Download png, svg
AI explanation
The clean air in D.C. made it easier for magical pollution-eating unicorns to thrive. These unicorns just so happened to be the main export of France, and as they multiplied, they inadvertently decreased the demand for gasoline-powered transportation in France, leading to a decrease in the need for gasoline overall.
Model: dalle-3
Prompt: Prompt: Generate a cybernetic art representation of Washington, D.C.'s skyline with the smog dispersing and a sense of environmental change, connected with a French gas station displaying fewer gasoline pumps and the rise of renewable energy sources. The image should capture the transition from pollution to clearer air and link it with the shift towards a greener energy landscape, conveying a futuristic and hopeful atmosphere of environmental awareness. 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: Air pollution in Washington, D.C. and Gasoline pumped in France. 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: Cybernetic art Whimsical illustration Cybernetic art Whimsical illustration 3D Pixar Style
ChatGPT: Cybernetic art
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 Air pollution in Washington, D.C. and Gasoline pumped in France, in the following situation: As air quality improved in D.C., it led to a "clearer" understanding of the impact of emissions on the environment. This "enlightened" perspective prompted France to invest more in renewable energy, reducing their reliance on gasoline. It's like the pollution particles just "wafted" away and carried the message across the Atlantic - talk about a breath of fresh air triggering a chain reaction!. Keep the description simple.
ChatGPT: In Washington, D.C., the smoggy sky gradually cleared, revealing a skyline bathed in clearer air. As the pollution particles dissipated, a sense of environmental awareness spread through the city. Across the Atlantic, in France, a gas station sign displayed a decreasing number of gasoline pumps, as renewable energy sources became more prevalent. The wisps of smog seemed to carry the message of change, linking D.C.'s improved air quality with France's shift toward cleaner energy.
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: [ Cybernetic art ] and depicting this scene: In Washington, D.C., the smoggy sky gradually cleared, revealing a skyline bathed in clearer air. As the pollution particles dissipated, a sense of environmental awareness spread through the city. Across the Atlantic, in France, a gas station sign displayed a decreasing number of gasoline pumps, as renewable energy sources became more prevalent. The wisps of smog seemed to carry the message of change, linking D.C.'s improved air quality with France's shift toward cleaner energy. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate a cybernetic art representation of Washington, D.C.'s skyline with the smog dispersing and a sense of environmental change, connected with a French gas station displaying fewer gasoline pumps and the rise of renewable energy sources. The image should capture the transition from pollution to clearer air and link it with the shift towards a greener energy landscape, conveying a futuristic and hopeful atmosphere of environmental awareness.
*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 a decrease in Air pollution in Washington, D.C. caused Gasoline pumped in France to decrease.
AI academic paper
 |
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection The Journal of Environmental Quirks Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title a clever pun.
Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8303654 and p < 0.01 for 1980 to 2022.
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]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Here is the title and abstract of the paper:
[[TITLE]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As we journey through the labyrinthine pathways of scientific inquiry, we often encounter curious connections and unexpected relationships. In this study, we embark on a quest to unravel the enigmatic link between air pollution in the vibrant environs of Washington, D.C., and the unassuming act of gasoline pumping in the picturesque landscapes of France. The esoteric allure of this investigation lies in its ability to merge two seemingly unrelated subjects, forming a nebulous cloud of intrigue within the academic sphere.
Venturing into the realm of air pollution, we are greeted by a smog of data and a haze of statistical analyses. The metropolis of Washington, D.C., serves as our backdrop, with its traffic-laden avenues and urban sprawl providing the canvas upon which the invisible tendrils of pollution weave their intricate tapestry. Meanwhile, across the Atlantic, the idyllic countryside of France beckons, where the humdrum activity of pumping gasoline intertwines with the tranquil rhythm of daily life. It is in this dichotomous juxtaposition that we seek to discern the fateful dance of correlation that manifests on our statistical stage.
Our inquiry is not without precedent, as echoes of similar studies reverberate through the annals of scientific literature. Yet, like intrepid explorers charting uncharted territories, we set out with zeal to uncover a nexus that has eluded the scrutiny of previous investigations. The fume-nomenal connection we seek is not merely a matter of idle curiosity, but rather a testament to the interconnectedness of our global ecosystem, where the exhalations of progress and consumption intertwine in an intricate ballet of cause and effect.
As we peer through the microscope of data analysis, we encounter a tableau of statistical measures and mathematical constructs, each vying for attention in our quest for enlightenment. Through meticulous scrutiny and rigorous examination, we endeavor to illuminate the veiled strands of relationship and dependence that lurk within the seemingly disparate realms of air pollution and gasoline consumption.
With bated breath and a hint of trepidation, we invite our esteemed colleagues to join us on this enthralling expedition, as we unveil the veiled tendrils of connection that bind these two divergent phenomena. Onward we march, armed with the tools of statistical inference and the spirit of intellectual adventure, towards a horizon where the synergy of pollution and petrol awaits, ready to embark upon a journey that promises to be not just illuminating, but perhaps a fume-nally revelatory odyssey.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 name a few real TV shows that sound like they might be relevant to the topic that you watched as research.
Here is the title and abstract of the paper:
[[TITLE]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As we journey through the labyrinthine pathways of scientific inquiry, we often encounter curious connections and unexpected relationships. In this study, we embark on a quest to unravel the enigmatic link between air pollution in the vibrant environs of Washington, D.C., and the unassuming act of gasoline pumping in the picturesque landscapes of France. The esoteric allure of this investigation lies in its ability to merge two seemingly unrelated subjects, forming a nebulous cloud of intrigue within the academic sphere.
Venturing into the realm of air pollution, we are greeted by a smog of data and a haze of statistical analyses. The metropolis of Washington, D.C., serves as our backdrop, with its traffic-laden avenues and urban sprawl providing the canvas upon which the invisible tendrils of pollution weave their intricate tapestry. Meanwhile, across the Atlantic, the idyllic countryside of France beckons, where the humdrum activity of pumping gasoline intertwines with the tranquil rhythm of daily life. It is in this dichotomous juxtaposition that we seek to discern the fateful dance of correlation that manifests on our statistical stage.
Our inquiry is not without precedent, as echoes of similar studies reverberate through the annals of scientific literature. Yet, like intrepid explorers charting uncharted territories, we set out with zeal to uncover a nexus that has eluded the scrutiny of previous investigations. The fume-nomenal connection we seek is not merely a matter of idle curiosity, but rather a testament to the interconnectedness of our global ecosystem, where the exhalations of progress and consumption intertwine in an intricate ballet of cause and effect.
As we peer through the microscope of data analysis, we encounter a tableau of statistical measures and mathematical constructs, each vying for attention in our quest for enlightenment. Through meticulous scrutiny and rigorous examination, we endeavor to illuminate the veiled strands of relationship and dependence that lurk within the seemingly disparate realms of air pollution and gasoline consumption.
With bated breath and a hint of trepidation, we invite our esteemed colleagues to join us on this enthralling expedition, as we unveil the veiled tendrils of connection that bind these two divergent phenomena. Onward we march, armed with the tools of statistical inference and the spirit of intellectual adventure, towards a horizon where the synergy of pollution and petrol awaits, ready to embark upon a journey that promises to be not just illuminating, but perhaps a fume-nally revelatory odyssey.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The study of air pollution and its elusive connections to various aspects of modern life has been a topic of immense interest within the scientific community. Smith et al. (2017) conducted a comprehensive analysis of the impact of vehicular emissions on urban air quality, laying the groundwork for subsequent investigations into the labyrinthine web of pollution dynamics. Their study provided valuable insights into the complex interactions between human activities and atmospheric composition, setting the stage for further exploration into the ethereal realm of airborne pollutants.
As we stray further into the realm of vehicular emissions, Doe and Jones (2019) offer a tantalizing examination of the underlying factors driving air pollution in metropolitan areas. Their work serves as a beacon in the gloom of pollution research, shedding light on the intricacies of urban air quality and highlighting the interconnected nature of atmospheric phenomena. Indeed, the web of pollution extends its tendrils across geopolitical borders, transcending the boundaries of nations to forge connections that challenge traditional notions of causality.
Amidst the serious and purposeful exploration of pollution dynamics, unexpected connections have emerged, casting a whimsical light on the intricate interplay of environmental variables. In "The Omniscient Nose: A Pungent Tale of Airborne Odors," the authors delve into the olfactory realm of atmospheric pollutants, weaving a fragrant tapestry of curious observations and aromatic revelations. This olfactory odyssey serves as a reminder that the study of air pollution is not merely a matter of statistical analysis, but a multisensory exploration that beckons researchers to inhale the nuances of pollution with a curious and discerning nose.
Venturing into the whimsical world of fiction, "Cloud Atlas" by David Mitchell presents a kaleidoscopic narrative that traverses temporal and geographical boundaries, resonating with the enigmatic connections we seek to unravel in our own investigation. The ethereal dance of interconnected storylines in "Cloud Atlas" mirrors the interconnectedness of pollution and petrol, inviting readers to ponder the invisible threads that bind disparate elements in a cosmic symphony of cause and effect.
In our quest for insights, we embraced the medium of television as a source of inspiration and inquiry, immersing ourselves in the fervent depiction of environmental challenges in shows such as "Breaking Bad," "The Crown," and "Stranger Things." While these may seem like unlikely sources for illumination on our topic, the parallel universes they present offer glimpses into the intricate dance of human activities and their environmental reverberations.
As we traverse the landscape of literature and popular culture, we find ourselves confronted with the whimsical and the profound, the unexpected and the enlightening. These esoteric influences have woven themselves into the fabric of our research, imbuing our inquiry with a sense of wonder and mirth that transcends the confines of traditional scientific exploration.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration . You used data from 1980 to 2022
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]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
[[INTRODUCTION]]
As we journey through the labyrinthine pathways of scientific inquiry, we often encounter curious connections and unexpected relationships. In this study, we embark on a quest to unravel the enigmatic link between air pollution in the vibrant environs of Washington, D.C., and the unassuming act of gasoline pumping in the picturesque landscapes of France. The esoteric allure of this investigation lies in its ability to merge two seemingly unrelated subjects, forming a nebulous cloud of intrigue within the academic sphere.
Venturing into the realm of air pollution, we are greeted by a smog of data and a haze of statistical analyses. The metropolis of Washington, D.C., serves as our backdrop, with its traffic-laden avenues and urban sprawl providing the canvas upon which the invisible tendrils of pollution weave their intricate tapestry. Meanwhile, across the Atlantic, the idyllic countryside of France beckons, where the humdrum activity of pumping gasoline intertwines with the tranquil rhythm of daily life. It is in this dichotomous juxtaposition that we seek to discern the fateful dance of correlation that manifests on our statistical stage.
Our inquiry is not without precedent, as echoes of similar studies reverberate through the annals of scientific literature. Yet, like intrepid explorers charting uncharted territories, we set out with zeal to uncover a nexus that has eluded the scrutiny of previous investigations. The fume-nomenal connection we seek is not merely a matter of idle curiosity, but rather a testament to the interconnectedness of our global ecosystem, where the exhalations of progress and consumption intertwine in an intricate ballet of cause and effect.
As we peer through the microscope of data analysis, we encounter a tableau of statistical measures and mathematical constructs, each vying for attention in our quest for enlightenment. Through meticulous scrutiny and rigorous examination, we endeavor to illuminate the veiled strands of relationship and dependence that lurk within the seemingly disparate realms of air pollution and gasoline consumption.
With bated breath and a hint of trepidation, we invite our esteemed colleagues to join us on this enthralling expedition, as we unveil the veiled tendrils of connection that bind these two divergent phenomena. Onward we march, armed with the tools of statistical inference and the spirit of intellectual adventure, towards a horizon where the synergy of pollution and petrol awaits, ready to embark upon a journey that promises to be not just illuminating, but perhaps a fume-nally revelatory odyssey.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
In this section, we elucidate the convoluted concoction of research methods employed in our pursuit of unraveling the fume-nomenal connection between air pollution in Washington, D.C., and gasoline pumped in France. Our strategy resembled a carefully choreographed dance of statistical analysis and data collection, guided by the beacons of scientific rigor and a splash of whimsy.
To commence our quest, we embarked on a digital odyssey across the vast expanse of the World Wide Web, wielding search engines and databases as our trusty compasses. Information hoisted from the Environmental Protection Agency and Energy Information Administration assimilated into our treasure trove, forming the bedrock upon which our analysis would unfold. Navigation through the myriad websites and databases at times felt akin to traversing a labyrinthine maze, with data points lurking behind virtual corners like capricious minotaurs.
Our gaze fell upon records stretching from the year 1980 to 2022, encapsulating over four decades of atmospheric musings and fuel-based endeavors. We diligently transcribed these data points onto our digital parchment, mindful of the vicissitudes of zeroes and ones that lurked in the digital realm. 'Twas a task that required the patience of a saint and the dexterity of a digital sommelier, for the vintage datasets we encountered held the potential to intoxicate our statistical palates.
Armed with these empirical relics, we summoned the forces of statistical machinery to breathe life into our numerical tapestry. Employing a svelte combination of correlation analysis, linear regression, and time-series modeling, we waltzed through the dizzying array of statistical procedures with the meticulous grace of a scientific ballroom dancer.
The inferential cauldron simmered with the concoction of p-values and confidence intervals, serving as our litmus test for the significance of the uncovered relationship. A p-value less than 0.01 elicited a fervent round of elation within our ranks, akin to a scientific touchdown in the realm of data-driven sports.
Throughout this tumultuous voyage, we stood vigilant against the sirens of spurious correlations and the pitfalls of statistical chasms, ensuring the sanctity of our findings in the face of erroneous statistical dalliances. Our methods resembled the delicate strokes of a virtuoso painter, carefully delineating the contours of our analytical masterpiece without succumbing to the chaotic cacophony of spurious patterns.
As the dust settled, and the digital ink dried on our statistical vellum, we found ourselves standing amidst the fume-nomenon that was our discovery, a revelation that transgressed geographical bounds and kindled the flames of curiosity within the halls of academia. We invite our scholarly comrades to not just inhale, but fully immerse themselves in the exhalations of our findings, for what awaits is a breath of erudition infusing the air of intellectual discourse.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration .
For the time period 1980 to 2022, you found a correlation 0.8303654, r-squared of 0.6895067, 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]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As we journey through the labyrinthine pathways of scientific inquiry, we often encounter curious connections and unexpected relationships. In this study, we embark on a quest to unravel the enigmatic link between air pollution in the vibrant environs of Washington, D.C., and the unassuming act of gasoline pumping in the picturesque landscapes of France. The esoteric allure of this investigation lies in its ability to merge two seemingly unrelated subjects, forming a nebulous cloud of intrigue within the academic sphere.
Venturing into the realm of air pollution, we are greeted by a smog of data and a haze of statistical analyses. The metropolis of Washington, D.C., serves as our backdrop, with its traffic-laden avenues and urban sprawl providing the canvas upon which the invisible tendrils of pollution weave their intricate tapestry. Meanwhile, across the Atlantic, the idyllic countryside of France beckons, where the humdrum activity of pumping gasoline intertwines with the tranquil rhythm of daily life. It is in this dichotomous juxtaposition that we seek to discern the fateful dance of correlation that manifests on our statistical stage.
Our inquiry is not without precedent, as echoes of similar studies reverberate through the annals of scientific literature. Yet, like intrepid explorers charting uncharted territories, we set out with zeal to uncover a nexus that has eluded the scrutiny of previous investigations. The fume-nomenal connection we seek is not merely a matter of idle curiosity, but rather a testament to the interconnectedness of our global ecosystem, where the exhalations of progress and consumption intertwine in an intricate ballet of cause and effect.
As we peer through the microscope of data analysis, we encounter a tableau of statistical measures and mathematical constructs, each vying for attention in our quest for enlightenment. Through meticulous scrutiny and rigorous examination, we endeavor to illuminate the veiled strands of relationship and dependence that lurk within the seemingly disparate realms of air pollution and gasoline consumption.
With bated breath and a hint of trepidation, we invite our esteemed colleagues to join us on this enthralling expedition, as we unveil the veiled tendrils of connection that bind these two divergent phenomena. Onward we march, armed with the tools of statistical inference and the spirit of intellectual adventure, towards a horizon where the synergy of pollution and petrol awaits, ready to embark upon a journey that promises to be not just illuminating, but perhaps a fume-nally revelatory odyssey.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our investigation into the relationship between air pollution in Washington, D.C. and gasoline consumption in France yielded intriguing results that are sure to ignite a spark of curiosity within the academic community. The Pearson correlation coefficient between the two variables was calculated to be 0.8303654, displaying a strong positive correlation. The coefficient of determination (R-squared) was found to be 0.6895067, emphasizing that a considerable proportion of the variability in gasoline consumption in France can be explained by the levels of air pollution in Washington, D.C. Furthermore, the p-value was less than 0.01, indicating that the observed correlation is statistically significant.
Figure 1 displays a scatterplot illustrating the robust association between air pollution in Washington, D.C. and gasoline pumped in France. The data points form a distinct pattern that unmistakably showcases the synchrony between the two variables.
This discovery, while initially surprising, speaks volumes about the intricate relationships that underpin environmental dynamics and cross-continental influences. The findings not only point to a tangible connection between seemingly disparate phenomena but also underscore the far-reaching impact of local environmental factors on global trends.
The implications of this revelation sparkle with potential, shedding light on the complex interplay between urban pollution and distant fuel consumption. This suggests a fume-nomenal interconnectedness that transcends geographical boundaries, sparking a fresh wave of inquiry and offering a breath of fresh air in the realm of environmental research.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
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]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
[[LITERATURE REVIEW]]
The study of air pollution and its elusive connections to various aspects of modern life has been a topic of immense interest within the scientific community. Smith et al. (2017) conducted a comprehensive analysis of the impact of vehicular emissions on urban air quality, laying the groundwork for subsequent investigations into the labyrinthine web of pollution dynamics. Their study provided valuable insights into the complex interactions between human activities and atmospheric composition, setting the stage for further exploration into the ethereal realm of airborne pollutants.
As we stray further into the realm of vehicular emissions, Doe and Jones (2019) offer a tantalizing examination of the underlying factors driving air pollution in metropolitan areas. Their work serves as a beacon in the gloom of pollution research, shedding light on the intricacies of urban air quality and highlighting the interconnected nature of atmospheric phenomena. Indeed, the web of pollution extends its tendrils across geopolitical borders, transcending the boundaries of nations to forge connections that challenge traditional notions of causality.
Amidst the serious and purposeful exploration of pollution dynamics, unexpected connections have emerged, casting a whimsical light on the intricate interplay of environmental variables. In "The Omniscient Nose: A Pungent Tale of Airborne Odors," the authors delve into the olfactory realm of atmospheric pollutants, weaving a fragrant tapestry of curious observations and aromatic revelations. This olfactory odyssey serves as a reminder that the study of air pollution is not merely a matter of statistical analysis, but a multisensory exploration that beckons researchers to inhale the nuances of pollution with a curious and discerning nose.
Venturing into the whimsical world of fiction, "Cloud Atlas" by David Mitchell presents a kaleidoscopic narrative that traverses temporal and geographical boundaries, resonating with the enigmatic connections we seek to unravel in our own investigation. The ethereal dance of interconnected storylines in "Cloud Atlas" mirrors the interconnectedness of pollution and petrol, inviting readers to ponder the invisible threads that bind disparate elements in a cosmic symphony of cause and effect.
In our quest for insights, we embraced the medium of television as a source of inspiration and inquiry, immersing ourselves in the fervent depiction of environmental challenges in shows such as "Breaking Bad," "The Crown," and "Stranger Things." While these may seem like unlikely sources for illumination on our topic, the parallel universes they present offer glimpses into the intricate dance of human activities and their environmental reverberations.
As we traverse the landscape of literature and popular culture, we find ourselves confronted with the whimsical and the profound, the unexpected and the enlightening. These esoteric influences have woven themselves into the fabric of our research, imbuing our inquiry with a sense of wonder and mirth that transcends the confines of traditional scientific exploration.
[[RESULTS]]
Our investigation into the relationship between air pollution in Washington, D.C. and gasoline consumption in France yielded intriguing results that are sure to ignite a spark of curiosity within the academic community. The Pearson correlation coefficient between the two variables was calculated to be 0.8303654, displaying a strong positive correlation. The coefficient of determination (R-squared) was found to be 0.6895067, emphasizing that a considerable proportion of the variability in gasoline consumption in France can be explained by the levels of air pollution in Washington, D.C. Furthermore, the p-value was less than 0.01, indicating that the observed correlation is statistically significant.
Figure 1 displays a scatterplot illustrating the robust association between air pollution in Washington, D.C. and gasoline pumped in France. The data points form a distinct pattern that unmistakably showcases the synchrony between the two variables.
This discovery, while initially surprising, speaks volumes about the intricate relationships that underpin environmental dynamics and cross-continental influences. The findings not only point to a tangible connection between seemingly disparate phenomena but also underscore the far-reaching impact of local environmental factors on global trends.
The implications of this revelation sparkle with potential, shedding light on the complex interplay between urban pollution and distant fuel consumption. This suggests a fume-nomenal interconnectedness that transcends geographical boundaries, sparking a fresh wave of inquiry and offering a breath of fresh air in the realm of environmental research.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The striking correlation we uncovered between air pollution in Washington, D.C. and gasoline consumption in France is nothing short of breathtaking. Our results not only align with prior research on the interconnectedness of pollution dynamics but also breathe new life into the study of environmental influences on global trends.
The findings of our study are a breath of fresh air in the scholarly discourse, validating the intuitive notion that air pollution knows no geopolitical boundaries. Building on the work of Smith et al. (2017) and Doe and Jones (2019), our results offer empirical support for the intricate connections between vehicular emissions, urban air quality, and the convoluted dance of global fuel consumption. The correlation coefficient of 0.8303654 serves as a beacon, illuminating the ethereal web of pollution dynamics— a web so delicate, one might say it's a-fragile.
Given the pungent tale of airborne odors presented in "The Omniscient Nose," it is perhaps not surprising that we uncovered such an olfactory in the data. Our findings point to a pungent relationship between the air quality in D.C. and the gasoline consumption in France. Indeed, one could say that the scent of our results perfumes the academic community with a whiff of curiosity that beckons us to take a deep breath and inhale the nuances of this fume-nomenal connection.
It is remarkable how our scholarly journey traverses the whimsical world of fiction and television, like a cloud atlas of eclectic influences that converge to shape our inquiry. In a sense, our findings serve as a narrative thread that weaves through time and space, resonating with Mitchell's "Cloud Atlas" and mirroring the interconnectedness of pollution and petrol in a cosmic symphony of empirical evidence.
In the grand narrative of environmental research, our findings add an unexpected plot twist, challenging conventional notions of causality and inviting the academic community to ponder the unseen threads that bind pollution and petrol in a serendipitous tango.
The implications of our research catapult environmental inquiry into uncharted territory, igniting a spark of curiosity that is sure to fan the flames of future studies. As we inhale the scents of our findings, let us not forget the whimsical influences that have shaped our scholarly pursuit, infusing our research with a sense of wonder and mirth that transcends the confines of traditional scientific exploration.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Washington, D.C. and Gasoline pumped in France. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
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]]
Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
[[ABSTRACT]]
Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
[[INTRDUCTION]]
As we journey through the labyrinthine pathways of scientific inquiry, we often encounter curious connections and unexpected relationships. In this study, we embark on a quest to unravel the enigmatic link between air pollution in the vibrant environs of Washington, D.C., and the unassuming act of gasoline pumping in the picturesque landscapes of France. The esoteric allure of this investigation lies in its ability to merge two seemingly unrelated subjects, forming a nebulous cloud of intrigue within the academic sphere.
Venturing into the realm of air pollution, we are greeted by a smog of data and a haze of statistical analyses. The metropolis of Washington, D.C., serves as our backdrop, with its traffic-laden avenues and urban sprawl providing the canvas upon which the invisible tendrils of pollution weave their intricate tapestry. Meanwhile, across the Atlantic, the idyllic countryside of France beckons, where the humdrum activity of pumping gasoline intertwines with the tranquil rhythm of daily life. It is in this dichotomous juxtaposition that we seek to discern the fateful dance of correlation that manifests on our statistical stage.
Our inquiry is not without precedent, as echoes of similar studies reverberate through the annals of scientific literature. Yet, like intrepid explorers charting uncharted territories, we set out with zeal to uncover a nexus that has eluded the scrutiny of previous investigations. The fume-nomenal connection we seek is not merely a matter of idle curiosity, but rather a testament to the interconnectedness of our global ecosystem, where the exhalations of progress and consumption intertwine in an intricate ballet of cause and effect.
As we peer through the microscope of data analysis, we encounter a tableau of statistical measures and mathematical constructs, each vying for attention in our quest for enlightenment. Through meticulous scrutiny and rigorous examination, we endeavor to illuminate the veiled strands of relationship and dependence that lurk within the seemingly disparate realms of air pollution and gasoline consumption.
With bated breath and a hint of trepidation, we invite our esteemed colleagues to join us on this enthralling expedition, as we unveil the veiled tendrils of connection that bind these two divergent phenomena. Onward we march, armed with the tools of statistical inference and the spirit of intellectual adventure, towards a horizon where the synergy of pollution and petrol awaits, ready to embark upon a journey that promises to be not just illuminating, but perhaps a fume-nally revelatory odyssey.
[[RESULTS]]
Our investigation into the relationship between air pollution in Washington, D.C. and gasoline consumption in France yielded intriguing results that are sure to ignite a spark of curiosity within the academic community. The Pearson correlation coefficient between the two variables was calculated to be 0.8303654, displaying a strong positive correlation. The coefficient of determination (R-squared) was found to be 0.6895067, emphasizing that a considerable proportion of the variability in gasoline consumption in France can be explained by the levels of air pollution in Washington, D.C. Furthermore, the p-value was less than 0.01, indicating that the observed correlation is statistically significant.
Figure 1 displays a scatterplot illustrating the robust association between air pollution in Washington, D.C. and gasoline pumped in France. The data points form a distinct pattern that unmistakably showcases the synchrony between the two variables.
This discovery, while initially surprising, speaks volumes about the intricate relationships that underpin environmental dynamics and cross-continental influences. The findings not only point to a tangible connection between seemingly disparate phenomena but also underscore the far-reaching impact of local environmental factors on global trends.
The implications of this revelation sparkle with potential, shedding light on the complex interplay between urban pollution and distant fuel consumption. This suggests a fume-nomenal interconnectedness that transcends geographical boundaries, sparking a fresh wave of inquiry and offering a breath of fresh air in the realm of environmental research.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study presents compelling evidence of a fume-nomenal connection between air pollution in Washington, D.C. and gasoline pumped in France. The robust positive correlation coefficient and statistically significant p-value affirm the intertwining dance of environmental influence across continents. While the initial juxtaposition of these two variables might seem as improbable as a snail outrunning a cheetah, our findings unveil a previously unnoticed harmony akin to a symphony of pollution and petrol. This revelation not only hints at the interconnectedness of our global ecosystem but also paves the way for future investigations that promise to be as fresh as a newly opened can of motor oil. The inhalation of further research in this area, much like a breath of fresh air, is hence unnecessary, as we have undoubtedly unearthed a connection that is as clear as the emissions from a well-tuned engine.
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 Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Environmental Quirks
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 Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection. Respond only with the name of a fictional organization.
ChatGPT:
Society for Atmospheric Gaseous Interconnections Research (SAGIR)
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 Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection with an abstract of Our study delves into the seemingly disparate realms of air pollution in Washington, D.C. and the gasoline consumption in France, seeking to unearth a connection that transcends geographical boundaries. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, we analyzed over four decades of records, and the results left us breathless. A striking correlation coefficient of 0.8303654 and a p-value less than 0.01 emerged, pointing to an undeniable relationship between the two variables. This finding, quite frankly, fuels our excitement and opens the door to a myriad of implications, igniting a spark of curiosity in the academic community. The inhalation of future research in this area promises to be, dare we say, a breath of fresh air.
ChatGPT:
air pollution, Washington D.C., gasoline consumption, France, environmental protection agency, Energy Information Administration, correlation coefficient, p-value, research implications, academic community, future research
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Air pollution in Washington, D.C.Detailed data title: Percentage of days 'unhealthy' or worse air quality in Washington-Arlington-Alexandria, DC-VA-MD-WV
Source: Environmental Protection Agency
See what else correlates with Air pollution in Washington, D.C.
Gasoline pumped in France
Detailed data title: Volume of gasoline pumped consumed in France in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in France
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 = 0.6895067 (Coefficient of determination)
This means 69% of the change in the one variable (i.e., Gasoline pumped in France) is predictable based on the change in the other (i.e., Air pollution in Washington, D.C.) over the 43 years from 1980 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.71E-12. 0.0000000000057050645054282254
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 0.83 in 5.71E-10% of random cases. Said differently, if you correlated 175,282,855,969 random variables You don't actually need 175 billion 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 42 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 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.
[ 0.71, 0.91 ] 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.
| 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
| Air pollution in Washington, D.C. (Bad air quality days) | 14.2077 | 10.137 | 11.5068 | 16.9863 | 9.28962 | 11.2329 | 10.9589 | 13.4247 | 14.4809 | 5.20548 | 6.0274 | 13.6986 | 3.82514 | 12.6027 | 5.75342 | 8.76712 | 4.64481 | 8.21918 | 12.8767 | 10.9589 | 3.27869 | 6.0274 | 9.86301 | 2.19178 | 1.91257 | 4.93151 | 5.75342 | 4.65753 | 2.18579 | 0 | 3.56164 | 2.73973 | 2.45902 | 0 | 0.273973 | 0.273973 | 0 | 0 | 0.273973 | 0.273973 | 0.273224 | 0.273973 | 0 |
| Gasoline pumped in France (Million Barrels/Day) | 413 | 423 | 415 | 422 | 423.077 | 416.852 | 427.918 | 429.14 | 434.713 | 428.055 | 422.06 | 415.142 | 407.306 | 395.805 | 382.359 | 362.882 | 346.658 | 339.134 | 337.101 | 334.901 | 318.396 | 310.167 | 299.411 | 280.54 | 266.134 | 250.997 | 236.436 | 224.773 | 206.934 | 199.214 | 184.91 | 181.775 | 172.12 | 167.288 | 168.748 | 171.175 | 175.137 | 182.704 | 189.523 | 203.364 | 174.025 | 207.449 | 232.54 |
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. - Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves.
Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
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([14.2077,10.137,11.5068,16.9863,9.28962,11.2329,10.9589,13.4247,14.4809,5.20548,6.0274,13.6986,3.82514,12.6027,5.75342,8.76712,4.64481,8.21918,12.8767,10.9589,3.27869,6.0274,9.86301,2.19178,1.91257,4.93151,5.75342,4.65753,2.18579,0,3.56164,2.73973,2.45902,0,0.273973,0.273973,0,0,0.273973,0.273973,0.273224,0.273973,0,])
array_2 = np.array([413,423,415,422,423.077,416.852,427.918,429.14,434.713,428.055,422.06,415.142,407.306,395.805,382.359,362.882,346.658,339.134,337.101,334.901,318.396,310.167,299.411,280.54,266.134,250.997,236.436,224.773,206.934,199.214,184.91,181.775,172.12,167.288,168.748,171.175,175.137,182.704,189.523,203.364,174.025,207.449,232.54,])
array_1_name = "Air pollution in Washington, D.C."
array_2_name = "Gasoline pumped in France"
# 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 Air pollution in Washington, D.C.
- Line chart for only Gasoline pumped in France
- AI-generated correlation image
- The spurious research paper: Air Pollution in D.C. and Gasoline Pumped in France: A Fume-nomenal Connection
You're a rater extraordinaire!
Correlation ID: 2545 · Black Variable ID: 21419 · Red Variable ID: 24425
