Spurious correlation #5,797 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Richmond, Virginia and the second variable is Jet fuel used in Saint Vincent/Grenadines. The chart goes from 1998 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Richmond, Virginia and the second variable is Jet fuel used in Saint Vincent/Grenadines. The chart goes from 1998 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air pollution decreased in Richmond, Virginia, it created a shortage of smog particles for the jet fuel in Saint Vincent/Grenadines to interact with. This led to a decrease in the consumption of jet fuel as the particles were no longer available to power the jets, ultimately clearing the skies in the Caribbean. It seems like even jet fuel needs a little smog love to keep burning!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of the city skyline of Richmond, Virginia with clear skies and diminished air pollution, juxtaposed with a view of the skies above Saint Vincent/Grenadines slowly clearing of smog due to reduced air pollution from Richmond. The focus here is on the contrast between the two cities as the environmental impact of decreased pollution becomes visible in the skies, highlighting the interconnectedness of pollution across regions. The images should capture the stark difference in the atmospheres of the two locations, emphasizing the positive change in the Caribbean as a result of reduced pollution from the city in Virginia, employing a visual similar to an architectural blueprint or a simple digital artwork. 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 Richmond, Virginia and Jet fuel used in Saint Vincent/Grenadines. 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 Brutalism Voxel art Steampunk Macabre
ChatGPT: Brutalism

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 Richmond, Virginia and Jet fuel used in Saint Vincent/Grenadines, in the following situation: As air pollution decreased in Richmond, Virginia, it created a shortage of smog particles for the jet fuel in Saint Vincent/Grenadines to interact with. This led to a decrease in the consumption of jet fuel as the particles were no longer available to power the jets, ultimately clearing the skies in the Caribbean. It seems like even jet fuel needs a little smog love to keep burning!. Keep the description simple.
ChatGPT: In Richmond, Virginia, the sky clears as fewer cars emit exhaust fumes, and factories release less smoke into the air. Meanwhile, in Saint Vincent/Grenadines, the jets' engines sputter as the air pollution from Richmond decreases, causing a shortage of smog particles in the atmosphere. The once smog-blanketed skies in the Caribbean begin to clear as the jets consume less fuel, their engines struggling without their usual smoggy companions.

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: [ Brutalism ] and depicting this scene: In Richmond, Virginia, the sky clears as fewer cars emit exhaust fumes, and factories release less smoke into the air. Meanwhile, in Saint Vincent/Grenadines, the jets' engines sputter as the air pollution from Richmond decreases, causing a shortage of smog particles in the atmosphere. The once smog-blanketed skies in the Caribbean begin to clear as the jets consume less fuel, their engines struggling without their usual smoggy companions. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of the city skyline of Richmond, Virginia with clear skies and diminished air pollution, juxtaposed with a view of the skies above Saint Vincent/Grenadines slowly clearing of smog due to reduced air pollution from Richmond. The focus here is on the contrast between the two cities as the environmental impact of decreased pollution becomes visible in the skies, highlighting the interconnectedness of pollution across regions. The images should capture the stark difference in the atmospheres of the two locations, emphasizing the positive change in the Caribbean as a result of reduced pollution from the city in Virginia, employing a visual similar to an architectural blueprint or a simple digital artwork.

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

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

AI academic paper

(Because p < 0.01)

Air Pollution in Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle

The Journal of Environmental Verse

Jan 2024

Reminder: This paper is AI-generated. Not real!

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Richmond, Virginia and Jet fuel used in Saint Vincent/Grenadines. 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Air Pollution in Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle

[[ABSTRACT]]
The correlation between air pollution in Richmond, Virginia, and jet fuel usage in Saint Vincent/Grenadines has sparked a complex puzzle. Curiosity soared like a jet plane, as researchers delved into the environmental implications of this seemingly far-fetched connection. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, our study soared to new heights, uncovering a correlation coefficient of 0.8989080 with a p-value less than 0.01 for the years 1998 to 2021.

Our findings took flight, sparking both intrigue and amusement. As we navigated through the smog of data, it became evident that the link between air pollution in Richmond and jet fuel combustion in Saint Vincent/Grenadines was more than just a flight of fancy. This connection, like a turbulent crosswind, tugged on the threads of environmental understanding, leaving a trail of questions and quips in its wake.

While our results provided insightful clarity, our journey through this research was not without its share of unexpected turbulence. As we unpacked the data, we found that this intercontinental environmental entanglement was no mere flight of the imagination. Rather, it pointed to a web of interconnected global phenomena, of which we are just beginning to scratch the surface.

In conclusion, our study offers a newly illuminated runway for further exploration, beckoning future researchers to take off on their own investigative voyages. For now, though, we bid adieu to this curious correlation, which has proven to be a cloud in the sky drawing our attention to the intricate dance of environmental factors that affect us all.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the annals of scientific inquiry, there are moments when seemingly unrelated phenomena converge in a whimsical waltz, inviting researchers to join in the dance of discovery. Such is the case with the enigmatic relationship between air pollution in the quaint city of Richmond, Virginia, and the jet-fueled adventures taking place in the pristine skies of Saint Vincent and the Grenadines. This harmonious union of terrestrial troubles and celestial travels has left both scientists and jesters scratching their heads in bemusement.
As we lift the veil on this riddle and unfold the tale of our investigation, it becomes clear that our journey was anything but ordinary. Picture this: a band of intrepid researchers armed with statistical prowess, navigating through the murky mists of environmental data, charting a course through the labyrinth of air pollution levels and jet fuel combustion rates. With each twist and turn, we encountered not just numbers, but a story waiting to be unraveled, like a tangled skein of statistical spaghetti.
In the grand tradition of scientific inquiry, our curiosity was piqued by a correlation coefficient that practically sung a siren song, beckoning us to venture further. Lo and behold, our analysis revealed a coefficient of 0.8989080, accompanied by a p-value less than 0.01, spanning the years 1998 to 2021. These findings, like a celestial supernova, burst forth into the scientific arena, dazzling us with their brilliance and prompting a collective "Aha!" amidst the research team.
Yet, as we soared on the wings of statistical significance, we couldn't help but encounter a few pockets of turbulence along the way. The linkage between air pollution in Richmond and jet fuel combustion in Saint Vincent and the Grenadines was no mere flight of fancy. Instead, it beckoned us to ponder the intricate interplay of global forces, as if the Earth itself were spinning an enthralling yarn for our scientific amusement.
In the end, our study serves not only to shed light on this curious correlation but also to invite others to take off on their own scholarly escapades, weaving their own scientific narratives into the fabric of environmental understanding. As we bid adieu to this unlikely pair of environmental bedfellows, one thing is clear: the skies and statistics are full of surprises, and the dance of discovery never fails to delight and confound in equal measure.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The connection between air pollution in Richmond, Virginia, and jet fuel combustion in Saint Vincent/Grenadines has commanded the attention of researchers, akin to the fusion of two unlikely dance partners at a masquerade ball. This seemingly whimsical pairing has prompted us to waltz through the annals of existing literature, starting with the sobering analyses of Smith and Doe, and culminating in more unconventional insights gleaned from the world of fiction and social media.

In "The Impact of Air Pollution on Urban Settings" by Smith et al., the authors find a comprehensive examination of various sources of air pollutants, emphasizing the influence of industrial activities, vehicular emissions, and residential combustion. While the streets of Richmond may be as familiar to the researchers as their morning coffee, the scholarly foray into understanding the jet fuel dynamics of Saint Vincent and the Grenadines beckons us to shift our scope to new horizons.

Moreover, Doe's "Aviation Fuel and Environmental Impacts" presents a meticulous dissection of the environmental repercussions of aviation fuel usage, shedding light on the intricate relationship between fuel composition and emissions. Yet, as we venture beyond the typical confines of airport terminals, we realize that the reach of jet fuel's impact extends far beyond the distant hum of aircraft engines, permeating the global tapestry of environmental phenomena in ways that transcend traditional academic boundaries.

However, as we pull back the curtain on our literary stage, we must also acknowledge the unassuming players in this eclectic symphony of knowledge. Sifting through the plethora of non-fiction and academic treatises, our quest for understanding has led us to encounter unexpected allies, such as "Cloud Atlas" by David Mitchell and "The Air He Breathes" by Brittainy C. Cherry – titles that, despite their literary nature, seem to whisper subtle echoes of our research topic, floating through the invisible currents of interconnected ideas.

To our further surprise, the voices of social media have also chimed in with their musings on the enigmatic bond between air pollution in Richmond and jet fuel usage in Saint Vincent and the Grenadines. A tweet by @EnviroGuru proclaims, "If you want to connect the dots between air quality and jet fuel, it's not just a matter of carbon emissions – there's a whole atmospheric ballet at play that deserves center stage!" Such astute observations, though delivered in 280 characters or less, serve as a testament to the widespread intrigue and speculation surrounding this unusual confluence of environmental factors.

As we navigate this literary landscape, it becomes evident that our quest for understanding spans not only the scholarly corridors of empirical research but also the uncharted realms of imagination and modern discourse. The dichotomy of serious inquiry and whimsical curiosity intertwines like a braid, inviting us to partake in the exhilarating dance of discovery, where every step reveals a new twist in the intricate plot of scientific exploration.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Richmond, Virginia and Jet fuel used in Saint Vincent/Grenadines. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration . You used data from 1998 to 2021

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 Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle

[[ABSTRACT]]
The correlation between air pollution in Richmond, Virginia, and jet fuel usage in Saint Vincent/Grenadines has sparked a complex puzzle. Curiosity soared like a jet plane, as researchers delved into the environmental implications of this seemingly far-fetched connection. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, our study soared to new heights, uncovering a correlation coefficient of 0.8989080 with a p-value less than 0.01 for the years 1998 to 2021.

Our findings took flight, sparking both intrigue and amusement. As we navigated through the smog of data, it became evident that the link between air pollution in Richmond and jet fuel combustion in Saint Vincent/Grenadines was more than just a flight of fancy. This connection, like a turbulent crosswind, tugged on the threads of environmental understanding, leaving a trail of questions and quips in its wake.

While our results provided insightful clarity, our journey through this research was not without its share of unexpected turbulence. As we unpacked the data, we found that this intercontinental environmental entanglement was no mere flight of the imagination. Rather, it pointed to a web of interconnected global phenomena, of which we are just beginning to scratch the surface.

In conclusion, our study offers a newly illuminated runway for further exploration, beckoning future researchers to take off on their own investigative voyages. For now, though, we bid adieu to this curious correlation, which has proven to be a cloud in the sky drawing our attention to the intricate dance of environmental factors that affect us all.

[[INTRODUCTION]]
In the annals of scientific inquiry, there are moments when seemingly unrelated phenomena converge in a whimsical waltz, inviting researchers to join in the dance of discovery. Such is the case with the enigmatic relationship between air pollution in the quaint city of Richmond, Virginia, and the jet-fueled adventures taking place in the pristine skies of Saint Vincent and the Grenadines. This harmonious union of terrestrial troubles and celestial travels has left both scientists and jesters scratching their heads in bemusement.
As we lift the veil on this riddle and unfold the tale of our investigation, it becomes clear that our journey was anything but ordinary. Picture this: a band of intrepid researchers armed with statistical prowess, navigating through the murky mists of environmental data, charting a course through the labyrinth of air pollution levels and jet fuel combustion rates. With each twist and turn, we encountered not just numbers, but a story waiting to be unraveled, like a tangled skein of statistical spaghetti.
In the grand tradition of scientific inquiry, our curiosity was piqued by a correlation coefficient that practically sung a siren song, beckoning us to venture further. Lo and behold, our analysis revealed a coefficient of 0.8989080, accompanied by a p-value less than 0.01, spanning the years 1998 to 2021. These findings, like a celestial supernova, burst forth into the scientific arena, dazzling us with their brilliance and prompting a collective "Aha!" amidst the research team.
Yet, as we soared on the wings of statistical significance, we couldn't help but encounter a few pockets of turbulence along the way. The linkage between air pollution in Richmond and jet fuel combustion in Saint Vincent and the Grenadines was no mere flight of fancy. Instead, it beckoned us to ponder the intricate interplay of global forces, as if the Earth itself were spinning an enthralling yarn for our scientific amusement.
In the end, our study serves not only to shed light on this curious correlation but also to invite others to take off on their own scholarly escapades, weaving their own scientific narratives into the fabric of environmental understanding. As we bid adieu to this unlikely pair of environmental bedfellows, one thing is clear: the skies and statistics are full of surprises, and the dance of discovery never fails to delight and confound in equal measure.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic bond between air pollution in Richmond, Virginia, and the sizzling combustion of jet fuel in the idyllic skies of Saint Vincent and the Grenadines, we embarked on a high-flying journey through the nebulous realms of research methodology. Our restless pursuit of evidence led us to traverse the vast expanse of the internet, gallivanting through the digital wilderness in search of pertinent data. Although we initially sought wisdom from the Oracle of Google, we ultimately anchored our study in the grounded repositories of the Environmental Protection Agency and the Energy Information Administration. These stalwart guardians of environmental and energy data paved the way for our odyssey, offering a treasure trove of empirical insights spanning the years 1998 to 2021.

Drawing our metaphorical swords of statistical rigor, we harnessed the power of correlation analysis to peer through the clouds of uncertainty and discern the patterns within the data. With furrowed brows and a spirit of scientific audacity, the research team wrangled with spreadsheets and statistical software, unleashing a battalion of formulas and algorithms to extract the elusive truth from the quagmire of numbers. Our statistical arsenal included the venerable Pearson correlation coefficient and its trusty sidekick, the p-value, both of which served as compasses guiding our journey through the labyrinth of data.

In our valiant quest for knowledge, we harnessed the arcane powers of time series analysis to capture the temporal nuances of air pollution in Richmond and jet fuel consumption in Saint Vincent and the Grenadines. Like alchemists seeking the philosopher's stone, we diligently examined the waxing and waning rhythms of these variables over the span of decades, teasing out the hidden melodies of their correlation.

As we zoomed through this sonic boom of data analysis, we navigated the treacherous terrain of multivariate regression models, endeavoring to disentangle the web of interconnected variables that shape the environmental tapestry. Our intrepid foray into this statistical jungle yielded a clarion call, echoing the profound interconnectedness between air pollution in Richmond and the combustion of jet fuel in Saint Vincent and the Grenadines—a synchrony that captured our imaginations and confounded our expectations.

Upon emerging from the statistical crucible, we found ourselves amidst a trove of numerical gems, each imbued with the luster of scientific significance. These shimmering findings not only unveiled the tantalizing correlation coefficient of 0.8989080, accompanied by a p-value less than 0.01, but also revealed the rich narrative woven by the intertwining threads of air pollution and jet fuel combustion.

While our journey through the empirical skies was marked by moments of turbulence and uncertainty, we stand resolute in the belief that our unconventional methodology has furnished a robust foundation for unraveling this grand enigma. With our empirical wings unfurled, we now cast our gazes towards the horizon of scholarly inquiry, beckoning others to join us in the delightful dance of environmental understanding. In the spirit of scientific adventure, we bid adieu to the methodology that has brought us to this moment, knowing full well that the jest of statistical insight is always in the details.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Richmond, Virginia and Jet fuel used in Saint Vincent/Grenadines. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Air Pollution in Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle

[[ABSTRACT]]
The correlation between air pollution in Richmond, Virginia, and jet fuel usage in Saint Vincent/Grenadines has sparked a complex puzzle. Curiosity soared like a jet plane, as researchers delved into the environmental implications of this seemingly far-fetched connection. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, our study soared to new heights, uncovering a correlation coefficient of 0.8989080 with a p-value less than 0.01 for the years 1998 to 2021.

Our findings took flight, sparking both intrigue and amusement. As we navigated through the smog of data, it became evident that the link between air pollution in Richmond and jet fuel combustion in Saint Vincent/Grenadines was more than just a flight of fancy. This connection, like a turbulent crosswind, tugged on the threads of environmental understanding, leaving a trail of questions and quips in its wake.

While our results provided insightful clarity, our journey through this research was not without its share of unexpected turbulence. As we unpacked the data, we found that this intercontinental environmental entanglement was no mere flight of the imagination. Rather, it pointed to a web of interconnected global phenomena, of which we are just beginning to scratch the surface.

In conclusion, our study offers a newly illuminated runway for further exploration, beckoning future researchers to take off on their own investigative voyages. For now, though, we bid adieu to this curious correlation, which has proven to be a cloud in the sky drawing our attention to the intricate dance of environmental factors that affect us all.

[[LITERATURE REVIEW]]
The connection between air pollution in Richmond, Virginia, and jet fuel combustion in Saint Vincent/Grenadines has commanded the attention of researchers, akin to the fusion of two unlikely dance partners at a masquerade ball. This seemingly whimsical pairing has prompted us to waltz through the annals of existing literature, starting with the sobering analyses of Smith and Doe, and culminating in more unconventional insights gleaned from the world of fiction and social media.
In "The Impact of Air Pollution on Urban Settings" by Smith et al., the authors find a comprehensive examination of various sources of air pollutants, emphasizing the influence of industrial activities, vehicular emissions, and residential combustion. While the streets of Richmond may be as familiar to the researchers as their morning coffee, the scholarly foray into understanding the jet fuel dynamics of Saint Vincent and the Grenadines beckons us to shift our scope to new horizons.
Moreover, Doe's "Aviation Fuel and Environmental Impacts" presents a meticulous dissection of the environmental repercussions of aviation fuel usage, shedding light on the intricate relationship between fuel composition and emissions. Yet, as we venture beyond the typical confines of airport terminals, we realize that the reach of jet fuel's impact extends far beyond the distant hum of aircraft engines, permeating the global tapestry of environmental phenomena in ways that transcend traditional academic boundaries.
However, as we pull back the curtain on our literary stage, we must also acknowledge the unassuming players in this eclectic symphony of knowledge. Sifting through the plethora of non-fiction and academic treatises, our quest for understanding has led us to encounter unexpected allies, such as "Cloud Atlas" by David Mitchell and "The Air He Breathes" by Brittainy C. Cherry – titles that, despite their literary nature, seem to whisper subtle echoes of our research topic, floating through the invisible currents of interconnected ideas.
To our further surprise, the voices of social media have also chimed in with their musings on the enigmatic bond between air pollution in Richmond and jet fuel usage in Saint Vincent and the Grenadines. A tweet by @EnviroGuru proclaims, "If you want to connect the dots between air quality and jet fuel, it's not just a matter of carbon emissions – there's a whole atmospheric ballet at play that deserves center stage!" Such astute observations, though delivered in 280 characters or less, serve as a testament to the widespread intrigue and speculation surrounding this unusual confluence of environmental factors.
As we navigate this literary landscape, it becomes evident that our quest for understanding spans not only the scholarly corridors of empirical research but also the uncharted realms of imagination and modern discourse. The dichotomy of serious inquiry and whimsical curiosity intertwines like a braid, inviting us to partake in the exhilarating dance of discovery, where every step reveals a new twist in the intricate plot of scientific exploration.

[[RESULTS]]
The analysis of the correlation between air pollution in Richmond, Virginia, and jet fuel combustion in Saint Vincent and the Grenadines took flight, revealing a soaring correlation coefficient of 0.8989080. This coefficient, akin to a pilot cruising smoothly through clear skies, indicated a strong positive relationship between these seemingly disparate variables. The r-squared value of 0.8080356 further underscored the robustness of this relationship, demonstrating that a substantial proportion of the variation in air pollution levels in Richmond could be explained by jet fuel combustion in Saint Vincent and the Grenadines.
The p-value of less than 0.01 served as a beacon of statistical significance, illuminating the path to a deeper understanding of this unexpected environmental connection. Like a rare bird sighting in a sprawling metropolis, this finding left our team in awe, prompting moments of both scientific elucidation and whimsical wonder.
Additionally, the scatterplot (Fig. 1) visually encapsulated the striking correlation between air pollution in Richmond and jet fuel usage in Saint Vincent and the Grenadines. The points on the plot formed a pattern so clear, it practically shouted, "Look at us, we're related!" Indeed, it was as if the data itself wanted to ensure that our findings didn't remain up in the air.
In essence, our results suggest that the relationship between air pollution in Richmond and jet fuel combustion in Saint Vincent and the Grenadines is more than just a passing cloud. It invites further investigation, like a mystery novel with an unresolved cliffhanger, leaving scientists and environmental enthusiasts eager to unravel the intricacies of this unexpected correlation.
Overall, our findings provide an illuminating window into the interconnected web of environmental factors that transcend geographical boundaries, as if the Earth itself were whispering a complex riddle, waiting to be deciphered by the scientific community. The interplay of statistics and environmental phenomena continues to surprise and delight, reminding us that the pursuit of knowledge is not just about reaching a destination, but also about enjoying the journey.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The correlation between air pollution in Richmond, Virginia, and jet fuel combustion in Saint Vincent and the Grenadines has certainly made for a head-spinning flight through the skies of scientific exploration. Our results, soaring high like a flock of migratory birds, have firmly supported and expanded upon the prior research that laid the groundwork for this unlikely pairing.

As we dust off the shelf of scholarly literature, we recall the earnest analysis of Smith and Doe, who delved deep into the earthly origins of air pollution and the skyward implications of jet fuel combustion. Their work, akin to a sturdy set of wings, provided us with a launching pad for our study, propelling us into the atmospheric embrace of intercontinental connections. With our findings revealing a correlation coefficient nearing unity, we can say with confidence that the spirit of their scholarly avian will has surely nested itself in our own research.

Moreover, the unexpected bedfellows of literature – the likes of "Cloud Atlas" and "The Air He Breathes" – have offered not only a whimsical touch to the discussion but also intangible threads of inspiration that have woven their way into our investigation. These literary musings, appearing like stray feathers in a scientific gust, have nudged us to view our findings not only through the lens of empirical analysis but also through the kaleidoscope of imaginative possibility.

Like seasoned birdwatchers, we have observed the statistical landscape with an attentive eye, spotting the captivating scatterplot as if it were a rare specimen of avian marvel. This visualization, akin to a majestic display of synchronized flight, vividly captured the undeniable association between air pollution in Richmond and jet fuel usage in Saint Vincent and the Grenadines. The plot spoke volumes, as if the data points were chirping in unison, "We're not just random noise – there's a pattern to our flight path!"

In essence, our investigation into the interwoven tale of air pollution and jet fuel combustion has not only confirmed the presence of a robust correlation but has also opened the door to a veritable aviary of future research possibilities. This unexpected alliance of environmental variables, much like a pair of unacquainted birds finding themselves on the same branch, beckons further exploration and contemplation. It is a reminder that the world of scientific inquiry is populated not only by concrete facts and figures but also by the ethereal melodies of curiosity and imagination.

As we nestle into the burgeoning landscape of interdisciplinary research, we find ourselves gazing expectantly towards the horizon, knowing that this initial foray into the realm of cross-continental environmental correlations is just the beginning of a flight that promises to be as unpredictable as it is exhilarating. With feathers ruffled in excitement, we eagerly await the flock of scholars and enthusiasts who will flock to this curious puzzle, ready to traverse the skies of investigation with us in pursuit of further enlightenment.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Richmond, Virginia and Jet fuel used in Saint Vincent/Grenadines. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Air Pollution in Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle

[[ABSTRACT]]
The correlation between air pollution in Richmond, Virginia, and jet fuel usage in Saint Vincent/Grenadines has sparked a complex puzzle. Curiosity soared like a jet plane, as researchers delved into the environmental implications of this seemingly far-fetched connection. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, our study soared to new heights, uncovering a correlation coefficient of 0.8989080 with a p-value less than 0.01 for the years 1998 to 2021.

Our findings took flight, sparking both intrigue and amusement. As we navigated through the smog of data, it became evident that the link between air pollution in Richmond and jet fuel combustion in Saint Vincent/Grenadines was more than just a flight of fancy. This connection, like a turbulent crosswind, tugged on the threads of environmental understanding, leaving a trail of questions and quips in its wake.

While our results provided insightful clarity, our journey through this research was not without its share of unexpected turbulence. As we unpacked the data, we found that this intercontinental environmental entanglement was no mere flight of the imagination. Rather, it pointed to a web of interconnected global phenomena, of which we are just beginning to scratch the surface.

In conclusion, our study offers a newly illuminated runway for further exploration, beckoning future researchers to take off on their own investigative voyages. For now, though, we bid adieu to this curious correlation, which has proven to be a cloud in the sky drawing our attention to the intricate dance of environmental factors that affect us all.

[[INTRDUCTION]]
In the annals of scientific inquiry, there are moments when seemingly unrelated phenomena converge in a whimsical waltz, inviting researchers to join in the dance of discovery. Such is the case with the enigmatic relationship between air pollution in the quaint city of Richmond, Virginia, and the jet-fueled adventures taking place in the pristine skies of Saint Vincent and the Grenadines. This harmonious union of terrestrial troubles and celestial travels has left both scientists and jesters scratching their heads in bemusement.
As we lift the veil on this riddle and unfold the tale of our investigation, it becomes clear that our journey was anything but ordinary. Picture this: a band of intrepid researchers armed with statistical prowess, navigating through the murky mists of environmental data, charting a course through the labyrinth of air pollution levels and jet fuel combustion rates. With each twist and turn, we encountered not just numbers, but a story waiting to be unraveled, like a tangled skein of statistical spaghetti.
In the grand tradition of scientific inquiry, our curiosity was piqued by a correlation coefficient that practically sung a siren song, beckoning us to venture further. Lo and behold, our analysis revealed a coefficient of 0.8989080, accompanied by a p-value less than 0.01, spanning the years 1998 to 2021. These findings, like a celestial supernova, burst forth into the scientific arena, dazzling us with their brilliance and prompting a collective "Aha!" amidst the research team.
Yet, as we soared on the wings of statistical significance, we couldn't help but encounter a few pockets of turbulence along the way. The linkage between air pollution in Richmond and jet fuel combustion in Saint Vincent and the Grenadines was no mere flight of fancy. Instead, it beckoned us to ponder the intricate interplay of global forces, as if the Earth itself were spinning an enthralling yarn for our scientific amusement.
In the end, our study serves not only to shed light on this curious correlation but also to invite others to take off on their own scholarly escapades, weaving their own scientific narratives into the fabric of environmental understanding. As we bid adieu to this unlikely pair of environmental bedfellows, one thing is clear: the skies and statistics are full of surprises, and the dance of discovery never fails to delight and confound in equal measure.

[[RESULTS]]
The analysis of the correlation between air pollution in Richmond, Virginia, and jet fuel combustion in Saint Vincent and the Grenadines took flight, revealing a soaring correlation coefficient of 0.8989080. This coefficient, akin to a pilot cruising smoothly through clear skies, indicated a strong positive relationship between these seemingly disparate variables. The r-squared value of 0.8080356 further underscored the robustness of this relationship, demonstrating that a substantial proportion of the variation in air pollution levels in Richmond could be explained by jet fuel combustion in Saint Vincent and the Grenadines.
The p-value of less than 0.01 served as a beacon of statistical significance, illuminating the path to a deeper understanding of this unexpected environmental connection. Like a rare bird sighting in a sprawling metropolis, this finding left our team in awe, prompting moments of both scientific elucidation and whimsical wonder.
Additionally, the scatterplot (Fig. 1) visually encapsulated the striking correlation between air pollution in Richmond and jet fuel usage in Saint Vincent and the Grenadines. The points on the plot formed a pattern so clear, it practically shouted, "Look at us, we're related!" Indeed, it was as if the data itself wanted to ensure that our findings didn't remain up in the air.
In essence, our results suggest that the relationship between air pollution in Richmond and jet fuel combustion in Saint Vincent and the Grenadines is more than just a passing cloud. It invites further investigation, like a mystery novel with an unresolved cliffhanger, leaving scientists and environmental enthusiasts eager to unravel the intricacies of this unexpected correlation.
Overall, our findings provide an illuminating window into the interconnected web of environmental factors that transcend geographical boundaries, as if the Earth itself were whispering a complex riddle, waiting to be deciphered by the scientific community. The interplay of statistics and environmental phenomena continues to surprise and delight, reminding us that the pursuit of knowledge is not just about reaching a destination, but also about enjoying the journey.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In wrapping up our research investigation into the curiously interconnected realms of air pollution in Richmond, Virginia, and jet fuel combustion in Saint Vincent and the Grenadines, we can’t help but feel like we’ve been on a whimsical journey through a scientific wonderland. It’s been a wild ride, folks, but we’re ready to bring this plane in for a landing (pun most definitely intended).

As our findings took flight, revealing a correlation coefficient that practically made our scientific socks fly off, it became abundantly clear that this unexpected connection was no mere flight of fancy. The data itself seemed to be orchestrating a grand symphony of statistical significance, leaving us in awe and prompting more than a few “oohs” and “aahs” among the research team. It was like witnessing a rare celestial event right here on Earth, with numbers dancing in perfect statistical harmony.

But let’s not forget the unexpected turbulence we encountered along the way. Like a mid-flight bout of turbulence, the complexities of this correlation threw us a few curveballs. Yet, much like a determined pilot navigating through stormy weather, we weathered the statistical storms, emerging with a sense of triumph and a newfound appreciation for the whimsical wonders of the scientific process.

In the end, our study has not only lifted the veil on this charmingly enigmatic correlation but has also set the stage for aspiring researchers to embark on their own scholarly escapades. And while we bid adieu to this captivating correlation, we can confidently say that no more research is needed in this area. The skies of scientific inquiry are full of other riddles waiting to be unraveled, and we can't afford to be stuck at the airport (statistical or otherwise) marveling at this particular correlation forever.

So, to all the future researchers out there, bon voyage! Take to the skies of discovery, chart your own courses through the wilds of statistical significance, and remember: the journey is just as important as the destination. Safe travels, and may your findings be as astonishing and delightfully unexpected as this one.

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 Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Verse

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 Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Environmental Investigations

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 Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle with an abstract of The correlation between air pollution in Richmond, Virginia, and jet fuel usage in Saint Vincent/Grenadines has sparked a complex puzzle. Curiosity soared like a jet plane, as researchers delved into the environmental implications of this seemingly far-fetched connection. Leveraging data from the Environmental Protection Agency and the Energy Information Administration, our study soared to new heights, uncovering a correlation coefficient of 0.8989080 with a p-value less than 0.01 for the years 1998 to 2021.
Our findings took flight, sparking both intrigue and amusement. As we navigated through the smog of data, it became evident that the link between air pollution in Richmond and jet fuel combustion in Saint Vincent/Grenadines was more than just a flight of fancy. This connection, like a turbulent crosswind, tugged on the threads of environmental understanding, leaving a trail of questions and quips in its wake.
While our results provided insightful clarity, our journey through this research was not without its share of unexpected turbulence. As we unpacked the data, we found that this intercontinental environmental entanglement was no mere flight of the imagination. Rather, it pointed to a web of interconnected global phenomena, of which we are just beginning to scratch the surface.
In conclusion, our study offers a newly illuminated runway for further exploration, beckoning future researchers to take off on their own investigative voyages. For now, though, we bid adieu to this curious correlation, which has proven to be a cloud in the sky drawing our attention to the intricate dance of environmental factors that affect us all.

ChatGPT:

air pollution, Richmond Virginia, jet fuel combustion, Saint Vincent, Grenadines, environmental implications, correlation coefficient, EPA data, EIA data, global environmental phenomena, research, intercontinental entanglement, global factors, environmental factors

*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 Richmond, Virginia
Detailed data title: Percentage of days 'unhealthy' or worse air quality in Richmond, VA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Richmond, Virginia

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

Correlation r = 0.8989080 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.8080356 (Coefficient of determination)
This means 80.8% of the change in the one variable (i.e., Jet fuel used in Saint Vincent/Grenadines) is predictable based on the change in the other (i.e., Air pollution in Richmond, Virginia) over the 24 years from 1998 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.4E-9.^Show 0.0000000024171387916949154000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.9 in 2.4E-7% of random cases. Said differently, if you correlated 413,712,280 random variables^Note You don't actually need 413 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 23 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 23 because we have two variables measured over a period of 24 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.

[ 0.78, 0.96 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Air pollution in Richmond, Virginia (Bad air quality days)	7.12329	7.94521	0.819672	4.10959	6.57534	1.36986	0.546448	2.19178	2.46575	1.91781	1.63934	0	1.09589	0.547945	1.0929	0	0	0	0	0.273973	0	0	0	0
Jet fuel used in Saint Vincent/Grenadines (Million Barrels/Day)	0.02172	0.021726	0.00628333	0.00847315	0.00912493	0.00782137	0.00498333	0.00651781	0.00651781	0.00869041	0.0108333	0.00355655	0.00261125	0.0021902	0.00191642	0.00108261	0.0010863	0.0010863	0.001	0.00130356	0.0010863	0.00130356	0.00109478	0.0011652

Why this works

Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([7.12329,7.94521,0.819672,4.10959,6.57534,1.36986,0.546448,2.19178,2.46575,1.91781,1.63934,0,1.09589,0.547945,1.0929,0,0,0,0,0.273973,0,0,0,0,])
array_2 = np.array([0.02172,0.021726,0.00628333,0.00847315,0.00912493,0.00782137,0.00498333,0.00651781,0.00651781,0.00869041,0.0108333,0.00355655,0.00261125,0.0021902,0.00191642,0.00108261,0.0010863,0.0010863,0.001,0.00130356,0.0010863,0.00130356,0.00109478,0.0011652,])
array_1_name = "Air pollution in Richmond, Virginia"
array_2_name = "Jet fuel used in Saint Vincent/Grenadines"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air pollution in Richmond, Virginia
Line chart for only Jet fuel used in Saint Vincent/Grenadines
AI-generated correlation image
The spurious research paper: Air Pollution in Richmond, Virginia and Jet Fuel Combustion in Saint Vincent - A Rhyming Riddle

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Correlation ID: 5797 · Black Variable ID: 21139 · Red Variable ID: 24865


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