Spurious correlation #4,806 · 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 Republican Presidential candidate in Montana and the second variable is Jet fuel used in Somalia. 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 Republican Presidential candidate in Montana and the second variable is Jet fuel used in Somalia. The chart goes from 1980 to 2020, and the two variables track closely in value over that time.

AI explanation

As the support for the Republican candidate in Montana soared, a surge of patriotic fervor was ignited. This led to an unusual but undeniable spike in the demand for fireworks across the state. As fate would have it, a local entrepreneur decided to capitalize on this booming market and started a new business venture - importing rare, artisanal fireworks from Somalia. Eager to showcase their fiery support, the residents of Montana celebrated with extravagant displays, unknowingly creating a strangely direct link between their political enthusiasm and the jet fuel used to transport these 'explosive' goods. So, in a bizarre twist of fate, as the Republican votes skyrocketed in Montana, so did the jet fuel usage in Somalia, all thanks to a combustible combination of politics, pyrotechnics, and a touch of entrepreneurial spirit!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a bustling steampunk-inspired Montana town, with towering smokestacks belching steam and sparks, while magnificent fireworks explode in the sky above. Artisanal fireworks from Somalia are being unloaded from airships onto the bustling streets, as a fleet of ornate, steampowered vehicles transports them to eager customers. In the distance, sleek airships depart from a skyport, carrying jet fuel to Somalia, leaving contrails in the vibrant, colorful sky. 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 Republican Presidential candidate in Montana and Jet fuel used in Somalia. 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: Psychedelic Cute 2D animation Steampunk Art nouveau Cyber folk
ChatGPT: Steampunk

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 Republican Presidential candidate in Montana and Jet fuel used in Somalia, in the following situation: As the support for the Republican candidate in Montana soared, a surge of patriotic fervor was ignited. This led to an unusual but undeniable spike in the demand for fireworks across the state. As fate would have it, a local entrepreneur decided to capitalize on this booming market and started a new business venture - importing rare, artisanal fireworks from Somalia. Eager to showcase their fiery support, the residents of Montana celebrated with extravagant displays, unknowingly creating a strangely direct link between their political enthusiasm and the jet fuel used to transport these 'explosive' goods. So, in a bizarre twist of fate, as the Republican votes skyrocketed in Montana, so did the jet fuel usage in Somalia, all thanks to a combustible combination of politics, pyrotechnics, and a touch of entrepreneurial spirit!. Keep the description simple.
ChatGPT: A wave of Republican votes in Montana triggers an uptick in fireworks demand, leading to the import of artisanal fireworks from Somalia. As colorful explosions light up the Montana sky, jet fuel usage surges in Somalia, creating an unforeseen connection between political fervor and transcontinental transportation.

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: [ Steampunk ] and depicting this scene: A wave of Republican votes in Montana triggers an uptick in fireworks demand, leading to the import of artisanal fireworks from Somalia. As colorful explosions light up the Montana sky, jet fuel usage surges in Somalia, creating an unforeseen connection between political fervor and transcontinental transportation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling steampunk-inspired Montana town, with towering smokestacks belching steam and sparks, while magnificent fireworks explode in the sky above. Artisanal fireworks from Somalia are being unloaded from airships onto the bustling streets, as a fleet of ornate, steampowered vehicles transports them to eager customers. In the distance, sleek airships depart from a skyport, carrying jet fuel to Somalia, leaving contrails in the vibrant, colorful sky.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Votes for the Republican Presidential candidate in Montana positively influenced Jet fuel used in Somalia.

AI academic paper

(Because p < 0.01)

Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia

The Journal of Transnational Political Jet Fuel Dynamics

Jan 2024

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Montana and Jet fuel used in Somalia. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
"Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia"

[[ABSTRACT]]
In this groundbreaking research, we delve into the unexpected and delightful world of politics and energy consumption to uncover a peculiar correlation between votes for the Republican presidential candidate in Montana and jet fuel used in Somalia. Pardon the pun, but we were in for a bumpy ride as we navigated through the data to unravel this quirky connection.

Utilizing data from prestigious sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we meticulously examined voting trends in Montana and jet fuel consumption in Somalia from 1980 to 2020. Our findings revealed a surprisingly strong correlation coefficient of 0.9129980 and a statistically significant p-value of less than 0.01. That's a confidence interval wider than a jumbo jet's wingspan!

Upon further analysis, we discovered that for every percentage increase in Republican votes in Montana, there was a corresponding increase in jet fuel consumption in Somalia. It seems that political leanings and energy usage are more intertwined than we ever imagined. We couldn't help but ponder, could this be the elusive "red state, blue state, jet fuel state" connection?

Our research sheds light on a peculiar relationship that defies conventional understanding. While the roads to the voting booths and the runways of Somalia may seem worlds apart, our data suggests a fascinating link between the two. As we continue to navigate the complex intersection of politics and energy, one thing is clear: there's more to democracy and fuel consumption than meets the eye. It's almost as surprising as when the electrician became a conductor - he was shocked.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intertwining of politics and energy consumption has long been a subject of interest, prompting us to dig deep into uncharted territory to uncover the unexpected relationship between votes for the Republican presidential candidate in Montana and jet fuel usage in Somalia. It's like trying to connect the dots between red states and blue skies!
As we embarked on this peculiar journey, we were met with raised eyebrows and quizzical looks. But undeterred, we embraced the challenge with the fervor of a scientist chasing a breakthrough. Our enthusiasm was unbridled, much like a labrador retriever let loose in a field of statistical data.
The process of collecting and analyzing data was no small feat. We combed through election results with the diligence of a librarian searching for a misplaced tome, and delved into energy consumption figures with the precision of a surgeon wielding a scalpel. It was a task that demanded meticulous attention to detail and an unyielding commitment, not unlike searching for a needle in a haystack, or in our case, a statistically significant correlation in a sea of numbers.
Our findings, as unexpected as a physicist showing up at a poetry slam, revealed a noteworthy correlation between Republican votes in Montana and jet fuel consumption in Somalia. The connection between these variables was stronger than a chemist's bond and statistically significant with a p-value that was lower than a limbo bar at a beach party.
This discovery challenges conventional wisdom and calls for further exploration into the underlying factors at play. The relationship between political preferences in one corner of the world and energy usage in another is a conundrum that beckons researchers to peer beyond the surface and unearth the mystique hiding within the data.
In unraveling this enigma, we pondered the implications of our findings with a mix of intrigue and amusement. The idea that the outcome of an election in the mountainous expanses of Montana could have an impact on the jet fuel traversing the skies over the deserts of Somalia is as perplexing as a paradox in quantum mechanics.
As we delve deeper into this uncharted territory, we invite fellow researchers to join us on this journey of discovery. The intersection of political behavior and energy dynamics, much like a pun at a science convention, is ripe with unexpected twists and curious connections waiting to be unraveled. And remember, when it comes to research, the journey is often as fascinating as the destination, much like a good dad joke - it might make you cringe, but you can't help but appreciate the cleverness behind it.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

As we explore the whimsical world of politics and energy consumption, we are compelled to examine prior research that may shed light on the peculiar correlation between Republican votes in Montana and jet fuel usage in Somalia. While this unexpected connection might seem akin to an obscure punchline, it beckons us to venture beyond the conventional and embrace the quirky intersection of electoral preferences and fuel dynamics.

Smith and Doe (2015) delve into the intricacies of political voting patterns in rural regions, highlighting the influence of local industries on the electoral landscape. Their work aptly captures the intricate web of factors that shape voting behaviors, leaving ample room for unexpected influences to emerge from the woodwork, much like a jack-in-the-box waiting to surprise unsuspecting passersby. Meanwhile, Jones et al. (2018) provide a comprehensive analysis of global energy consumption trends, inviting us to ponder the far-reaching implications of energy dynamics on a transnational scale. It's as if they're beckoning us to traverse the globe in search of unforeseen connections, much like intrepid explorers charting unknown territories.

Serious tone aside, it's time to inject some levity with a quick dad joke break: Why don't scientists trust atoms? Because they make up everything!

Turning our attention to the realm of literature, the work of "Energy and Democracy: Exploring the Intersections" by Maxwell Powers and Sarah Kilowatts offers a thought-provoking exploration of the intertwined nature of energy dynamics and political systems. It's almost as if they're hinting at the hidden ties between electoral outcomes and fuel consumption, weaving a narrative that unfolds like a mystery novel set in the convoluted corridors of power.

Moving beyond non-fiction, let's not overlook the potential insights that can be gleaned from fiction. Consider Arthur Conan Doyle's "The Hound of the Baskervilles," where the unraveling of perplexing connections mirrors our own quest to decode the enigmatic relationship between votes in Montana and jet fuel in Somalia. It's as if Sherlock Holmes himself is beckoning us to piece together the clues, albeit in a context that's more perplexing than a riddle wrapped in an enigma.

Oh, and let's not forget about "The Settlers of Catan." While it might seem that this classic board game has little to do with our topic at hand, the intricate web of resource management and strategic positioning echoes the complexities of our investigation. Who would have thought that a game about settling islands could offer insights into the potential interplay between political choices and energy use? It's as unexpected as finding a treasure map in a game of Monopoly!

But I digress. In delving into this unexplored terrain, we mustn't lose sight of the fact that while our inquiry into the connection between Republican votes in Montana and jet fuel consumption in Somalia may reveal unexpected surprises, it's the journey of discovery that truly captivates the imagination. Just like a good dad joke, the allure lies in the playful twists and turns that leave us amused and intrigued – and that, dear readers, is what makes research truly delightful.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Republican Presidential candidate in Montana and Jet fuel used in Somalia. 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 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]]
"Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia"

[[ABSTRACT]]
In this groundbreaking research, we delve into the unexpected and delightful world of politics and energy consumption to uncover a peculiar correlation between votes for the Republican presidential candidate in Montana and jet fuel used in Somalia. Pardon the pun, but we were in for a bumpy ride as we navigated through the data to unravel this quirky connection.

Utilizing data from prestigious sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we meticulously examined voting trends in Montana and jet fuel consumption in Somalia from 1980 to 2020. Our findings revealed a surprisingly strong correlation coefficient of 0.9129980 and a statistically significant p-value of less than 0.01. That's a confidence interval wider than a jumbo jet's wingspan!

Upon further analysis, we discovered that for every percentage increase in Republican votes in Montana, there was a corresponding increase in jet fuel consumption in Somalia. It seems that political leanings and energy usage are more intertwined than we ever imagined. We couldn't help but ponder, could this be the elusive "red state, blue state, jet fuel state" connection?

Our research sheds light on a peculiar relationship that defies conventional understanding. While the roads to the voting booths and the runways of Somalia may seem worlds apart, our data suggests a fascinating link between the two. As we continue to navigate the complex intersection of politics and energy, one thing is clear: there's more to democracy and fuel consumption than meets the eye. It's almost as surprising as when the electrician became a conductor - he was shocked.

[[INTRODUCTION]]
The intertwining of politics and energy consumption has long been a subject of interest, prompting us to dig deep into uncharted territory to uncover the unexpected relationship between votes for the Republican presidential candidate in Montana and jet fuel usage in Somalia. It's like trying to connect the dots between red states and blue skies!
As we embarked on this peculiar journey, we were met with raised eyebrows and quizzical looks. But undeterred, we embraced the challenge with the fervor of a scientist chasing a breakthrough. Our enthusiasm was unbridled, much like a labrador retriever let loose in a field of statistical data.
The process of collecting and analyzing data was no small feat. We combed through election results with the diligence of a librarian searching for a misplaced tome, and delved into energy consumption figures with the precision of a surgeon wielding a scalpel. It was a task that demanded meticulous attention to detail and an unyielding commitment, not unlike searching for a needle in a haystack, or in our case, a statistically significant correlation in a sea of numbers.
Our findings, as unexpected as a physicist showing up at a poetry slam, revealed a noteworthy correlation between Republican votes in Montana and jet fuel consumption in Somalia. The connection between these variables was stronger than a chemist's bond and statistically significant with a p-value that was lower than a limbo bar at a beach party.
This discovery challenges conventional wisdom and calls for further exploration into the underlying factors at play. The relationship between political preferences in one corner of the world and energy usage in another is a conundrum that beckons researchers to peer beyond the surface and unearth the mystique hiding within the data.
In unraveling this enigma, we pondered the implications of our findings with a mix of intrigue and amusement. The idea that the outcome of an election in the mountainous expanses of Montana could have an impact on the jet fuel traversing the skies over the deserts of Somalia is as perplexing as a paradox in quantum mechanics.
As we delve deeper into this uncharted territory, we invite fellow researchers to join us on this journey of discovery. The intersection of political behavior and energy dynamics, much like a pun at a science convention, is ripe with unexpected twists and curious connections waiting to be unraveled. And remember, when it comes to research, the journey is often as fascinating as the destination, much like a good dad joke - it might make you cringe, but you can't help but appreciate the cleverness behind it.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unveil the intricate dance between Republican votes in Montana and jet fuel consumption in Somalia, we embarked on a methodical journey that would make even the most daring adventurer take pause. Our approach combined the precision of a neurosurgeon with the tenacity of a bloodhound on a scent, all in the name of scholarly inquiry and a good laugh, just like a dad joke popping up at the dinner table.

Data Collection:
We gathered data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration websites, navigating through virtual corridors of information with the dexterity of a web-surfing acrobat. The data spanned from 1980 to 2020, capturing four decades of political fervor and energy dynamics. It was a task that demanded the patience of a saint and the eyesight of a hawk, as we scoured through countless spreadsheets and databases, like a detective searching for clues in a crime scene. And just like an energy-efficient light bulb, we made sure to leave no dataset unturned.

Unconventional Regression Analysis:
To uncover the mysterious link between Republican votes and jet fuel consumption, we utilized a regression analysis that was as unique as a unicorn in a field of horses. Taking inspiration from the unconventional, we employed a modified form of the classic linear regression model, incorporating variables such as political ideologies, global energy trends, and perhaps a sprinkle of statistical magic, just for good measure. Our model was as robust and compelling as a well-told bedtime story, capturing the imagination of the data and weaving a narrative that shed light on the relationship between these seemingly disparate variables.

Statistical Rigor and Validation:
We spared no expense in ensuring the validity and robustness of our findings. With the precision of a watchmaker and the rigor of a seasoned gambler assessing the odds, we calculated correlation coefficients, p-values, and confidence intervals with utmost care. Our statistical tests were as thorough as a shopaholic scouring the sales rack, leaving no stone unturned in our quest for significance. And just like a magician revealing the secrets behind a trick, we were unrelenting in our pursuit of transparency and accuracy.

Cross-Validation and Sensitivity Analysis:
In an effort to preempt any doubts or skepticism, we conducted cross-validation and sensitivity analyses, ensuring that our results held steady under varying scenarios. Our approach was akin to stress-testing a bridge, assuring that the connection between Republican votes in Montana and jet fuel consumption in Somalia remained steadfast, much like a dad's unwavering commitment to puns at family gatherings.

Ethical Considerations:
In the spirit of scholarly integrity and scientific endeavor, we adhered to ethical guidelines and principles throughout our research. Our commitment to transparency and intellectual honesty was unwavering, much like the force of gravity keeping the planets in their celestial dance. We engaged with the data and analysis with the utmost respect and responsibility, always mindful of the impact and implications of our findings, like a conscientious parent guiding a mischievous child.

In summary, our methodology fused the precision of scientific inquiry with the whimsy of unexpected connections, akin to a clever pun hidden within a serious discussion. Our approach aimed not only to unravel the relationship between political preferences and energy consumption but also to infuse a touch of levity into the often-mundane world of research. Remember, in the world of academia, as in life, a little laughter goes a long way!

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

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Montana and Jet fuel used in Somalia. 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 .

For the time period 1980 to 2020, you found a correlation 0.9129980, r-squared of 0.8335654, and p < 0.01.

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

Here is the title and abstract of the paper:
[[TITLE]]
"Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia"

[[ABSTRACT]]
In this groundbreaking research, we delve into the unexpected and delightful world of politics and energy consumption to uncover a peculiar correlation between votes for the Republican presidential candidate in Montana and jet fuel used in Somalia. Pardon the pun, but we were in for a bumpy ride as we navigated through the data to unravel this quirky connection.

Utilizing data from prestigious sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we meticulously examined voting trends in Montana and jet fuel consumption in Somalia from 1980 to 2020. Our findings revealed a surprisingly strong correlation coefficient of 0.9129980 and a statistically significant p-value of less than 0.01. That's a confidence interval wider than a jumbo jet's wingspan!

Upon further analysis, we discovered that for every percentage increase in Republican votes in Montana, there was a corresponding increase in jet fuel consumption in Somalia. It seems that political leanings and energy usage are more intertwined than we ever imagined. We couldn't help but ponder, could this be the elusive "red state, blue state, jet fuel state" connection?

Our research sheds light on a peculiar relationship that defies conventional understanding. While the roads to the voting booths and the runways of Somalia may seem worlds apart, our data suggests a fascinating link between the two. As we continue to navigate the complex intersection of politics and energy, one thing is clear: there's more to democracy and fuel consumption than meets the eye. It's almost as surprising as when the electrician became a conductor - he was shocked.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intertwining of politics and energy consumption has long been a subject of interest, prompting us to dig deep into uncharted territory to uncover the unexpected relationship between votes for the Republican presidential candidate in Montana and jet fuel usage in Somalia. It's like trying to connect the dots between red states and blue skies!
As we embarked on this peculiar journey, we were met with raised eyebrows and quizzical looks. But undeterred, we embraced the challenge with the fervor of a scientist chasing a breakthrough. Our enthusiasm was unbridled, much like a labrador retriever let loose in a field of statistical data.
The process of collecting and analyzing data was no small feat. We combed through election results with the diligence of a librarian searching for a misplaced tome, and delved into energy consumption figures with the precision of a surgeon wielding a scalpel. It was a task that demanded meticulous attention to detail and an unyielding commitment, not unlike searching for a needle in a haystack, or in our case, a statistically significant correlation in a sea of numbers.
Our findings, as unexpected as a physicist showing up at a poetry slam, revealed a noteworthy correlation between Republican votes in Montana and jet fuel consumption in Somalia. The connection between these variables was stronger than a chemist's bond and statistically significant with a p-value that was lower than a limbo bar at a beach party.
This discovery challenges conventional wisdom and calls for further exploration into the underlying factors at play. The relationship between political preferences in one corner of the world and energy usage in another is a conundrum that beckons researchers to peer beyond the surface and unearth the mystique hiding within the data.
In unraveling this enigma, we pondered the implications of our findings with a mix of intrigue and amusement. The idea that the outcome of an election in the mountainous expanses of Montana could have an impact on the jet fuel traversing the skies over the deserts of Somalia is as perplexing as a paradox in quantum mechanics.
As we delve deeper into this uncharted territory, we invite fellow researchers to join us on this journey of discovery. The intersection of political behavior and energy dynamics, much like a pun at a science convention, is ripe with unexpected twists and curious connections waiting to be unraveled. And remember, when it comes to research, the journey is often as fascinating as the destination, much like a good dad joke - it might make you cringe, but you can't help but appreciate the cleverness behind it.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the data from 1980 to 2020 revealed a striking correlation coefficient of 0.9129980 between Republican votes in Montana and jet fuel consumption in Somalia. This correlation coefficient is stronger than a caffeine molecule's bond to a tired researcher on a Friday afternoon. The r-squared value of 0.8335654 indicates that approximately 83.36% of the variability in jet fuel usage in Somalia can be explained by the fluctuations in Republican votes in Montana. It’s almost as predictable as a classic knock-knock joke, but with more statistical significance!

A visual representation of this relationship is presented in Figure 1, which depicts a scatterplot demonstrating the tight association between the two variables. It's almost as clear as a pie chart at a math convention: for every increase in Republican votes in Montana, there is a corresponding spike in jet fuel consumption in Somalia. It's as if the voters in Montana are whispering "jet fuel, we choose you!"

The p-value of less than 0.01 further cements the strength of this relationship, with a confidence interval wider than a politician’s smile during campaign season. This finding aligns with our initial expectations as much as a perfect bell curve aligns with a statistics lecture - it's a thing of beauty.

In summary, our results uncover a remarkable association between the voting preferences in Montana and the jet fuel consumption in Somalia. This intriguing correlation raises questions about the intertwined nature of political activities and global energy dynamics. It's almost as surprising as a quantum physicist walking into a bar and not worrying about standing in two places at once.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Montana and Jet fuel used in Somalia. 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]]
"Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia"

[[ABSTRACT]]
In this groundbreaking research, we delve into the unexpected and delightful world of politics and energy consumption to uncover a peculiar correlation between votes for the Republican presidential candidate in Montana and jet fuel used in Somalia. Pardon the pun, but we were in for a bumpy ride as we navigated through the data to unravel this quirky connection.

Utilizing data from prestigious sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we meticulously examined voting trends in Montana and jet fuel consumption in Somalia from 1980 to 2020. Our findings revealed a surprisingly strong correlation coefficient of 0.9129980 and a statistically significant p-value of less than 0.01. That's a confidence interval wider than a jumbo jet's wingspan!

Upon further analysis, we discovered that for every percentage increase in Republican votes in Montana, there was a corresponding increase in jet fuel consumption in Somalia. It seems that political leanings and energy usage are more intertwined than we ever imagined. We couldn't help but ponder, could this be the elusive "red state, blue state, jet fuel state" connection?

Our research sheds light on a peculiar relationship that defies conventional understanding. While the roads to the voting booths and the runways of Somalia may seem worlds apart, our data suggests a fascinating link between the two. As we continue to navigate the complex intersection of politics and energy, one thing is clear: there's more to democracy and fuel consumption than meets the eye. It's almost as surprising as when the electrician became a conductor - he was shocked.

[[LITERATURE REVIEW]]
As we explore the whimsical world of politics and energy consumption, we are compelled to examine prior research that may shed light on the peculiar correlation between Republican votes in Montana and jet fuel usage in Somalia. While this unexpected connection might seem akin to an obscure punchline, it beckons us to venture beyond the conventional and embrace the quirky intersection of electoral preferences and fuel dynamics.
Smith and Doe (2015) delve into the intricacies of political voting patterns in rural regions, highlighting the influence of local industries on the electoral landscape. Their work aptly captures the intricate web of factors that shape voting behaviors, leaving ample room for unexpected influences to emerge from the woodwork, much like a jack-in-the-box waiting to surprise unsuspecting passersby. Meanwhile, Jones et al. (2018) provide a comprehensive analysis of global energy consumption trends, inviting us to ponder the far-reaching implications of energy dynamics on a transnational scale. It's as if they're beckoning us to traverse the globe in search of unforeseen connections, much like intrepid explorers charting unknown territories.
Serious tone aside, it's time to inject some levity with a quick dad joke break: Why don't scientists trust atoms? Because they make up everything!
Turning our attention to the realm of literature, the work of "Energy and Democracy: Exploring the Intersections" by Maxwell Powers and Sarah Kilowatts offers a thought-provoking exploration of the intertwined nature of energy dynamics and political systems. It's almost as if they're hinting at the hidden ties between electoral outcomes and fuel consumption, weaving a narrative that unfolds like a mystery novel set in the convoluted corridors of power.
Moving beyond non-fiction, let's not overlook the potential insights that can be gleaned from fiction. Consider Arthur Conan Doyle's "The Hound of the Baskervilles," where the unraveling of perplexing connections mirrors our own quest to decode the enigmatic relationship between votes in Montana and jet fuel in Somalia. It's as if Sherlock Holmes himself is beckoning us to piece together the clues, albeit in a context that's more perplexing than a riddle wrapped in an enigma.
Oh, and let's not forget about "The Settlers of Catan." While it might seem that this classic board game has little to do with our topic at hand, the intricate web of resource management and strategic positioning echoes the complexities of our investigation. Who would have thought that a game about settling islands could offer insights into the potential interplay between political choices and energy use? It's as unexpected as finding a treasure map in a game of Monopoly!
But I digress. In delving into this unexplored terrain, we mustn't lose sight of the fact that while our inquiry into the connection between Republican votes in Montana and jet fuel consumption in Somalia may reveal unexpected surprises, it's the journey of discovery that truly captivates the imagination. Just like a good dad joke, the allure lies in the playful twists and turns that leave us amused and intrigued – and that, dear readers, is what makes research truly delightful.

[[RESULTS]]
The analysis of the data from 1980 to 2020 revealed a striking correlation coefficient of 0.9129980 between Republican votes in Montana and jet fuel consumption in Somalia. This correlation coefficient is stronger than a caffeine molecule's bond to a tired researcher on a Friday afternoon. The r-squared value of 0.8335654 indicates that approximately 83.36% of the variability in jet fuel usage in Somalia can be explained by the fluctuations in Republican votes in Montana. It’s almost as predictable as a classic knock-knock joke, but with more statistical significance!
A visual representation of this relationship is presented in Figure 1, which depicts a scatterplot demonstrating the tight association between the two variables. It's almost as clear as a pie chart at a math convention: for every increase in Republican votes in Montana, there is a corresponding spike in jet fuel consumption in Somalia. It's as if the voters in Montana are whispering "jet fuel, we choose you!"
The p-value of less than 0.01 further cements the strength of this relationship, with a confidence interval wider than a politician’s smile during campaign season. This finding aligns with our initial expectations as much as a perfect bell curve aligns with a statistics lecture - it's a thing of beauty.
In summary, our results uncover a remarkable association between the voting preferences in Montana and the jet fuel consumption in Somalia. This intriguing correlation raises questions about the intertwined nature of political activities and global energy dynamics. It's almost as surprising as a quantum physicist walking into a bar and not worrying about standing in two places at once.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our results have unveiled a fascinating relationship between Republican votes in Montana and jet fuel consumption in Somalia, setting the stage for a delightful fusion of politics and energy dynamics. This unexpected convergence of electoral tendencies in the United States and fuel utilization in a distant corner of the world reminds us that the scientific journey can be as unexpected as finding a statistical anomaly in a pile of data.

Building upon the whimsical underpinnings of research highlighted in our literature review, it's clear that our findings not only support prior studies but also inject a fresh perspective into the realm of peculiar correlations. Smith and Doe's exploration of rural voting patterns now takes on a new dimension, akin to discovering a hidden compartment in a jigsaw puzzle – surprising yet oddly satisfying. Similarly, the work of Jones et al. urging us to embrace unexpected connections in energy consumption resonates deeply with our own revelations, almost like uncovering a gemstone in a mine of statistical data.

Much like a good dad joke, our results bring joy and laughter while shedding light on an unexpected phenomenon. It seems that the saying "politics makes for strange bedfellows" now extends its embrace to the energy sector, creating an alliance that is as intriguing as a politician's campaign promise.

The significant correlation coefficient and p-value in our study affirm the robustness of this connection, as reliable as a lab technician's precise measurements. This resounding statistical support not only underscores the solidity of our findings but also adds a touch of certainty to the unpredictable dance of electoral choices and fuel consumption trends.

As we delve further into this boundary-pushing investigation, it's impossible to ignore the delightful interplay between regulatory policies, global economic shifts, and the social fabric being revealed by our research. It's almost as if we've stumbled upon the Rosetta Stone of political economy, unraveling a code as intricate as a cryptic crossword.

In this realm of unexpected insight, our study provides a lighthearted yet thought-provoking contribution to the quirky tapestry of academic inquiry. With the data at hand, it’s safe to say that our findings are as solid as a scientific law, bolstering our understanding of the curious link between political preferences and a far-off land's fuel consumption. It's as satisfying as the punchline of a well-crafted pun – unexpected, yet undeniably delightful.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Montana and Jet fuel used in Somalia. 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]]
"Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia"

[[ABSTRACT]]
In this groundbreaking research, we delve into the unexpected and delightful world of politics and energy consumption to uncover a peculiar correlation between votes for the Republican presidential candidate in Montana and jet fuel used in Somalia. Pardon the pun, but we were in for a bumpy ride as we navigated through the data to unravel this quirky connection.

Utilizing data from prestigious sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we meticulously examined voting trends in Montana and jet fuel consumption in Somalia from 1980 to 2020. Our findings revealed a surprisingly strong correlation coefficient of 0.9129980 and a statistically significant p-value of less than 0.01. That's a confidence interval wider than a jumbo jet's wingspan!

Upon further analysis, we discovered that for every percentage increase in Republican votes in Montana, there was a corresponding increase in jet fuel consumption in Somalia. It seems that political leanings and energy usage are more intertwined than we ever imagined. We couldn't help but ponder, could this be the elusive "red state, blue state, jet fuel state" connection?

Our research sheds light on a peculiar relationship that defies conventional understanding. While the roads to the voting booths and the runways of Somalia may seem worlds apart, our data suggests a fascinating link between the two. As we continue to navigate the complex intersection of politics and energy, one thing is clear: there's more to democracy and fuel consumption than meets the eye. It's almost as surprising as when the electrician became a conductor - he was shocked.

[[INTRDUCTION]]
The intertwining of politics and energy consumption has long been a subject of interest, prompting us to dig deep into uncharted territory to uncover the unexpected relationship between votes for the Republican presidential candidate in Montana and jet fuel usage in Somalia. It's like trying to connect the dots between red states and blue skies!
As we embarked on this peculiar journey, we were met with raised eyebrows and quizzical looks. But undeterred, we embraced the challenge with the fervor of a scientist chasing a breakthrough. Our enthusiasm was unbridled, much like a labrador retriever let loose in a field of statistical data.
The process of collecting and analyzing data was no small feat. We combed through election results with the diligence of a librarian searching for a misplaced tome, and delved into energy consumption figures with the precision of a surgeon wielding a scalpel. It was a task that demanded meticulous attention to detail and an unyielding commitment, not unlike searching for a needle in a haystack, or in our case, a statistically significant correlation in a sea of numbers.
Our findings, as unexpected as a physicist showing up at a poetry slam, revealed a noteworthy correlation between Republican votes in Montana and jet fuel consumption in Somalia. The connection between these variables was stronger than a chemist's bond and statistically significant with a p-value that was lower than a limbo bar at a beach party.
This discovery challenges conventional wisdom and calls for further exploration into the underlying factors at play. The relationship between political preferences in one corner of the world and energy usage in another is a conundrum that beckons researchers to peer beyond the surface and unearth the mystique hiding within the data.
In unraveling this enigma, we pondered the implications of our findings with a mix of intrigue and amusement. The idea that the outcome of an election in the mountainous expanses of Montana could have an impact on the jet fuel traversing the skies over the deserts of Somalia is as perplexing as a paradox in quantum mechanics.
As we delve deeper into this uncharted territory, we invite fellow researchers to join us on this journey of discovery. The intersection of political behavior and energy dynamics, much like a pun at a science convention, is ripe with unexpected twists and curious connections waiting to be unraveled. And remember, when it comes to research, the journey is often as fascinating as the destination, much like a good dad joke - it might make you cringe, but you can't help but appreciate the cleverness behind it.

[[RESULTS]]
The analysis of the data from 1980 to 2020 revealed a striking correlation coefficient of 0.9129980 between Republican votes in Montana and jet fuel consumption in Somalia. This correlation coefficient is stronger than a caffeine molecule's bond to a tired researcher on a Friday afternoon. The r-squared value of 0.8335654 indicates that approximately 83.36% of the variability in jet fuel usage in Somalia can be explained by the fluctuations in Republican votes in Montana. It’s almost as predictable as a classic knock-knock joke, but with more statistical significance!
A visual representation of this relationship is presented in Figure 1, which depicts a scatterplot demonstrating the tight association between the two variables. It's almost as clear as a pie chart at a math convention: for every increase in Republican votes in Montana, there is a corresponding spike in jet fuel consumption in Somalia. It's as if the voters in Montana are whispering "jet fuel, we choose you!"
The p-value of less than 0.01 further cements the strength of this relationship, with a confidence interval wider than a politician’s smile during campaign season. This finding aligns with our initial expectations as much as a perfect bell curve aligns with a statistics lecture - it's a thing of beauty.
In summary, our results uncover a remarkable association between the voting preferences in Montana and the jet fuel consumption in Somalia. This intriguing correlation raises questions about the intertwined nature of political activities and global energy dynamics. It's almost as surprising as a quantum physicist walking into a bar and not worrying about standing in two places at once.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unveiled a startling connection between Republican votes in Montana and jet fuel usage in Somalia. It's as if the red states and the blue skies have conspired to create this unexpected correlation – talk about political parties fueling the skies!

The statistical analysis revealed an undeniable relationship with a confidence interval wider than a runway and a p-value lower than a subterranean fossil fuel deposit. It's like finding a correlation in a haystack of data! This finding challenges traditional assumptions and beckons fellow researchers to delve deeper into the enigmatic relationship between political choices and global energy dynamics. It's a mystery worthy of Sherlock Holmes' investigation, but with more statistical significance.

As for the implications of our findings, it seems that the political landscape in Montana may hold more influence than meets the eye, quite literally, as it echoes across the airspace in Somalia. This unexpected link between two seemingly disparate regions leaves us pondering the intricate web of interconnectedness in our globalized world. It's as if Montanans were saying, "We're fueling more than ballots with our votes!"

In light of these revelatory findings, we assert that no further research in this area is needed. After all, we've successfully uncovered an unexpected connection that is equal parts surprising and amusing, much like a good dad joke shared at a serious academic conference. It's as if the statistical stars have aligned and urged us to say, "That's all, folks!"

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 Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Transnational Political Jet Fuel Dynamics

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 Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia. Respond only with the name of a fictional organization.

ChatGPT:

The International Consortium for Interdisciplinary Research on Unlikely Connections

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 Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia with an abstract of In this groundbreaking research, we delve into the unexpected and delightful world of politics and energy consumption to uncover a peculiar correlation between votes for the Republican presidential candidate in Montana and jet fuel used in Somalia. Pardon the pun, but we were in for a bumpy ride as we navigated through the data to unravel this quirky connection.
Utilizing data from prestigious sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration, we meticulously examined voting trends in Montana and jet fuel consumption in Somalia from 1980 to 2020. Our findings revealed a surprisingly strong correlation coefficient of 0.9129980 and a statistically significant p-value of less than 0.01. That's a confidence interval wider than a jumbo jet's wingspan!
Upon further analysis, we discovered that for every percentage increase in Republican votes in Montana, there was a corresponding increase in jet fuel consumption in Somalia. It seems that political leanings and energy usage are more intertwined than we ever imagined. We couldn't help but ponder, could this be the elusive "red state, blue state, jet fuel state" connection?
Our research sheds light on a peculiar relationship that defies conventional understanding. While the roads to the voting booths and the runways of Somalia may seem worlds apart, our data suggests a fascinating link between the two. As we continue to navigate the complex intersection of politics and energy, one thing is clear: there's more to democracy and fuel consumption than meets the eye. It's almost as surprising as when the electrician became a conductor - he was shocked.

ChatGPT:

Republican votes Montana, jet fuel consumption Somalia, correlation, voting trends Montana, jet fuel usage, political leanings, energy usage, red state blue state, democracy fuel consumption

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

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Data details

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

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

Correlation r = 0.9129980 (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 = 0.8335654 (Coefficient of determination)
This means 83.4% of the change in the one variable (i.e., Jet fuel used in Somalia) is predictable based on the change in the other (i.e., Votes for the Republican Presidential candidate in Montana) over the 11 years from 1980 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 8.7E-5.^Show 0.0000871559820738611600000000
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 0.91 in 0.0087% of random cases. Said differently, if you correlated 11,474 random variables^Note Which I absolutely did.
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.

[ 0.69, 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 Republican Presidential candidate in Montana (Percentage of votes)	56.8245	60.4745	52.0715	35.1225	44.1315	58.4395	59.0681	49.5325	55.3515	56.4662	56.9185
Jet fuel used in Somalia (Million Barrels/Day)	0.976243	1.13689	0.7	0.4	0.4	0.975	0.975	0.91	0.91	0.912493	0.891527

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([56.8245,60.4745,52.0715,35.1225,44.1315,58.4395,59.0681,49.5325,55.3515,56.4662,56.9185,])
array_2 = np.array([0.976243,1.13689,0.7,0.4,0.4,0.975,0.975,0.91,0.91,0.912493,0.891527,])
array_1_name = "Votes for the Republican Presidential candidate in Montana"
array_2_name = "Jet fuel used in Somalia"

# 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 Republican Presidential candidate in Montana
Line chart for only Jet fuel used in Somalia
AI-generated correlation image
The spurious research paper: Jetting to the Polls: Exploring the Connection Between Republican Votes in Montana and Jet Fuel Consumption in Somalia

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Correlation ID: 4806 · Black Variable ID: 26128 · Red Variable ID: 24917


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