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AI explanation
As the votes for the Libertarian Presidential candidate in New York increased, it created a ripple effect leading to a surge in interest in "rocking the vote." This newfound enthusiasm for voting caused an unexpected spike in demand for campaign materials, leading to an uptick in production and transportation. This, in turn, led to more fossil fuels being burned, kindling a fiery debate on the impact of third-party candidates on global energy usage. It seems like even from a distance, political choices can have far-reaching, electrifying consequences in unexpected places.
Model: dalle-3
Prompt: Create an image of a New York City skyscraper interior, with people bustling around, and a ballot box filling up with votes for the Libertarian Presidential candidate. Show the numbers on the ballot box steadily increasing. Additionally, depict a busy market scene in Haiti, with people lined up to purchase fossil fuels for their daily needs. As campaign materials are produced and transported across the country, showcase a surge in fuel usage. The image should convey the unexpected link between distant places, sparking a fiery debate on the impact of political choices on global energy usage. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. 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: Vaporwave A scene from Skyrim Cybernetic art a meme An image that looks like it is a scene from 'Star Wars'
ChatGPT: A scene from Skyrim
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti, in the following situation: As the votes for the Libertarian Presidential candidate in New York increased, it created a ripple effect leading to a surge in interest in "rocking the vote." This newfound enthusiasm for voting caused an unexpected spike in demand for campaign materials, leading to an uptick in production and transportation. This, in turn, led to more fossil fuels being burned, kindling a fiery debate on the impact of third-party candidates on global energy usage. It seems like even from a distance, political choices can have far-reaching, electrifying consequences in unexpected places.. Keep the description simple.
ChatGPT: In a bustling New York City skyscraper, a ballot box fills with Votes for the Libertarian Presidential candidate as the numbers steadily increase. Meanwhile, in a busy market in Haiti, people line up to purchase fossil fuels for their daily needs. As the enthusiasm for voting grows, campaign materials are produced and transported across the country, causing a surge in fuel usage. This sparks a fiery debate on the impact of political choices on global energy usage, linking distant places in unexpected ways.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A scene from Skyrim ] and depicting this scene: In a bustling New York City skyscraper, a ballot box fills with Votes for the Libertarian Presidential candidate as the numbers steadily increase. Meanwhile, in a busy market in Haiti, people line up to purchase fossil fuels for their daily needs. As the enthusiasm for voting grows, campaign materials are produced and transported across the country, causing a surge in fuel usage. This sparks a fiery debate on the impact of political choices on global energy usage, linking distant places in unexpected ways. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a New York City skyscraper interior, with people bustling around, and a ballot box filling up with votes for the Libertarian Presidential candidate. Show the numbers on the ballot box steadily increasing. Additionally, depict a busy market scene in Haiti, with people lined up to purchase fossil fuels for their daily needs. As campaign materials are produced and transported across the country, showcase a surge in fuel usage. The image should convey the unexpected link between distant places, sparking a fiery debate on the impact of political choices on global energy usage.
*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 Votes for the Libertarian Presidential candidate in New York caused Fossil fuel use in Haiti to increase. Include one good pun.
AI academic paper
 |
The Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption The Journal of Quirky Social Sciences 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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
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 0.9819962 and p < 0.01 for 1984 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 Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Here is the title and abstract of the paper:
[[TITLE]]
The Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As the age-old saying goes, "politics makes strange bedfellows," and our research is here to prove just how strange those bedfellows can get. In this paper, we embark on a quirky quest to unravel the unexpected connection between voting patterns for the Libertarian presidential candidate in New York and fossil fuel use in Haiti. While these two phenomena may seem as related as a pineapple and a basketball, our data-driven investigation will demonstrate otherwise.
The libertarian impact on New York has always raised eyebrows - or perhaps even prompted a double take like spotting a unicorn on the subway. However, our research stretches beyond the borders of the Empire State to unearth its reverberations across the Caribbean, specifically in Haiti. Yes, we are daring to delve into the world of energy consumption and political ideologies with the same fearless spirit one would use to approach a haphazardly set up Jenga tower.
Much like discovering a hidden treasure map in a dusty attic, our findings promise to shed whimsical light on the enthralling correlation between these seemingly unrelated phenomena. Through the lens of statistical analysis and economic modeling, we will reveal the uncharted territories of socio-political dynamics and energy economics, bringing a touch of levity to the often somber world of academic research.
So, buckle up for this academic rollercoaster ride, because we're about to take you on a journey that's as improbable as finding a snorkel in the Sahara. Let's venture forth and unearth the fossilized connection between New York's presidential votes and Haiti's fuel consumption.
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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.
Here is the title and abstract of the paper:
[[TITLE]]
The Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the age-old saying goes, "politics makes strange bedfellows," and our research is here to prove just how strange those bedfellows can get. In this paper, we embark on a quirky quest to unravel the unexpected connection between voting patterns for the Libertarian presidential candidate in New York and fossil fuel use in Haiti. While these two phenomena may seem as related as a pineapple and a basketball, our data-driven investigation will demonstrate otherwise.
The libertarian impact on New York has always raised eyebrows - or perhaps even prompted a double take like spotting a unicorn on the subway. However, our research stretches beyond the borders of the Empire State to unearth its reverberations across the Caribbean, specifically in Haiti. Yes, we are daring to delve into the world of energy consumption and political ideologies with the same fearless spirit one would use to approach a haphazardly set up Jenga tower.
Much like discovering a hidden treasure map in a dusty attic, our findings promise to shed whimsical light on the enthralling correlation between these seemingly unrelated phenomena. Through the lens of statistical analysis and economic modeling, we will reveal the uncharted territories of socio-political dynamics and energy economics, bringing a touch of levity to the often somber world of academic research.
So, buckle up for this academic rollercoaster ride, because we're about to take you on a journey that's as improbable as finding a snorkel in the Sahara. Let's venture forth and unearth the fossilized connection between New York's presidential votes and Haiti's fuel consumption.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Smith (2010) explored the intricate relationship between political ideologies and environmental impacts, highlighting the potential for unexpected connections that may seem as unlikely as finding a polar bear in the Sahara. Doe et al. (2015) delved into the energy consumption patterns in Caribbean nations, scrutinizing the factors influencing fuel use and painting a vivid picture of the complex web of socio-political dynamics at play. Jones (2018) provided a comprehensive analysis of third-party voting trends in New York, offering insights that could rival the twists and turns of a gripping mystery novel.
Turning to non-fiction literature, the works of "Eco-Politics: Unveiling the Green Agenda" by Green et al. (2019) and "Island Economies: Navigating Energy Challenges" by Caribbean Energy Consortium (2017) shed light on the multifaceted intersection of political stances and energy realities, akin to uncovering a treasure trove of information in an unsuspecting attic.
In the realm of fiction, the riveting novel "The Fossilized Chronicles: A Tale of Energy and Elections" by Literary Luminary (2016) and the enigmatic "Libertarian Legacy: Unearthing Strange Connections" by Mystery Maven (2014) present narratives that seem to blur the lines between reality and fantasy, much like the improbable correlation we aim to unravel in this study.
The literature review also extended to more unconventional sources, including an exhaustive analysis of grocery store receipts, a journey through the footnotes of ancient historical texts, and a daring exploration of the contents of a time capsule from 1912. While these sources may seem outlandish, they sparked a creative spark that could rival the illumination of finding a glow-in-the-dark dinosaur skeleton in a darkened room.
In summary, the literature review encompassed a wide array of scholarly and unconventional sources, laying the groundwork for probing the unexpected and obscure connection between New York's presidential votes and Haiti's fuel consumption.
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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration . You used data from 1984 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 Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
[[INTRODUCTION]]
As the age-old saying goes, "politics makes strange bedfellows," and our research is here to prove just how strange those bedfellows can get. In this paper, we embark on a quirky quest to unravel the unexpected connection between voting patterns for the Libertarian presidential candidate in New York and fossil fuel use in Haiti. While these two phenomena may seem as related as a pineapple and a basketball, our data-driven investigation will demonstrate otherwise.
The libertarian impact on New York has always raised eyebrows - or perhaps even prompted a double take like spotting a unicorn on the subway. However, our research stretches beyond the borders of the Empire State to unearth its reverberations across the Caribbean, specifically in Haiti. Yes, we are daring to delve into the world of energy consumption and political ideologies with the same fearless spirit one would use to approach a haphazardly set up Jenga tower.
Much like discovering a hidden treasure map in a dusty attic, our findings promise to shed whimsical light on the enthralling correlation between these seemingly unrelated phenomena. Through the lens of statistical analysis and economic modeling, we will reveal the uncharted territories of socio-political dynamics and energy economics, bringing a touch of levity to the often somber world of academic research.
So, buckle up for this academic rollercoaster ride, because we're about to take you on a journey that's as improbable as finding a snorkel in the Sahara. Let's venture forth and unearth the fossilized connection between New York's presidential votes and Haiti's fuel consumption.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To uncover the enigmatic link between voting habits in New York and fossil fuel use in Haiti, our research team navigated through a maze of data sources with the same determination one would have when attempting to unravel a Gordian knot. We accessed electoral data from the MIT Election Data and Science Lab and delved into energy consumption statistics from the Energy Information Administration, embracing the cutting-edge technological resources available at our fingertips. The Harvard Dataverse also provided a trove of valuable information that we sifted through with the fervor of a treasure hunter on a quest for academic gold.
Our first step was to gather Presidential election data specifically related to the Libertarian Party, a feat similar in complexity to trying to spot a chameleon in a bag of skittles. We then meticulously compiled both county-level voting data from New York and fossil fuel use figures from Haiti, developing a dataset that could rival the intricacy of a Rubik's Cube. Our timeframe of analysis, spanning from 1984 to 2020, allowed us to capture the evolutionary dance of political tides and energy trends over the past few decades.
With this eclectic mix of data in hand, we set out to conduct a statistical waltz, employing sophisticated techniques akin to a chef crafting a delicate soufflé. Our analysis involved not only straightforward correlation and regression models but also delved into more esoteric methodologies such as time-series analysis and panel data techniques. We wanted to ensure that our investigation of these seemingly disassociated phenomena was as thorough as an avocado enthusiast inspecting each specimen at the market for ripeness.
In order to reveal the intricate web of relationships between voting behavior and energy consumption, we also complemented our quantitative analysis with qualitative insights garnered from interviews with experts in political science and energy economics. This qualitative component added a dash of spice to our rigorous statistical analysis, much like a pinch of cayenne pepper in a gourmet dish.
Ultimately, our methodological approach can be likened to a whimsical fusion of rigorous statistical analysis and charmingly convoluted data wrangling. Through the lens of these methodologies, we endeavored to untangle the web that connects New York's libertarian preferences with Haiti's fuel consumption, presenting our findings with the same jovial spirit one would employ when donning a clown nose at a formal gathering.
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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration .
For the time period 1984 to 2020, you found a correlation 0.9819962, r-squared of 0.9643166, 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 Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the age-old saying goes, "politics makes strange bedfellows," and our research is here to prove just how strange those bedfellows can get. In this paper, we embark on a quirky quest to unravel the unexpected connection between voting patterns for the Libertarian presidential candidate in New York and fossil fuel use in Haiti. While these two phenomena may seem as related as a pineapple and a basketball, our data-driven investigation will demonstrate otherwise.
The libertarian impact on New York has always raised eyebrows - or perhaps even prompted a double take like spotting a unicorn on the subway. However, our research stretches beyond the borders of the Empire State to unearth its reverberations across the Caribbean, specifically in Haiti. Yes, we are daring to delve into the world of energy consumption and political ideologies with the same fearless spirit one would use to approach a haphazardly set up Jenga tower.
Much like discovering a hidden treasure map in a dusty attic, our findings promise to shed whimsical light on the enthralling correlation between these seemingly unrelated phenomena. Through the lens of statistical analysis and economic modeling, we will reveal the uncharted territories of socio-political dynamics and energy economics, bringing a touch of levity to the often somber world of academic research.
So, buckle up for this academic rollercoaster ride, because we're about to take you on a journey that's as improbable as finding a snorkel in the Sahara. Let's venture forth and unearth the fossilized connection between New York's presidential votes and Haiti's fuel consumption.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our investigation into the perplexing relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti has unearthed some astonishing statistical revelations. From the years 1984 to 2020, our data analysis revealed a staggeringly high correlation coefficient of 0.9819962, accompanied by an r-squared value of 0.9643166, and a p-value of less than 0.01. These results painted a picture as clear as a Mona Lisa from a distance, demonstrating a remarkably strong association between these seemingly disparate variables.
In fact, the relationship between Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti was as striking as stumbling upon a clownfish in a coal mine. Who knew that political leanings in one part of the world could be so intricately entwined with energy consumption habits in another? This correlation appears to be as unlikely as discovering a penguin in the Sahara desert, yet our findings leave little room for doubt.
Fig. 1 provides a visual representation of this perplexing connection, showcasing a scatterplot that leaves little doubt about the robustness of this statistical relationship. This figure is akin to stumbling upon a unicorn in the data visualization forest, serving as an emblematic symbol of the whimsical nature of our research findings.
In conclusion, our study offers a fresh perspective on the unexpected interplay between political voting tendencies and energy consumption patterns. These results not only add a new dimension to the scholarly discourse on political and energy economics but also serve as a lighthearted reminder that statistical correlations can sometimes be as surprising as spotting a pineapple at a basketball game.
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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
The Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
[[LITERATURE REVIEW]]
Smith (2010) explored the intricate relationship between political ideologies and environmental impacts, highlighting the potential for unexpected connections that may seem as unlikely as finding a polar bear in the Sahara. Doe et al. (2015) delved into the energy consumption patterns in Caribbean nations, scrutinizing the factors influencing fuel use and painting a vivid picture of the complex web of socio-political dynamics at play. Jones (2018) provided a comprehensive analysis of third-party voting trends in New York, offering insights that could rival the twists and turns of a gripping mystery novel.
Turning to non-fiction literature, the works of "Eco-Politics: Unveiling the Green Agenda" by Green et al. (2019) and "Island Economies: Navigating Energy Challenges" by Caribbean Energy Consortium (2017) shed light on the multifaceted intersection of political stances and energy realities, akin to uncovering a treasure trove of information in an unsuspecting attic.
In the realm of fiction, the riveting novel "The Fossilized Chronicles: A Tale of Energy and Elections" by Literary Luminary (2016) and the enigmatic "Libertarian Legacy: Unearthing Strange Connections" by Mystery Maven (2014) present narratives that seem to blur the lines between reality and fantasy, much like the improbable correlation we aim to unravel in this study.
The literature review also extended to more unconventional sources, including an exhaustive analysis of grocery store receipts, a journey through the footnotes of ancient historical texts, and a daring exploration of the contents of a time capsule from 1912. While these sources may seem outlandish, they sparked a creative spark that could rival the illumination of finding a glow-in-the-dark dinosaur skeleton in a darkened room.
In summary, the literature review encompassed a wide array of scholarly and unconventional sources, laying the groundwork for probing the unexpected and obscure connection between New York's presidential votes and Haiti's fuel consumption.
[[RESULTS]]
Our investigation into the perplexing relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti has unearthed some astonishing statistical revelations. From the years 1984 to 2020, our data analysis revealed a staggeringly high correlation coefficient of 0.9819962, accompanied by an r-squared value of 0.9643166, and a p-value of less than 0.01. These results painted a picture as clear as a Mona Lisa from a distance, demonstrating a remarkably strong association between these seemingly disparate variables.
In fact, the relationship between Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti was as striking as stumbling upon a clownfish in a coal mine. Who knew that political leanings in one part of the world could be so intricately entwined with energy consumption habits in another? This correlation appears to be as unlikely as discovering a penguin in the Sahara desert, yet our findings leave little room for doubt.
Fig. 1 provides a visual representation of this perplexing connection, showcasing a scatterplot that leaves little doubt about the robustness of this statistical relationship. This figure is akin to stumbling upon a unicorn in the data visualization forest, serving as an emblematic symbol of the whimsical nature of our research findings.
In conclusion, our study offers a fresh perspective on the unexpected interplay between political voting tendencies and energy consumption patterns. These results not only add a new dimension to the scholarly discourse on political and energy economics but also serve as a lighthearted reminder that statistical correlations can sometimes be as surprising as spotting a pineapple at a basketball game.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our findings have certainly opened a veritable treasure chest of puzzling connections, shedding light on the thought-provoking relationship between voting behaviors in New York and fossil fuel use in Haiti. Our results, which exhibited a correlation coefficient of 0.9819962 and a p-value of less than 0.01, not only supported the prior research by Smith (2010) and Doe et al. (2015) but also added a layer of intrigue that could rival a Sherlock Holmes mystery.
The strong association we uncovered between Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti is as unexpected as finding a snowplow in the Saharan sands. This correlation seems as unlikely as chancing upon a coin-operated machine in a coconut grove. And yet, our study has laid bare the captivating interplay between political leanings in one geographical sphere and energy consumption patterns in another, akin to discovering a treasure map in a library book.
The staggering statistical relationship we observed is as remarkable as finding an oasis in the desert of data analysis. Much like uncovering a diamond in the rough, our results defy conventional expectations, underscoring the playful unpredictability of statistical phenomena. While Smith (2010) hinted at the potential for surprising connections, our study has taken this notion to a whole new level, much like stumbling upon a pot of gold at the end of a statistical rainbow.
In summary, our findings not only validate the earlier research on the intricate interconnections between political ideologies and energy usage but also elevate the scholarly discourse to new heights. Our results serve as a lighthearted yet substantial reminder that statistical correlations can occasionally be as startling as finding a straw in a haystack. Much like a jigsaw puzzle falling into place, our study has offered an exciting peek into the unconventional and whimsical side of statistical relationships, providing a refreshing perspective that is as refreshing as finding a lemonade stand in the Arctic.
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 Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti. Make lots of jokes, goofy observations, and puns.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
[[ABSTRACT]]
This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
[[INTRDUCTION]]
As the age-old saying goes, "politics makes strange bedfellows," and our research is here to prove just how strange those bedfellows can get. In this paper, we embark on a quirky quest to unravel the unexpected connection between voting patterns for the Libertarian presidential candidate in New York and fossil fuel use in Haiti. While these two phenomena may seem as related as a pineapple and a basketball, our data-driven investigation will demonstrate otherwise.
The libertarian impact on New York has always raised eyebrows - or perhaps even prompted a double take like spotting a unicorn on the subway. However, our research stretches beyond the borders of the Empire State to unearth its reverberations across the Caribbean, specifically in Haiti. Yes, we are daring to delve into the world of energy consumption and political ideologies with the same fearless spirit one would use to approach a haphazardly set up Jenga tower.
Much like discovering a hidden treasure map in a dusty attic, our findings promise to shed whimsical light on the enthralling correlation between these seemingly unrelated phenomena. Through the lens of statistical analysis and economic modeling, we will reveal the uncharted territories of socio-political dynamics and energy economics, bringing a touch of levity to the often somber world of academic research.
So, buckle up for this academic rollercoaster ride, because we're about to take you on a journey that's as improbable as finding a snorkel in the Sahara. Let's venture forth and unearth the fossilized connection between New York's presidential votes and Haiti's fuel consumption.
[[RESULTS]]
Our investigation into the perplexing relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti has unearthed some astonishing statistical revelations. From the years 1984 to 2020, our data analysis revealed a staggeringly high correlation coefficient of 0.9819962, accompanied by an r-squared value of 0.9643166, and a p-value of less than 0.01. These results painted a picture as clear as a Mona Lisa from a distance, demonstrating a remarkably strong association between these seemingly disparate variables.
In fact, the relationship between Votes for the Libertarian Presidential candidate in New York and Fossil fuel use in Haiti was as striking as stumbling upon a clownfish in a coal mine. Who knew that political leanings in one part of the world could be so intricately entwined with energy consumption habits in another? This correlation appears to be as unlikely as discovering a penguin in the Sahara desert, yet our findings leave little room for doubt.
Fig. 1 provides a visual representation of this perplexing connection, showcasing a scatterplot that leaves little doubt about the robustness of this statistical relationship. This figure is akin to stumbling upon a unicorn in the data visualization forest, serving as an emblematic symbol of the whimsical nature of our research findings.
In conclusion, our study offers a fresh perspective on the unexpected interplay between political voting tendencies and energy consumption patterns. These results not only add a new dimension to the scholarly discourse on political and energy economics but also serve as a lighthearted reminder that statistical correlations can sometimes be as surprising as spotting a pineapple at a basketball game.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In closing, our research has taken us on a journey as improbable as finding a snorkel in the Sahara, unveiling the fossilized connection between New York's presidential votes and Haiti's fuel consumption, akin to stumbling upon a clownfish in a coal mine. The correlation coefficient of 0.9819962 and a p-value of < 0.01 have left us as flabbergasted as chancing upon a penguin in the Sahara desert.
The statistically significant relationship between the two seemingly unrelated phenomena is bound to make as much sense as a pineapple at a basketball game. It's as unexpected as finding a unicorn in the data visualization forest, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another.
Our findings stretch beyond the borders of the Empire State to unearth its reverberations across the Caribbean, specifically in Haiti. Our study not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can often be as surprising as finding a fossil in your backyard.
In light of these findings, we assert that no more research is needed in this area. After all, how many more surprises can one handle?
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 Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Quirky Social Sciences
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 Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Transnational Political and Environmental Studies
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 Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption with an abstract of This research paper investigates the surprising relationship between voting tendencies for the Libertarian presidential candidate in New York and fossil fuel use in Haiti, spanning the years 1984 to 2020. Leveraging data from the MIT Election Data and Science Lab, Harvard Dataverse and Energy Information Administration, our study unveils a correlation coefficient of 0.9819962 and a statistically significant p-value of < 0.01 between these seemingly unrelated phenomena. Our findings open a Pandora's Box of peculiar connections, shedding light on the potential interplay between political ideologies in one part of the world and the energy habits in another. This research not only adds an exciting new dimension to the field of political and energy economics but also serves as a playful reminder that statistical relationships can sometimes be as surprising as finding a fossil in your backyard.
ChatGPT:
Libertarian presidential candidate, New York voting tendencies, fossil fuel use, Haiti, correlation coefficient, statistical significance, political ideologies, energy habits, political economics, energy economics
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Votes for the Libertarian Presidential candidate in New YorkDetailed data title: Percentage of all votes cast for the Libertarian Presidential candidate in New York
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Libertarian Presidential candidate in New York
Fossil fuel use in Haiti
Detailed data title: Total fossil fuel use in Haiti in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in Haiti
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 = 0.9643166 (Coefficient of determination)
This means 96.4% of the change in the one variable (i.e., Fossil fuel use in Haiti) is predictable based on the change in the other (i.e., Votes for the Libertarian Presidential candidate in New York) over the 10 years from 1984 through 2020.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.5E-7. 0.0000004497977263171473000000
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 0.98 in 4.5E-5% of random cases. Said differently, if you correlated 2,223,222 random variables You don't actually need 2 million 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 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.
[ 0.92, 1 ] 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.
| 1984 | 1988 | 1992 | 1996 | 2000 | 2004 | 2008 | 2012 | 2016 | 2020 | |
| Votes for the Libertarian Presidential candidate in New York (Percentage of votes) | 0.175545 | 0.186704 | 0.190001 | 0.189777 | 0.109896 | 0.155835 | 0.253768 | 0.661703 | 0.736239 | 0.695403 |
| Fossil fuel use in Haiti (Billion kWh) | 0.19 | 0.263 | 0.226 | 0.355 | 0.24816 | 0.26978 | 0.2867 | 0.82626 | 0.95222 | 0.805145 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
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([0.175545,0.186704,0.190001,0.189777,0.109896,0.155835,0.253768,0.661703,0.736239,0.695403,])
array_2 = np.array([0.19,0.263,0.226,0.355,0.24816,0.26978,0.2867,0.82626,0.95222,0.805145,])
array_1_name = "Votes for the Libertarian Presidential candidate in New York"
array_2_name = "Fossil fuel use in Haiti"
# 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.
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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 the Libertarian Presidential candidate in New York
- Line chart for only Fossil fuel use in Haiti
- AI-generated correlation image
- The spurious research paper: The Libertarian Effect: Unveiling the Fossilized Connection Between New York's Presidential Votes and Haiti's Fuel Consumption
Your rating is much appreciated!
Correlation ID: 4626 · Black Variable ID: 26143 · Red Variable ID: 23717
