Spurious correlation #2,368 · 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 Oklahoma City and the second variable is Fossil fuel use in North Macedonia. The chart goes from 1992 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 Oklahoma City and the second variable is Fossil fuel use in North Macedonia. The chart goes from 1992 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air pollution in Oklahoma City increased, it created a 'wind' of change in the fossil fuel industry. The polluted air drifted all the way to North Macedonia, where it 'fueled' a greater demand for their fossil fuels. You could say it was a case of 'Okla-homa gonna need more fuel, son!'

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image using DALL·E-3 that combines the contrasting scenes of Oklahoma City's skyline against North Macedonia's industrial areas. The image should depict a serene Oklahoma City skyline, with clear blue skies and people enjoying outdoor activities like hiking and biking. Concurrently, it should showcase North Macedonia with an increase in cars on the road and smoke rising from industrial areas, symbolizing the rise in fossil fuel use. The visual should emphasize the transfer of environmental impact from one location to another, due to cleaner air in one place sparking increased fossil fuel use in another. The use of charcoal style should create a visually striking contrast between the two scenes. 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 Oklahoma City and Fossil fuel use in North Macedonia. 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: Charcoal Vaporwave Cyberpunk Surrealism Realistic
ChatGPT: Charcoal

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 Oklahoma City and Fossil fuel use in North Macedonia, in the following situation: As air quality improved in Oklahoma City, citizens started feeling "gas"-tronomically inclined to explore the great outdoors. This led to a surge in demand for fossil fuels in North Macedonia, as people were "fueled" to travel and experience new "rock"-sotic locations. It's like a twisted game of environmental "telephone" – one city's cleaner air becomes another's fuel-burning desire.. Keep the description simple.
ChatGPT: In a visual scene, we see the skyline of Oklahoma City with clear blue skies and people enjoying outdoor activities like hiking and biking. Meanwhile, in North Macedonia, we see an increase in cars on the road and smoke rising from industrial areas, symbolizing the rise in fossil fuel use. The imagery represents the transfer of environmental impact from one location to another due to cleaner air in one place sparking increased fossil fuel use in another.

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: [ Charcoal ] and depicting this scene: In a visual scene, we see the skyline of Oklahoma City with clear blue skies and people enjoying outdoor activities like hiking and biking. Meanwhile, in North Macedonia, we see an increase in cars on the road and smoke rising from industrial areas, symbolizing the rise in fossil fuel use. The imagery represents the transfer of environmental impact from one location to another due to cleaner air in one place sparking increased fossil fuel use in another. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image using DALL·E-3 that combines the contrasting scenes of Oklahoma City's skyline against North Macedonia's industrial areas. The image should depict a serene Oklahoma City skyline, with clear blue skies and people enjoying outdoor activities like hiking and biking. Concurrently, it should showcase North Macedonia with an increase in cars on the road and smoke rising from industrial areas, symbolizing the rise in fossil fuel use. The visual should emphasize the transfer of environmental impact from one location to another, due to cleaner air in one place sparking increased fossil fuel use in another. The use of charcoal style should create a visually striking contrast between the two scenes.

*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 increases in Air pollution in Oklahoma City positively influenced Fossil fuel use in North Macedonia. Include one good pun.

AI academic paper

(Because p < 0.01)

The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

The International Journal of Ecological Enigmas

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Oklahoma City and Fossil fuel use in North Macedonia. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

[[ABSTRACT]]
This paper delves into the interconnectedness of air pollution in Oklahoma City and the fervent fossil fuel use in North Macedonia with a touch of whimsy and a hint of sass. Drawing upon data from the Environmental Protection Agency and the Energy Information Administration, our research team sought to address this burning question with statistical analyses revealing a remarkably robust correlation coefficient of 0.6852993 and p < 0.01 for the time period spanning 1992 to 2021. Our findings provide compelling evidence for the intriguing relationship between these seemingly incongruous phenomena, giving one pause to reconsider the nature of atmospheric dynamics and global ties that bind.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The Pollution Puzzle, a persistent predicament perplexing policymakers and citizens alike, has long confounded researchers seeking to unravel the intricate web of factors contributing to air quality degradation. In this scholarly endeavor, we embark on a whimsical yet rigorous examination of the connection between the atmospheric woes of Oklahoma City and the fossil fuel frenzy in North Macedonia. Our investigation aims to shed light on this enigmatic relationship, armed with data, statistical analyses, and a touch of intellectual cheekiness.
Air quality concerns in Oklahoma City have been a topic of contentious debate, with citizens often left breathless by the hazy pollution-laden skies. Meanwhile, North Macedonia has been fervently burning fossil fuels, igniting a figurative firestorm of carbon emissions and environmental apprehension. Ah, the juxtaposition of these two seemingly unrelated phenomena—almost as mystifying as a magician pulling a rabbit out of a hat, but with far more serious implications for public health and the global climate.
Our study draws upon data from the stalwart Environmental Protection Agency and the indefatigable Energy Information Administration, embracing the digital dance of bytes and bits to unravel the intricacies of air quality and fossil fuel consumption. Through the discerning lens of statistical analyses, we aim to extract the essence of this connection, revealing a correlation coefficient so robust it could lift weights at the metaphorical statistical gym.
Now, dear reader, brace yourself for a journey into the world of air particles, carbon emissions, and geographical serendipity. As we delve into the depths of this Pollution Puzzle, prepare to be amused, surprised, and perhaps even enlightened by the ties that bind two distant lands in an atmospheric tango of global significance.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The interplay between air pollution in Oklahoma City and fossil fuel use in North Macedonia has been a topic of increasing interest and inquiry among researchers in the fields of environmental science and public health. Smith et al. (2015) conducted a comprehensive analysis of air quality in Oklahoma City, noting the significant presence of particulate matter and volatile organic compounds in the atmosphere. Meanwhile, Doe and Jones (2018) delved into the fervent fossil fuel use in North Macedonia, highlighting the country's heavy reliance on coal and the consequential emissions of sulfur dioxide and nitrogen oxides.

Moving beyond the realm of scholarly articles, several non-fiction books have also contributed to the discourse on air pollution and fossil fuel consumption. In "The Air We Breathe: A Global Analysis of Environmental Health" by Environmental Expert, the authors explore the interconnectedness of air quality across diverse geographical regions, offering insights into the potential impact of international factors on local pollution levels. In "Fueling the Fire: A Comprehensive Study of Fossil Fuel Dependence" by Energy Specialist, the dynamics of fossil fuel use in various countries are examined, providing valuable context for understanding the drivers of environmental degradation.

On a more fictional note, literary works such as "Smoke and Mirrors: Tales of Environmental Intrigue" by Fictional Author and "Coal Chronicles: A Novel of Fossil Fuel Fantasy" by Imaginary Writer present imaginative narratives that perhaps inadvertently tap into the thematic undercurrents of air pollution and fossil fuel use.

The literature review, however, does not solely rely on conventional academic and literary sources. As part of an unconventional approach, the researchers perused a startling array of material, including but not limited to supermarket receipts, vintage postcards, and the musings of a particularly insightful housecat named Whiskers. While the scientific rigor of these sources is decidedly questionable, they undeniably added an element of unexpected whimsy to the review process.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Oklahoma City and Fossil fuel use in North Macedonia. Make lots of jokes, goofy observations, and puns.

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 1992 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]]
The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

[[ABSTRACT]]
This paper delves into the interconnectedness of air pollution in Oklahoma City and the fervent fossil fuel use in North Macedonia with a touch of whimsy and a hint of sass. Drawing upon data from the Environmental Protection Agency and the Energy Information Administration, our research team sought to address this burning question with statistical analyses revealing a remarkably robust correlation coefficient of 0.6852993 and p < 0.01 for the time period spanning 1992 to 2021. Our findings provide compelling evidence for the intriguing relationship between these seemingly incongruous phenomena, giving one pause to reconsider the nature of atmospheric dynamics and global ties that bind.

[[INTRODUCTION]]
The Pollution Puzzle, a persistent predicament perplexing policymakers and citizens alike, has long confounded researchers seeking to unravel the intricate web of factors contributing to air quality degradation. In this scholarly endeavor, we embark on a whimsical yet rigorous examination of the connection between the atmospheric woes of Oklahoma City and the fossil fuel frenzy in North Macedonia. Our investigation aims to shed light on this enigmatic relationship, armed with data, statistical analyses, and a touch of intellectual cheekiness.
Air quality concerns in Oklahoma City have been a topic of contentious debate, with citizens often left breathless by the hazy pollution-laden skies. Meanwhile, North Macedonia has been fervently burning fossil fuels, igniting a figurative firestorm of carbon emissions and environmental apprehension. Ah, the juxtaposition of these two seemingly unrelated phenomena—almost as mystifying as a magician pulling a rabbit out of a hat, but with far more serious implications for public health and the global climate.
Our study draws upon data from the stalwart Environmental Protection Agency and the indefatigable Energy Information Administration, embracing the digital dance of bytes and bits to unravel the intricacies of air quality and fossil fuel consumption. Through the discerning lens of statistical analyses, we aim to extract the essence of this connection, revealing a correlation coefficient so robust it could lift weights at the metaphorical statistical gym.
Now, dear reader, brace yourself for a journey into the world of air particles, carbon emissions, and geographical serendipity. As we delve into the depths of this Pollution Puzzle, prepare to be amused, surprised, and perhaps even enlightened by the ties that bind two distant lands in an atmospheric tango of global significance.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The data used in this study were primarily sourced from the Environmental Protection Agency (EPA) and the Energy Information Administration (EIA), forming a digital symphony of information spanning the years 1992 to 2021. The data retrieval process was akin to a digital treasure hunt, navigating the labyrinth of internet repositories and databases with the precision of a seasoned information sleuth.

To establish the extent of air pollution in Oklahoma City, measurements of key air pollutants such as particulate matter (PM2.5 and PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were extracted from EPA databases. These data were collected from monitoring stations strategically stationed across Oklahoma City, providing a glimpse into the atmospheric commotion reminiscent of a bustling city orchestra.

Concurrently, the levels of fossil fuel use in North Macedonia were illuminated through the EIA's comprehensive datasets on energy production, consumption, and emissions. The combustion of coal, oil, and natural gas was dissected with the precision of a culinary connoisseur, allowing for a nuanced understanding of the fossil fuel fervor permeating the Macedonian landscape.

Statistical analyses were employed to unravel the tangled web of data, with correlation coefficients donning their metaphorical statistical capes to reveal the strength and direction of the relationship between air pollution in Oklahoma City and fossil fuel use in North Macedonia. The statistical analyses were conducted with the gravity of a courtroom drama and the anticipation of a cliffhanger, unveiling a correlation coefficient of 0.6852993 with a p-value of less than 0.01, casting a spotlight on the robust interplay between these seemingly disparate phenomena.

The collaboration of EPA and EIA data conjured a tableau of atmospheric and energy intricacies, enriching our understanding of the interconnectedness between environmental quality and fossil fuel fervor. The methodology employed in this study, akin to a scientific waltz, led us through the dance of data collection, analysis, and interpretation, culminating in a harmonious synthesis of insights into the Pollution Puzzle.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Oklahoma City and Fossil fuel use in North Macedonia. Make lots of jokes, goofy observations, and puns.

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 1992 to 2021, you found a correlation 0.6852993, r-squared of 0.4696351, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

[[ABSTRACT]]
This paper delves into the interconnectedness of air pollution in Oklahoma City and the fervent fossil fuel use in North Macedonia with a touch of whimsy and a hint of sass. Drawing upon data from the Environmental Protection Agency and the Energy Information Administration, our research team sought to address this burning question with statistical analyses revealing a remarkably robust correlation coefficient of 0.6852993 and p < 0.01 for the time period spanning 1992 to 2021. Our findings provide compelling evidence for the intriguing relationship between these seemingly incongruous phenomena, giving one pause to reconsider the nature of atmospheric dynamics and global ties that bind.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The Pollution Puzzle, a persistent predicament perplexing policymakers and citizens alike, has long confounded researchers seeking to unravel the intricate web of factors contributing to air quality degradation. In this scholarly endeavor, we embark on a whimsical yet rigorous examination of the connection between the atmospheric woes of Oklahoma City and the fossil fuel frenzy in North Macedonia. Our investigation aims to shed light on this enigmatic relationship, armed with data, statistical analyses, and a touch of intellectual cheekiness.
Air quality concerns in Oklahoma City have been a topic of contentious debate, with citizens often left breathless by the hazy pollution-laden skies. Meanwhile, North Macedonia has been fervently burning fossil fuels, igniting a figurative firestorm of carbon emissions and environmental apprehension. Ah, the juxtaposition of these two seemingly unrelated phenomena—almost as mystifying as a magician pulling a rabbit out of a hat, but with far more serious implications for public health and the global climate.
Our study draws upon data from the stalwart Environmental Protection Agency and the indefatigable Energy Information Administration, embracing the digital dance of bytes and bits to unravel the intricacies of air quality and fossil fuel consumption. Through the discerning lens of statistical analyses, we aim to extract the essence of this connection, revealing a correlation coefficient so robust it could lift weights at the metaphorical statistical gym.
Now, dear reader, brace yourself for a journey into the world of air particles, carbon emissions, and geographical serendipity. As we delve into the depths of this Pollution Puzzle, prepare to be amused, surprised, and perhaps even enlightened by the ties that bind two distant lands in an atmospheric tango of global significance.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

The connection between air pollution in Oklahoma City and fossil fuel use in North Macedonia has been unveiled with statistical revelry. Our research team scoured data from the Environmental Protection Agency and the Energy Information Administration, gleaning insights from the digital troves of information in a manner akin to the delightful dance of digital detectives tracking down leads in a modern-day mystery.

Upon scrutinizing the data for the time period of 1992 to 2021, a captivating correlation coefficient of 0.6852993 was revealed, accompanied by an r-squared value of 0.4696351 and a p-value of less than 0.01. These statistics, reminiscent of hidden treasure waiting to be unearthed, unveiled a remarkable linkage between the air quality woes in Oklahoma City and the enthusiastic combustion of fossil fuels in North Macedonia.

In Fig. 1, a scatterplot evocatively depicts the strong correlation between these two seemingly incongruous phenomena, capturing the essence of their intertwined fate with the finesse of a whimsical artist painting on the canvas of statistical significance.

The statistical tie revealed in our findings provides a captivating narrative of the atmospheric tango between these distant lands, emphasizing the bewildering interconnectedness of seemingly disparate environmental factors. It raises intriguing questions about the nature of global environmental dynamics and the boundless ties that transcend geographical distances, offering a dash of whimsy and a hint of sass to the world of atmospheric chemistry and environmental discourse.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Oklahoma City and Fossil fuel use in North Macedonia. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

[[ABSTRACT]]
This paper delves into the interconnectedness of air pollution in Oklahoma City and the fervent fossil fuel use in North Macedonia with a touch of whimsy and a hint of sass. Drawing upon data from the Environmental Protection Agency and the Energy Information Administration, our research team sought to address this burning question with statistical analyses revealing a remarkably robust correlation coefficient of 0.6852993 and p < 0.01 for the time period spanning 1992 to 2021. Our findings provide compelling evidence for the intriguing relationship between these seemingly incongruous phenomena, giving one pause to reconsider the nature of atmospheric dynamics and global ties that bind.

[[LITERATURE REVIEW]]
The interplay between air pollution in Oklahoma City and fossil fuel use in North Macedonia has been a topic of increasing interest and inquiry among researchers in the fields of environmental science and public health. Smith et al. (2015) conducted a comprehensive analysis of air quality in Oklahoma City, noting the significant presence of particulate matter and volatile organic compounds in the atmosphere. Meanwhile, Doe and Jones (2018) delved into the fervent fossil fuel use in North Macedonia, highlighting the country's heavy reliance on coal and the consequential emissions of sulfur dioxide and nitrogen oxides.
Moving beyond the realm of scholarly articles, several non-fiction books have also contributed to the discourse on air pollution and fossil fuel consumption. In "The Air We Breathe: A Global Analysis of Environmental Health" by Environmental Expert, the authors explore the interconnectedness of air quality across diverse geographical regions, offering insights into the potential impact of international factors on local pollution levels. In "Fueling the Fire: A Comprehensive Study of Fossil Fuel Dependence" by Energy Specialist, the dynamics of fossil fuel use in various countries are examined, providing valuable context for understanding the drivers of environmental degradation.
On a more fictional note, literary works such as "Smoke and Mirrors: Tales of Environmental Intrigue" by Fictional Author and "Coal Chronicles: A Novel of Fossil Fuel Fantasy" by Imaginary Writer present imaginative narratives that perhaps inadvertently tap into the thematic undercurrents of air pollution and fossil fuel use.
The literature review, however, does not solely rely on conventional academic and literary sources. As part of an unconventional approach, the researchers perused a startling array of material, including but not limited to supermarket receipts, vintage postcards, and the musings of a particularly insightful housecat named Whiskers. While the scientific rigor of these sources is decidedly questionable, they undeniably added an element of unexpected whimsy to the review process.

[[RESULTS]]
The connection between air pollution in Oklahoma City and fossil fuel use in North Macedonia has been unveiled with statistical revelry. Our research team scoured data from the Environmental Protection Agency and the Energy Information Administration, gleaning insights from the digital troves of information in a manner akin to the delightful dance of digital detectives tracking down leads in a modern-day mystery.
Upon scrutinizing the data for the time period of 1992 to 2021, a captivating correlation coefficient of 0.6852993 was revealed, accompanied by an r-squared value of 0.4696351 and a p-value of less than 0.01. These statistics, reminiscent of hidden treasure waiting to be unearthed, unveiled a remarkable linkage between the air quality woes in Oklahoma City and the enthusiastic combustion of fossil fuels in North Macedonia.
In Fig. 1, a scatterplot evocatively depicts the strong correlation between these two seemingly incongruous phenomena, capturing the essence of their intertwined fate with the finesse of a whimsical artist painting on the canvas of statistical significance.
The statistical tie revealed in our findings provides a captivating narrative of the atmospheric tango between these distant lands, emphasizing the bewildering interconnectedness of seemingly disparate environmental factors. It raises intriguing questions about the nature of global environmental dynamics and the boundless ties that transcend geographical distances, offering a dash of whimsy and a hint of sass to the world of atmospheric chemistry and environmental discourse.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The revelatory results of our research not only lend credence to the previous scholarly examinations of air pollution in Oklahoma City and fossil fuel use in North Macedonia, but they also breathe new life into some of the more whimsical elements of the literature review. Smith et al.'s work on Oklahoma City's air quality and Doe and Jones' investigation into North Macedonia's fossil fuel fervor are now bolstered by our statistically robust correlation coefficient of 0.6852993. The p-value of less than 0.01 adds an extra punch to the statistical prowess, proving that the dance of atmospheric dynamics is not to be taken lightly.

Intriguingly, the unexpected sources consulted in our literature review, including supermarket receipts and the musings of a particularly insightful housecat, suddenly seem less fanciful and more prescient in light of our robust findings. Who knew that Whiskers the housecat could be onto something with his observations about the interconnectedness of global environmental factors? Perhaps the purr-spective of domestic felines shouldn't be dismissed so readily.

Our results not only support the existing literature but also add a touch of statistical revelry to the narrative of air pollution and fossil fuel use. The scatterplot, depicted with a finesse akin to that of a whimsical artist, visually encapsulates the seemingly incongruous yet irrefutably linked fate of these distant locales. The discussion is no longer confined to scholarly circles but has now opened up to embrace the unexpected insights that may arise from unconventional sources.

In summary, our findings serve to underscore the enduring connection between air pollution in Oklahoma City and the fossil fuel frenzy in North Macedonia, adding a dash of whimsy and a hint of sass to the ongoing dialogue about environmental interconnectedness. With statistical gravitas and a touch of the unexpected, our research invites further exploration of the captivating atmospheric tango that binds these seemingly disparate regions.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Oklahoma City and Fossil fuel use in North Macedonia. Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

[[ABSTRACT]]
This paper delves into the interconnectedness of air pollution in Oklahoma City and the fervent fossil fuel use in North Macedonia with a touch of whimsy and a hint of sass. Drawing upon data from the Environmental Protection Agency and the Energy Information Administration, our research team sought to address this burning question with statistical analyses revealing a remarkably robust correlation coefficient of 0.6852993 and p < 0.01 for the time period spanning 1992 to 2021. Our findings provide compelling evidence for the intriguing relationship between these seemingly incongruous phenomena, giving one pause to reconsider the nature of atmospheric dynamics and global ties that bind.

[[INTRDUCTION]]
The Pollution Puzzle, a persistent predicament perplexing policymakers and citizens alike, has long confounded researchers seeking to unravel the intricate web of factors contributing to air quality degradation. In this scholarly endeavor, we embark on a whimsical yet rigorous examination of the connection between the atmospheric woes of Oklahoma City and the fossil fuel frenzy in North Macedonia. Our investigation aims to shed light on this enigmatic relationship, armed with data, statistical analyses, and a touch of intellectual cheekiness.
Air quality concerns in Oklahoma City have been a topic of contentious debate, with citizens often left breathless by the hazy pollution-laden skies. Meanwhile, North Macedonia has been fervently burning fossil fuels, igniting a figurative firestorm of carbon emissions and environmental apprehension. Ah, the juxtaposition of these two seemingly unrelated phenomena—almost as mystifying as a magician pulling a rabbit out of a hat, but with far more serious implications for public health and the global climate.
Our study draws upon data from the stalwart Environmental Protection Agency and the indefatigable Energy Information Administration, embracing the digital dance of bytes and bits to unravel the intricacies of air quality and fossil fuel consumption. Through the discerning lens of statistical analyses, we aim to extract the essence of this connection, revealing a correlation coefficient so robust it could lift weights at the metaphorical statistical gym.
Now, dear reader, brace yourself for a journey into the world of air particles, carbon emissions, and geographical serendipity. As we delve into the depths of this Pollution Puzzle, prepare to be amused, surprised, and perhaps even enlightened by the ties that bind two distant lands in an atmospheric tango of global significance.

[[RESULTS]]
The connection between air pollution in Oklahoma City and fossil fuel use in North Macedonia has been unveiled with statistical revelry. Our research team scoured data from the Environmental Protection Agency and the Energy Information Administration, gleaning insights from the digital troves of information in a manner akin to the delightful dance of digital detectives tracking down leads in a modern-day mystery.
Upon scrutinizing the data for the time period of 1992 to 2021, a captivating correlation coefficient of 0.6852993 was revealed, accompanied by an r-squared value of 0.4696351 and a p-value of less than 0.01. These statistics, reminiscent of hidden treasure waiting to be unearthed, unveiled a remarkable linkage between the air quality woes in Oklahoma City and the enthusiastic combustion of fossil fuels in North Macedonia.
In Fig. 1, a scatterplot evocatively depicts the strong correlation between these two seemingly incongruous phenomena, capturing the essence of their intertwined fate with the finesse of a whimsical artist painting on the canvas of statistical significance.
The statistical tie revealed in our findings provides a captivating narrative of the atmospheric tango between these distant lands, emphasizing the bewildering interconnectedness of seemingly disparate environmental factors. It raises intriguing questions about the nature of global environmental dynamics and the boundless ties that transcend geographical distances, offering a dash of whimsy and a hint of sass to the world of atmospheric chemistry and environmental discourse.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In the grand finale of this whimsical tango between air pollution in Oklahoma City and the fossil fuel frenzy in North Macedonia, we have untangled a web of statistical intrigue and atmospheric serendipity. Our findings, akin to a magician's revealing sleight of hand, showcase a robust correlation coefficient and a p-value that would make any statistician do a double take.

The connection between these two seemingly incongruous phenomena, like a riveting plot twist in a melodramatic play, reminds us of the boundless complexity of the environmental stage on which we all inadvertently act. It's as if the atmospheric particles of Oklahoma City and the carbon emissions of North Macedonia have been waltzing together in a clandestine ballet, hidden in plain sight until our statistical spotlight illuminated their harmonious entanglement.

The scatterplot, a visual ode to this unlikely union, paints a picture so evocative that it's almost reminiscent of a surrealist masterpiece. It is as if Salvador Dali himself sketched the intertwined fate of air pollution and fossil fuel use, infusing the canvas of statistical significance with a touch of his trademark eccentricity.

As we bid farewell to our research endeavors, we are left with a lingering sense of incredulity and a chuckle of amused bewilderment at the whimsical nature of environmental dynamics. This Pollution Puzzle, while revealing its intriguing secrets, leaves us with a parting gift of intellectual cheekiness and a reminder that the intricate dance of atmospheric interconnectedness always has a surprise or two up its metaphorical sleeve.

In conclusion, we assert that no further research is needed in this area, as we have unraveled the enigmatic connection between air pollution in Oklahoma City and fossil fuel use in North Macedonia with all the whimsy and sass one could ever desire.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Ecological Enigmas

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Environmental Symbiosis and Climate Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia with an abstract of This paper delves into the interconnectedness of air pollution in Oklahoma City and the fervent fossil fuel use in North Macedonia with a touch of whimsy and a hint of sass. Drawing upon data from the Environmental Protection Agency and the Energy Information Administration, our research team sought to address this burning question with statistical analyses revealing a remarkably robust correlation coefficient of 0.6852993 and p < 0.01 for the time period spanning 1992 to 2021. Our findings provide compelling evidence for the intriguing relationship between these seemingly incongruous phenomena, giving one pause to reconsider the nature of atmospheric dynamics and global ties that bind.

ChatGPT:

air pollution, Oklahoma City air quality, fossil fuel use, North Macedonia, correlation coefficient, statistical analysis, Environmental Protection Agency data, Energy Information Administration data, atmospheric dynamics, global ties that bind, air quality 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 Oklahoma City
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Oklahoma City, OK
Source: Environmental Protection Agency
See what else correlates with Air pollution in Oklahoma City

Fossil fuel use in North Macedonia
Detailed data title: Total fossil fuel use in North Macedonia in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in North Macedonia

Correlation r = 0.6852993 (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 = 0.4696351 (Coefficient of determination)
This means 47% of the change in the one variable (i.e., Fossil fuel use in North Macedonia) is predictable based on the change in the other (i.e., Air pollution in Oklahoma City) over the 30 years from 1992 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.9E-5.^Show 0.0000293451406706288000000000
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 0.69 in 0.0029% of random cases. Said differently, if you correlated 34,077 random variables^Note You don't actually need 34 thousand variables to find a correlation like this one. 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.

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 29 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 29 because we have two variables measured over a period of 30 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.

[ 0.43, 0.84 ] 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.

	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
Air pollution in Oklahoma City (Bad air quality days)	3.82514	3.83562	10.6849	12.3288	6.01093	6.84932	16.4384	9.0411	9.83607	10.6849	9.86301	8.49315	3.55191	9.0411	13.9726	2.73973	2.73224	4.38356	3.0137	12.0548	10.6557	2.19178	1.36986	0.547945	0.819672	1.91781	3.28767	0.547945	1.36612	2.73973
Fossil fuel use in North Macedonia (Billion kWh)	4.904	4.379	4.795	5.011	5.444	5.483	5.607	5.146	5.30254	5.39184	5.01396	5.04216	4.8739	5.12582	5.03746	5.15872	5.14274	5.22452	4.53926	5.0055	4.90492	4.23094	3.83708	3.26992	3.24853	3.9582	3.33858	4.16962	3.56764	3.59928

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^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.
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. ^Note 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. ^{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([3.82514,3.83562,10.6849,12.3288,6.01093,6.84932,16.4384,9.0411,9.83607,10.6849,9.86301,8.49315,3.55191,9.0411,13.9726,2.73973,2.73224,4.38356,3.0137,12.0548,10.6557,2.19178,1.36986,0.547945,0.819672,1.91781,3.28767,0.547945,1.36612,2.73973,])
array_2 = np.array([4.904,4.379,4.795,5.011,5.444,5.483,5.607,5.146,5.30254,5.39184,5.01396,5.04216,4.8739,5.12582,5.03746,5.15872,5.14274,5.22452,4.53926,5.0055,4.90492,4.23094,3.83708,3.26992,3.24853,3.9582,3.33858,4.16962,3.56764,3.59928,])
array_1_name = "Air pollution in Oklahoma City"
array_2_name = "Fossil fuel use in North Macedonia"

# 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 Oklahoma City
Line chart for only Fossil fuel use in North Macedonia
AI-generated correlation image
The spurious research paper: The Pollution Puzzle: Pondering the Interplay between Air Quality in Oklahoma City and Fossil Fuel Frenzy in North Macedonia

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Correlation ID: 2368 · Black Variable ID: 21001 · Red Variable ID: 23873


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