Spurious correlation #3,858 · 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 Des Moines and the second variable is Kerosene used in Canada. The chart goes from 1980 to 2022, 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 Des Moines and the second variable is Kerosene used in Canada. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air pollution in Des Moines decreased, it cleared the way for fresher ideas. This led to the development of more efficient energy sources in Canada, reducing the reliance on kerosene and igniting a spark for change. In other words, Des Moines became the air-rodynamic force for a kerosene revolution in Canada.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image in the style of a Polaroid photo showing Des Moines with a clear, pollution-free sky and thriving trees. Squirrels are happily playing in the parks, and their cheerful chattering is heard throughout the city. In the same photo, depict a Canadian forest where a group of squirrels is seen with less kerosene, no longer feeling the need to hoard it for a doomsday scenario. The scene should highlight the untouched and thriving trees, along with fresh, clean air. Both scenes should convey the positive impact of decreased air pollution in Des Moines on the behavior of squirrels and the reduced need for kerosene hoarding in Canada. 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 Des Moines and Kerosene used in Canada. 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: Steampunk a Polaroid photo Art nouveau a meme a funny image macro
ChatGPT: a Polaroid photo

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 Des Moines and Kerosene used in Canada, in the following situation: Because the decrease in air pollution in Des Moines led to happier squirrels, causing them to hoard less kerosene in Canada for a doomsday scenario.. Keep the description simple.
ChatGPT: In Des Moines, the sky is clear of pollution, and the trees are thriving. Squirrels are happily playing in the parks, and their cheerful chattering is heard throughout the city. Meanwhile, in a Canadian forest, a group of squirrels is seen with less kerosene as they no longer feel the need to hoard it for a doomsday scenario. The trees are untouched by pollutants, and the air is fresh and clean. Both scenes jointly highlight the positive impact of decreased air pollution in Des Moines on the behavior of squirrels and the reduced need for kerosene hoarding in Canada.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ a Polaroid photo ] and depicting this scene: In Des Moines, the sky is clear of pollution, and the trees are thriving. Squirrels are happily playing in the parks, and their cheerful chattering is heard throughout the city. Meanwhile, in a Canadian forest, a group of squirrels is seen with less kerosene as they no longer feel the need to hoard it for a doomsday scenario. The trees are untouched by pollutants, and the air is fresh and clean. Both scenes jointly highlight the positive impact of decreased air pollution in Des Moines on the behavior of squirrels and the reduced need for kerosene hoarding in Canada. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image in the style of a Polaroid photo showing Des Moines with a clear, pollution-free sky and thriving trees. Squirrels are happily playing in the parks, and their cheerful chattering is heard throughout the city. In the same photo, depict a Canadian forest where a group of squirrels is seen with less kerosene, no longer feeling the need to hoard it for a doomsday scenario. The scene should highlight the untouched and thriving trees, along with fresh, clean air. Both scenes should convey the positive impact of decreased air pollution in Des Moines on the behavior of squirrels and the reduced need for kerosene hoarding in Canada.

*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 Des Moines caused Kerosene used in Canada to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

The Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage

Journal of Environmental Satire and Irreverence

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 Des Moines and Kerosene used in Canada. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"The Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage"

[[ABSTRACT]]
In this groundbreaking study, we delve deep into the enigmatic relationship between air pollution in Des Moines and kerosene usage in Canada. While some may think these two topics are as unrelated as a fish and a bicycle, our findings reveal a surprisingly strong correlation. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we applied rigorous statistical analyses and uncovered a correlation coefficient of 0.7376787 with p < 0.01 for the years 1980 to 2022.

Our research team was astounded by the scope and significance of this correlation. It's almost as astonishing as finding a porcupine in a balloon factory! Upon further investigation, we identified potential mechanisms that could explain this unexpected connection. From the combustion of kerosene lamps to the release of pollutants into the atmosphere, the link between Des Moines' air quality and Canadian kerosene usage is as intriguing as a detective novel.

Furthermore, our results prompt us to ponder the implications of our findings. Could addressing kerosene usage in Canada lead to cleaner air in Des Moines? Or is there a deeper, cosmic connection at play? Whatever the case may be, this research opens up a world of possibilities and sparks the imagination, much like discovering a pun in a serious academic paper.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between air pollution and various sources of energy has long been a subject of interest for environmental scientists and policymakers. From coal-fired power plants to vehicular emissions, the impact of human activities on air quality is as palpable as a dad joke at a family gathering. In this study, we turn our attention to the intriguing connection between Des Moines' air pollution and the usage of kerosene in Canada.
While the idea of linking air pollution in Des Moines to Canadian kerosene usage might initially seem as far-fetched as a unicorn at a petting zoo, our research uncovers a compelling association between these seemingly disparate phenomena. Our findings may surprise you more than finding a hidden stash of dad jokes in a serious academic paper!
The combustion of kerosene for various purposes, including lighting and heating, leads to the release of pollutants such as sulfur dioxide and particulate matter into the atmosphere. These emissions can travel great distances and have the potential to impact air quality far beyond Canadian borders. It's almost like telling a bad joke - it can have far-reaching consequences!
By analyzing a comprehensive dataset spanning over four decades, we observed a correlation coefficient that was stronger than the gravitational pull of a black hole, coming in at 0.7376787 with p < 0.01. This robust statistical relationship suggests a significant connection between the fluctuations in Canadian kerosene usage and the levels of air pollutants recorded in Des Moines. It's almost as clear as day, or as clear as the air in Des Moines could be with reduced pollution!
As we delve deeper into the potential mechanisms underlying this connection, we uncover a web of factors that link the burning of kerosene in Canada to the air quality in Des Moines. The interplay between atmospheric transport, chemical transformations, and emissions from kerosene combustion is as intricate as a complex riddle, offering an intellectually stimulating challenge akin to solving a crossword puzzle.
This research has profound implications for environmental policy and public health initiatives, raising thought-provoking questions and inspiring innovative solutions. Could reducing kerosene usage in Canada lead to tangible improvements in air quality across the border? The implications are as profound as realizing that the "dad" in "dad joke" stands for "Destroyer of All Dignity."
In the following sections, we present our methodology, results, and discussion, unraveling the mystery behind the burning connection, and exploring its implications for environmental stewardship. Just like a good punchline, our findings are sure to leave a lasting impression and spark further inquiry in this fascinating area of study.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Smith et al. conducted a comprehensive study on the impact of kerosene combustion on air quality, highlighting the release of sulfur compounds and particulate matter into the atmosphere. Their findings underscore the potential for long-range transport of these pollutants and raise important questions about the regional and global implications of kerosene usage. It's like they found the missing piece of the puzzle, or should I say, the missing "kerosene" of the puzzle!

In "Air Pollution and Its Effects" by Doe, the authors delve into the complexities of urban air pollution, emphasizing the contribution of various sources to the deteriorating air quality in cities. While the focus is primarily on local sources, the study provides valuable insights into the interconnected nature of air pollution and the need for holistic approaches in addressing environmental challenges. It's like a symphony of pollutants playing in perfect disharmony!

Jones and colleagues explored the role of international energy trade on air quality, shedding light on the indirect impacts of energy consumption patterns in one country on the atmospheric conditions of another. Their work underscores the importance of considering transboundary effects in environmental policymaking and calls for collaborative efforts to mitigate air pollution across borders. It's like the pollution traveled more than a tourist visiting Canada from Des Moines!

Books like "The Silent Killer: Understanding Air Pollution" and "The Burning Truth: A Global Perspective on Energy and the Environment" offer valuable insights into the broader context of air pollution and energy use. The authors present compelling narratives that highlight the urgency of addressing environmental challenges and adopting sustainable practices. It's almost like receiving a wake-up call from Mother Nature herself!

Turning to fiction, novels such as "Smoke Signals" and "The Polluted Skies Chronicles" capture the imagination with their vivid portrayal of environmental dystopias and the struggle for clean air in a world plagued by pollution. While these works are fictional, they offer thought-provoking reflections on the potential consequences of unchecked environmental degradation. It's like taking a trip to a parallel universe where clean air is a rare commodity!

On social media, hashtags like #CleanAirNow and #KeroseneDebate have sparked discussions on the environmental impact of kerosene use and its implications for air quality. Users share personal anecdotes and engage in debates about the role of individual choices in shaping environmental outcomes. It's like a virtual town hall meeting, but with more puns and memes!

These diverse sources provide a rich tapestry of perspectives on the complex interplay between air pollution and energy use. As we navigate through the scholarly literature, non-fiction works, and online discourse, we gain a deeper appreciation for the multifaceted nature of this topic. It's like trying to juggle with pollution masks and kerosene lamps at the same time - a balancing act that requires careful consideration of all the factors at play!

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 Des Moines and Kerosene used in Canada. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration . You used data from 1980 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"The Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage"

[[ABSTRACT]]
In this groundbreaking study, we delve deep into the enigmatic relationship between air pollution in Des Moines and kerosene usage in Canada. While some may think these two topics are as unrelated as a fish and a bicycle, our findings reveal a surprisingly strong correlation. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we applied rigorous statistical analyses and uncovered a correlation coefficient of 0.7376787 with p < 0.01 for the years 1980 to 2022.

Our research team was astounded by the scope and significance of this correlation. It's almost as astonishing as finding a porcupine in a balloon factory! Upon further investigation, we identified potential mechanisms that could explain this unexpected connection. From the combustion of kerosene lamps to the release of pollutants into the atmosphere, the link between Des Moines' air quality and Canadian kerosene usage is as intriguing as a detective novel.

Furthermore, our results prompt us to ponder the implications of our findings. Could addressing kerosene usage in Canada lead to cleaner air in Des Moines? Or is there a deeper, cosmic connection at play? Whatever the case may be, this research opens up a world of possibilities and sparks the imagination, much like discovering a pun in a serious academic paper.

[[INTRODUCTION]]
The relationship between air pollution and various sources of energy has long been a subject of interest for environmental scientists and policymakers. From coal-fired power plants to vehicular emissions, the impact of human activities on air quality is as palpable as a dad joke at a family gathering. In this study, we turn our attention to the intriguing connection between Des Moines' air pollution and the usage of kerosene in Canada.
While the idea of linking air pollution in Des Moines to Canadian kerosene usage might initially seem as far-fetched as a unicorn at a petting zoo, our research uncovers a compelling association between these seemingly disparate phenomena. Our findings may surprise you more than finding a hidden stash of dad jokes in a serious academic paper!
The combustion of kerosene for various purposes, including lighting and heating, leads to the release of pollutants such as sulfur dioxide and particulate matter into the atmosphere. These emissions can travel great distances and have the potential to impact air quality far beyond Canadian borders. It's almost like telling a bad joke - it can have far-reaching consequences!
By analyzing a comprehensive dataset spanning over four decades, we observed a correlation coefficient that was stronger than the gravitational pull of a black hole, coming in at 0.7376787 with p < 0.01. This robust statistical relationship suggests a significant connection between the fluctuations in Canadian kerosene usage and the levels of air pollutants recorded in Des Moines. It's almost as clear as day, or as clear as the air in Des Moines could be with reduced pollution!
As we delve deeper into the potential mechanisms underlying this connection, we uncover a web of factors that link the burning of kerosene in Canada to the air quality in Des Moines. The interplay between atmospheric transport, chemical transformations, and emissions from kerosene combustion is as intricate as a complex riddle, offering an intellectually stimulating challenge akin to solving a crossword puzzle.
This research has profound implications for environmental policy and public health initiatives, raising thought-provoking questions and inspiring innovative solutions. Could reducing kerosene usage in Canada lead to tangible improvements in air quality across the border? The implications are as profound as realizing that the "dad" in "dad joke" stands for "Destroyer of All Dignity."
In the following sections, we present our methodology, results, and discussion, unraveling the mystery behind the burning connection, and exploring its implications for environmental stewardship. Just like a good punchline, our findings are sure to leave a lasting impression and spark further inquiry in this fascinating area of study.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the perplexing link between Des Moines' air pollution and Canadian kerosene usage, our research team utilized a combination of rigorous statistical analyses and unconventional investigative strategies. We collected data from a variety of sources, scouring the depths of the internet like intrepid explorers on a digital treasure hunt. It was almost as thrilling as finding the missing puzzle piece in a jigsaw puzzle.

The primary sources of data for our study were the Environmental Protection Agency (EPA) and the Energy Information Administration (EIA). We selected these sources not only for their comprehensive and reliable data but also for their entertaining acronyms. After all, what's life without a good acronym joke?

Our dataset spanned from the year 1980 to 2022, capturing a considerable timeframe that allowed us to examine long-term trends and fluctuations. We then conducted a series of statistical analyses, employing methods as robust as a weightlifter on leg day.

First, we calculated correlation coefficients between the levels of air pollutants in Des Moines and the recorded kerosene usage in Canada. This process involved more calculations than a math whiz at a Sudoku competition.

Next, we performed a time-series analysis to detect any temporal patterns and trends in the data. The intricacies of this analysis were as fascinating as unraveling a mystery novel, with plot twists and turns that kept us on the edge of our seats.

Finally, we employed advanced modeling techniques to explore potential causal relationships and mechanisms underlying the observed correlation. Our models were more intricate than a Rube Goldberg machine, but hopefully more practical and less convoluted.

In addition to these standard statistical methods, we also engaged in some unconventional investigative tactics. We considered the possibility of interdimensional portals, time-traveling kerosene molecules, and parallel universes where kerosene fumes affect air pollution in Des Moines. While these ideas may seem as far-fetched as a conspiracy theory, we approached them with the same level of seriousness as a dad deploying his best dad joke at a family gathering.

Overall, our methodology combined the best of conventional statistical analysis with a touch of imaginative exploration, resulting in a comprehensive and engaging approach to unraveling the burning connection between Des Moines' air pollution and Canadian kerosene usage. Much like a good dad joke, our research was both scientifically sound and delightfully unexpected.

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 Des Moines and Kerosene used in Canada. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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 Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage"

[[ABSTRACT]]
In this groundbreaking study, we delve deep into the enigmatic relationship between air pollution in Des Moines and kerosene usage in Canada. While some may think these two topics are as unrelated as a fish and a bicycle, our findings reveal a surprisingly strong correlation. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we applied rigorous statistical analyses and uncovered a correlation coefficient of 0.7376787 with p < 0.01 for the years 1980 to 2022.

Our research team was astounded by the scope and significance of this correlation. It's almost as astonishing as finding a porcupine in a balloon factory! Upon further investigation, we identified potential mechanisms that could explain this unexpected connection. From the combustion of kerosene lamps to the release of pollutants into the atmosphere, the link between Des Moines' air quality and Canadian kerosene usage is as intriguing as a detective novel.

Furthermore, our results prompt us to ponder the implications of our findings. Could addressing kerosene usage in Canada lead to cleaner air in Des Moines? Or is there a deeper, cosmic connection at play? Whatever the case may be, this research opens up a world of possibilities and sparks the imagination, much like discovering a pun in a serious academic paper.

[[LITERATURE REVIEW]]
Smith et al. conducted a comprehensive study on the impact of kerosene combustion on air quality, highlighting the release of sulfur compounds and particulate matter into the atmosphere. Their findings underscore the potential for long-range transport of these pollutants and raise important questions about the regional and global implications of kerosene usage. It's like they found the missing piece of the puzzle, or should I say, the missing "kerosene" of the puzzle!
In "Air Pollution and Its Effects" by Doe, the authors delve into the complexities of urban air pollution, emphasizing the contribution of various sources to the deteriorating air quality in cities. While the focus is primarily on local sources, the study provides valuable insights into the interconnected nature of air pollution and the need for holistic approaches in addressing environmental challenges. It's like a symphony of pollutants playing in perfect disharmony!
Jones and colleagues explored the role of international energy trade on air quality, shedding light on the indirect impacts of energy consumption patterns in one country on the atmospheric conditions of another. Their work underscores the importance of considering transboundary effects in environmental policymaking and calls for collaborative efforts to mitigate air pollution across borders. It's like the pollution traveled more than a tourist visiting Canada from Des Moines!
Books like "The Silent Killer: Understanding Air Pollution" and "The Burning Truth: A Global Perspective on Energy and the Environment" offer valuable insights into the broader context of air pollution and energy use. The authors present compelling narratives that highlight the urgency of addressing environmental challenges and adopting sustainable practices. It's almost like receiving a wake-up call from Mother Nature herself!
Turning to fiction, novels such as "Smoke Signals" and "The Polluted Skies Chronicles" capture the imagination with their vivid portrayal of environmental dystopias and the struggle for clean air in a world plagued by pollution. While these works are fictional, they offer thought-provoking reflections on the potential consequences of unchecked environmental degradation. It's like taking a trip to a parallel universe where clean air is a rare commodity!
On social media, hashtags like #CleanAirNow and #KeroseneDebate have sparked discussions on the environmental impact of kerosene use and its implications for air quality. Users share personal anecdotes and engage in debates about the role of individual choices in shaping environmental outcomes. It's like a virtual town hall meeting, but with more puns and memes!
These diverse sources provide a rich tapestry of perspectives on the complex interplay between air pollution and energy use. As we navigate through the scholarly literature, non-fiction works, and online discourse, we gain a deeper appreciation for the multifaceted nature of this topic. It's like trying to juggle with pollution masks and kerosene lamps at the same time - a balancing act that requires careful consideration of all the factors at play!

[[RESULTS]]
The analysis of the data revealed a robust correlation coefficient of 0.7376787, suggesting a strong positive relationship between air pollution in Des Moines and the usage of kerosene in Canada. This connection is as clear as a sunny day in Des Moines – well, as clear as it can be with reduced pollution, of course!
The r-squared value of 0.5441699 indicated that approximately 54.42% of the variability in air pollution in Des Moines could be explained by the fluctuations in Canadian kerosene usage. It's almost as if we've unlocked a hidden level in a video game – this correlation is more than just a mere Easter egg!
The significance level of p < 0.01 further strengthens our confidence in the observed relationship. With such a low p-value, we can be more confident in our findings than in a dad joke at a comedy club – and that’s saying something!
Fig. 1 displays a scatterplot illustrating the strong correlation between air pollution in Des Moines and kerosene usage in Canada. The points on the plot hug the regression line as though they were giving it a warm embrace – much like the relationship between correlation and causation (if only it were that simple!).
In conclusion, our findings provide compelling evidence of a substantial link between air pollution in Des Moines and Canadian kerosene usage. This unexpected connection opens up countless avenues for further research and policy considerations. It's as if we've stumbled upon a treasure trove of correlations, just waiting to be explored – much like finding a dad joke treasure chest on Talk Like a Pirate Day! Arrr, matey, the connections be as plentiful as pieces of eight!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has uncovered a remarkably robust correlation between air pollution in Des Moines and the usage of kerosene in Canada, confirming and building upon the findings of previous research. The correlations we observed were almost as strong as the gravitational pull of a black hole - pulling us deeper into the mysterious relationship between these seemingly disparate elements. The correlation coefficient of 0.7376787, akin to a rock-solid foundation, lends unequivocal support to the notion that changes in Canadian kerosene usage are closely tied to fluctuations in air pollution levels in Des Moines.

Our results align with the work of Smith et al., who emphasized the substantial impact of kerosene combustion on air quality. It's as if they handed us a flashlight in the dimly lit cave of correlation research – shedding light on the mechanisms through which kerosene usage can influence air pollution, much like the way a kerosene lamp illuminates a dark room. Similarly, the findings echo the insights of Jones and colleagues regarding the transboundary effects of energy trade, extending our understanding of how activities in one country can reverberate across borders, just like a lighthearted joke in a serious discussion.

The r-squared value of 0.5441699 further underscores the substantial influence of Canadian kerosene usage on air pollution in Des Moines, explaining over half of the variability in air pollution levels. This finding is as solid as a rock, or should I say, as solid as a Canadian hockey puck? Our results not only verify the existence of the correlation but also pave the way for strategic interventions to mitigate air pollution by addressing kerosene usage. It's like finding the key to solving a complex puzzle – unlocking the potential for targeted policies and collaborative efforts to improve air quality in Des Moines and beyond.

The significance level of p < 0.01 reinforces the confidence in our findings, akin to the unwavering confidence of a dad with a pun up his sleeve. With such a low p-value, we can stand by our conclusion with certainty, just like a dad joke - no matter how groan-inducing, it's hard to refute. The scatterplot visualization further illustrates the strong relationship between air pollution in Des Moines and Canadian kerosene usage, providing a graphical representation that is as clear as Des Moines' air on a windy day.

In navigating through the seemingly disparate realms of air pollution and kerosene usage, our research has unraveled a web of correlations and implications that extend far beyond their respective geographic origins. This unexpected connection challenges us to reevaluate the interconnectedness of environmental phenomena and invites a holistic approach to addressing the multifaceted drivers of air pollution. It's like discovering a surprise item in a video game - our findings are more than just an Easter egg; they're a stepping stone toward a deeper understanding of the complex dynamics shaping our environment.

Our study kindles the flame of curiosity, prompting further exploration into the interplay between energy consumption, air quality, and cross-border pollution. The implications of our research extend beyond academic curiosity and beckon us to consider the actionable steps that can be taken to address the intricacies of this connection. It's like finding the punchline to a complex joke – our findings invite a collective "Aha!" moment and set the stage for informed, targeted initiatives that can lead to tangible improvements in air quality.

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 Des Moines and Kerosene used in Canada. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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 Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage"

[[ABSTRACT]]
In this groundbreaking study, we delve deep into the enigmatic relationship between air pollution in Des Moines and kerosene usage in Canada. While some may think these two topics are as unrelated as a fish and a bicycle, our findings reveal a surprisingly strong correlation. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we applied rigorous statistical analyses and uncovered a correlation coefficient of 0.7376787 with p < 0.01 for the years 1980 to 2022.

Our research team was astounded by the scope and significance of this correlation. It's almost as astonishing as finding a porcupine in a balloon factory! Upon further investigation, we identified potential mechanisms that could explain this unexpected connection. From the combustion of kerosene lamps to the release of pollutants into the atmosphere, the link between Des Moines' air quality and Canadian kerosene usage is as intriguing as a detective novel.

Furthermore, our results prompt us to ponder the implications of our findings. Could addressing kerosene usage in Canada lead to cleaner air in Des Moines? Or is there a deeper, cosmic connection at play? Whatever the case may be, this research opens up a world of possibilities and sparks the imagination, much like discovering a pun in a serious academic paper.

[[INTRDUCTION]]
The relationship between air pollution and various sources of energy has long been a subject of interest for environmental scientists and policymakers. From coal-fired power plants to vehicular emissions, the impact of human activities on air quality is as palpable as a dad joke at a family gathering. In this study, we turn our attention to the intriguing connection between Des Moines' air pollution and the usage of kerosene in Canada.
While the idea of linking air pollution in Des Moines to Canadian kerosene usage might initially seem as far-fetched as a unicorn at a petting zoo, our research uncovers a compelling association between these seemingly disparate phenomena. Our findings may surprise you more than finding a hidden stash of dad jokes in a serious academic paper!
The combustion of kerosene for various purposes, including lighting and heating, leads to the release of pollutants such as sulfur dioxide and particulate matter into the atmosphere. These emissions can travel great distances and have the potential to impact air quality far beyond Canadian borders. It's almost like telling a bad joke - it can have far-reaching consequences!
By analyzing a comprehensive dataset spanning over four decades, we observed a correlation coefficient that was stronger than the gravitational pull of a black hole, coming in at 0.7376787 with p < 0.01. This robust statistical relationship suggests a significant connection between the fluctuations in Canadian kerosene usage and the levels of air pollutants recorded in Des Moines. It's almost as clear as day, or as clear as the air in Des Moines could be with reduced pollution!
As we delve deeper into the potential mechanisms underlying this connection, we uncover a web of factors that link the burning of kerosene in Canada to the air quality in Des Moines. The interplay between atmospheric transport, chemical transformations, and emissions from kerosene combustion is as intricate as a complex riddle, offering an intellectually stimulating challenge akin to solving a crossword puzzle.
This research has profound implications for environmental policy and public health initiatives, raising thought-provoking questions and inspiring innovative solutions. Could reducing kerosene usage in Canada lead to tangible improvements in air quality across the border? The implications are as profound as realizing that the "dad" in "dad joke" stands for "Destroyer of All Dignity."
In the following sections, we present our methodology, results, and discussion, unraveling the mystery behind the burning connection, and exploring its implications for environmental stewardship. Just like a good punchline, our findings are sure to leave a lasting impression and spark further inquiry in this fascinating area of study.

[[RESULTS]]
The analysis of the data revealed a robust correlation coefficient of 0.7376787, suggesting a strong positive relationship between air pollution in Des Moines and the usage of kerosene in Canada. This connection is as clear as a sunny day in Des Moines – well, as clear as it can be with reduced pollution, of course!
The r-squared value of 0.5441699 indicated that approximately 54.42% of the variability in air pollution in Des Moines could be explained by the fluctuations in Canadian kerosene usage. It's almost as if we've unlocked a hidden level in a video game – this correlation is more than just a mere Easter egg!
The significance level of p < 0.01 further strengthens our confidence in the observed relationship. With such a low p-value, we can be more confident in our findings than in a dad joke at a comedy club – and that’s saying something!
Fig. 1 displays a scatterplot illustrating the strong correlation between air pollution in Des Moines and kerosene usage in Canada. The points on the plot hug the regression line as though they were giving it a warm embrace – much like the relationship between correlation and causation (if only it were that simple!).
In conclusion, our findings provide compelling evidence of a substantial link between air pollution in Des Moines and Canadian kerosene usage. This unexpected connection opens up countless avenues for further research and policy considerations. It's as if we've stumbled upon a treasure trove of correlations, just waiting to be explored – much like finding a dad joke treasure chest on Talk Like a Pirate Day! Arrr, matey, the connections be as plentiful as pieces of eight!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has brought to light an undeniable connection between the air pollution in Des Moines and the usage of kerosene in Canada. The correlation coefficient of 0.7376787 with a p-value of less than 0.01 establishes a relationship stronger than the bond between a cup of coffee and a Monday morning. It's as clear as the air in Des Moines would be with reduced pollution!

Our findings suggest that the combustion of kerosene in Canada has a substantial impact on the air quality in Des Moines, highlighting the need for transnational cooperation in addressing this issue. It's like uncovering a hidden agenda in a spy movie – this connection is both surprising and consequential.

As we wrap up our exploration of this burning connection, it's essential to acknowledge the broader implications of our research. The potential for mitigating air pollution in Des Moines through measures targeting kerosene usage in Canada is as promising as a sunny day after a week of rain. It's almost as if we've found the missing piece of the puzzle in the fight for cleaner air!

However, it's crucial to remember that correlation does not imply causation, like having a lot of math books doesn't make someone a mathematician. Further interdisciplinary investigations are needed to unravel the complexities of this relationship and its practical applications. But for now, we can bask in the glory of this groundbreaking discovery, like finding a five-dollar bill in an old pair of jeans.

In conclusion, our study sheds light on the intriguing connection between air pollution in Des Moines and Canadian kerosene usage, opening up a world of possibilities for environmental policy and international cooperation. It's like uncovering a hidden gem in a sea of data – this correlation is truly a treasure worth exploring.

It's safe to say that no more research is needed in this area. It's as settled as the bill at a restaurant with friends who conveniently forgot their wallets. We've connected the dots, or in this case, the air pollutants, and it's time to take this discovery and run with it, like a marathon runner with a determination as strong as our correlation coefficient.

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 Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Environmental Satire and Irreverence

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 Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage. Respond only with the name of a fictional organization.

ChatGPT:

Society for Environmental Air Quality Research and 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 Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage with an abstract of In this groundbreaking study, we delve deep into the enigmatic relationship between air pollution in Des Moines and kerosene usage in Canada. While some may think these two topics are as unrelated as a fish and a bicycle, our findings reveal a surprisingly strong correlation. Utilizing data from the Environmental Protection Agency and the Energy Information Administration, we applied rigorous statistical analyses and uncovered a correlation coefficient of 0.7376787 with p < 0.01 for the years 1980 to 2022.
Our research team was astounded by the scope and significance of this correlation. It's almost as astonishing as finding a porcupine in a balloon factory! Upon further investigation, we identified potential mechanisms that could explain this unexpected connection. From the combustion of kerosene lamps to the release of pollutants into the atmosphere, the link between Des Moines' air quality and Canadian kerosene usage is as intriguing as a detective novel.
Furthermore, our results prompt us to ponder the implications of our findings. Could addressing kerosene usage in Canada lead to cleaner air in Des Moines? Or is there a deeper, cosmic connection at play? Whatever the case may be, this research opens up a world of possibilities and sparks the imagination, much like discovering a pun in a serious academic paper.

ChatGPT:

Des Moines air pollution, Canadian kerosene usage, correlation, statistical analysis, Environmental Protection Agency, Energy Information Administration, combustion of kerosene lamps, air quality, pollutants, implications, cosmic connection, cleaner air.

*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 Des Moines
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Des Moines-West Des Moines, IA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Des Moines

Kerosene used in Canada
Detailed data title: Volume of kerosene used consumed in Canada in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Kerosene used in Canada

Correlation r = 0.7376787 (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 = 0.5441699 (Coefficient of determination)
This means 54.4% of the change in the one variable (i.e., Kerosene used in Canada) is predictable based on the change in the other (i.e., Air pollution in Des Moines) over the 43 years from 1980 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-8.^Show 0.0000000166875987015422150000
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 0.74 in 1.7E-6% of random cases. Said differently, if you correlated 59,924,739 random variables^Note You don't actually need 59 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 42 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.56, 0.85 ] 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.

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Air pollution in Des Moines (Bad air quality days)	15.978	1.64384	2.73973	14.5205	3.82514	1.64384	0.273973	0	0	0.821918	0	0	2.37389	0.327869	0	2.46575	0.546448	0	1.09589	2.46575	1.91257	0.273973	0	1.09589	0.819672	3.56164	0.547945	1.36986	0.273224	0.273973	0.821918	0	0.546448	0	0	0	0.273224	0.273973	0.547945	0	0.546448	0.273973	0
Kerosene used in Canada (Million Barrels/Day)	66	51	45	38	15.0328	14.9507	13.1699	12.4219	12.847	13.1753	11.8548	11.2411	11.2131	10.7836	9.28493	9.47397	9.01366	9.0548	7.90137	7.87671	8.00273	6.40822	6.55342	7.30959	7.85246	8.52877	5.37808	5.8	5.26229	5.73973	7.12055	6.53699	5.82787	9.48219	10.4904	9.35343	9.36885	8.90685	7.8411	8.29041	8.06011	7.79726	4.69589

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.
Outlandish outliers: There are "outliers" in this data.^Note In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.

(This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.

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([15.978,1.64384,2.73973,14.5205,3.82514,1.64384,0.273973,0,0,0.821918,0,0,2.37389,0.327869,0,2.46575,0.546448,0,1.09589,2.46575,1.91257,0.273973,0,1.09589,0.819672,3.56164,0.547945,1.36986,0.273224,0.273973,0.821918,0,0.546448,0,0,0,0.273224,0.273973,0.547945,0,0.546448,0.273973,0,])
array_2 = np.array([66,51,45,38,15.0328,14.9507,13.1699,12.4219,12.847,13.1753,11.8548,11.2411,11.2131,10.7836,9.28493,9.47397,9.01366,9.0548,7.90137,7.87671,8.00273,6.40822,6.55342,7.30959,7.85246,8.52877,5.37808,5.8,5.26229,5.73973,7.12055,6.53699,5.82787,9.48219,10.4904,9.35343,9.36885,8.90685,7.8411,8.29041,8.06011,7.79726,4.69589,])
array_1_name = "Air pollution in Des Moines"
array_2_name = "Kerosene used in Canada"

# 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 Des Moines
Line chart for only Kerosene used in Canada
AI-generated correlation image
The spurious research paper: The Burning Connection: Exploring the Link Between Des Moines Air Pollution and Canadian Kerosene Usage

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Correlation ID: 3858 · Black Variable ID: 20546 · Red Variable ID: 24275


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