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Spurious correlation #4,809 · 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 Republican 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. Small Image
Download png
, svg

AI explanation

When Republican senators in Wyoming fly high with their policies, it really fuels the airwaves. You could say their political ambitions have refueled the demand for Jet fuel in Niue, propelling the nation to new heights!

Model: dalle-3
Prompt: Generate an image of a bustling Wyoming scene, with Republican voters lining up to cast their ballots. Above them, a high-tech private jet, adorned with the American flag, takes off. The jet's engines roar as it climbs higher into the sky. In the background, a tanker truck refuels a small plane on the tarmac in Niue, symbolizing the increased demand for jet fuel due to the ambitious political endeavors of Wyoming's Republican senators. Capture the scene's energy and the juxtaposition of political events alongside aviation infrastructure. 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: Republican votes for 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: Hyper-realistic Hyper-realistic High-tech An image that looks like it is a scene from 'Star Wars' Art nouveau
ChatGPT: High-tech

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 Republican votes for Senators in Wyoming and Jet fuel used in Niue, in the following situation: When Republican senators in Wyoming fly high with their policies, it really fuels the airwaves. You could say their political ambitions have refueled the demand for Jet fuel in Niue, propelling the nation to new heights!. Keep the description simple.
ChatGPT: In a bustling scene in Wyoming, Republican voters line up to cast their ballots, proudly displaying their support. Above them, a private jet emblazoned with the American flag takes off, its engines roaring as it climbs higher into the sky. Meanwhile, in Niue, a tanker truck refuels a small plane on the tarmac, symbolizing the increased demand for jet fuel brought on by the ambitious political endeavors of Wyoming's Republican senators.

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: [ High-tech ] and depicting this scene: In a bustling scene in Wyoming, Republican voters line up to cast their ballots, proudly displaying their support. Above them, a private jet emblazoned with the American flag takes off, its engines roaring as it climbs higher into the sky. Meanwhile, in Niue, a tanker truck refuels a small plane on the tarmac, symbolizing the increased demand for jet fuel brought on by the ambitious political endeavors of Wyoming's Republican senators. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling Wyoming scene, with Republican voters lining up to cast their ballots. Above them, a high-tech private jet, adorned with the American flag, takes off. The jet's engines roar as it climbs higher into the sky. In the background, a tanker truck refuels a small plane on the tarmac in Niue, symbolizing the increased demand for jet fuel due to the ambitious political endeavors of Wyoming's Republican senators. Capture the scene's energy and the juxtaposition of political events alongside aviation infrastructure.

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

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

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

AI academic paper

(Because p < 0.01)
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

The Journal of Eclectic Political and Environmental Studies

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8919074 and p < 0.01 for 2000 to 2018.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

As researchers, we are often told to think outside the box. And boy, did we take that advice to heart! In this study, we set out to unravel the mysteries of a connection that seems as improbable as finding a unicorn in a haystack – the correlation between Republican votes for Senators in the windswept plains of Wyoming and the jet fuel consumption on the remote and idyllic island of Niue. It's the kind of peculiar pairing that makes you scratch your head and ponder the whimsical ways in which the world works.

Venturing into uncharted territory, we delved into the realm of political preferences and energy consumption, armed with our trusty arsenal of data, statistical tools, and a relentless determination to uncover the unexpected. As we embark on this wacky journey, hold on tight, because this research paper is sure to sprinkle in some data-driven humor and bring levity to the often dry landscapes of academic discourse.

So, what do voting habits in the Cowboy State have to do with the jet-setting fuel demands on the "Rock of Polynesia"? While it might sound like the setup for a punchline in a cosmic joke, our analysis has revealed a peculiar relationship that cannot be dismissed as mere happenstance. As we strap in for this wild ride, let's embrace the quirkiness of science and revel in the unpredictable adventure of uncovering the intriguing dynamics of Republican votes and jet fuel usage. So fasten your seatbelts and ready your sense of wonder, because we're about to take off into the zany world of statistical surprises!


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As researchers, we are often told to think outside the box. And boy, did we take that advice to heart! In this study, we set out to unravel the mysteries of a connection that seems as improbable as finding a unicorn in a haystack – the correlation between Republican votes for Senators in the windswept plains of Wyoming and the jet fuel consumption on the remote and idyllic island of Niue. It's the kind of peculiar pairing that makes you scratch your head and ponder the whimsical ways in which the world works.
Venturing into uncharted territory, we delved into the realm of political preferences and energy consumption, armed with our trusty arsenal of data, statistical tools, and a relentless determination to uncover the unexpected. As we embark on this wacky journey, hold on tight, because this research paper is sure to sprinkle in some data-driven humor and bring levity to the often dry landscapes of academic discourse.
So, what do voting habits in the Cowboy State have to do with the jet-setting fuel demands on the "Rock of Polynesia"? While it might sound like the setup for a punchline in a cosmic joke, our analysis has revealed a peculiar relationship that cannot be dismissed as mere happenstance. As we strap in for this wild ride, let's embrace the quirkiness of science and revel in the unpredictable adventure of uncovering the intriguing dynamics of Republican votes and jet fuel usage. So fasten your seatbelts and ready your sense of wonder, because we're about to take off into the zany world of statistical surprises!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In their seminal work, "The Politics of Energy Consumption in North America," Smith and Doe explore the intricate dance between political landscapes and energy usage. Their analysis provides a comprehensive examination of the factors influencing energy consumption, shedding light on the multifaceted relationship between political affiliation and fuel demands. Similarly, Jones et al., in "Voting Patterns and Environmental Impact," delve into the complex nexus of voting behaviors and environmental consequences, with a focus on the surprising interplay between conservative ideologies and resource utilization.

As we delve deeper into the enigmatic connection between Wyoming's GOP votes and Niue's jet fuel usage, we must also consider the impact of geographical isolation. In "Islands in the Jetstream," Taylor and Brown meticulously dissect the idiosyncrasies of energy consumption on remote islands, offering insights into the unique challenges and dependencies faced by these isolated communities. Furthermore, "Flying High: A Comprehensive Study of Aviation Fuels" by Kelly and White presents a thorough analysis of jet fuel usage trends, albeit in a less geopolitical context.

The fictional realm also offers intriguing avenues for exploration. J.K. Rowling's "Harry Potter and the Chamber of Senate Secrets" may not directly address our research question, but the intricate web of political maneuvering and magical energy consumption could provide unforeseen parallels to our study. Additionally, in a more lighthearted and speculative vein, "The Wyoming Wasteland: A Tale of Political Winds and Jet Streams" by G. R. R. Tolkien humorously imagines a world where political allegiances shape the patterns of aviation fuel distribution.

Taking a cue from the strategic maneuvering inherent in board games, "Settlers of Wyoming: Catan Edition" serves as a playful reminder of the intricate resource allocation dynamics that underpin our investigation. Furthermore, "Jet Fuel Jenga" invites us to consider the delicate balance of energy needs and political forces, illustrating the precarious nature of our interconnected world in a whimsical manner.

As we traverse the dizzying landscape of literature related to our offbeat research topic, it becomes evident that the intersection of Republican votes in Wyoming and jet fuel synthesis in Niue forms a tapestry of intrigue and amusement. While our inquiry may have initially raised eyebrows, the literature review reaffirms the richness of this interdisciplinary exploration and sets the stage for our quirky quest for answers.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 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]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

[[INTRODUCTION]]
As researchers, we are often told to think outside the box. And boy, did we take that advice to heart! In this study, we set out to unravel the mysteries of a connection that seems as improbable as finding a unicorn in a haystack – the correlation between Republican votes for Senators in the windswept plains of Wyoming and the jet fuel consumption on the remote and idyllic island of Niue. It's the kind of peculiar pairing that makes you scratch your head and ponder the whimsical ways in which the world works.
Venturing into uncharted territory, we delved into the realm of political preferences and energy consumption, armed with our trusty arsenal of data, statistical tools, and a relentless determination to uncover the unexpected. As we embark on this wacky journey, hold on tight, because this research paper is sure to sprinkle in some data-driven humor and bring levity to the often dry landscapes of academic discourse.
So, what do voting habits in the Cowboy State have to do with the jet-setting fuel demands on the "Rock of Polynesia"? While it might sound like the setup for a punchline in a cosmic joke, our analysis has revealed a peculiar relationship that cannot be dismissed as mere happenstance. As we strap in for this wild ride, let's embrace the quirkiness of science and revel in the unpredictable adventure of uncovering the intriguing dynamics of Republican votes and jet fuel usage. So fasten your seatbelts and ready your sense of wonder, because we're about to take off into the zany world of statistical surprises!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To untangle the perplexing nexus between Wyoming's GOP votes and Niue's jet fuel usage, our research team dived headfirst into a whirlwind of methodological maneuvers. First off, we donned our virtual snorkels and scoured the expansive seas of digital data, trawling through the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration's archives. Armed with spreadsheets and a knack for navigating statistical seas, we cast our net wide and reeled in data spanning the years 2000 to 2018.

With this treasure trove of information in hand, we set our compass to steely precision, charting a course through the choppy waters of regression analysis. Using multivariate regression models, we paddled through the choppy waters of statistical inference, carefully accounting for potential confounding variables like population size, economic indicators, and, of course, the ever-elusive factor of political preference. As we sifted through the waves of data points, we remained vigilant for any dread pirate of spurious correlations that might seek to sabotage our expedition.

Once our statistical ship was anchored in the harbor of correlation calculation, we whipped out our trusty calculator and computed the correlation coefficient with the meticulous care of a master artisan crafting an exquisite masterpiece. Lo and behold, the resulting correlation coefficient of 0.8919074 emerged from the statistical fog, waving its significance flag with a p-value of less than 0.01. A result so striking, it was as if the data were winking and nudging us towards the uncanny connection between red votes and jet fuel.

In our quest for scientific merriment, we also took a detour into the realm of data visualization, sculpting the data into bar graphs and scatterplots with all the flourish of a Renaissance artist. These visual aids served as our compass, guiding us through the turbulent seas of academic scrutiny and beckoning fellow researchers and skeptics to join us in this exhilarating voyage of statistical discovery.

As our expedition draws to a close, we stand on the shores of empirical observation, having weathered the stormy seas of data collection, statistical analysis, and scholarly conjecture. Our findings, while intriguing and delightfully bizarre, stand as a testament to the intrepid spirit of scientific inquiry and the unfathomable quirks of the world we seek to understand.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

For the time period 2000 to 2018, you found a correlation 0.8919074, r-squared of 0.7954989, 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]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
As researchers, we are often told to think outside the box. And boy, did we take that advice to heart! In this study, we set out to unravel the mysteries of a connection that seems as improbable as finding a unicorn in a haystack – the correlation between Republican votes for Senators in the windswept plains of Wyoming and the jet fuel consumption on the remote and idyllic island of Niue. It's the kind of peculiar pairing that makes you scratch your head and ponder the whimsical ways in which the world works.
Venturing into uncharted territory, we delved into the realm of political preferences and energy consumption, armed with our trusty arsenal of data, statistical tools, and a relentless determination to uncover the unexpected. As we embark on this wacky journey, hold on tight, because this research paper is sure to sprinkle in some data-driven humor and bring levity to the often dry landscapes of academic discourse.
So, what do voting habits in the Cowboy State have to do with the jet-setting fuel demands on the "Rock of Polynesia"? While it might sound like the setup for a punchline in a cosmic joke, our analysis has revealed a peculiar relationship that cannot be dismissed as mere happenstance. As we strap in for this wild ride, let's embrace the quirkiness of science and revel in the unpredictable adventure of uncovering the intriguing dynamics of Republican votes and jet fuel usage. So fasten your seatbelts and ready your sense of wonder, because we're about to take off into the zany world of statistical surprises!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our intrepid journey into the wacky world of statistical analysis has led us to some truly astounding findings. After crunching the numbers and sifting through the data with the gusto of a pirate searching for treasure, we uncovered a correlation coefficient of 0.8919074 between Republican votes for Senators in Wyoming and the jet fuel consumption in Niue. It's the kind of correlation that would make even the most seasoned statistician do a double take, akin to stumbling upon a pineapple in the middle of a snowy tundra.

To put it in perspective, our r-squared value of 0.7954989 suggests that a staggering 79.55% of the variation in Niue's jet fuel usage can be explained by the Republican votes for Senators in Wyoming. It's almost as if there's a secret handshake between political preferences in the land of bison and the fuel needs of a tiny island in the South Pacific, reminiscent of a clandestine cabal plotting to unite seemingly disparate entities.

Not to mention, our p-value of less than 0.01 has us more confident in this connection than a scientist who just discovered a new element on the periodic table. The probability of this relationship occurring by chance is so slim that it's like finding a needle in a haystack, or in this case, a red state-blue state connection across thousands of miles of ocean.

Fig. 1 showcases the visual evidence of this mind-boggling correlation, with a scatterplot that could rival the abstract paintings of the avant-garde movement. The points on the graph seem to dance in perfect unison, illustrating the unlikely harmony between the political landscape of Wyoming and the aviation fuel demands in Niue. It's a waltz of data points that could make even the most stoic researcher do a little jig in disbelief.

These results, while unconventional and puzzling, stand as a testament to the zany and unpredictable connections that can emerge from the annals of statistical exploration. So, fasten your seatbelts and prepare for a statistical rollercoaster ride, because our findings have taken us on a journey no less perplexing than a Rubik's Cube in a funhouse.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

[[LITERATURE REVIEW]]
In their seminal work, "The Politics of Energy Consumption in North America," Smith and Doe explore the intricate dance between political landscapes and energy usage. Their analysis provides a comprehensive examination of the factors influencing energy consumption, shedding light on the multifaceted relationship between political affiliation and fuel demands. Similarly, Jones et al., in "Voting Patterns and Environmental Impact," delve into the complex nexus of voting behaviors and environmental consequences, with a focus on the surprising interplay between conservative ideologies and resource utilization.
As we delve deeper into the enigmatic connection between Wyoming's GOP votes and Niue's jet fuel usage, we must also consider the impact of geographical isolation. In "Islands in the Jetstream," Taylor and Brown meticulously dissect the idiosyncrasies of energy consumption on remote islands, offering insights into the unique challenges and dependencies faced by these isolated communities. Furthermore, "Flying High: A Comprehensive Study of Aviation Fuels" by Kelly and White presents a thorough analysis of jet fuel usage trends, albeit in a less geopolitical context.
The fictional realm also offers intriguing avenues for exploration. J.K. Rowling's "Harry Potter and the Chamber of Senate Secrets" may not directly address our research question, but the intricate web of political maneuvering and magical energy consumption could provide unforeseen parallels to our study. Additionally, in a more lighthearted and speculative vein, "The Wyoming Wasteland: A Tale of Political Winds and Jet Streams" by G. R. R. Tolkien humorously imagines a world where political allegiances shape the patterns of aviation fuel distribution.
Taking a cue from the strategic maneuvering inherent in board games, "Settlers of Wyoming: Catan Edition" serves as a playful reminder of the intricate resource allocation dynamics that underpin our investigation. Furthermore, "Jet Fuel Jenga" invites us to consider the delicate balance of energy needs and political forces, illustrating the precarious nature of our interconnected world in a whimsical manner.
As we traverse the dizzying landscape of literature related to our offbeat research topic, it becomes evident that the intersection of Republican votes in Wyoming and jet fuel synthesis in Niue forms a tapestry of intrigue and amusement. While our inquiry may have initially raised eyebrows, the literature review reaffirms the richness of this interdisciplinary exploration and sets the stage for our quirky quest for answers.

[[RESULTS]]
Our intrepid journey into the wacky world of statistical analysis has led us to some truly astounding findings. After crunching the numbers and sifting through the data with the gusto of a pirate searching for treasure, we uncovered a correlation coefficient of 0.8919074 between Republican votes for Senators in Wyoming and the jet fuel consumption in Niue. It's the kind of correlation that would make even the most seasoned statistician do a double take, akin to stumbling upon a pineapple in the middle of a snowy tundra.
To put it in perspective, our r-squared value of 0.7954989 suggests that a staggering 79.55% of the variation in Niue's jet fuel usage can be explained by the Republican votes for Senators in Wyoming. It's almost as if there's a secret handshake between political preferences in the land of bison and the fuel needs of a tiny island in the South Pacific, reminiscent of a clandestine cabal plotting to unite seemingly disparate entities.
Not to mention, our p-value of less than 0.01 has us more confident in this connection than a scientist who just discovered a new element on the periodic table. The probability of this relationship occurring by chance is so slim that it's like finding a needle in a haystack, or in this case, a red state-blue state connection across thousands of miles of ocean.
Fig. 1 showcases the visual evidence of this mind-boggling correlation, with a scatterplot that could rival the abstract paintings of the avant-garde movement. The points on the graph seem to dance in perfect unison, illustrating the unlikely harmony between the political landscape of Wyoming and the aviation fuel demands in Niue. It's a waltz of data points that could make even the most stoic researcher do a little jig in disbelief.
These results, while unconventional and puzzling, stand as a testament to the zany and unpredictable connections that can emerge from the annals of statistical exploration. So, fasten your seatbelts and prepare for a statistical rollercoaster ride, because our findings have taken us on a journey no less perplexing than a Rubik's Cube in a funhouse.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our investigation into the seemingly whimsical relationship between Republican votes for Senators in Wyoming and the jet fuel consumption in Niue has left us both scratching our heads and eager to share our mind-bending discoveries. As we wade into the choppy waters of correlation and causation, it's worth pondering the age-old chicken-and-egg question: do political preferences in the heart of the American West truly hold sway over the energy needs of a speck in the Pacific Ocean, or are we simply caught in a cosmic game of statistical cat's cradle?

Drawing upon the whimsy residing within the literature review, our results align with the prior playful ponderings of Smith and Doe, who outlined the intricate dance between political landscapes and energy usage. It appears as though our findings have pirouetted into harmony with their insights, with a correlation coefficient so strong that it could lift the spirits of even the most deflated party balloon at a political convention in Wyoming. Furthermore, the work of Taylor and Brown on the idiosyncrasies of energy consumption on remote islands seems to echo in our data, as we witness the intercontinental dance between Wyoming's political winds and Niue's jet streams.

Intriguingly, our statistical rollercoaster ride has not only supported but rather exuberantly embraced the whimsical fantasies proposed in the literary realm. As our scatterplot danced to the beat of statistical syncopation, it echoed the intricate political maneuvering and magical energy consumption of J.K. Rowling's wizarding world, and the hidden web of allegiances shaping aviation fuel distribution in G. R. R. Tolkien's tongue-in-cheek tale. Just as in the fictional narratives, our research has shown that reality can indeed be stranger than fiction, especially when examining the curious connection between seemingly unrelated variables.

While our results may have initially raised eyebrows – and perhaps a few chuckles – our findings speak volumes about the interconnected nature of the world around us. The puzzle pieces of political forces and energy demands, much like a jet fuel Jenga tower, have revealed an unexpectedly delicate equilibrium that defies conventional wisdom. And let's not forget the p < 0.01, which firmly plants our feet on the ground and assures us that this is no statistical fluke, but a legitimate rumblestrip on the highway of academic inquiry.

In closing, our quirky quest for answers has yielded a bounty of unexpected connections, offering a refreshing reminder that the world of science and research is not devoid of whimsy and wonder. So, as we bid adieu to this zany journey of discovery, we leave you with a gentle reminder that in the realm of statistical exploration, truth can indeed be stranger than fiction, and correlations can be as surprising as a pop-up in Whac-A-Mole.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Republican votes for Senators in Wyoming and Jet fuel used in Niue. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use

[[ABSTRACT]]
This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

[[INTRDUCTION]]
As researchers, we are often told to think outside the box. And boy, did we take that advice to heart! In this study, we set out to unravel the mysteries of a connection that seems as improbable as finding a unicorn in a haystack – the correlation between Republican votes for Senators in the windswept plains of Wyoming and the jet fuel consumption on the remote and idyllic island of Niue. It's the kind of peculiar pairing that makes you scratch your head and ponder the whimsical ways in which the world works.
Venturing into uncharted territory, we delved into the realm of political preferences and energy consumption, armed with our trusty arsenal of data, statistical tools, and a relentless determination to uncover the unexpected. As we embark on this wacky journey, hold on tight, because this research paper is sure to sprinkle in some data-driven humor and bring levity to the often dry landscapes of academic discourse.
So, what do voting habits in the Cowboy State have to do with the jet-setting fuel demands on the "Rock of Polynesia"? While it might sound like the setup for a punchline in a cosmic joke, our analysis has revealed a peculiar relationship that cannot be dismissed as mere happenstance. As we strap in for this wild ride, let's embrace the quirkiness of science and revel in the unpredictable adventure of uncovering the intriguing dynamics of Republican votes and jet fuel usage. So fasten your seatbelts and ready your sense of wonder, because we're about to take off into the zany world of statistical surprises!

[[RESULTS]]
Our intrepid journey into the wacky world of statistical analysis has led us to some truly astounding findings. After crunching the numbers and sifting through the data with the gusto of a pirate searching for treasure, we uncovered a correlation coefficient of 0.8919074 between Republican votes for Senators in Wyoming and the jet fuel consumption in Niue. It's the kind of correlation that would make even the most seasoned statistician do a double take, akin to stumbling upon a pineapple in the middle of a snowy tundra.
To put it in perspective, our r-squared value of 0.7954989 suggests that a staggering 79.55% of the variation in Niue's jet fuel usage can be explained by the Republican votes for Senators in Wyoming. It's almost as if there's a secret handshake between political preferences in the land of bison and the fuel needs of a tiny island in the South Pacific, reminiscent of a clandestine cabal plotting to unite seemingly disparate entities.
Not to mention, our p-value of less than 0.01 has us more confident in this connection than a scientist who just discovered a new element on the periodic table. The probability of this relationship occurring by chance is so slim that it's like finding a needle in a haystack, or in this case, a red state-blue state connection across thousands of miles of ocean.
Fig. 1 showcases the visual evidence of this mind-boggling correlation, with a scatterplot that could rival the abstract paintings of the avant-garde movement. The points on the graph seem to dance in perfect unison, illustrating the unlikely harmony between the political landscape of Wyoming and the aviation fuel demands in Niue. It's a waltz of data points that could make even the most stoic researcher do a little jig in disbelief.
These results, while unconventional and puzzling, stand as a testament to the zany and unpredictable connections that can emerge from the annals of statistical exploration. So, fasten your seatbelts and prepare for a statistical rollercoaster ride, because our findings have taken us on a journey no less perplexing than a Rubik's Cube in a funhouse.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has soared to new heights, uncovering a correlation so unexpected it's like finding Bigfoot sipping tea with the Loch Ness Monster. Our findings reveal a connection between Republican votes in Wyoming and jet fuel use in Niue that's more tightly woven than a cat's cradle. It's a statistical tango that would make even the most seasoned researchers do the electric slide in disbelief.

With a correlation coefficient of 0.8919074 and a p-value so minuscule it's like finding a four-leaf clover in a field of statistics, we can confidently say that this relationship is as real as a unicorn in the wilds of Wyoming. The connection between political predilections and island aviation fuel demands is akin to finding a pot of gold at the end of a data rainbow – improbable, yet undeniably fascinating.

Our results stand as a testament to the wacky and wonderful world of statistics, reinforcing the notion that truth is often stranger than fiction. As we bid adieu to this captivating chapter of research, we do so with the assurance that no more investigation is needed in this offbeat area – we've unraveled the enigma and found the unicorn in the haystack. So, let's raise a toast to the quirks of scientific exploration and revel in the delightfully bizarre connections that make the world of research an endlessly amusing ride.


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 Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eclectic Political and Environmental Studies


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 Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for International Energy and Political Relations


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 Flying High: The Link Between Wyoming's GOP Votes and Niue's Jet Fuel Use with an abstract of This paper presents a whimsical investigation into the curious connection between Republican votes for Senators in Wyoming and the amount of jet fuel used in the remote island nation of Niue. While the correlation may seem more absurd than a chicken crossing the road, our team has painstakingly gathered and analyzed data from the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration to tackle this enigmatic relationship. We calculated a correlation coefficient of 0.8919074 and p < 0.01 for the years spanning 2000 to 2018. Our findings, while boggling the mind, shed light on the unexpected interplay between political preferences and energy consumption in far-flung locales. So, buckle up and prepare for a wild ride as we navigate the skies of statistics and soar through the realms of political and environmental peculiarities.

ChatGPT:

Wyoming GOP votes, Niue jet fuel use, correlation coefficient, MIT Election Data and Science Lab, Harvard Dataverse, Energy Information Administration, political preferences, energy consumption, statistics, environmental peculiarities

*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 Republican Senators in Wyoming
Detailed data title: Total number of votes cast for Federal Republican Senate candidates in Wyoming
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Republican 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 = 0.8919074 (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 = 0.7954989 (Coefficient of determination)
This means 79.5% 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 Republican Senators in Wyoming) over the 7 years from 2000 through 2018.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.007. 0.0069553624487964935000000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.89 in 0.7% of random cases. Said differently, if you correlated 144 random variables Which I absolutely did.
with the same 6 degrees of freedom, 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.

[ 0.42, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2000200220062008201220142018
Votes for Republican Senators in Wyoming (Total votes)157622133710135174372109185250121554136210
Jet fuel used in Niue (Million Barrels/Day)0.008233330.008147260.008672810.01791230.009611540.01087290.0110803




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([157622,133710,135174,372109,185250,121554,136210,])
array_2 = np.array([0.00823333,0.00814726,0.00867281,0.0179123,0.00961154,0.0108729,0.0110803,])
array_1_name = "Votes for Republican 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)



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Correlation ID: 4809 · Black Variable ID: 26341 · Red Variable ID: 24769
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