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AI explanation
The Democrats in Minnesota rallied for clean energy, leading to a demand for eco-friendly jet fuel. This prompted Papua New Guinea to start importing more sustainable jet fuel from the US, ultimately boosting the overall usage. It's a political and environmental chain reaction taking off at a global level!
Model: dalle-3
Prompt: Prompt: Generate an image of a bustling airport in Papua New Guinea where a large airplane, fueled by eco-friendly jet fuel from the US, lands smoothly on the tarmac. Simultaneously, in Minnesota, a group of people proudly cast their votes for Democratic Senators, champions of clean energy policies. The interconnected scenes depict the eco-friendly jet fuel's arrival, driven by the Democrats' environmental initiatives, sparking a shift towards sustainable fuel usage at a global level. The image should illustrate the environmental connection between the two locations and the impact of clean energy policies. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for Democratic Senators in Minnesota and Jet fuel used in Papua New Guinea. 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: Realistic Glitch art Cyberpunk Scalar art Concept art
ChatGPT: Realistic
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for Democratic Senators in Minnesota and Jet fuel used in Papua New Guinea, in the following situation: The Democrats in Minnesota rallied for clean energy, leading to a demand for eco-friendly jet fuel. This prompted Papua New Guinea to start importing more sustainable jet fuel from the US, ultimately boosting the overall usage. It's a political and environmental chain reaction taking off at a global level!. Keep the description simple.
ChatGPT: In a bustling airport in Papua New Guinea, a large airplane fueled by eco-friendly jet fuel from the US lands smoothly on the tarmac. Meanwhile, in Minnesota, a group of people proudly cast their votes for Democratic Senators, who had championed clean energy policies. The two scenes are interconnected as the eco-friendly jet fuel, driven by the Democrats' environmental initiatives, arrives in Papua New Guinea, sparking a shift towards sustainable fuel usage at a global level.
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: [ Realistic ] and depicting this scene: In a bustling airport in Papua New Guinea, a large airplane fueled by eco-friendly jet fuel from the US lands smoothly on the tarmac. Meanwhile, in Minnesota, a group of people proudly cast their votes for Democratic Senators, who had championed clean energy policies. The two scenes are interconnected as the eco-friendly jet fuel, driven by the Democrats' environmental initiatives, arrives in Papua New Guinea, sparking a shift towards sustainable fuel usage at a global level. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of a bustling airport in Papua New Guinea where a large airplane, fueled by eco-friendly jet fuel from the US, lands smoothly on the tarmac. Simultaneously, in Minnesota, a group of people proudly cast their votes for Democratic Senators, champions of clean energy policies. The interconnected scenes depict the eco-friendly jet fuel's arrival, driven by the Democrats' environmental initiatives, sparking a shift towards sustainable fuel usage at a global level. The image should illustrate the environmental connection between the two locations and the impact of clean energy policies.
*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.
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 an increase in Democrat votes for Senators in Minnesota caused Jet fuel used in Papua New Guinea to increase.
AI academic paper
 |
The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea The Journal of Ecological Politics and International Energy Relations Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title seem clever.
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 0.9243605 and p < 0.01 for 1980 to 2020.
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]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. 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.
Here is the title and abstract of the paper:
[[TITLE]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As researchers, we often find ourselves traversing uncharted territories in search of unexpected connections and correlations that leave us pleasantly bewildered. Our latest foray into the world of political voting patterns and energy consumption has led us to uncover a surprising relationship between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea. This remarkable discovery has captivated our scientific curiosity and nudged us to delve deeper into the underlying mechanisms driving this unexpected association.
The pursuit of scientific knowledge often takes us to unexpected places, much like a physicist taking an impromptu trip to the zoo - it's a journey of discovery that is bound to ruffle some feathers. In this case, the feathers being ruffled are those of conventional wisdom, as our findings challenge the notion of disparate, unrelated spheres of political decision-making and fuel consumption.
Utilizing a rich and comprehensive dataset spanning over four decades, we employed rigorous statistical methods to scrutinize the intricate relationship between Democrat votes in Minnesota and jet fuel consumption in Papua New Guinea. Our analysis revealed a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, illustrating a strong and significant positive association between these seemingly distant variables.
As we ponder the implications of our findings, we are reminded of a classic dad joke: "I would tell you a joke about UDP, but you might not get it." Much like this playful jest, our research has unearthed a connection that invites further exploration and leaves us with a sense of genuine surprise.
In the following sections, we will delve into the intricacies of our methodology, present our findings in detail, and discuss potential explanations for this unexpected relationship. Our aim is to shed light on a phenomenon that challenges traditional boundaries and inspires further inquiry into the fascinating interplay between political dynamics and energy usage.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.
Here is the title and abstract of the paper:
[[TITLE]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As researchers, we often find ourselves traversing uncharted territories in search of unexpected connections and correlations that leave us pleasantly bewildered. Our latest foray into the world of political voting patterns and energy consumption has led us to uncover a surprising relationship between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea. This remarkable discovery has captivated our scientific curiosity and nudged us to delve deeper into the underlying mechanisms driving this unexpected association.
The pursuit of scientific knowledge often takes us to unexpected places, much like a physicist taking an impromptu trip to the zoo - it's a journey of discovery that is bound to ruffle some feathers. In this case, the feathers being ruffled are those of conventional wisdom, as our findings challenge the notion of disparate, unrelated spheres of political decision-making and fuel consumption.
Utilizing a rich and comprehensive dataset spanning over four decades, we employed rigorous statistical methods to scrutinize the intricate relationship between Democrat votes in Minnesota and jet fuel consumption in Papua New Guinea. Our analysis revealed a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, illustrating a strong and significant positive association between these seemingly distant variables.
As we ponder the implications of our findings, we are reminded of a classic dad joke: "I would tell you a joke about UDP, but you might not get it." Much like this playful jest, our research has unearthed a connection that invites further exploration and leaves us with a sense of genuine surprise.
In the following sections, we will delve into the intricacies of our methodology, present our findings in detail, and discuss potential explanations for this unexpected relationship. Our aim is to shed light on a phenomenon that challenges traditional boundaries and inspires further inquiry into the fascinating interplay between political dynamics and energy usage.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Given the unexpected nature of our findings, we begin this literature review by looking at established research on political voting patterns and energy consumption, before embarking on a playful tangent. Smith and Doe (2008) examined the political landscape of Minnesota and its voting behaviors. Their work delved into the historical context and demographic factors shaping voting preferences in the state. Meanwhile, Jones (2015) explored the intricacies of energy consumption in geographical regions with limited access to modern infrastructure, shedding light on the challenges and opportunities in remote energy usage.
Transitioning to a more lighthearted note, we can't help but draw inspiration from non-fiction works that tangentially relate to our unexpected findings. In "The Energy of Nations" by Jeremy Leggett, the author examines the interplay between politics and energy, albeit on a global scale. On the political front, "Minnesota Politics and Government" by Daniel S. Rowe offers a comprehensive analysis of the state's political landscape. Turning to the realm of fiction, "Jet Fuel" by Leopoldo Gout and "Minnesota Nice" by Ellen and David K. Wenzel present intriguing titles that, while not directly related to our study, certainly capture the essence of our unexpected correlation.
Venturing into the world of social media, we stumbled upon an intriguing post on Twitter that read, "Just realized that my favorite Senator from Minnesota and my favorite jet fuel brand both have 'blue' in their names. Coincidence? I think not! #MinnesotaBlue #JetFuelDreams" This light-hearted commentary showcases the spontaneous musings of individuals navigating the fascinating landscape of political and energy-related discussions. Similarly, a Facebook post humorously quipped, "Who would've thought that the secret to Papua New Guinea's energy woes lies in the voting booths of Minnesota? #BlueWaveofFuel"
In navigating the unexpected terrain of our research, we are reminded of the words of wisdom from the academic sphere: "Why did the statistician break up with the chemist? They had no chemistry." Much like this quip, our study unearths a surprising connection that piques our academic curiosity and beckons further investigation into the whimsical interplay of political dynamics and energy consumption.
Next in the paper, we would delve into a detailed presentation of our methodology, findings, and discussion of potential explanations for this intriguing correlation.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. 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]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
[[INTRODUCTION]]
As researchers, we often find ourselves traversing uncharted territories in search of unexpected connections and correlations that leave us pleasantly bewildered. Our latest foray into the world of political voting patterns and energy consumption has led us to uncover a surprising relationship between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea. This remarkable discovery has captivated our scientific curiosity and nudged us to delve deeper into the underlying mechanisms driving this unexpected association.
The pursuit of scientific knowledge often takes us to unexpected places, much like a physicist taking an impromptu trip to the zoo - it's a journey of discovery that is bound to ruffle some feathers. In this case, the feathers being ruffled are those of conventional wisdom, as our findings challenge the notion of disparate, unrelated spheres of political decision-making and fuel consumption.
Utilizing a rich and comprehensive dataset spanning over four decades, we employed rigorous statistical methods to scrutinize the intricate relationship between Democrat votes in Minnesota and jet fuel consumption in Papua New Guinea. Our analysis revealed a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, illustrating a strong and significant positive association between these seemingly distant variables.
As we ponder the implications of our findings, we are reminded of a classic dad joke: "I would tell you a joke about UDP, but you might not get it." Much like this playful jest, our research has unearthed a connection that invites further exploration and leaves us with a sense of genuine surprise.
In the following sections, we will delve into the intricacies of our methodology, present our findings in detail, and discuss potential explanations for this unexpected relationship. Our aim is to shed light on a phenomenon that challenges traditional boundaries and inspires further inquiry into the fascinating interplay between political dynamics and energy usage.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To uncover the perplexing relationship between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea, we embarked on a methodological adventure that involved traversing through vast troves of data and employing an array of analytical techniques that would make even a statistician ponder his life choices.
First and foremost, we amassed a treasure trove of data from renowned sources such as the MIT Election Data and Science Lab, Harvard Dataverse, and the Energy Information Administration. This process involved sifting through countless spreadsheets, databases, and web archives - an endeavor reminiscent of a valiant knight bravely navigating through a labyrinth to seek the elusive golden fleece (or in our case, correlations that leave us scratching our heads).
Once we had assembled our dataset, spanning from 1980 to 2020, we embarked on the arduous task of cleaning and organizing the data. We sieved through the data with the meticulousness of a grape inspector selecting only the ripest grapes for the finest wine, discarding any discrepancies and outliers like a discerning sommelier casting aside a flawed vintage.
The next step in our odyssey involved the application of rigorous statistical methods to tease out the hidden associations between the proportion of Democrat Senate votes in Minnesota and the jet fuel consumption in Papua New Guinea. We navigated through the statistical landscape like intrepid explorers, sifting through regression analyses, correlation coefficients, and trend analyses with the mindfulness of a seasoned cartographer carefully plotting a new course through uncharted territories.
As we meticulously combed through the data, our pursuit of correlation led us to uncover a surprising relationship with a correlation coefficient of 0.9243605 and a p-value that proudly proclaimed "< 0.01." These results left us as startled as a physicist bumping into an elusive particle in the Large Hadron Collider's data – it was a discovery that seemed both improbable and deeply intriguing.
In the spirit of scientific inquiry and a good pun, we approached our analysis with all the humor of a dad joke enthusiast. We were meticulous in our quest to uncover the truth, yet we couldn't resist the occasional quip to lighten the mood, much like a wise-cracking scientist pondering the intricacies of quantum mechanics.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. 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 0.9243605, r-squared of 0.8544423, 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]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As researchers, we often find ourselves traversing uncharted territories in search of unexpected connections and correlations that leave us pleasantly bewildered. Our latest foray into the world of political voting patterns and energy consumption has led us to uncover a surprising relationship between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea. This remarkable discovery has captivated our scientific curiosity and nudged us to delve deeper into the underlying mechanisms driving this unexpected association.
The pursuit of scientific knowledge often takes us to unexpected places, much like a physicist taking an impromptu trip to the zoo - it's a journey of discovery that is bound to ruffle some feathers. In this case, the feathers being ruffled are those of conventional wisdom, as our findings challenge the notion of disparate, unrelated spheres of political decision-making and fuel consumption.
Utilizing a rich and comprehensive dataset spanning over four decades, we employed rigorous statistical methods to scrutinize the intricate relationship between Democrat votes in Minnesota and jet fuel consumption in Papua New Guinea. Our analysis revealed a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, illustrating a strong and significant positive association between these seemingly distant variables.
As we ponder the implications of our findings, we are reminded of a classic dad joke: "I would tell you a joke about UDP, but you might not get it." Much like this playful jest, our research has unearthed a connection that invites further exploration and leaves us with a sense of genuine surprise.
In the following sections, we will delve into the intricacies of our methodology, present our findings in detail, and discuss potential explanations for this unexpected relationship. Our aim is to shed light on a phenomenon that challenges traditional boundaries and inspires further inquiry into the fascinating interplay between political dynamics and energy usage.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The examination of Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea uncovered a notable correlation. This unexpected relationship has left us both intrigued and in need of some "plane" explanation.
The correlation coefficient of 0.9243605, along with an r-squared value of 0.8544423, indicates a strong positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in Papua New Guinea. If we were to concoct a cocktail of political preferences and aviation fuel, it would certainly be something to "fly" for!
Figure 1 displays a clear and compelling scatterplot that visually encapsulates the robust correlation between the two variables; it's almost as if the data points are jetting off on a statistically significant journey of influence.
It would seem that Democrat support in Minnesota leaves a discernible imprint on the jet fuel scene in Papua New Guinea. This revelation has us wondering if there's a direct flight from Minnesota to Papua New Guinea or if Democrat support is just that powerful. Perhaps we need to call it the "Democrat Jetstream Effect."
In conclusion, our findings have led us to contemplate the reach of political influence across vast geographical distances as well as to perfect our airplane-themed dad jokes. As we ponder the implications of this surprising connection, we are reminded of a classic dad joke: "I used to be a baker, but I couldn't make enough dough." Similarly, our research has certainly kneaded its way into uncovering unexpected relationships in the world of statistics and beyond.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. 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]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
[[LITERATURE REVIEW]]
Given the unexpected nature of our findings, we begin this literature review by looking at established research on political voting patterns and energy consumption, before embarking on a playful tangent. Smith and Doe (2008) examined the political landscape of Minnesota and its voting behaviors. Their work delved into the historical context and demographic factors shaping voting preferences in the state. Meanwhile, Jones (2015) explored the intricacies of energy consumption in geographical regions with limited access to modern infrastructure, shedding light on the challenges and opportunities in remote energy usage.
Transitioning to a more lighthearted note, we can't help but draw inspiration from non-fiction works that tangentially relate to our unexpected findings. In "The Energy of Nations" by Jeremy Leggett, the author examines the interplay between politics and energy, albeit on a global scale. On the political front, "Minnesota Politics and Government" by Daniel S. Rowe offers a comprehensive analysis of the state's political landscape. Turning to the realm of fiction, "Jet Fuel" by Leopoldo Gout and "Minnesota Nice" by Ellen and David K. Wenzel present intriguing titles that, while not directly related to our study, certainly capture the essence of our unexpected correlation.
Venturing into the world of social media, we stumbled upon an intriguing post on Twitter that read, "Just realized that my favorite Senator from Minnesota and my favorite jet fuel brand both have 'blue' in their names. Coincidence? I think not! #MinnesotaBlue #JetFuelDreams" This light-hearted commentary showcases the spontaneous musings of individuals navigating the fascinating landscape of political and energy-related discussions. Similarly, a Facebook post humorously quipped, "Who would've thought that the secret to Papua New Guinea's energy woes lies in the voting booths of Minnesota? #BlueWaveofFuel"
In navigating the unexpected terrain of our research, we are reminded of the words of wisdom from the academic sphere: "Why did the statistician break up with the chemist? They had no chemistry." Much like this quip, our study unearths a surprising connection that piques our academic curiosity and beckons further investigation into the whimsical interplay of political dynamics and energy consumption.
Next in the paper, we would delve into a detailed presentation of our methodology, findings, and discussion of potential explanations for this intriguing correlation.
[[RESULTS]]
The examination of Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea uncovered a notable correlation. This unexpected relationship has left us both intrigued and in need of some "plane" explanation.
The correlation coefficient of 0.9243605, along with an r-squared value of 0.8544423, indicates a strong positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in Papua New Guinea. If we were to concoct a cocktail of political preferences and aviation fuel, it would certainly be something to "fly" for!
Figure 1 displays a clear and compelling scatterplot that visually encapsulates the robust correlation between the two variables; it's almost as if the data points are jetting off on a statistically significant journey of influence.
It would seem that Democrat support in Minnesota leaves a discernible imprint on the jet fuel scene in Papua New Guinea. This revelation has us wondering if there's a direct flight from Minnesota to Papua New Guinea or if Democrat support is just that powerful. Perhaps we need to call it the "Democrat Jetstream Effect."
In conclusion, our findings have led us to contemplate the reach of political influence across vast geographical distances as well as to perfect our airplane-themed dad jokes. As we ponder the implications of this surprising connection, we are reminded of a classic dad joke: "I used to be a baker, but I couldn't make enough dough." Similarly, our research has certainly kneaded its way into uncovering unexpected relationships in the world of statistics and beyond.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our findings have shed light on a truly "plane-tastic" connection between the political landscape of Minnesota and the jet fuel consumption patterns in Papua New Guinea. With a correlation coefficient nearing unity, it appears that the "blue wave" of Democrat support in Minnesota surges across the Pacific, leaving a palpable impact on jet fuel usage in Papua New Guinea. These results not only support but also elevate prior research, affirming the substantial influence of political dynamics on distant energy consumption patterns.
Drawing from the established literature, Smith and Doe's (2008) exploration of Minnesota's political voting behaviors now takes on a new shade of significance. The historical and demographic factors that shape voting patterns not only resonate within the boundaries of Minnesota but seem to extend their reach across geographical expanses, defying traditional explanations. Similarly, Jones's (2015) insights into energy consumption in remote areas gain new dimension as our study underlines the unforeseen interplay between political allegiances and energy usage in a disparate locale. It seems that our research has successfully fueled a new avenue of inquiry into the intricate connections between seemingly unrelated variables.
The playful tangents of our literature review, while originally intended for lighthearted amusement, have now assumed a poignant relevance. The musings on Twitter and Facebook, however whimsical they initially appeared, now encapsulate the essence of our findings with unexpected accuracy, demonstrating the permeation of political influence across vast distances in the most unusual ways. As we navigate this uncharted territory of academic inquiry, it's as if the jokes themselves have taken flight, transcending mere amusement to reflect the genuine intrigue and unexpected outcomes of scientific pursuit.
The robust statistical evidence presented in this study has not only lent support to the unforeseen correlation between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea but has also ignited a "fuel-ish" blaze of curiosity that demands further investigation. Just as the statistician who broke up with the chemist, our study has "jetted" off into uncharted realms, leaving us to reckon with unexpected unions in the realm of statistics and scientific exploration. As we mull over the implications of our findings, we are reminded of a timeless quip: "The past, the present, and the future walk into a bar. It was tense," much like the interplay of historical, contemporary, and unforeseen influences converging in our research landscape. Our study presents a unique juncture of statistical significance and unbridled intellectual curiosity, beckoning the scientific community to delve deeper into the whimsical yet revealing connections that may await discovery in the intricate tapestry of research and inquiry.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Democrat votes for Senators in Minnesota and Jet fuel used in Papua New Guinea. 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]]
"The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea"
[[ABSTRACT]]
This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
[[INTRDUCTION]]
As researchers, we often find ourselves traversing uncharted territories in search of unexpected connections and correlations that leave us pleasantly bewildered. Our latest foray into the world of political voting patterns and energy consumption has led us to uncover a surprising relationship between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea. This remarkable discovery has captivated our scientific curiosity and nudged us to delve deeper into the underlying mechanisms driving this unexpected association.
The pursuit of scientific knowledge often takes us to unexpected places, much like a physicist taking an impromptu trip to the zoo - it's a journey of discovery that is bound to ruffle some feathers. In this case, the feathers being ruffled are those of conventional wisdom, as our findings challenge the notion of disparate, unrelated spheres of political decision-making and fuel consumption.
Utilizing a rich and comprehensive dataset spanning over four decades, we employed rigorous statistical methods to scrutinize the intricate relationship between Democrat votes in Minnesota and jet fuel consumption in Papua New Guinea. Our analysis revealed a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, illustrating a strong and significant positive association between these seemingly distant variables.
As we ponder the implications of our findings, we are reminded of a classic dad joke: "I would tell you a joke about UDP, but you might not get it." Much like this playful jest, our research has unearthed a connection that invites further exploration and leaves us with a sense of genuine surprise.
In the following sections, we will delve into the intricacies of our methodology, present our findings in detail, and discuss potential explanations for this unexpected relationship. Our aim is to shed light on a phenomenon that challenges traditional boundaries and inspires further inquiry into the fascinating interplay between political dynamics and energy usage.
[[RESULTS]]
The examination of Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea uncovered a notable correlation. This unexpected relationship has left us both intrigued and in need of some "plane" explanation.
The correlation coefficient of 0.9243605, along with an r-squared value of 0.8544423, indicates a strong positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in Papua New Guinea. If we were to concoct a cocktail of political preferences and aviation fuel, it would certainly be something to "fly" for!
Figure 1 displays a clear and compelling scatterplot that visually encapsulates the robust correlation between the two variables; it's almost as if the data points are jetting off on a statistically significant journey of influence.
It would seem that Democrat support in Minnesota leaves a discernible imprint on the jet fuel scene in Papua New Guinea. This revelation has us wondering if there's a direct flight from Minnesota to Papua New Guinea or if Democrat support is just that powerful. Perhaps we need to call it the "Democrat Jetstream Effect."
In conclusion, our findings have led us to contemplate the reach of political influence across vast geographical distances as well as to perfect our airplane-themed dad jokes. As we ponder the implications of this surprising connection, we are reminded of a classic dad joke: "I used to be a baker, but I couldn't make enough dough." Similarly, our research has certainly kneaded its way into uncovering unexpected relationships in the world of statistics and beyond.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has uncanny similarities to a captivating magic show – just when you think you've seen it all, a surprising connection emerges, leaving us both mystified and entertained. Our findings have transported us into the realm of statistical sorcery, showcasing a strong positive association between Democrat Senate votes in Minnesota and jet fuel consumption in Papua New Guinea. It's as though the very essence of political preference is fueling the distant aviation habits of Papua New Guinea, leaving us pondering the enigmatic magic of political power.
Our study has broadened our intellectual horizons and highlighted the unexpected ways in which variables from seemingly disparate domains can exert influence on each other – much like a surprising chemistry between two individuals at a scientific conference! As we reflect on the implications of our findings, we are reminded of a classic dad joke: "I told my wife she should embrace her mistakes. She gave me a hug." Similarly, our research has embraced the unexpected connection between political votes and jet fuel consumption, integrating humor into the sometimes serious world of academic inquiry.
With our research shedding light on this unanticipated relationship, we can confidently assert that no more research is needed in this area. It seems that the Democratic Jetstream Effect has flown in, unmasked, and tickled our intellectual curiosity, leaving us with a full tank of statistical satisfaction.
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 The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Ecological Politics and International Energy Relations
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 The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea. Respond only with the name of a fictional organization.
ChatGPT:
The International Association for Cross-Cultural Energy Policy Research
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea with an abstract of This paper ventures into the uncharted territory of linking political voting patterns in the Land of 10,000 Lakes to the consumption of jet fuel in the picturesque Papua New Guinea. Utilizing a comprehensive dataset spanning over four decades and drawing on rigorous statistical methods, we uncovered an unexpected correlation that has left us pleasantly bewildered.
With a correlation coefficient of 0.9243605 and a robust p-value of < 0.01, our findings reveal a striking positive association between the proportion of Democrat votes for Senators in Minnesota and the amount of jet fuel consumed in the verdant lands of Papua New Guinea. It appears that as Democrat support in Minnesota rises, so too does the utilization of jet fuel in the distant island nation.
Our results have left us reconciling with the notion that, indeed, what happens in Minnesota may not stay in Minnesota. It seems that the land of 10,000 lakes may wield an inadvertent yet tangible influence on the fuel consumption habits of the remote Melanesian paradise.
In conclusion, as we ponder the implications of our findings, we are reminded of a classic dad joke: "Why don't skeletons fight each other? They don't have the guts." Yet, in our case, it seems that the skeletal political landscape of Minnesota is challenging the geographical boundaries of influence, leaving us tickled and gasoline-ing up for further research into this unexpected connection.
ChatGPT:
"Minnesota Senate votes, jet fuel consumption, correlation," "Political voting patterns, fuel consumption correlation," "Democrat votes Minnesota, jet fuel Papua New Guinea," "Minnesota political influence, Papua New Guinea jet fuel," "Relationship between Democrat Senate votes, jet fuel consumption," "Political voting patterns, environmental impact," "Minneapolis Democrat votes, Papua New Guinea jet fuel," "Minnesota Senate voting trends, global fuel consumption," "Influence of Minnesota Senate votes on jet fuel use."
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
Discover a new correlation
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Data details
Votes for Democratic Senators in MinnesotaDetailed data title: Total number of votes cast for Federal Democrat Senate candidates in Minnesota
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for Democratic Senators in Minnesota
Jet fuel used in Papua New Guinea
Detailed data title: Volume of jet fuel used consumed in Papua New Guinea in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Jet fuel used in Papua New Guinea
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 = 0.8544423 (Coefficient of determination)
This means 85.4% of the change in the one variable (i.e., Jet fuel used in Papua New Guinea) is predictable based on the change in the other (i.e., Votes for Democratic Senators in Minnesota) over the 14 years from 1980 through 2020.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.3E-6. 0.0000022936547758211875000000
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 0.92 in 0.00023% of random cases. Said differently, if you correlated 435,985 random variables You don't actually need 435 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 13 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 13 because we have two variables measured over a period of 14 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.
[ 0.77, 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.
| 1982 | 1984 | 1988 | 1990 | 1994 | 1996 | 2000 | 2002 | 2006 | 2008 | 2012 | 2014 | 2018 | 2020 | |
| Votes for Democratic Senators in Minnesota (Total votes) | 840401 | 852844 | 856694 | 911999 | 781860 | 1098430 | 1181550 | 1078630 | 1278850 | 1212630 | 1854600 | 1053200 | 2936710 | 1566520 |
| Jet fuel used in Papua New Guinea (Million Barrels/Day) | 1.08333 | 1.26389 | 1.1 | 1.2 | 1.1 | 1.4 | 1.45614 | 1.61846 | 1.79438 | 1.82 | 2.27037 | 0.999397 | 2.81417 | 1.57511 |
Why this works
- Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
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
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. 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([840401,852844,856694,911999,781860,1098430,1181550,1078630,1278850,1212630,1854600,1053200,2936710,1566520,])
array_2 = np.array([1.08333,1.26389,1.1,1.2,1.1,1.4,1.45614,1.61846,1.79438,1.82,2.27037,0.999397,2.81417,1.57511,])
array_1_name = "Votes for Democratic Senators in Minnesota"
array_2_name = "Jet fuel used in Papua New Guinea"
# 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. 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.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Votes for Democratic Senators in Minnesota
- Line chart for only Jet fuel used in Papua New Guinea
- AI-generated correlation image
- The spurious research paper: The Blue and the Fuel: Unearthing the Surprising Relationship Between Democrat Senate Votes in Minnesota and Jet Fuel Consumption in Papua New Guinea
Thanks for being the explorer we needed!
Correlation ID: 5607 · Black Variable ID: 26260 · Red Variable ID: 24801
