butterfly Effect" by Gleick (1987) explores the interconnectedness of seemingly unrelated events, akin to the surprising association between voting patterns in Wyoming and jet fuel usage in Niue. Additionally, "Freakonomics" by Levitt and Dubner (2005) delves into the unexpected correlations that underpin complex societal interactions, offering a lens through which to view the unanticipated relationship at the heart of this investigation.
In the realm of fiction, works such as "Cloud Atlas" by David Mitchell and "American Gods" by Neil Gaiman illustrate the unexpected interweaving of disparate elements, resonating with the enigmatic correlation under scrutiny in this study. These literary works provide an allegorical backdrop for understanding the intricacies of the relationship between political preferences in landlocked Wyoming and aviation fuel consumption in the remote expanse of Niue.
Furthermore, cinematic productions such as "The Secret Life of Walter Mitty" and "Up in the Air" offer narratives that touch on themes of unexpected connections and far-reaching impacts, analogous to the surprising linkage between political voting behavior and jet fuel usage. These films contribute a visual dimension to the perplexing relationship explored in this research, reminding us that truth can indeed be stranger than fiction.
As the scholarly investigation of the peculiar correlation between Democrat votes for Senators in Wyoming and the consumption of jet fuel in Niue unfolds, it becomes apparent that this area of inquiry extends beyond the realms of conventional scientific understanding and ventures into the territory of the absurd and the unexpected – much like a punchline that catches you off guard.

[[RESULTS]]
The results of the analysis revealed a significant positive correlation between the number of Democrat votes for Senators in Wyoming and the quantity of jet fuel utilized in Niue from 2000 to 2018. The correlation coefficient of 0.8650622 indicates a strong positive linear relationship between the two variables, resembling a statistical bromance that defies geographical distance and political affiliations. It seems that even in the realm of statistical analysis, opposites attract – much like the magnetic poles of a research magnet.
Furthermore, the r-squared value of 0.7483326 suggests that approximately 75% of the variation in jet fuel usage in Niue can be explained by the number of Democrat votes for Senators in Wyoming. This finding sheds light on the influential role of political preferences in shaping transcontinental energy consumption patterns, highlighting the unexpected fusion of geopolitical considerations and environmental impact – a true confluence of policy and pollution, if you will.
The p-value of less than 0.05 provides compelling evidence to reject the null hypothesis, indicating that the observed correlation is unlikely to have occurred due to random chance. This statistical significance is as striking as a beacon illuminating a dark and foggy night, guiding researchers towards the uncharted territory of quirky correlations and improbable connections.
In summary, the results point to a remarkable association between the political dynamics of Wyoming and the aviation fuel dynamics of Niue, serving as a testament to the unpredictable nature of statistical relationships. This unexpected correlation may seem as unlikely as a penguin in the Sahara, but it beckons further exploration, challenging researchers to unravel the intricate threads that weave together the seemingly disparate realms of American politics and South Pacific aviation.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study provide empirical support for the hitherto dubious relationship between Democrat votes for Senators in Wyoming and the utilization of jet fuel in Niue. The significant positive correlation uncovered in our analysis reinforces the observations of previous scholars who have delved into the enigmatic interactions between seemingly disconnected phenomena. The statistical bromance between these variables can no longer be dismissed as mere happenstance; the data demands our attention and further exploration, much like a persistent dad joke that refuses to be ignored.

The unexpected connection between political inclinations in the heartland of the United States and aviation fuel consumption in a remote South Pacific island challenges conventional wisdom. It beckons us to ponder the extent to which distant and ostensibly unrelated factors can influence each other, akin to the way a dad joke can elicit a chuckle from the most stringent of audiences.

The high r-squared value suggests that a substantial portion of the variation in jet fuel utilization in Niue is attributable to the number of Democrat votes for Senators in Wyoming. This underscores the considerable impact of political preferences on transoceanic energy consumption patterns, reaffirming the profound influence of seemingly local decisions on global phenomena. It is as if the improbable fusion of these variables is a statistical magic trick, enchanting researchers and defying their expectations, much like the unexpected punchline of a cleverly crafted dad joke.

Moreover, the statistical significance of the correlation, as indicated by the p-value, dispels any lingering doubts about the authenticity of this association. It serves as a reminder that in the realm of data analysis, improbable relationships can sometimes be as striking as an unexpected turn in a well-crafted joke. The rejection of the null hypothesis is akin to the punchline landing just right, leaving researchers with no choice but to acknowledge the underlying truth in the absurd association between the electoral behavior in Wyoming and the aviation fuel dynamics of Niue.

In conclusion, the findings of this study solidify the existence of an unconventional bond between political voting behavior and intercontinental energy consumption. Just as a dad joke is unexpectedly clever, this correlation challenges us to grapple with the unanticipated connections that underpin the tapestry of societal and environmental dynamics, igniting our curiosity and spurring further investigation into the unexpected interplay of political leanings and aviation fuel usage.

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 Democrat votes for Senators in Wyoming and Jet fuel used in Niue. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue"

[[ABSTRACT]]
This research examines the peculiar relationship between the voting preferences of Democrats for Senators in Wyoming and the amount of jet fuel used in the obscure island nation of Niue, nestled in the South Pacific. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our study reveals a surprising connection between these seemingly unrelated elements. The correlation coefficient of 0.8650622 and a p-value of less than 0.05 for the years 2000 to 2018 provide strong statistical evidence of this unexpected association.

Utilizing rigorous statistical analysis, we found that as the number of Democrat votes for Senators in Wyoming increased, there was a corresponding rise in the amount of jet fuel utilized in Niue. This phenomenon defies conventional wisdom and uncovers an intriguing interplay between political leanings in landlocked Wyoming and aviation fuel consumption in the far-off island of Niue.

In light of these findings, we propose that further investigation is warranted to unravel the mechanisms underlying this unlikely correlation, taking into account the landlocked nature of Wyoming, the remoteness of Niue, and potential confounding variables. As we dig into these peculiar connections, it becomes clear that there is more than meets the eye, much like the father who can channel the voting tendencies of Wyoming and the jet fuel of Niue into a single pun.

[[INTRDUCTION]]
In the world of scientific research, one often comes across unexpected connections and peculiar correlations that boggle the mind and challenge conventional wisdom. It is akin to stumbling upon a statistical anomaly that leaves one scratching their head in bewilderment, much like the perplexing relationship between the voting patterns of Democrats in Wyoming and the jet fuel consumption in the remote island nation of Niue.
Now, I may not be a dad myself, but I must say, uncovering the connection between these seemingly disparate variables was as surprising as finding an electron in a hayfield – quite the "negative" search result for the protons out there. The statistical analysis revealed a correlation that was stronger than the caffeine content in a freshly brewed cup of coffee – a caffeinated relationship, if you will.
The findings of this research project have stirred up more curiosity than a beaker of vinegar and baking soda in a middle school science fair volcano demonstration. The statistical evidence suggests a connection as robust as the polymer chains in a well-constructed DNA helix – binding together two distant entities in an unanticipated manner.
As we embark on this scholarly exploration, let us remember that science often surprises us in ways that are as mind-bending as a Möbius strip – bending reality in unexpected ways, much like the enigmatic relationship between Wyoming's voting behaviors and Niue's jet fuel usage. This investigation aims to shed light on the intricacies of these unexpected connections, much like a beacon guiding lost statistical travelers through the fog of uncertainty.

[[RESULTS]]
The results of the analysis revealed a significant positive correlation between the number of Democrat votes for Senators in Wyoming and the quantity of jet fuel utilized in Niue from 2000 to 2018. The correlation coefficient of 0.8650622 indicates a strong positive linear relationship between the two variables, resembling a statistical bromance that defies geographical distance and political affiliations. It seems that even in the realm of statistical analysis, opposites attract – much like the magnetic poles of a research magnet.
Furthermore, the r-squared value of 0.7483326 suggests that approximately 75% of the variation in jet fuel usage in Niue can be explained by the number of Democrat votes for Senators in Wyoming. This finding sheds light on the influential role of political preferences in shaping transcontinental energy consumption patterns, highlighting the unexpected fusion of geopolitical considerations and environmental impact – a true confluence of policy and pollution, if you will.
The p-value of less than 0.05 provides compelling evidence to reject the null hypothesis, indicating that the observed correlation is unlikely to have occurred due to random chance. This statistical significance is as striking as a beacon illuminating a dark and foggy night, guiding researchers towards the uncharted territory of quirky correlations and improbable connections.
In summary, the results point to a remarkable association between the political dynamics of Wyoming and the aviation fuel dynamics of Niue, serving as a testament to the unpredictable nature of statistical relationships. This unexpected correlation may seem as unlikely as a penguin in the Sahara, but it beckons further exploration, challenging researchers to unravel the intricate threads that weave together the seemingly disparate realms of American politics and South Pacific aviation.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the findings of this study have unveiled a surprising connection between the voting behaviors of Democrats in Wyoming and the jet fuel consumption in Niue, challenging conventional expectations and providing fertile ground for future inquiries. This correlation, despite the geographical gulf and the political chasm, stands as a testament to the capricious nature of statistical relationships, much like a surprising punchline in the midst of a dry academic discussion.

The robust correlation coefficient and statistical significance of the relationship suggest that there is more to this interplay than meets the eye, much like a cleverly constructed pun that leaves the reader pondering its layers of meaning. As we unpack the implications of this unlikely association, it becomes apparent that further investigation is warranted, even if it feels as unexpected as a practical joke in a laboratory setting.

It is clear that this peculiar correlation sparks curiosity and invites a deeper exploration into the underlying mechanisms that bind together the political leanings of Wyoming and the aviation energy dynamics of Niue. Nevertheless, as the father of a growing body of evidence on this matter, it can be said that no more research is required at this time, much like a firm assertion from a corny dad at the end of a family road trip.

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 Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Political Meteorology

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 Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue. Respond only with the name of a fictional organization.

ChatGPT:

The International Society for Atmospheric and Political 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 Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue with an abstract of This research examines the peculiar relationship between the voting preferences of Democrats for Senators in Wyoming and the amount of jet fuel used in the obscure island nation of Niue, nestled in the South Pacific. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, our study reveals a surprising connection between these seemingly unrelated elements. The correlation coefficient of 0.8650622 and a p-value of less than 0.05 for the years 2000 to 2018 provide strong statistical evidence of this unexpected association.
Utilizing rigorous statistical analysis, we found that as the number of Democrat votes for Senators in Wyoming increased, there was a corresponding rise in the amount of jet fuel utilized in Niue. This phenomenon defies conventional wisdom and uncovers an intriguing interplay between political leanings in landlocked Wyoming and aviation fuel consumption in the far-off island of Niue.
In light of these findings, we propose that further investigation is warranted to unravel the mechanisms underlying this unlikely correlation, taking into account the landlocked nature of Wyoming, the remoteness of Niue, and potential confounding variables. As we dig into these peculiar connections, it becomes clear that there is more than meets the eye, much like the father who can channel the voting tendencies of Wyoming and the jet fuel of Niue into a single pun.

ChatGPT:

Wyoming, remote voting, Democrats, Senators, jet fuel, Niue, correlation, statistical analysis, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, political leanings, aviation fuel consumption, landlocked, remoteness, confounding variables

*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 Democratic Senators in Wyoming
Detailed data title: Total number of votes cast for Federal Democrat Senate candidates in Wyoming
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Democratic Senators in Wyoming

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

Correlation r = 0.8650622 (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 = 0.7483326 (Coefficient of determination)
This means 74.8% of the change in the one variable (i.e., Jet fuel used in Niue) is predictable based on the change in the other (i.e., Votes for Democratic Senators in Wyoming) over the 7 years from 2000 through 2018.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.012.^Show 0.0119302285700921500000000000
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 0.87 in 1.2% of random cases. Said differently, if you correlated 84 random variables^Note Which I absolutely did.
with the same 6 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 6 because we have two variables measured over a period of 7 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.

[ 0.32, 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.

	2000	2002	2006	2008	2012	2014	2018
Votes for Democratic Senators in Wyoming (Total votes)	47087	49570	57671	126833	53019	29377	61227
Jet fuel used in Niue (Million Barrels/Day)	0.00823333	0.00814726	0.00867281	0.0179123	0.00961154	0.0108729	0.0110803

Why this works

Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” 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.
Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{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([47087,49570,57671,126833,53019,29377,61227,])
array_2 = np.array([0.00823333,0.00814726,0.00867281,0.0179123,0.00961154,0.0108729,0.0110803,])
array_1_name = "Votes for Democratic Senators in Wyoming"
array_2_name = "Jet fuel used in Niue"

# 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 Democratic Senators in Wyoming
Line chart for only Jet fuel used in Niue
AI-generated correlation image
The spurious research paper: Skies of Blue States: Remote Voting Behaviors in Wyoming and the Jet Stream of Niue

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Correlation ID: 5606 · Black Variable ID: 26339 · Red Variable ID: 24769


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